path: root/data/samples/wrapped/en/democratizing_innovation.eric_von_hippel.sst

% SiSU 4.0

@title: Democratizing Innovation
 :language: US

@creator:
 :author: von Hippel, Eric

@date:
 :published: 2005
 :created: 2005
 :issued: 2005
 :available: 2005
 :modified: 2005
 :valid: 2005

@rights:
 :copyright: Copyright (C) 2005 Eric von Hippel. Exclusive rights to publish and sell this book in print form in English are licensed to The MIT Press. All other rights are reserved by the author. An electronic version of this book is available under a Creative Commons license.
 :license: Creative Commons US Attribution-NonCommercial-NoDerivs license 2.0. http://creativecommons.org/licenses/by-nc-nd/2.0/legalcode Some Rights Reserved. You are free to copy, distribute, display and perform the work, under the following conditions: Attribution, you must give the original author credit; you may not use this work for commercial purposes; No Derivative Works, you may not alter, transform, or build-upon this work. For reuse or distribution you must make clear to others the license terms of this work. Any conditions can be waived if you get permission from the copyright holder. Your fair use and other rights are in no way affected by the above.

@classify:
 :topic_register: SiSU markup sample:book:discourse;book:discourse:innovation|democracy|open source software;innovation;technological innovations:economic aspects;diffusion of innovations;democracy;open source software:innovation

@identifier:
 :isbn: 9780262720472
 :oclc: 56880369

% HC79.T4H558 2005
% 338'.064-dc22 2004061060

@links:
 { Democratizing Innovation }http://web.mit.edu/evhippel/www/democ1.htm
 { Eric von Hippel }http://web.mit.edu/evhippel/www/
 { @ Wikipedia }http://en.wikipedia.org/wiki/Democratizing_Innovation
 { Democratizing Innovation @ Amazon.com }http://www.amazon.com/Democratizing-Innovation-Eric-Von-Hippel/dp/0262720477
 { Democratizing Innovation @ Barnes & Noble }http://search.barnesandnoble.com/booksearch/isbnInquiry.asp?isbn=9780262720472

@make:
 :breaks: new=:B,C; break=1
 :texpdf_font: Liberation Sans
 :home_button_image: {di_evh.png }http://web.mit.edu/evhippel/www/
 :footer: {Eric von Hippel}http://web.mit.edu/evhippel/www/

:A~ @title @author

--~#

1~attribution Attribution

Dedicated to all who are building the information commons.

% Contents
% Acknowledgements ix
% 1 Introduction and Overview 1
% 2 Development of Products by Lead Users 19
% 3 Why Many Users Want Custom Products 33
% 4 Users' Innovate-or-Buy Decisions 45
% 5 Users' Low-Cost Innovation Niches 63
% 6 Why Users Often Freely Reveal Their Innovations 77
% 7 Innovation Communities 93
% 8 Adapting Policy to User Innovation 107
% 9 Democratizing Innovation 121
% 10 Application: Searching for Lead User Innovations 133
% 11 Application: Toolkits for User Innovation and Custom Design 147
% 12 Linking User Innovation to Other Phenomena and Fields 165
% Notes 179
% Bibliography 183
% Index 197

1~acknowledgements Acknowledgements

Early in my research on the democratization of innovation I was very fortunate
to gain five major academic mentors and friends. Nathan Rosenberg, Richard
Nelson, Zvi Griliches, Edwin Mansfield, and Ann Carter all provided crucial
support as I adopted economics as the organizing framework and toolset for my
work. Later, I collaborated with a number of wonderful co-authors, all of whom
are friends as well: Stan Finkelstein, Nikolaus Franke, Dietmar Harhoff,
Joachim Henkel, Cornelius Herstatt, Ralph Katz, Georg von Krogh, Karim Lakhani,
Gary Lilien, Christian Luthje, Pamela Morrison, William Riggs, John Roberts,
Stephan Schrader, Mary Sonnack, Stefan Thomke, Marcie Tyre, and Glen Urban.
Other excellent research collaborators and friends of long standing include
Carliss Baldwin, Sonali Shah, Sarah Slaughter, and Lars Jeppesen.

At some point as interest in a topic grows, there is a transition from dyadic
academic relationships to a real research community. In my case, the essential
person in enabling that transition was my close friend and colleague Dietmar
Harhoff. He began to send wonderful Assistant Professors (Habilitanden) over
from his university, Ludwig Maximilians Universität in Munich, to do
collaborative research with me as MIT Visiting Scholars. They worked on issues
related to the democratization of innovation while at MIT and then carried on
when they returned to Europe. Now they are training others in their turn.

I have also greatly benefited from close contacts with colleagues in industry.
As Director of the MIT Innovation Lab, I work together with senior innovation
managers in just a few companies to develop and try out innovation tools in
actual company settings. Close intellectual colleagues and friends of many
years standing in this sphere include Jim Euchner from Pitney-Bowes, Mary
Sonnack and Roger Lacey from 3M, John Wright from IFF, Dave Richards from
Nortel Networks, John Martin from Verizon, Ben Hyde from the Apache Foundation,
Brian Behlendorf from the Apache Foundation and CollabNet, and Joan Churchill
and Susan Hiestand from Lead User Concepts. Thank you so much for the huge (and
often humbling) insights that your and our field experimentation has provided!

I am also eager to acknowledge and thank my family for the joy and learning
they experience and share with me. My wife Jessie is a professional editor and
edited my first book in a wonderful way. For this book, however, time devoted
to bringing up the children made a renewed editorial collaboration impossible.
I hope the reader will not suffer unduly as a consequence! My children
Christiana Dagmar and Eric James have watched me work on the book---indeed they
could not avoid it as I often write at home. I hope they have been drawing the
lesson that academic research can be really fun. Certainly, that is the lesson
I drew from my father, Arthur von Hippel. He wrote his books in his study
upstairs when I was a child and would often come down to the kitchen for a cup
of coffee. In transit, he would throw up his hands and say, to no one in
particular, "/{Why}/ do I choose to work on such difficult problems?" And then
he would look deeply happy. Dad, I noticed the smile!

Finally my warmest thanks to my MIT colleagues and students and also to MIT as
an institution. MIT is a really inspiring place to work and learn from others.
We all understand the requirements for good research and learning, and we all
strive to contribute to a very supportive academic environment. And, of course,
new people are always showing up with new and interesting ideas, so fun and
learning are always being renewed!

--+#

:B~ Democratizing Innovation

1~ 1 Introduction and Overview

When I say that innovation is being democratized, I mean that users of products
and services---both firms and individual consumers---are increasingly able to
innovate for themselves. User-centered innovation processes offer great
advantages over the manufacturer-centric innovation development systems that
have been the mainstay of commerce for hundreds of years. Users that innovate
can develop exactly what they want, rather than relying on manufacturers to act
as their (often very imperfect) agents. Moreover, individual users do not have
to develop everything they need on their own: they can benefit from innovations
developed and freely shared by others.
={ Economic benefit, expectations of by lead users :
     by users +43 ;
   Manufacturers :
     innovation and +11 ;
   Users :
     See also Lead users | expectations of economic benefit by +33 | innovation and +33
}

The trend toward democratization of innovation applies to information products
such as software and also to physical products. As a quick illustration of the
latter, consider the development of high-performance windsurfing techniques and
equipment in Hawaii by an informal user group. High-performance windsurfing
involves acrobatics such as jumps and flips and turns in mid-air. Larry
Stanley, a pioneer in high-performance windsurfing, described the development
of a major innovation in technique and equipment to Sonali Shah:
={ Stanley, L. ;
   Shah, S. ;
   Information commons :
     See also Information communities | See also Innovation communities ;
   windsurfing
}

In 1978 Jürgen Honscheid came over from West Germany for the first Hawaiian
World Cup and discovered jumping, which was new to him, although Mike Horgan
and I were jumping in 1974 and 1975. There was a new enthusiasm for jumping and
we were all trying to outdo each other by jumping higher and higher. The
problem was that . . . the riders flew off in mid-air because there was no way
to keep the board with you---and as a result you hurt your feet, your legs, and
the board.
={ Honscheid, J. ;
   Horgan, M.
}

Then I remembered the "Chip," a small experimental board we had built with
footstraps, and thought "it's dumb not to use this for jumping." That's when I
first started jumping with footstraps and discovering controlled flight. I
could go so much faster than I ever thought and when you hit a wave it was like
a motorcycle rider hitting a ramp; you just flew into the air. All of a sudden
not only could you fly into the air, but you could land the thing, and not only
that, but you could change direction in the air!

The whole sport of high-performance windsurfing really started from that. As
soon as I did it, there were about ten of us who sailed all the time together
and within one or two days there were various boards out there that had
footstraps of various kinds on them, and we were all going fast and jumping
waves and stuff. It just kind of snowballed from there. (Shah 2000)
={ Shah, S. ;
   windsurfing +1 }

By 1998, more than a million people were engaged in windsurfing, and a large
fraction of the boards sold incorporated the user-developed innovations for the
high-performance sport.

The user-centered innovation process just illustrated is in sharp contrast to
the traditional model, in which products and services are developed by
manufacturers in a closed way, the manufacturers using patents, copyrights, and
other protections to prevent imitators from free riding on their innovation
investments. In this traditional model, a user's only role is to have needs,
which manufacturers then identify and fill by designing and producing new
products. The manufacturer-centric model does fit some fields and conditions.
However, a growing body of empirical work shows that users are the first to
develop many and perhaps most new industrial and consumer products. Further,
the contribution of users is growing steadily larger as a result of continuing
advances in computer and communications capabilities.
={ Intellectual property rights :
     See also Private-collective innovation | copyrights and | innovation and +2 ;
   Copyrights :
     See Intellectual property rights ;
   Manufacturers :
     government policy and +2 ;
   Product development +2 ;
   Users :
     government policy and ;
   Economic benefit, expectations of by lead users :
     by manufacturers +5 ;
   Economic benefit, expectations of by lead users :
     by manufacturers +12 ;
   Government policy :
     manufacturer innovation and +2 ;
   Manufacturers :
     expectations of economic benefit by +26
   }

In this book I explain in detail how the emerging process of user-centric,
democratized innovation works. I also explain how innovation by users provides
a very necessary complement to and feedstock for manufacturer innovation.

The ongoing shift of innovation to users has some very attractive qualities. It
is becoming progressively easier for many users to get precisely what they want
by designing it for themselves. And innovation by users appears to increase
social welfare. At the same time, the ongoing shift of product-development
activities from manufacturers to users is painful and difficult for many
manufacturers. Open, distributed innovation is "attacking" a major structure of
the social division of labor. Many firms and industries must make fundamental
changes to long-held business models in order to adapt. Further, governmental
policy and legislation sometimes preferentially supports innovation by
manufacturers. Considerations of social welfare suggest that this must change.
The workings of the intellectual property system are of special concern. But
despite the difficulties, a democratized and user-centric system of innovation
appears well worth striving for.
={ Government policy :
    See also Digital Millennium Copyright Act | and social welfare | user innovation and ;
  Social welfare :
    government policy and | innovation and +3 | user innovation and +3 }

% check government policy

Users, as the term will be used in this book, are firms or individual consumers
that expect to benefit from /{using}/ a product or a service. In contrast,
manufacturers expect to benefit from /{selling}/ a product or a service. A firm
or an individual can have different relationships to different products or
innovations. For example, Boeing is a manufacturer of airplanes, but it is also
a user of machine tools. If we were examining innovations developed by Boeing
for the airplanes it sells, we would consider Boeing a manufacturer-innovator
in those cases. But if we were considering innovations in metal-forming
machinery developed by Boeing for in-house use in building airplanes, we would
categorize those as user-developed innovations and would categorize Boeing as a
user-innovator in those cases.
={ Users : characteristics of +2 ;
   Manufacturers : characteristics of +2
}

Innovation user and innovation manufacturer are the two general "functional"
relationships between innovator and innovation. Users are unique in that they
alone benefit /{directly}/ from innovations. All others (here lumped under the
term "manufacturers") must sell innovation-related products or services to
users, indirectly or directly, in order to profit from innovations. Thus, in
order to profit, inventors must sell or license knowledge related to
innovations, and manufacturers must sell products or services incorporating
innovations. Similarly, suppliers of innovation-related materials or
services---unless they have direct use for the innovations---must sell the
materials or services in order to profit from the innovations.
={ Innovation :
    See also Innovation communities | functional sources of ;
  Suppliers
}

The user and manufacturer categorization of relationships between innovator and
innovation can be extended to specific functions, attributes, or features of
products and services. When this is done, it may turn out that different
parties are associated with different attributes of a particular product or
service. For example, householders are the users of the switching attribute of
a household electric light switch---they use it to turn lights on and off.
However, switches also have other attributes, such as "easy wiring" qualities,
that may be used only by the electricians who install them. Therefore, if an
electrician were to develop an improvement to the installation attributes of a
switch, it would be considered a user-developed innovation.

A brief overview of the contents of the book follows.

!_ Development of Products by Lead Users (Chapter 2)
={ Economic benefit, expectations of by lead users +6 ;
  Lead users +6 :
    characteristics of +6 | commercial attractiveness of +6 | economic benefit, expectations of +6 | identification of +6 | innovation and +50 | library information search system and +6
}

Empirical studies show that many users---from 10 percent to nearly 40
percent---engage in developing or modifying products. About half of these
studies do not determine representative innovation frequencies; they were
designed for other purposes. Nonetheless, when taken together, the findings
make it very clear that users are doing a /{lot}/ of product modification and
product development in many fields.
={ innovation :
    attractiveness of +8
}

Studies of innovating users (both individuals and firms) show them to have the
characteristics of "lead users." That is, they are ahead of the majority of
users in their populations with respect to an important market trend, and they
expect to gain relatively high benefits from a solution to the needs they have
encountered there. The correlations found between innovation by users and lead
user status are highly significant, and the effects are very large.

Since lead users are at the leading edge of the market with respect to
important market trends, one can guess that many of the novel products they
develop for their own use will appeal to other users too and so might provide
the basis for products manufacturers would wish to commercialize. This turns
out to be the case. A number of studies have shown that many of the innovations
reported by lead users are judged to be commercially attractive and/or have
actually been commercialized by manufacturers.
={ Manufacturers :
    lead users and +1
}

Research provides a firm grounding for these empirical findings. The two
defining characteristics of lead users and the likelihood that they will
develop new or modified products have been found to be highly correlated
(Morrison et al. 2004). In addition, it has been found that the higher the
intensity of lead user characteristics displayed by an innovator, the greater
the commercial attractiveness of the innovation that the lead user develops
(Franke and von Hippel 2003a). In figure 1.1, the increased concentration of
innovations toward the right indicates that the likelihood of innovating is
higher for users having higher lead user index values. The rise in average
innovation attractiveness as one moves from left to right indicates that
innovations developed by lead users tend to be more commercially attractive.
(Innovation attractiveness is the sum of the novelty of the innovation and the
expected future generality of market demand.)
={ Morrison, Pamela ;
   Franke, N. +5 ;
   von Hippel, E. +5
}

%% Figure 1.1
% 2 3 4 5 6 7 8 9 10 11 12 13 14
% 10
% 5
% 0
% Attractiveness
% of
% innovations
% Innovation
% Estimated OLS curve
% "Lead-user?ness" of users

{di_evh_f1-1.png}image

!_ Figure 1.1
User-innovators with stronger "lead user" characteristics develop innovations
having higher appeal in the general marketplace. Estimated OLS function: Y =
2.06 + 0.57x, where Y represents attractiveness of innovation and x represents
lead-user-ness of respondent. Adjusted R^{2}^ = 0.281; p = 0.002; n = 30.
Source of data: Franke and von Hippel 2003.

!_ Why Many Users Want Custom Products (Chapter 3)
={ Custom products :
     heterogeneity of user needs and +2 ;
   User need +2 ;
   Users :
     innovate-or-buy decisions by +8 | needs of +2
}

Why do so many users develop or modify products for their own use? Users may
innovate if and as they want something that is not available on the market and
are able and willing to pay for its development. It is likely that many users
do not find what they want on the market. Meta-analysis of market-segmentation
studies suggests that users' needs for products are highly heterogeneous in
many fields (Franke and Reisinger 2003).
={ Reisinger, H. }

Mass manufacturers tend to follow a strategy of developing products that are
designed to meet the needs of a large market segment well enough to induce
purchase from and capture significant profits from a large number of customers.
When users' needs are heterogeneous, this strategy of "a few sizes fit all"
will leave many users somewhat dissatisfied with the commercial products on
offer and probably will leave some users seriously dissatisfied. In a study of
a sample of users of the security features of Apache web server software,
Franke and von Hippel (2003b) found that users had a very high heterogeneity of
need, and that many had a high willingness to pay to get precisely what they
wanted. Nineteen percent of the users sampled actually innovated to tailor
Apache more closely to their needs. Those who did were found to be
significantly more satisfied.
={ Apache web server software ;
   Manufacturers :
     lead users and
}

!_ Users' Innovate-or-Buy Decisions (Chapter 4)
={ Custom products :
     heterogeneity of user needs and +3 | manufacturers and +3 | agency costs and +2 ;
   User need +3 ;
   Users : needs of +3 ;
   Manufacturers :
     innovation and +9 | innovate-or-buy decisions and +4 ;
   Users : agency costs and +2
}

Even if many users want "exactly right products" and are willing and able to
pay for their development, why do users often do this for themselves rather
than hire a custom manufacturer to develop a special just-right product for
them? After all, custom manufacturers specialize in developing products for one
or a few users. Since these firms are specialists, it is possible that they
could design and build custom products for individual users or user firms
faster, better, or cheaper than users could do this for themselves. Despite
this possibility, several factors can drive users to innovate rather than buy.
Both in the case of user firms and in the case of individual user-innovators,
agency costs play a major role. In the case of individual user-innovators,
enjoyment of the innovation process can also be important.
={ Agency costs +1 ;
   Manufacturers :
     custom products and +2 ;
   Custom products : users and +3 ;
   Economic benefit, expectations of by lead users :
     by manufacturers +13
}

With respect to agency costs, consider that when a user develops its own custom
product that user can be trusted to act in its own best interests. When a user
hires a manufacturer to develop a custom product, the situation is more
complex. The user is then a principal that has hired the custom manufacturer to
act as its agent. If the interests of the principal and the agent are not the
same, there will be agency costs. In general terms, agency costs are (1) costs
incurred to monitor the agent to ensure that it (or he or she) follows the
interests of the principal, (2) the cost incurred by the agent to commit itself
not to act against the principal's interest (the "bonding cost"), and (3) costs
associated with an outcome that does not fully serve the interests of the
principal (Jensen and Meckling 1976). In the specific instance of product and
service development, a major divergence of interests between user and custom
manufacturer does exist: the user wants to get precisely what it needs, to the
extent that it can afford to do so. In contrast, the custom manufacturer wants
to lower its development costs by incorporating solution elements it already
has or that it predicts others will want in the future---even if by doing so it
does not serve its present client's needs as well as it could.
={ Jensen, M. ;
   Meckling, W.
}

A user wants to preserve its need specification because that specification is
chosen to make /{that user's}/ overall solution quality as high as possible at
the desired price. For example, an individual user may specify a
mountain-climbing boot that will precisely fit his unique climbing technique
and allow him to climb Everest more easily. Any deviations in boot design will
require compensating modifications in the climber's carefully practiced and
deeply ingrained climbing technique---a much more costly solution from the
user's point of view. A custom boot manufacturer, in contrast, will have a
strong incentive to incorporate the materials and processes it has in stock and
expects to use in future even if this produces a boot that is not precisely
right for the present customer. For example, the manufacturer will not want to
learn a new way to bond boot components together even if that would produce the
best custom result for one client. The net result is that when one or a few
users want something special they will often get the best result by innovating
for themselves.
={ Innovation communities :
     See also Information communities +1
}

A small model of the innovate-or-buy decision follows. This model shows in a
quantitative way that user firms with unique needs will always be better off
developing new products for themselves. It also shows that development by
manufacturers can be the most economical option when n or more user firms want
the same thing. However, when the number of user firms wanting the same thing
falls between 1 and n, manufacturers may not find it profitable to develop a
new product for just a few users. In that case, more than one user may invest
in developing the same thing independently, owing to market failure. This
results in a waste of resources from the point of view of social welfare. The
problem can be addressed by new institutional forms, such as the user
innovation communities that will be studied later in this book.
={ Innovation communities :
     social welfare, and ;
   Manufacturers :
     social welfare and +21 ;
   Social welfare :
     manufacturer innovation and +21 | user innovation and +21
}

Chapter 4 concludes by pointing out that an additional incentive can drive
individual user-innovators to innovate rather than buy: they may value the
/{process}/ of innovating because of the enjoyment or learning that it brings
them. It might seem strange that user-innovators can enjoy product development
enough to want to do it themselves---after all, manufacturers pay their product
developers to do such work! On the other hand, it is also clear that enjoyment
of problem solving is a motivator for many individual problem solvers in at
least some fields. Consider for example the millions of crossword-puzzle
aficionados. Clearly, for these individuals enjoyment of the problem-solving
process rather than the solution is the goal. One can easily test this by
attempting to offer a puzzle solver a completed puzzle---the very output he or
she is working so hard to create. One will very likely be rejected with the
rebuke that one should not spoil the fun! Pleasure as a motivator can apply to
the development of commercially useful innovations as well. Studies of the
motivations of volunteer contributors of code to widely used software products
have shown that these individuals too are often strongly motivated to innovate
by the joy and learning they find in this work (Hertel et al. 2003; Lakhani and
Wolf 2005).
={ Hertel, G. ;
   Lakhani, K. ;
   Wolf, B. ;
   Innovation process ;
   Users :
     innovation process and +7 ;
   Free software : See also Open source software ;
   Hackers ;
   Herrmann, S.
}

!_ Users' Low-Cost Innovation Niches (Chapter 5)
={ Users :
     low-cost innovation niches of +3
}

An exploration of the basic processes of product and service development show
that users and manufacturers tend to develop different /{types}/ of
innovations. This is due in part to information asymmetries: users and
manufacturers tend to know different things. Product developers need two types
of information in order to succeed at their work: need and context-of-use
information (generated by users) and generic solution information (often
initially generated by manufacturers specializing in a particular type of
solution). Bringing these two types of information together is not easy. Both
need information and solution information are often very "sticky"---that is,
costly to move from the site where the information was generated to other
sites. As a result, users generally have a more accurate and more detailed
model of their needs than manufacturers have, while manufacturers have a better
model of the solution approach in which they specialize than the user has.
={ Innovation process ;
   Users : innovation process and ;
   Information asymmetries +3 ;
   Manufacturers : information asymmetries of +2 ;
   Sticky information +2 : innovation and +2 ;
   Users : information asymmetries of +2 ;
   Local information +2
}

When information is sticky, innovators tend to rely largely on information they
already have in stock. One consequence of the information asymmetry between
users and manufacturers is that users tend to develop innovations that are
functionally novel, requiring a great deal of user-need information and
use-context information for their development. In contrast, manufacturers tend
to develop innovations that are improvements on well-known needs and that
require a rich understanding of solution information for their development. For
example, firms that use inventory-management systems, such as retailers, tend
to be the developers of new approaches to inventory management. In contrast,
manufacturers of inventory-management systems and equipment tend to develop
improvements to the equipment used to implement these user-devised approaches
(Ogawa 1998).
={ Ogawa, S. ;
   Innovation :
     functional sources of
}

If we extend the information-asymmetry argument one step further, we see that
information stickiness implies that information on hand will also differ among
/{individual}/ users and manufacturers. The information assets of some
particular user (or some particular manufacturer) will be closest to what is
required to develop a particular innovation, and so the cost of developing that
innovation will be relatively low for that user or manufacturer. The net result
is that user innovation activities will be distributed across many users
according to their information endowments. With respect to innovation, one user
is by no means a perfect substitute for another.

!_ Why Users Often Freely Reveal Their Innovations (Chapter 6)
={ Free revealing of innovation information :
     case for +5 | evidence of +5 | in information communities +5 | intellectual property rights and +5 | users and +5 ;
   Users :
     free revealing by +5
}

The social efficiency of a system in which individual innovations are developed
by individual users is increased if users somehow diffuse what they have
developed to others. Manufacturer-innovators /{partially}/ achieve this when
they sell a product or a service on the open market (partially because they
diffuse the product incorporating the innovation, but often not all the
information that others would need to fully understand and replicate it). If
user-innovators do not somehow also diffuse what they have done, multiple users
with very similar needs will have to independently develop very similar
innovations---a poor use of resources from the viewpoint of social welfare.
Empirical research shows that users often do achieve widespread diffusion by an
unexpected means: they often "freely reveal" what they have developed. When we
say that an innovator freely reveals information about a product or service it
has developed, we mean that all intellectual property rights to that
information are voluntarily given up by the innovator, and all interested
parties are given access to it---the information becomes a public good.
={ Free revealing of innovation information :
     manufacturers and +2 ;
   Innovation :
     distributed process of +4 ;
   Intellectual property rights :
     free revealing and ;
   Manufacturers :
     free revealing and +2
}

The empirical finding that users often freely reveal their innovations has been
a major surprise to innovation researchers. On the face of it, if a
user-innovator's proprietary information has value to others, one would think
that the user would strive to prevent free diffusion rather than help others to
free ride on what it has developed at private cost. Nonetheless, it is now very
clear that individual users and user firms---and sometimes
manufacturers---often freely reveal detailed information about their
innovations.

The practices visible in "open source" software development were important in
bringing this phenomenon to general awareness. In these projects it was clear
/{policy}/ that project contributors would routinely and systematically freely
reveal code they had developed at private expense (Raymond 1999). However, free
revealing of product innovations has a history that began long before the
advent of open source software. Allen, in his 1983 study of the
eighteenth-century iron industry, was probably the first to consider the
phenomon systematically. Later, Nuvolari (2004) discussed free revealing in the
early history of mine pumping engines. Contemporary free revealing by users has
been documented by von Hippel and Finkelstein (1979) for medical equipment, by
Lim (2000) for semiconductor process equipment, by Morrison, Roberts, and von
Hippel (2000) for library information systems, and by Franke and Shah (2003)
for sporting equipment. Henkel (2003) has documented free revealing among
manufacturers in the case of embedded Linux software.
={ Allen, R. ;
   Finkelstein, S. ;
   Franke, N. ;
   Henkel, J. ;
   Lim, K. ;
   Linux ;
   Morrison, Pamela ;
   Nuvolari, A. ;
   Raymond, E. ;
   Roberts, J. ;
   Shah, S. ;
   von Hippel, E. ;
   Free revealing of innovation information :
     open source software and +7 ;
   Intellectual property rights :
     open source software and +1 ;
   Open source software :
     See also Free software communities and | free revealing and +7 | intellectual property rights and +2 ;
   Library information search system
}

Innovators often freely reveal because it is often the best or the only
practical option available to them. Hiding an innovation as a trade secret is
unlikely to be successful for long: too many generally know similar things, and
some holders of the "secret" information stand to lose little or nothing by
freely revealing what they know. Studies find that innovators in many fields
view patents as having only limited value. Copyright protection and copyright
licensing are applicable only to "writings," such as books, graphic images, and
computer software.
={ Intellectual property rights :
     copyrights and | trade secrets and | free revealing and | licensing of | patents and ;
   Government policy :
     trade secrets and
}

Active efforts by innovators to freely reveal---as opposed to sullen
acceptance---are explicable because free revealing can provide innovators with
significant private benefits as well as losses or risks of loss. Users who
freely reveal what they have done often find that others then improve or
suggest improvements to the innovation, to mutual benefit (Raymond 1999).
Freely revealing users also may benefit from enhancement of reputation, from
positive network effects due to increased diffusion of their innovation, and
from other factors. Being the first to freely reveal a particular innovation
can also enhance the benefits received, and so there can actually be a rush to
reveal, much as scientists rush to publish in order to gain the benefits
associated with being the first to have made a particular advancement.
={ Raymond, E. }

!_ Innovation Communities (Chapter 7)
={ Innovation communities +3 }

Innovation by users tends to be widely distributed rather than concentrated
among just a very few very innovative users. As a result, it is important for
user-innovators to find ways to combine and leverage their efforts. Users
achieve this by engaging in many forms of cooperation. Direct, informal
user-to-user cooperation (assisting others to innovate, answering questions,
and so on) is common. Organized cooperation is also common, with users joining
together in networks and communities that provide useful structures and tools
for their interactions and for the distribution of innovations. Innovation
communities can increase the speed and effectiveness with which users and also
manufacturers can develop and test and diffuse their innovations. They also can
greatly increase the ease with which innovators can build larger systems from
interlinkable modules created by community participants.
={ Users :
     innovation communities and +2
}

Free and open source software projects are a relatively well-developed and very
successful form of Internet-based innovation community. However, innovation
communities are by no means restricted to software or even to information
products, and they can play a major role in the development of physical
products. Franke and Shah (2003) have documented the value that user innovation
communities can provide to user-innovators developing physical products in the
field of sporting equipment. The analogy to open source innovation communities
is clear.
={ Franke, N. ;
   Shah, S. ;
   Free software ;
   Innovation communities :
     open source software and | physical products and | sporting equipment and ;
   Open source software :
     innovation communities and
}

The collective or community effort to provide a public good---which is what
freely revealed innovations are---has traditionally been explored in the
literature on "collective action." However, behaviors seen in extant innovation
communities fail to correspond to that literature at major points. In essence,
innovation communities appear to be more robust with respect to recruiting and
rewarding members than the literature would predict. Georg von Krogh and I
attribute this to innovation contributors' obtaining some private rewards that
are not shared equally by free riders (those who take without contributing).
For example, a product that a user-innovator develops and freely reveals might
be perfectly suited to that user-innovator's requirements but less well suited
to the requirements of free riders. Innovation communities thus illustrate a
"private-collective" model of innovation incentive (von Hippel and von Krogh
2003).
={ von Hippel, E. ;
   von Krogh, G. ;
   Free revealing of innovation information :
     collective action model for | private-collective model for ;
   Innovation communities :
     and sources of innovation ;
   Private-collective model ;
   Social welfare :
     private-collective model and +2 ;
   Users :
     social welfare and +6
}

!_ Adapting Policy to User Innovation (Chapter 8)
={ Government policy :
     social welfare and +5 | user innovation and +5 ;
   Social welfare :
     and government policy +5
}

Is innovation by users a "good thing?" Welfare economists answer such a
question by studying how a phenomenon or a change affects social welfare.
Henkel and von Hippel (2005) explored the social welfare implications of user
innovation. They found that, relative to a world in which only manufacturers
innovate, social welfare is very probably increased by the presence of
innovations freely revealed by users. This finding implies that policy making
should support user innovation, or at least should ensure that legislation and
regulations do not favor manufacturers at the expense of user-innovators.
={ Henkel, J. ;
   von Hippel, E. ;
   Free revealing of innovation information :
     manufacturers and
}

The transitions required of policy making to achieve neutrality with respect to
user innovation vs. manufacturer innovation are significant. Consider the
impact on open and distributed innovation of past and current policy decisions.
Research done in the past 30 years has convinced many academics that
intellectual property law is sometimes or often not having its intended effect.
Intellectual property law was intended to increase the amount of innovation
investment. Instead, it now appears that there are economies of scope in both
patenting and copyright that allow firms to use these forms of intellectual
property law in ways that are directly opposed to the intent of policy makers
and to the public welfare. Major firms can invest to develop large portfolios
of patents. They can then use these to create "patent thickets"---dense
networks of patent claims that give them plausible grounds for threatening to
sue across a wide range of intellectual property. They may do this to prevent
others from introducing a superior innovation and/or to demand licenses from
weaker competitors on favorable terms (Shapiro 2001). Movie, publishing, and
software firms can use large collections of copyrighted work to a similar
purpose (Benkler 2002). In view of the distributed nature of innovation by
users, with each tending to create a relatively small amount of intellectual
property, users are likely to be disadvantaged by such strategies.
={ Benkler, Y. ;
  Shapiro, C. ;
  Intellectual property rights :
    copyrights and +1 ;
  Government policy :
    copyrights and +1 | patents and | patent thickets and ;
  Intellectual property rights :
    patents and | patent thickets and | licensing of
}

It is also important to note that users (and manufacturers) tend to build
prototypes of their innovations economically by modifying products already
available on the market to serve a new purpose. Laws such as the (US) Digital
Millennium Copyright Act, intended to prevent consumers from illegally copying
protected works, also can have the unintended side effect of preventing users
from modifying products that they purchase (Varian 2002). Both fairness and
social welfare considerations suggest that innovation-related policies should
be made neutral with respect to the sources of innovation.
={ Digital Millennium Copyright Act ;
   Varian, H.
}

It may be that current impediments to user innovation will be solved by
legislation or by policy making. However, beneficiaries of existing law and
policy will predictably resist change. Fortunately, a way to get around some of
these problems is in the hands of innovators themselves. Suppose many
innovators in a particular field decide to freely reveal what they have
developed, as they often have reason to do. In that case, users can
collectively create an information commons (a collection of information freely
available to all) containing substitutes for some or a great deal of
information now held as private intellectual property. Then user-innovators can
work around the strictures of intellectual property law by simply using these
freely revealed substitutes (Lessig 2001). This is essentially what is
happening in the field of software. For many problems, user-innovators in that
field now have a choice between proprietary, closed software provided by
Microsoft and other firms and open source software that they can legally
download from the Internet and legally modify to serve their own specific
needs.
={ Lessig, L. ;
   Microsoft ;
   Free revealing of innovation information :
     collective action model for | in information communities | intellectual property rights and | users and +1 ;
   Information commons ;
   Intellectual property rights :
     free revealing and | information communities and ;
   Microsoft ;
   User need ;
   Users :
     free revealing by
}

Policy making that levels the playing field between users and manufacturers
will force more rapid change onto manufacturers but will by no means destroy
them. Experience in fields where open and distributed innovation processes are
far advanced show how manufacturers can and do adapt. Some, for example, learn
to supply proprietary platform products that offer user-innovators a framework
upon which to develop and use their improvements.
={ Manufacturers :
     innovation and +7
}

!_ Democratizing Innovation (Chapter 9)

Users' ability to innovate is improving /{radically}/ and /{rapidly}/ as a
result of the steadily improving quality of computer software and hardware,
improved access to easy-to-use tools and components for innovation, and access
to a steadily richer innovation commons. Today, user firms and even individual
hobbyists have access to sophisticated programming tools for software and
sophisticated CAD design tools for hardware and electronics. These
information-based tools can be run on a personal computer, and they are rapidly
coming down in price. As a consequence, innovation by users will continue to
grow even if the degree of heterogeneity of need and willingness to invest in
obtaining a precisely right product remains constant.
={ Free revealing of innovation information :
   users and ;
   Task partitioning +5 :
     See also Toolkits ;
   Toolkits :
     manufacturers and +5 | task partitioning +5 | user-friendly tools for | users and +5 ;
   User need ;
   Users :
     innovation and +5
}

Equivalents of the innovation resources described above have long been
available within corporations to a few. Senior designers at firms have long
been supplied with engineers and designers under their direct control, and with
the resources needed to quickly construct and test prototype designs. The same
is true in other fields, including automotive design and clothing design: just
think of the staffs of engineers and modelmakers supplied so that top auto
designers can quickly realize and test their designs.

But if, as we have seen, the information needed to innovate in important ways
is widely distributed, the traditional pattern of concentrating
innovation-support resources on a few individuals is hugely inefficient.
High-cost resources for innovation support cannot efficiently be allocated to
"the right people with the right information:" it is very difficult to know who
these people may be before they develop an innovation that turns out to have
general value. When the cost of high-quality resources for design and
prototyping becomes very low (the trend we have described), these resources can
be diffused very widely, and the allocation problem diminishes in significance.
The net result is and will be to democratize the opportunity to create.
={ Manufacturers :
     innovation and +9 ;
   Users :
     innovation and +9
}

On a level playing field, users will be an increasingly important source of
innovation and will increasingly substitute for or complement manufacturers'
innovation-related activities. In the case of information products, users have
the possibility of largely or completely doing without the services of
manufacturers. Open source software projects are object lessons that teach us
that users can create, produce, diffuse, provide user field support for,
update, and use complex products by and for themselves in the context of user
innovation communities. In physical product fields, product development by
users can evolve to the point of largely or totally supplanting product
development---but not product manufacturing---by manufacturers. (The economies
of scale associated with manufacturing and distributing physical products give
manufacturers an advantage over "do-it-yourself" users in those activities.)
={ Custom products :
     manufacturers and +2 | users and +2 ;
   Innovation communities +1 :
     open source software and | physical products and ;
   Manufacturers :
     custom products and +2 ;
   Users :
     custom products and +2
}

The evolving pattern of the locus of product development in kitesurfing
illustrates how users can displace manufacturers from the role of product
developer. In that industry, the collective product-design and testing work of
a user innovation community has clearly become superior in both quality and
quantity relative to the levels of in-house development effort that
manufacturers of kitesurfing equipment can justify. Accordingly, manufacturers
of such equipment are increasingly shifting away from product design and
focusing on producing product designs first developed and tested by user
innovation communities.
={ Innovation communities :
     kitesurfing and ;
   Kitesurfing
}

How can or should manufacturers adapt to users' encroachment on elements of
their traditional business activities? There are three general possibilities:
(1) Produce user-developed innovations for general commercial sale and/or offer
custom manufacturing to specific users. (2) Sell kits of product-design tools
and/or "product platforms" to ease users' innovation-related tasks. (3) Sell
products or services that are complementary to user-developed innovations.
Firms in fields where users are already very active in product design are
experimenting with all these possibilities.
={ Custom products :
     product platforms and | toolkits and ;
   Toolkits :
     platform products and
}

!_ Application: Searching for Lead User Innovations (Chapter 10)
={ Custom products :
     manufacturers and +2 ;
   Manufacturers :
     custom products and +2 ;
   Users :
     custom products and +2 ;
   Lead users +59 :
     idea generation and +2 | identification of +2 | innovation and +2
}

Manufacturers design their innovation processes around the way they think the
process works. The vast majority of manufacturers still think that product
development and service development are always done by manufacturers, and that
their job is always to find a need and fill it rather than to sometimes find
and commercialize an innovation that lead users have already developed.
Accordingly, manufacturers have set up market-research departments to explore
the needs of users in the target market, product-development groups to think up
suitable products to address those needs, and so forth. The needs and prototype
solutions of lead users---if encountered at all---are typically rejected as
outliers of no interest. Indeed, when lead users' innovations do enter a firm's
product line---and they have been shown to be the actual source of many major
innovations for many firms--- they typically arrive with a lag and by an
unconventional and unsystematic route. For example, a manufacturer may
"discover" a lead user innovation only when the innovating user firm contacts
the manufacturer with a proposal to produce its design in volume to supply its
own in-house needs. Or sales or service people employed by a manufacturer may
spot a promising prototype during a visit to a customer's site.
={ Marketing research +1 }

Modification of firms' innovation processes to /{systematically}/ search for
and further develop innovations created by lead users can provide manufacturers
with a better interface to the innovation process as it actually works, and so
provide better performance. A natural experiment conducted at 3M illustrates
this possibility. Annual sales of lead user product ideas generated by the
average lead user project at 3M were conservatively forecast by management to
be more than 8 times the sales forecast for new products developed in the
traditional manner---$146 million versus $18 million per year. In addition,
lead user projects were found to generate ideas for new product lines, while
traditional market-research methods were found to produce ideas for incremental
improvements to existing product lines. As a consequence, 3M divisions funding
lead user project ideas experienced their highest rate of major product line
generation in the past 50 years (Lilien et al. 2002).
={ Lilien, G. ;
   Lead users :
     3M and ;
   3M Corporation
}

!_ Application: Toolkits for User Innovation and Custom Design (Chapter 11)
={ Toolkits +2 }

Firms that understand the distributed innovation process and users' roles in it
can /{change}/ factors affecting lead user innovation and so affect its rate
and direction in ways they value. Toolkits for user innovation custom design
offer one way of doing this. This approach involves partitioning
product-development and service-development projects into
solution-information-intensive subtasks and need-information-intensive
subtasks. Need-intensive subtasks are then assigned to users along with a kit
of tools that enable them to effectively execute the tasks assigned to them.
The resulting co-location of sticky information and problem-solving activity
makes innovation within the solution space offered by a particular toolkit
cheaper for users. It accordingly attracts them to the toolkit and so
influences what they develop and how they develop it. The custom semiconductor
industry was an early adopter of toolkits. In 2003, more than $15 billion worth
of semiconductors were produced that had been designed using this approach.
={ Toolkits :
     platform products and +2 ;
   Lead users :
     innovation and ;
   Sticky information :
     innovation and
}

Manufacturers that adopt the toolkit approach to supporting and channeling user
innovation typically face major changes in their business models, and important
changes in industry structure may also follow. For example, as a result of the
introduction of toolkits to the field of semiconductor manufacture, custom
semiconductor manufacturers---formerly providers of both design and
manufacturing services to customers---lost much of the work of custom product
design to customers. Many of these manufacturers then became specialist silicon
foundries, supplying production services primarily. Manufacturers may or may
not wish to make such changes. However, experience in fields where toolkits
have been deployed shows that customers tend to prefer designing their own
custom products with the aid of a toolkit over traditional manufacturer-centric
development practices. As a consequence, the only real choice for manufacturers
in a field appropriate to the deployment of toolkits may be whether to lead or
to follow in the transition to toolkits.

!_ Linking User Innovation to Other Phenomena and Fields (Chapter 12)

In chapter 12 I discuss links between user innovation and some related
phenomena and literatures. With respect to phenomena, I point out the
relationship of user innovation to /{information}/ communities, of which user
innovation communities are a subset. One open information community is the
online encyclopedia Wikipedia (www.wikipedia.org). Other such communities
include the many specialized Internet sites where individuals with both common
and rare medical conditions can find one another and can find specialists in
those conditions. Many of the advantages associated with user innovation
communities also apply to open information networks and communities. Analyses
appropriate to information communities follow the same overall pattern as the
analyses provided in this book for innovation communities. However, they are
also simpler, because in open information communities there may be little or no
proprietary information being transacted and thus little or no risk of related
losses for participants.
={ Wikipedia ;
   Information commons ;
   Information communities :
     See also Innovation communities ;
   Innovation communities +2 :
     and sources of innovation +2 ;
   Intellectual property rights :
     information communities and +2 | innovation and +2
}

Next I discuss links between user-centric innovation phenomena and the
literature on the economics of knowledge that have been forged by Foray (2004)
and Weber (2004). I also discuss how Porter's 1991 work on the competitive
advantage of nations can be extended to incorporate findings on nations' lead
users as product developers. Finally, I point out how findings explained in
this book link to and complement research on the Social Construction of
Technology (Pinch and Bijker 1987).
={ Bijker, W. ;
   Foray, D. ;
   Pinch, T. ;
   Weber, S. ;
   Porter, M. ;
   Knowledge, production and distribution of
}

I conclude this introductory chapter by reemphasizing that user innovation,
free revealing, and user innovation communities will flourish under many but
not all conditions. What we know about manufacturer-centered innovation is
still valid; however, lead-user-centered innovation patterns are increasingly
important, and they present major new opportunities and challenges for us all.
={ Free revealing of innovation information :
     free revealing and ;
   Users :
     free revealing by
}

1~ 2 Development of Products by Lead Users

The idea that novel products and services are developed by manufacturers is
deeply ingrained in both traditional expectations and scholarship. When we as
users of products complain about the shortcomings of an existing product or
wish for a new one, we commonly think that "they" should develop it---not us.
Even the conventional term for an individual end user, "consumer," implicitly
suggests that users are not active in product and service development.
Nonetheless, there is now very strong empirical evidence that product
development and modification by both user firms and users as individual
consumers is frequent, pervasive, and important.
={ Consumers +5 }

I begin this chapter by reviewing the evidence that many users indeed do
develop and modify products for their own use in many fields. I then show that
innovation is concentrated among /{lead}/ users, and that lead users'
innovations often become commercial products.

!_ Many Users Innovate

The evidence on user innovation frequency and pervasiveness is summarized in
table 2.1. We see here that the frequency with which user firms and individual
consumers develop or modify products for their own use range from 10 percent to
nearly 40 percent in fields studied to date. The matter has been studied across
a wide range of industrial product types where innovating users are user firms,
and also in various types of sporting equipment, where innovating users are
individual consumers.
={ Lead users :
     sporting equipment and +1 ;
   Sporting equipment :
     lead users and +1
}

The studies cited in table 2.1 clearly show that a lot of product development
and modification by users is going on. However, these findings should not be
taken to reflect innovation rates in overall populations of users. All of the
studies probably were affected by a response bias. (That is, if someone sends a
questionnaire about whether you innovated or not, you might be more inclined to
respond if your answer is "Yes."). Also, each of the studies looked at
innovation rates affecting a particular product type among users who care a
great deal about that product type. Thus, university surgeons (study 4 in table
2.1) care a great deal about having just-right surgical equipment, just as
serious mountain bikers (study 8) care a great deal about having just-right
equipment for their sport. As the intensity of interest goes down, it is likely
that rates of user innovation drop too. This is probably what is going on in
the case of the study of purchasers of outdoor consumer products (study 6). All
we are told about that sample of users of outdoor consumer products is that
they are recipients of one or more mail order catalogs from suppliers of
relatively general outdoor items---winter jackets, sleeping bags, and so on.
Despite the fact that these users were asked if they have developed or modified
any item in this broad category of goods (rather than a very specific one such
as a mountain bike), just 10 percent answered in the affirmative. Of course, 10
percent or even 5 percent of a user population numbering in the tens of
millions worldwide is still a very large number---so we again realize that many
users are developing and modifying products.
={ Lead users :
     outdoor consumer products and ;
   Outdoor products
}

!_ Table 2.1
Many respondents reported developing or modifying products for their own use in
the eight product areas listed here.
={ Lüthje, C. +1 ;
   Urban, G. +1 ;
   Franke, N. +1 ;
   Herstatt, C. +1 ;
   Morrison, Pamela +1 ;
   von Hippel, E. +1 ;
   Lead users :
     Apache web server software and +1r | library information search system and +1 | mountain biking and +1 | outdoor consumer products and +1 | pipe hanger hardware and +1 | printed circuit CAD software and +1 | surgical equipment and +3 ;
   Library information search system +1 ;
   Mountain biking +1 ;
   Outdoor products +1 ;
   Pipe hanger hardware +1 ;
   Printed circuit CAD software +1 ;
   Surgical equipment +1
}

table{~h c4; 20; 45; 15; 20;

~
Number and type of Users Sampled
Percentage developing and building product for own use
Source

Industrial products
~
~
~

1. Printed circuit CAD software
136 user firm attendees at PC-CAD conference
24.3%
Urban and von Hippel 1988

2. Pipe hanger hardware
Employees in 74 pipe hanger installation firms
36%
Herstatt and von Hippel 1992

3. Library information systems
Employees in 102 Australian libraries using computerized OPAC library information systems
26%
Morrison et al. 2000

4. Surgical equipment
261 surgeons working in university clinics in Germany
22%
Lüthje 2003

5. Apache OS server software security features
131 technically sophisticated Apache features users (webmasters)
19.1%
Franke and von Hippel 2003

Consumer products
~
~
~

6. Outdoor consumer products
153 recipients of mail order catalogs for outdoor activity products for consumers
9.8%
Lüthje 2004

7. "Extreme" sporting equipment
197 members of 4 specialized sporting clubs in 4 "extreme" sports
37.8%
Franke and Shah 2003

8. Mountain biking equipment
291 mountain bikers in a geographic region
19.2%
Lüthje et al.

}table

The cited studies also do not set an upper or a lower bound on the commercial
or technical importance of user-developed products and product modifications
that they report, and it is likely that most are of minor significance.
However, most innovations from any source are minor, so user-innovators are no
exception in this regard. Further, to say an innovation is minor is not the
same as saying it is trivial: minor innovations are cumulatively responsible
for much or most technical progress. Hollander (1965) found that about 80
percent of unit cost reductions in Rayon manufacture were the cumulative result
of minor technical changes. Knight (1963, VII, pp. 2--3) measured performance
advances in general-purpose digital computers and found, similarly, that "these
advances occur as the result of equipment designers using their knowledge of
electronics technology to produce a multitude of small improvements that
together produce significant performance advances."
={ Hollander, S. ;
   Knight, K. ;
   Users :
     process improvements by +1
}

Although most products and product modifications that users or others develop
will be minor, users are by no means restricted to developing minor or
incremental innovations. Qualitative observations have long indicated that
important process improvements are developed:rubyd gsub!(//, "") by users.
Smith (1776, pp. 11--13) pointed out the importance of "the invention of a
great number of machines which facilitate and abridge labor, and enable one man
to do the work of many." He also noted that "a great part of the machines made
use of in those manufactures in which labor is most subdivided, were originally
the invention of common workmen, who, being each of them employed in some very
simple operation, naturally turned their thoughts towards finding out easier
and readier methods of performing it." Rosenberg (1976) studied the history of
the US machine tool industry and found that important and basic machine types
like lathes and milling machines were first developed and built by user firms
having a strong need for them. Textile manufacturing firms, gun manufacturers
and sewing machine manufacturers were important early user-developers of
machine tools. Other studies show quantitatively that some of the most
important and novel products and processes have been developed by user firms
and by individual users. Enos (1962) reported that nearly all the most
important innovations in oil refining were developed by user firms. Freeman
(1968) found that the most widely licensed chemical production processes were
developed by user firms. Von Hippel (1988) found that users were the developers
of about 80 percent of the most important scientific instrument innovations,
and also the developers of most of the major innovations in semiconductor
processing. Pavitt (1984) found that a considerable fraction of invention by
British firms was for in-house use. Shah (2000) found that the most
commercially important equipment innovations in four sporting fields tended to
be developed by individual users.
={ Enos, J. ;
   Freeman, C. ;
   Pavitt, K. ;
   Rosenberg, N. ;
   Shah, S. ;
   Smith, A. ;
   von Hippel, E. +23 ;
   Sporting equipment :
     lead users and
}

!_ Lead User Theory
={ Lead users :
     theory of +3
}

A second major finding of empirical research into innovation by users is that
most user-developed products and product modifications (and the most
commercially attractive ones) are developed by users with "lead user"
characteristics. Recall from chapter 1 that lead users are defined as members
of a user population having two distinguishing characteristics: (1) They are at
the leading edge of an important market trend(s), and so are currently
experiencing needs that will later be experienced by many users in that market.
(2) They anticipate relatively high benefits from obtaining a solution to their
needs, and so may innovate.
={ Economic benefit, expectations of by lead users +1 ;
   Lead users :
     economic benefit, expectations of +1
}

The theory that led to defining "lead users" in terms of these two
characteristics was derived as follows (von Hippel 1986). First, the "ahead on
an important market trend" variable was included because of its assumed effect
on the commercial attractiveness of innovations developed by users residing at
a leading-edge position in a market. Market needs are not static---they evolve,
and often they are driven by important underlying trends. If people are
distributed with respect to such trends as diffusion theory indicates, then
people at the leading edges of important trends will be experiencing needs
today (or this year) that the bulk of the market will experience tomorrow (or
next year). And, if users develop and modify products to satisfy their own
needs, then the innovations that lead users develop should later be attractive
to many. The expected benefits variable and its link to innovation likelihood
was derived from studies of industrial product and process innovations. These
showed that the greater the benefit an entity expects to obtain from a needed
innovation, the greater will be that entity's investment in obtaining a
solution, where a solution is an innovation either developed or purchased
(Schmookler 1966; Mansfield 1968).
={ Mansfield, E. ;
   Schmookler, J.
}

Empirical studies to date have confirmed lead user theory. Morrison, Roberts,
and Midgely (2004) studied the characteristics of innovating and non-innovating
users of computerized library information systems in a sample of Australian
libraries. They found that the two lead user characteristics were distributed
in a continuous, unimodal manner in that sample. They also found that the two
characteristics of lead users and the actual development of innovations by
users were highly correlated. Franke and von Hippel (2003b) confirmed these
findings in a study of innovating and non-innovating users of Apache web server
software. They also found that the commercial attractiveness of innovations
developed by users increased along with the strength of those users' lead user
characteristics.
={ Franke, N. ;
   Midgely, David ;
   Morrison, Pamela +19 ;
   Roberts, J. ;
   Apache web server software ;
   Lead users :
     Apache web server software and | library information search system and ;
   Library information search system
}

!_ Evidence of Innovation by Lead Users

Several studies have found that user innovation is largely the province of
users that have lead user characteristics, and that products lead users develop
often form the basis for commercial products. These general findings appear
robust: the studies have used a variety of techniques and have addressed a
variety of markets and innovator types. Brief reviews of four studies will
convey the essence of what has been found.

!_ Innovation in Industrial Product User Firms

In the first empirical study of lead users' role in innovation, Urban and von
Hippel (1988) studied user innovation activity related to a type of software
used to design printed circuit boards. A major market trend to which printed
circuit computer-aided design software (PC-CAD) must respond is the steady
movement toward packing electronic circuitry more densely onto circuit boards.
Higher density means one that can shrink boards in overall size and that
enables the circuits they contain to operate faster---both strongly desired
attributes. Designing a board at the leading edge of what is technically
attainable in density at any particular time is a very demanding task. It
involves some combination of learning to make the printed circuit wires
narrower, learning how to add more layers of circuitry to a board, and using
smaller electronic components.
={ Urban, G. +1 ;
   Lead users :
     printed circuit CAD software and +3 ;
   Lead users :
     printed circuit CAD software and +3 ;
   Printed circuit CAD software +3
}

To explore the link between user innovation and needs at the leading edge of
the density trend, Urban and von Hippel collected a sample of 138 user-firm
employees who had attended a trade show on the topic of PC-CAD. To learn the
position of each firm on the density trend, they asked questions about the
density of the boards that each PC-CAD user firm was currently producing. To
learn about each user's likely expected benefits from improvements to PC-CAD,
they asked questions about how satisfied each respondent was with their firm's
present PC-CAD capabilities. To learn about users' innovation activities, they
asked questions about whether each firm had modified or built its own PC-CAD
software for its own in-house use.

Users' responses were cluster analyzed, and clear lead user (n = 38) and
non-lead-user (n = 98) clusters were found. Users in the lead user cluster were
those that made the densest boards on average and that also were dissatisfied
with their PC-CAD capabilities. In other words, they were at the leading edge
of an important market trend, and they had a high incentive to innovate to
improve their capabilities. Strikingly, 87 percent of users in the lead user
cluster reported either developing or modifying the PC-CAD software that they
used. In contrast, only 1 percent of non-lead users reported this type of
innovation. Clearly, in this case user innovation was very strongly
concentrated in the lead user segment of the user population. A discriminant
analysis on indicated that "build own system" was the most important indicator
of membership in the lead user cluster. The discriminant analysis had 95.6
percent correct classification of cluster membership.

The commercial attractiveness of PC-CAD solutions developed by lead users was
high. This was tested by determining whether lead users and more ordinary users
preferred a new PC-CAD system concept containing features developed by lead
users over the best commercial PC-CAD system available at the time of the study
(as determined by a large PC-CAD system manufacturer's competitive analysis)
and two additional concepts. The concept containing lead user features was
significantly preferred at even twice the price (p < 0.01).
={ Lead users :
     commercial attractiveness of
}

!_ Innovation in Libraries
={ Lead users :
     library information search system and +11 ;
   Library information search system +11
}

Morrison, Roberts, and von Hippel (2000) explored user modifications made by
Australian libraries to computerized information search systems called Online
Public Access systems ("OPACs"). Libraries might not seem the most likely spot
for technological innovators to lurk. However, computer technologies and the
Internet have had a major effect on how libraries are run, and many libraries
now have in-house programming expertise. Computerized search methods for
libraries were initially developed by advanced and technically sophisticated
user institutions. Development began in the United States in the 1970s with
work by major universities and the Library of Congress, with support provided
by grants from the federal government (Tedd 1994). Until roughly 1978, the only
such systems extant were those that had been developed by libraries for their
own use. In the late 1970s, the first commercial providers of computerized
search systems for libraries appeared in the United States, and by 1985 there
were at least 48 OPAC vendors in the United States alone (Matthews 1985). In
Australia (site of the study sample), OPAC adoption began about 8 years later
than in the United States (Tedd 1994).
={ Tedd, L. ;
   Roberts, J. +3
}

Morrison, Roberts, and I obtained responses from 102 Australian libraries that
were users of OPACs. We found that 26 percent of these had in fact modified
their OPAC hardware or software far beyond the user-adjustment capabilities
provided by the system manufacturers. The types of innovations that the
libraries developed varied widely according to local needs. For example, the
library that modified its OPAC to "add book retrieval instructions for staff
and patrons" (table 2.2) did so because its collection of books was distributed
in a complex way across a number of buildings--- making it difficult for staff
and patrons to find books without precise directions. There was little
duplication of innovations except in the case of adding Internet search
capabilities to OPACs. In that unusual case, nine libraries went ahead and did
the programming needed to add this important feature in advance of its being
offered by the manufacturers of their systems.

!_ Table 2.2
OPAC modifications created by users served a wide variety of functions.

table{~h c2; 50; 50;

Improved library management
Improved information-search capabilities

Add library patron summary statistics
Integrate images in records (2)

Add library identifiers
Combined menu/command searches

Add location records for physical audit
Add title sorting and short title listing

Add book retrieval instructions for staff and patrons
Add fast access key commands

Add CD ROM System backup
Add multilingual search formats \\  key word searches (2)

Add book access control based on copyright
Add topic linking and subject access

Patrons can check their status via OPAC
Add prior search recall feature

Patrons can reserve books via OPAC (2)
Add search "navigation aids"

Remote access to OPAC by different systems
Add different hierarchical searches

Add graduated system access via password
Access to other libraries' catalogs (2)

Add interfaces to other in-house IT systems
Add or customize web interface (9)

  Word processing and correspondence (2)
  Hot links for topics

  Umbrella for local information collection (2)
  Extended searches

  Local systems adaptation
  Hot links for source material

}table

Source of data: Morrison et al. 2000, table 1. Number of users (if more than
one) developing functionally similar innovations is shown in parentheses after
description of innovation.

The libraries in the sample were asked to rank themselves on a number of
characteristics, including "leading edge status" (LES). (Leading edge status, a
construct developed by Morrison, is related to and highly correlated with the
lead user construct (in this sample, ρ ,{(LES, CLU)}, = 0.904, /{p}/ = 0.000).
~{ LES contains four types of measures. Three ("benefits recognized early,"
"high benefits expected," and "direct elicitation of the construct") contain
the core components of the lead user construct. The fourth ("applications
generation") is a measure of a number of innovation-related activities in which
users might engage: they "suggest new applications," they "pioneer those
applications," and (because they have needs or problems earlier than their
peers) they may be "used as a test site" (Morrison, Midgely, and Roberts 2004).
}~ Self-evaluation bias was checked for by asking respondents to name other
libraries they regarded as having the characteristics of lead users.
Self-evaluations and evaluations by others did not differ significantly.
={ Midgely, David ;
   Morrison, Pamela ;
   Roberts, J.
}

Libraries that had modified their OPAC systems were found to have significantly
higher LES---that is, to be lead users. They were also found to have
significantly higher incentives to make modifications than non-innovators,
better in-house technical skills, and fewer "external resources" (for example,
they found it difficult to find outside vendors to develop the modifications
they wanted for them). Application of these four variables in a logit model
classified libraries into innovator and non-innovator categories with an
accuracy of 88 percent (table 2.3).

!_ Table 2.3
Factors associated with innovating in librararies (logit model). χ^{2}^/,{4}, =
33.85; ρ^{2}^ = 0.40; classification rate = 87.78%.

table{~h c3; 40; 30; 30;

~
Coefficient
Standard error

Leading-edge status
1.862
0.601

Lack of incentive to modify
--0.845
0.436

Lack of in-house technology skills
--1.069
0.412

Lack of external resources
0.695
0.456

Constant
--2.593
0.556

}table

Source: Morrison et al. 2000, table 6.

The commercial value of user-developed innovations in the library OPAC sample
was assessed in a relatively informal way. Two development mangers employed by
the Australian branches of two large OPAC manufacturers were asked to evaluate
the commercial value of each user innovation in the sample. They were asked two
questions about each: (1) "How important commercially to your firm is the
functionality added to OPACs by this user-developed modification?" (2) "How
novel was the information contained in the user innovation to your firm at the
time that innovation was developed?" Responses from both managers indicated
that about 70 percent (25 out of 39) of the user modifications provided
functionality improvements of at least "medium" commercial importance to
OPACs---and in fact many of the functions were eventually incorporated in the
OPACs the manufacturers sold. However, the managers also felt that their firms
generally already knew about the lead users' needs when the users developed
their solutions, and that the innovations the users developed provided novel
information to their company only in 10--20 percent of the cases. (Even when
manufacturers learn about lead users' needs early, they may not think it
profitable to develop their own solution for an "emerging" need until years
later. I will develop this point in chapter 4.)
={ Lead users :
     commercial attractiveness of ;
   Manufacturers :
     innovation and | lead users and
}

!_ "Consumer" Innovation in Sports Communities
={ Franke, N. +11 ;
   Shah, S. +11 ;
   Innovation :
     and sporting equipment +11 ;
   Lead users :
     manufacturers and +11 ;
   Sporting equipment :
     lead users and +11
}

% check manufacturers ref, see previous paragraph

Franke and Shah (2003) studied user innovation in four communities of sports
enthusiasts. The communities, all located in Germany, were focused on four very
different sports.
={ Manufacturers :
     innovation and | lead users and
}

One community was devoted to canyoning, a new sport popular in the Alps.
Canyoning combines mountain climbing, abseiling (rappelling), and swimming in
canyons. Members do things like rappel down the middle of an active waterfall
into a canyon below. Canyoning requires significant skill and involves physical
risk. It is also a sport in rapid evolution as participants try new challenges
and explore the edges of what is both achievable and fun.

The second community studied was devoted to sailplaning. Sailplaning or
gliding, a more mature sport than canyoning, involves flying in a closed,
engineless glider carrying one or two people. A powered plane tows the glider
to a desired altitude by means of a rope; then the rope is dropped and the
engineless glider flies on its own, using thermal updrafts in the atmosphere to
gain altitude as possible. The sailplaning community studied by Franke and Shah
consisted of students of technical universities in Germany who shared an
interest in sailplaning and in building their own sailplanes.

Boardercross was the focus of the third community. In this sport, six
snowboarders compete simultaneously in a downhill race. Racetracks vary, but
each is likely to incorporate tunnels, steep curves, water holes, and jumps.
The informal community studied consisted of semi-professional athletes from all
over the world who met in as many as ten competitions a year in Europe, in
North America, and in Japan.

The fourth community studied was a group of semi-professional cyclists with
various significant handicaps, such as cerebral palsy or an amputated limb.
Such individuals must often design or make improvements to their equipment to
accommodate their particular disabilities. These athletes knew each other well
from national and international competitions, training sessions, and seminars
sponsored by the Deutscher Sportbund (German National Sports Council).

A total of 197 respondents (a response rate of 37.8 percent) answered a
questionnaire about innovation activities in their communities. Thirty-two
percent reported that they had developed or modified equipment they used for
their sport. The rate of innovation varied among the sports, the high being 41
percent of the sailplane enthusiasts reporting innovating and the low being 18
percent of the boardercross snowboarders reporting. (The complexity of the
equipment used in the various sports probably had something to do with this
variation: a sailplane has many more components than a snowboard.)

The innovations developed varied a great deal. In the sailplane community,
users developed innovations ranging from a rocket-assisted emergency ejection
system to improvements in cockpit ventilation. Snowboarders invented such
things as improved boots and bindings. Canyoners' inventions included very
specialized solutions, such as a way to cut loose a trapped rope by using a
chemical etchant. With respect to commercial potential,
={ Lead users :
     commercial attractiveness of
}

Franke and Shah found that 23 percent of the user-developed innovations
reported were or soon would be produced for sale by a manufacturer. Franke and
Shah found that users who innovated were significantly higher on measures of
the two lead user characteristics than users who did not innovate (table 2.4).
They also found that the innovators spent more time in sporting and
community-related activities and felt they had a more central role in the
community.

!_ Table 2.4
Factors associated with innovation in sports communities.

table{~h c4; 55; 15; 15; 15;

~
Innovators^{a}^
Non-innovators^{b}^
Significance of difference^{c}^

Time in community
~
~
~

Years as a community member
4.46
3.17
p < 0.01

Days per year spent with community members
43.07
32.73
p < 0.05

Days per year spent participating in the sport
72.48
68.71
not significant

Role in community^{d}^
~
~
~

"I am a very active member of the community."
2.85
3.82
p < 0.01


"I get together with members of the community for activities that are not related to the sport (movies, dinner parties, etc.)."
3.39
4.14
p < 0.05

"The community takes my opinion into account when making decisions"
2.89
3.61
p < 0.05

Lead user characteristic 1: being ahead of the trend^{d}^
~
~
~

"I usually find out about new products and solutions earlier than others."
2.71
4.03
p < 0.001

"I have benefited significantly by the early adoption and use of new products."
3.58
4.34
p < 0.01

"I have tested prototype versions of new products for manufacturers."
4.94
5.65
p < 0.05

"In my sport I am regarded as being on the "cutting edge."
4.56
5.38
p < 0.01


"I improved and developed new techniques in boardercrossing."
4.29
5.84
p < 0.001

Lead user characteristic 2: high benefit from innovation^{d}^
~
~
~

"I have new needs which are not satisfied by existing products."
3.27
4.38
p < 0.001


"I am dissatisfied with the existing equipment."
3.90
5.13
p < 0.001

}table

Source: Franke and Shah 2003, table 3. \\
a. All values are means; n = 60. \\
b. All values are means; n = 129. \\
c. Two-tailed t-tests for independent samples. \\
d. Rated on seven-point scale, with 1 = very accurate and 7 = not accurate at all. Two-tailed t-tests for independent samples.

!_ Innovation among Hospital Surgeons
={ Surgical equipment +4 ;
   Lead users :
     surgical equipment and +4
}

Lüthje (2003) explored innovations developed by surgeons working at university
clinics in Germany. Ten such clinics were chosen randomly, and 262 surgeons
responded to Lüthje's questionnaire---a response rate of 32.6 percent. Of the
university surgeons responding, 22 percent reported developing or improving
some item(s) of medical equipment for use in their own practices. Using a logit
model to determine the influence of user characteristics on innovation
activity, Lüthje found that innovating surgeons tended to be lead users (p <
0.01). He also found that solutions to problems encountered in their own
surgical practices were the primary benefit that the innovating surgeons
expected to obtain from the solutions they developed (p < 0.01). In addition,
he found that the level of technical knowledge the surgeon held was
significantly correlated with innovation (p < 0.05). Also, perhaps as one might
expect in the field of medicine, the "contextual barrier" of concerns about
legal problems and liability risks was found to have a strongly significant
negative correlation with the likelihood of user invention by surgeons (p <
0.01).
={ Lüthje, C. +1 ;
   Sticky information :
     toolkits and
}

With respect to the commercial value of the innovations the lead user surgeons
had developed, Lüthje reported that 48 percent of the innovations developed by
his lead user respondents were or soon would be marketed by manufacturers of
medical equipment.

!_ Discussion

The studies reviewed in this chapter all found that user innovations in general
and commercially attractive ones in particular tended to be developed by lead
users. These studies were set in a range of fields, but all were focused on
hardware innovations or on information innovations such as new software. It is
therefore important to point out that, in many fields, innovation in techniques
is at least as important as equipment innovation. For example, many novel
surgical operations are performed with standard equipment (such as scalpels),
and many novel innovations in snowboarding are based on existing, unmodified
equipment. Technique-only innovations are also likely to be the work of lead
users, and indeed many of the equipment innovations documented in the studies
reviewed here involved innovations in technique as well as innovations in
equipment.
={ Lead users :
     commercial attractiveness of +1 ;
   Users :
     innovation process and +1
}

Despite the strength of the findings, many interesting puzzles remain that can
be addressed by the further development of lead user theory. For example,
empirical studies of innovation by lead users are unlikely to have sampled the
world's foremost lead users. Thus, in effect, the studies reviewed here
determined lead users to be those highest on lead user characteristics that
were within their samples. Perhaps other samples could have been obtained in
each of the fields studied containing users that were even more "leading edge"
with respect to relevant market trends. If so, why were the samples of
moderately leading-edge users showing user innovation if user innovation is
concentrated among "extreme" lead users? There are at least three possible
explanations. First, most of the studies of user innovation probably included
users reasonably close to the global leading edge in their samples. Had the
"top" users been included, perhaps the result would have been that still more
attractive user innovations would have been found. Second, it may be that the
needs of local user communities differ, and so local lead users really may be
the world's lead users with respect to their particular needs. Third, even if a
sample contains lead users that are not near the global top with respect to
lead users' characteristics, local lead users might still have reasons to
(re)develop innovations locally. For example, it might be cheaper, faster, more
interesting, or more enjoyable to innovate than to search for a similar
innovation that a "global top" lead user might already have developed.
={ Economic benefit, expectations of by lead users ;
   Innovation process ;
   Lead users :
     economic benefit, expectations of ;
   Local information ;
   Users :
     low-cost innovation niches of
}

1~ 3 Why Many Users Want Custom Products
={ Custom products :
     heterogeneity of user needs and +42 | users and +42 ;
   User need +42 ;
   Users :
     custom products and +42 | innovation and +42 | needs of
}

The high rates of user innovation documented in chapter 2 suggest that many
users may want custom products. Why should this be so? I will argue that it is
because many users have needs that differ in detail, and many also have both
sufficient willingness to pay and sufficient resources to obtain a custom
product that is just right for their individual needs. In this chapter, I first
present the case for heterogeneity of user needs. I then review a study that
explores users' heterogeneity of need and willingness to pay for product
customization.

!_ Heterogeneity of User Needs

If many individual users or user firms want something different in a product
type, it is said that heterogeneity of user need for that product type is high.
If users' needs are highly heterogeneous, only small numbers of users will tend
to want exactly the same thing. In such a case it is unlikely that
mass-produced products will precisely suit the needs of many users. Mass
manufacturers tend to want to build products that will appeal to more users
rather than fewer, so as to spread their fixed costs of development and
production. If many users want something different, and if they have adequate
interest and resources to get exactly the product they need, they will be
driven either to develop it for themselves or to pay a custom manufacturer to
develop it for them.
={ Manufacturers :
     custom products and | expectations of economic benefit by | innovation and
}

Are users' needs for new products (and services) often highly heterogeneous? A
test of reason suggests that they are. An individual's or a firm's need for a
many products depends on detailed considerations regarding the user's initial
state and resources, on the pathway the user must traverse to get from the
initial state to the preferred state, and on detailed considerations regarding
their preferred end state as well. These are likely to be different for each
individual user and for each user firm at some level of detail. This, in turn,
suggests that needs for many new products and services that are precisely right
for each user will differ: that needs for those products will be highly
heterogeneous.

Suppose, for example, that you decide you need a new item of household
furnishing. Your house is already furnished with hundreds of items, big and
small, and the new item must "fit in" properly. In addition, your precise needs
for the new item are likely to be affected by your living situation, your
resources, and your preferences. For example: "We need a new couch that Uncle
Bill will like, that the kids can jump on, that matches the wallpaper I adore,
that reflects my love of coral reefs and overall good taste, and that we can
afford." Many of these specific constraints are not results of current whim and
are not easy to change. Perhaps you can change the wallpaper, but you are less
likely to change Uncle Bill, your kids, your established tastes with respect to
a living environment, or your resource constraints.

The net result is that the most desired product characteristics might be
specific to each individual or firm. Of course, many will be willing to
satisfice---make compromises---on many items because of limits on the money or
time they have available to get exactly what they want. Thus, a serious
mountain biker may be willing to simply buy almost any couch on sale even if he
or she is not fully happy with it. On the other hand, that same biker may be
totally unwilling to compromise about getting mountain biking equipment that is
precisely right for his or her specific needs. In terms of industrial products,
NASA may insist on getting precisely right components for the Space Shuttle if
they affect mission safety, but may be willing to satisfice on other items.

!_ Evidence from Studies of User Innovation

Two studies of innovation by users provide indirect information on the
heterogeneity of user need. They provide descriptions of the functions of the
innovations developed by users in their samples. Inspection of these
descriptions shows a great deal of variation and few near-duplicates. Different
functionality, of course, implies that the developers of the products had
different needs. In the 2000 study of user modifications of library IT systems
by Morrison, Roberts, and von Hippel, discussed earlier, only 14 of 39
innovations are functionally similar to any other innovations in the sample. If
one type of functionality that was repeatedly developed ("web interface") is
excluded, the overlap is even lower (see table 2.2). Other responses by study
participants add to this impression of high heterogeneity of need among users.
Thirty percent of the respondents reported that their library IT system had
been highly customized by the manufacturer during installation to meet their
specific needs. In addition, 54 percent of study respondents agreed with the
statement "We would like to make additional improvements to our IT system
functionality that can't be made by simply adjusting the standard,
customer-accessible parameters provided by the supplier."
={ Morrison, Pamela ;
   Roberts, J. ;
   von Hippel, E. +34 ;
   Lead users :
     library information search system and ;
   Library information search system
}

Similar moderate overlap in the characteristics of user innovations can be seen
in innovation descriptions provided in the study of mountain biking by Lüthje,
Herstatt, and von Hippel (2002). In that study sample, I estimate that at most
10 of 43 innovations had functionality similar to that of another sample
member. This diversity makes sense: mountain biking, which outsiders might
assume is a single type of athletic activity, in fact has many subspecialties.
={ Herstatt, C. +7 ;
   Lüthje, C. +7 ;
   Mountain biking +7
}

As can be seen in table 3.1, the specializations of mountain bikers in the our
study sample involved very different mountain biking terrains, and important
variations in riding conditions and riding specializations. The innovations
users developed were appropriate to their own heterogeneous riding activities
and so were quite heterogeneous in function. Consider three examples drawn from
our study:

_* I ride on elevated, skinny planks and ladders, do jumps, steep technical
downhills, obstacles and big drops. Solution devised: I needed sophisticated
cycling armor and protective clothing. So I designed arm and leg armor, chest
protection, shorts, pants and a jacket that enable me to try harder things with
less fear of injury.

_* I do back-country touring and needed a way to easily lift and carry a fully
loaded mountain bike on the sides of steep hills and mountains and dangle it
over cliffs as I climbed. Solution devised: I modified the top tube and the top
of my seat post to provide secure attachment points for a carrying strap, then
I modified a very plush and durable mountaineering sling to serve as the
over-shoulder strap. Because the strap sits up high, I only need to bend my
knees a little bit to lift the bike onto my shoulders, yet it is just high
enough to keep the front wheel from hitting when I am climbing a steep hill.
Eventually, I came up with a quick-release lateral strap to keep the main strap
from sliding off my shoulder, but it will easily break away if I fall or land
in a fast river and need to ditch my bike.

_* When riding on ice, my bike has no traction and I slip and fall. Solution
devised: I increased the traction of my tires by getting some metal studs used
by the auto industry for winter tires. Then I selected some mountain biking
tires with large blocks of rubber in the tread pattern, drilled a hole in the
center of each block and inserted a stud in each hole.

!_ Table 3.1
Activity specializations of innovating mountain bikers.

table{~h c6; 20; 13; 20; 13; 20; 14;

Preferred terrain
Number of bikers
Outside conditions
Number of bikers
Focus on particular riding abilities
Number of bikers

Fast downhill tracks (steep, drops, fast)
44 (39.6%)
Darkness, night riding
45 (40.5%)
Jumps, drops, stunts, obstacles
34 (30.6%)

Technical single tracks (up and down, rocky, jumps)
68 (61.3%)
Snow, ice, cold
60 (54.1%)
Technical ability/balance
22 (19.8%)

Smooth single tracks (hilly, rolling, speed, sand, hardpack)
13 (11.7%)
Rain, mud
53 (47.7%)
Fast descents / downhill
34 (30.6%)

Urban and streets
9 (8.1%)
Heat
15 (13.5%)
Endurance
9 (8.1%)

No special terrain preferred
5 (4.5%)
High altitude
10 (9.0%)
Climbing
17 (13%)

~
~
No extreme outside conditions
29 (26.1%)
Sprint
3 (2.7%)

~
~
~
~
No focus on specific riding ability
36 (32.4%)

}table

Source: Lüthje,Herstatt, and vonHippel 2002. This table includes the 111 users
in the study sample who had ideas for improvements to mountain biking
equipment. (Of these, 61 had actually gone on to build the equipment they
envisioned.) Many of these users reported experience in more than one category
of activity, so the sum in each column is higher than 111.

!_ Evidence from Studies of Market Segmentation

Empirical data on heterogeneity of demand for specific products and services
are sparse. Those most interested in studying the matter are generally mass
manufacturers of products and services for consumers---and they do not make a
practice of prospecting for heterogeneity. Instead, they are interested in
finding areas where users' needs are similar enough to represent profitable
markets for standard products produced in large volumes. Manufacturers
customarily seek such areas via market-segmentation studies that partition
markets into a very few segments---perhaps only three, four, or five. Each
segment identified consists of customers with relatively similar needs for a
particular product (Punj and Stewart 1983; Wind 1978). For example, toothpaste
manufacturers may divide their markets into segments such as boys and girls,
adults interested in tooth whitening, and so on.
={ Punj, G. ;
   Stewart, D. ;
   Wind, Y. ;
   Custom products :
     market segmentation and +3 ;
   Manufacturers :
     innovation and ;
   Marketing research +1
}

Since the 1970s, nearly all market-segmentation studies have been carried out
by means of cluster analysis (Green 1971; Green and Schaffer 1998). After
cluster analysis places each participant in the segment of the market most
closely matching his needs, a measure of within-segment need variation is
determined. This is the proportion of total variation that is within each
cluster, and it shows how much users' needs deviate from the averages in
"their" respective segments. If within-segment variation is low, users within
the segment will have fairly homogeneous needs, and so may be reasonably
satisfied with a standard product designed to serve all customers in their
segment. If it high, many users are likely to be dissatisfied---some seriously
so.
={ Green, P. ;
   Schaffer, C.
}

Within-segment variation is seldom reported in published studies, but a survey
of market-segmentation studies published in top-tier journals did find 15
studies reporting that statistic. These studies specified 5.5 clusters on
average, and had an average remaining within-cluster variance of 46 percent
(Franke and Reisinger 2003). Franke and von Hippel (2003b) found similar
results in an independent sample. In that study, an average of 3.7 market
segments were specified and 54 percent of total variance was left as
within-segment variation after the completion of cluster analysis. These data
suggest that heterogeneity of need might be very substantial among users in
many product categories. ~{ Cluster analysis does not specify the "right"
number of clusters---it simply segments a sample into smaller and smaller
clusters until the analyst calls a halt. Determining an appropriate number of
clusters within a sample can be done in different ways. Of course, it always
possible to say that "I only want to deal with three market segments, so I will
stop my analysis when my sample has been segmented into three clusters." More
commonly, analysts will examine the increase of squared error sums of each
step, and generally will view the optimal number of clusters as having been
reached when the plot shows a sudden "elbow" (Myers 1996). Since this technique
does not incorporate information on remaining within-cluster heterogeneity, it
can lead to solutions with a large amount of within-cluster variance. The
"cubic clustering criterion" (CCC) partially addresses this concern by
measuring the within-cluster homogeneity relative to the between-cluster
heterogeneity. It suggests choosing the number of clusters where this value
peaks (Milligan and Cooper 1985). However, this method appears to be rarely
used: Ketchen and Shook (1996) found it used in only 5 of 45 segmentation
studies they examined. }~
={ Franke, N. +20 ;
   Reisinger, H.
}

!_ A Study of Heterogeneity and Willingness To Pay

A need for a novel product not on the market must be accompanied by adequate
willingness to pay (and resources) if it is to be associated with the actual
development or purchase of a custom product. What is needed to reliably
establish the relationship among heterogeneity of demand, willingness to pay,
and custom product development or purchase is studies that address all three
factors in the same sample. My colleague Nikolaus Franke and I conducted one
such study in a population of users of web server software, a product used
primarily by industrial firms (Franke and von Hippel 2003b).

Franke and I looked in detail at users' needs for security features in Apache
web server software, and at users' willingness to pay for solutions that
precisely fit their needs. Apache web server software is open source software
that is explicitly designed to allow modification by anyone having appropriate
skills. Anyone may download open source software from the Internet and use it
without charge. Users are also explicitly granted the legal right to study the
software's source code, to modify the software, and to distribute modified or
unmodified versions to others. (See chapter 7 for a full discussion of open
source software.)
={ Apache web server software +16 ;
   Custom products :
     Apache web server software and +16 ;
   Lead users :
     Apache web server software and +16 ;
   Users :
     and paying for innovations
}

Apache web server software is used on web server computers connected to the
Internet. A web server's function is to respond to requests from Internet
browsers for particular documents or content. A typical server waits for
clients' requests, locates the requested resource, applies the requested method
to the resource, and sends the response back to the client. Web server software
began by offering relatively simple functionality. Over time, however, Apache
and other web server software programs have evolved into the complicated front
end for many of the technically demanding applications that now run on the
Internet. For example, web server software is now used to handle security and
authentication of users, to provide e-commerce shopping carts, and gateways to
databases. In the face of strong competition from commercial competitors
(including Microsoft and Sun/Netscape), the Apache web server has become the
most popular web server software on the Internet, used by 67 percent of the
many millions of World Wide Web sites extant in early 2004. It has also
received many industry awards for excellence.

Franke and I created a preliminary list of server security functions from
published and web-based sources. The preliminary list was evaluated and
corrected by experts in web server security and Apache web server software. We
eventually ended up with a list of 45 security functions that some or many
users might need. Solutions to some were already incorporated in the standard
Apache code downloadable by users, others were available in additional modules,
and a few were not yet addressed by any security module generally available to
the Apache community. (Security threats can emerge quickly and become matters
of great concern before a successful response is developed and offered to the
general community. A recent example is site flooding, a form of attack in which
vandals attempt to cause a website to fail by flooding it with a very large
number of simultaneous requests for a response.)

Users of the security functions of web server software are the webmasters
employed by firms to make sure that their software is up to date and functions
properly. A major portion of a webmaster's job is to ensure that the software
used is secure from attacks launched by those who wish illicit access or simply
want to cause the software to fail in some way. We collected responses to our
study questions from two samples of Apache webmasters: webmasters who posted a
question or an answer on a question at the Apache Usenet Forum ~{
http://groups-beta.google.com/group/comp.infosystems.www.servers.unix }~ and
webmasters who subscribed to a specialized online Apache newsgroup. ~{
http://modules.apache.org/ }~ This stratified sample gave us an adequate
representation of webmasters who both did and did not have the technical skills
needed to modify Apache security software to better fit their needs:
subscribers to apache-modules.org tend to have a higher level of technical
skills on average than those posting to the Apache Usenet Forum. Data were
obtained by means of an Internet-based questionnaire.

!_ The Heterogeneity of Users' Needs

Franke and I found the security module needs of Apache users were very
heterogeneous indeed both among those that had the in-house capability to write
code to modify Apache and those that did not. The calibrated coefficient of
heterogeneity, H,{c},, was 0.98, indicating that there was essentially no
tendency of the users to cluster beyond chance. (We defined the "heterogeneity
of need" in a group as the degree to which the needs of i individuals can be
satisfied with j standard products which optimally meet their needs. This means
that heterogeneity of need is high when many standard products are necessary to
satisfy the needs of i individuals and low when the needs can be satisfied by a
few standard products. The higher the coefficient the more heterogeneous are
the needs of users in a sample. If the calibrated heterogeneity coefficient
H,{c}, equals 1, there is no systematic tendency of the users to cluster. If it
is lower than 1, there is some tendency of the individuals to cluster. A
coefficient of 0 means that the needs of all individuals are exactly the same.
~{ To measure heterogeneity, Franke and I analyzed the extent to which j
standards, varying from [1; i], meet the needs of the i individuals in our
sample. Conceptually, we first locate a product in multi-dimensional need space
(dimensions = 45 in the case of our present study) that minimizes the distances
to each individual's needs. (This step is analogous to the Ward's method in
cluster analysis that also minimizes within cluster variation; see Punj and
Stewart 1983.) The "error" is then measured as the sum of squared Euclidean
distances. We then repeated these steps to determine the error for two
optimally positioned products, three products, and so on up to a number
equaling I -- 1. The sum of squared errors for all cases is then a simple
coefficient that measures how much the needs of i individuals can be satisfied
with j standard products. The "coefficient of heterogeneity" just specified is
sensitive both to the (average) /{distance}/ between the needs and for the
/{configuration}/ of the needs: when the needs tend to form clusters the
heterogeneity coefficient is lower than if they are evenly spread. To make the
coefficient comparable across different populations, we calibrate it using a
bootstrapping technique (Efron 1979) involving dividing the coefficient by the
expected value (this value is generated by averaging the heterogeneity of many
random distributions of heterogeneity of the same kind). The average random
heterogeneity coefficient is then an appropriate value for calibration
purposes: it assumes that there is no systematic relationship between the needs
of the individuals or between the need dimensions. }~ )
={ Franke, N. ;
   Punj, G. ;
   Stewart, D.
}

Even this understates the heterogeneity. Responding Apache webmasters went far
beyond the 45 security-related functions of web server software that we offered
for their evaluation. In our questionnaire we offered an open question asking
users to list up to four additional needs they experienced that were not
covered by the standard list. Nearly 50 percent used the opportunity to add
additional functions. When duplicates were eliminated, we found that 92
distinct additional security-related needs had been noted by one or more
webmaster users.~{ Conceptually, it can be possible to generate "one perfect
product" for everyone--- in which case heterogeneity of demand is zero---by
simply creating all the features wanted by anyone (45 + 92 features in the case
of this study), and incorporating them in the "one perfect product." Users
could then select the features they want from a menu contained in the one
perfect product to tailor it to their own tastes. Doing this is at least
conceptually possible in the case of software, but less so in the case of a
physical product for two reasons: (1) delivering all possible physical options
to everyone who buys the product would be expensive for physical goods (while
costing nothing extra in the case of information products); (2) some options
are mutually exclusive (an automobile cannot be both red and green at the same
time). }~

High heterogeneity of need in our sample suggests that there should be a high
interest in obtaining modifications to Apache---and indeed, overall
satisfaction with the existing version was only moderate.

!_ Willingness to Pay for Improvements

It is not enough to want a better-fitting custom product. One must also be
willing and able to pay to get what one wants. Those in the Apache sample who
did innovate were presumably willing to pay the price to do so. But how much
were the users in our sample---the innovators and the non-innovators--- willing
to pay /{now}/ for improvements? Estimating a user's willingness to pay (WTP)
is known to be a difficult task. Franke and I used the contingent valuation
method, in which respondents are directly asked how much they are willing to
pay for a product or service (Mitchell and Carson 1989). Results obtained by
that method often overestimate WTP significantly. Empirical studies that
compare expressed WTP with actual cash payments on average showed actual
spending behavior to be somewhat smaller than expressed WTP in the case of
private purchases (such as in our case). In contrast, they generally find
willingness to pay to be greatly overstated in the case of public goods such as
the removal of a road from a wilderness area. ~{ The difference between actual
willingness to pay and expressed willingness to pay is much lower for private
goods (our case) than for public goods. In the case of private goods, Loomis et
al. (1996) found the expressed willingness to pay for art prints to be twice
the actual WTP. Willis and Powe (1998) found that among visitors to a castle
the expressed WTP was 60 percent lower than the actual WTP. In the case of
public goods, Brown et al. (1996), in a study of willingness to pay for removal
of a road from a wilderness area, found the expressed WTP to be 4--6 times the
actual WTP. Lindsey and Knaap (1999), in a study of WTP for a public urban
greenway, found the expressed WTP to be 2-10 times the actual WPT. Neil et al.
(1994) found the expressed WTP for conserving an original painting in the
desert to be 9 times the actual WTP. Seip and Strand (1992) found that less
than 10 percent of those who expressed interest in paying to join an
environmental organization actually joined. }~
={ Carson, R. ;
   Mitchell, R.
}

To compensate for the likely overstatement of expressed relative to actual WTP
in our study, Franke and I conservatively deflated respondents' indicated
willingness to pay by 80 percent. (Although the product in question was
intended for private use, webmasters were talking about their willingness to
spend company money, not their own money.) We asked each user who had indicated
that he was not really satisfied with a function (i.e., whose satisfaction with
the respective function was 4 or less on a 7-point scale, where 1 = not
satisfied at all, and 7 = very satisfied) to estimate how much he would be
willing to pay to get a very satisfactory solution regarding this function.
After deflation, our sample of 137 webmasters said they were willing to pay
$700,000 in aggregate to modify web server software to a point that fully
satisfied them with respect to their security function needs. This amounts to
an average of $5,232 total willingness to pay per respondent. This is a
striking number because the price of commercial web server software similar to
Apache's for one server was about $1,100 at the time of our study (source:
www.sun.com, November 2001). If we assume that each webmaster was in charge of
ten servers on average, this means that each webmaster was willing to pay half
the price of a total server software package to get his heterogeneous needs for
security features better satisfied.

!_ Increased Satisfaction from Customization of Apache

Recall that it takes some technical skill to modify Apache web server software
by writing new code. In table 3.2, Franke and I examined only the technically
skilled users in our sample who claimed the capability of making modifications
to Apache web server software. For these technically skilled users, we found
significantly higher satisfaction levels among those that actually did
customize their software---but even the users that made modifications were not
fully satisfied.

!_ Table 3.2
Skilled users who customized their software were more satisfied than those who
did not customize.

table{~h c4; 55; 15; 15; 15;

~
Users who customized (n = 18)
Users who did not customize (n = 44)
Difference (one-tailed t-test)

Satisfaction with basic web server functionality
5.5
4.3
0.100

Satisfaction with authentication of client
3.0
1.0
0.001

Satisfaction with e-commerce-related functions
1.3
0.0
0.023

Satisfaction with within-site user access control
8.5
6.9
0.170

Satisfaction with other security functions
3.9
3.9
0.699

Overall satisfaction
4.3
2.6
0.010

}table

Source: Franke and von Hippel 2003, table 8. In this table, 45 individual
functions are grouped into five general categories. The satisfaction index
ranges from -21 to +21.

One might wonder why users with the ability to modify Apache closer to their
liking were not totally satisfied. The answer can be found in respondents'
judgments regarding how much effort it would require to modify Apache still
more to their liking. We asked all respondents who indicated dissatisfaction of
level 4 or lower with a specific function of Apache how much working time it
would cost them to improve the function to the point where they would judge it
to be very satisfactory (to be at a satisfaction level of 7). For the whole
sample and all dissatisfactions, we obtained a working time of 8,938
person-days necessary to get a very satisfactory solution. This equals $78 of
incremental benefit per incremental programmer working day ($716,758 divided by
8,938 days). This is clearly below the regular wages a skilled programmer gets.
Franke and I concluded from this that skilled users do not improve their
respective Apache versions to the point where they are perfectly satisfied
because the costs of doing so would exceed the benefits.

!_ Discussion

Heterogeneity of user need is likely to be high for many types of products.
Data are still scanty, but high heterogeneity of need is a very straightforward
explanation for why there is so much customization by users: many users have
"custom" needs for products and services.

Those interested can easily enhance their intuitions about heterogenity of user
need and related innovation by users. User innovation appears to be common
enough so that one can find examples for oneself in a reasonably small, casual
sample. Readers therefore may find it possible (and enjoyable) to do their own
informal tests of the matter. My own version of such a test is to ask the
students in one of my MIT classes (typically about 50 students) to think about
a particular product that many use, such as a backpack. I first ask them how
satisfied they are with their backpack. Initially, most will say "It's OK." But
after some discussion and thinking, a few complaints will slowly begin to
surface (slowly, I think, because we all take some dissatisfaction with our
products as the unremarkable norm). "It doesn't fit comfortably" in this or
that particular way. "When my lunch bag or thermos leaks the books and papers I
am carrying get wet---there should be a water proof partition." "I carry large
drawings to school rolled up in my backpack with the ends sticking out. They
are ruined if it rains and I have not taken the precaution of wrapping them in
plastic." Next, I ask whether any students have modified their backpacks to
better meet their needs. Interestingly enough, one or two typically have. Since
backpacks are not products of very high professional or hobby interest to most
users, the presence of even some user innovation to adapt to individual users'
unmet needs in such small, casual samples is an interesting intuition builder
with respect to the findings discussed in this chapter.

1~ 4 Users' Innovate-or-Buy Decisions
={ Users :
     innovation and +4 | innovate-or-buy decisions by +74
}

Why does a user wanting a custom product sometimes innovate for itself rather
than buying from a manufacturer of custom products? There is, after all, a
choice---at least it would seem so. However, if a user with the resources and
willingness to pay does decide to buy, it may be surprised to discover that it
is not so easy to find a manufacturer willing to make exactly what an
individual user wants. Of course, we all know that mass manufacturers with
businesses built around providing standard products in large numbers will be
reluctant to accommodate special requests. Consumers know this too, and few
will be so foolish as to contact a major soup producer like Campbell's with a
request for a special, "just-right" can of soup. But what about manufacturers
that specialize in custom products? Isn't it their business to respond to
special requests? To understand which way the innovate-or-buy choice will go,
one must consider both transaction costs and information asymmetries specific
to users and manufacturers. I will talk mainly about transaction costs in this
chapter and mainly about information asymmetries in chapter 5.
={ Custom products :
   users and +3 ;
   Innovation process +3 ;
   Manufacturers :
     innovation and +3 ;
   Transaction costs +3 ;
   Users :
     innovation process and +3 | and paying for innovations
}

I begin this chapter by discussing four specific and significant transaction
costs that affect users' innovate-or-buy decisions. Next I review a case study
that illustrates these. Then, I use a simple quantitative model to further
explore when user firms will find it more cost-effective to develop a
solution---a new product or service---for themselves rather than hiring a
manufacturer to solve the problem for them. Finally, I point out that
/{individual}/ users can sometimes be more inclined to innovate than one might
expect because they sometimes value the /{process}/ of innovating as well as
the novel product or service that is created.

!_ Users' vs. Manufacturers' Views of Innovation Opportunities
={ Agency costs +15 ;
   Manufacturers :
     agency costs and +15 ;
   Transaction costs :
     See also Agency costs ;
   Users :
     agency costs and +15 | transaction costs and +15
}

Three specific contributors to transaction costs---in addition to the "usual
suspects," such as opportunism---often have important effects on users'
decisions whether to buy a custom product or to develop it for themselves.
These are (1) differences between users' and manufacturers' views regarding
what constitutes a desirable solution, (2) differences in innovation quality
signaling requirements between user and manufacturer innovators, and (3)
differences in legal requirements placed on user and manufacturer innovators.
The first two of these factors involve considerations of agency costs. When a
user hires a manufacturer to develop a custom product, the user is a principal
that has hired the custom manufacturer as to act as its agent. When the
interests of the principal and the agent are not the same, agency costs will
result. Recall from chapter 1 that agency costs are (1) costs incurred to
monitor the agent to ensure that it follows the interests of the principal, (2)
the cost incurred by the agent to commit itself not to act against the
principal's interest (the "bonding cost"), and (3) costs associated with an
outcome that does not fully serve the interests of the principal (Jensen and
Meckling 1976). In the specific instance of product and service development,
agency considerations enter because a user's and a manufacturer's interests
with respect to the development of a custom product often differ significantly.
={ Jensen, M. ;
   Meckling, W.
}

!_ Preferences Regarding Solutions

Individual products and services are components of larger user solutions. A
user therefore wants a product that will make the best overall tradeoff between
solution quality and price. Sometimes the best overall tradeoff will result in
a willingness to pay a surprisingly large amount to get a solution component
precisely right. For example, an individual user may specify tennis racket
functionality that will fit her specific technique and relative strengths and
will be willing to pay a great deal for exactly that racket. Deviations in
racket functionality would require compensating modifications in her carefully
practiced and deeply ingrained hitting technique---a much more costly overall
solution from the user's point of view. In contrast, a user will be much less
concerned with precisely /{how}/ the desired functionality is attained. For
example, tennis players will typically be unconcerned about whether a tennis
racket is made from metal, carbon fiber, plastic or wood---or, for that matter,
from mud---if it performs precisely as desired. And, indeed, users have quickly
shifted to new types of rackets over the years as new materials promise a
better fit to their particular functional requirements.

Of course, the same thing is true in the case of products for industrial users.
For example, a firm with a need for a process machine may be willing to pay a
great deal for one that is precisely appropriate to the characteristics of the
input materials being processed, and to the skills of employees who will
operate the machine. Deviations in either matter would require compensating
modifications in material supply and employee training---likely to be a much
more costly overall solution from the user's point of view. In contrast, the
user firm will be much less concerned with precisely how the desired
functionality is achieved by the process machine, and will care only that it
performs precisely as specified.

Manufacturers faced with custom development requests from users make similar
calculations, but theirs revolve around attempting to conserve the
applicability of a low-cost (to them) solution. Manufacturers tend to
specialize in and gain competitive advantage from their capabilities in one or
a few specific solution types. They then seek to find as many profitable
applications for those solutions types as possible. For example, a specialist
in fabricating custom products from carbon fiber might find it profitable to
make any kind of product---from airplane wings to tennis rackets---as long as
they are made from carbon fiber. In contrast, that same manufacturer would have
no competitive advantage in---and so no profit from making--- any of these same
products from metal or wood.

Specializations in solution types can be very narrow indeed. For example,
thousands of manufacturers specialize in adhesive-based fastening solutions,
while other thousands specialize in mechanical fastening solutions involving
such things as metal screws and nails. Importantly, companies that produce
products and solution types that have close functional equivalence from the
user's point of view can look very different from the point of view of a
solution supplier. For example, a manufacturer of standard or custom adhesives
needs chemists on staff with an expertise in chemical formulation. It also
needs chemistry labs and production equipment designed to mix specialized
batches of chemicals on a small scale, and it needs the equipment, expertise
and regulatory approvals to package that kind of product in a way that is
convenient to the customer and also in line with regulatory safeguards. In
contrast, manufacturers specializing in standard or custom metal fastening
solutions need none of these things. What they need instead are mechanical
design engineers, a machine shop to build product prototypes and production
tooling, specialized metal-forming production equipment such as screw machines,
and so on.

Users, having an investment only in a need specification and not in a solution
type, want the best functional solution to their problem, independent of
solution type used. Manufacturers, in contrast, want to supply custom solutions
to users that utilize their existing expertise and production capabilities.
Thus, in the case of the two fastening technology alternatives just described,
users will prefer whatever solution approach works best. In contrast, adhesives
manufacturers will find it tremendously more attractive to create a solution
involving adhesive-based fastening, and manufacturers specializing in
mechanical fastening will similarly strongly prefer to offer to develop
solutions involving mechanical fastening.

The difference between users' incentives to get the best functional solution to
their need and specialist manufacturers' incentives to embed a specific
solution type in the product to be developed are a major source of agency costs
in custom product development, because there is typically an information
asymmetry between user and manufacturer with respect to what will be the best
solution. Manufacturers tend to know more than users about this and to have a
strong incentive to provide biased information to users in order to convince
them that the solution type in which they specialize is the best one to use.
Such biases will be difficult for users to detect because, again, they are less
expert than the suppliers in the various solution technologies that are
candidates.
={ Information asymmetries ;
   Users :
     information asymmetries of
}

Theoretically, this agency cost would disappear if it were possible to fully
specify a contract (Aghion and Tirole 1994; Bessen 2004). But in product
development, contracting can be problematic. Information regarding
characteristics of solutions and needs is inescapably incomplete at the time of
contracting---users cannot fully specify what they want in advance of trying
out prototype solutions, and manufacturers are not fully sure how planned
solution approaches will work out before investing in customer-specific
development.
={ Aghion, P. ;
   Bessen, J. ;
   Contracting ;
   Tirole, J.
}

!_ Users' Expectations

When users buy a product from manufacturers, they tend to expect a package of
other services to come along with the product they receive. However, when users
develop a product for themselves, some of these are not demanded or can be
supplied in a less formal, less expensive way by users for themselves. This set
of implicit expectations can raise the cost to a user of a custom solution
bought from a manufacturer relative to a home-developed solution.
={ Manufacturers :
     innovation and +11 ;
   Users :
     innovation and +11
}

Users typically expect a solution they have purchased to work correctly and
reliably "right out of the box." In effect, a sharp line is drawn between
product development at the manufacturer's site and routine, trouble-free usage
at the purchaser's site. When the user builds a product for itself, however,
both the development and the use functions are in the same organization and may
explicitly be overlapped. Repeated tests and repeated repairs and improvements
during early use are then more likely to be understood and tolerated as an
acceptable part of the development process.

A related difference in expectations has to do with field support for a product
that has been purchased rather than developed in house. In the case of a
purchased custom product, users expect that manufacturers will provide
replacement parts and service if needed. Responding to this expectation is
costly for a custom manufacturer. It must keep a record of what it has built
for each particular user, and of any special parts incorporated in that user's
products so that they can be built or purchased again if needed. In contrast,
if a user has developed a product for itself, it has people on site who know
details of its design. These employees will be capable of rebuilding or
repairing or redesigning the product /{ad hoc}/ if and as the need arises. (Of
course, if these knowledgeable employees leave the user firm while the product
they designed is still in use, such informality can prove costly.)

Manufacturers also must invest in indirect quality signals that may not have an
effect on actual quality, but instead are designed to assure both the specific
user being served and the market in general that the product being supplied is
of high quality. These represent another element of agency costs that
user-innovators do not incur. When users develop an innovation for themselves,
they end up intimately knowing the actual quality of the solution they have
developed, and knowing why and how it is appropriate to their task. As an
example, an engineer building a million-dollar process machine for in-house use
might feel it perfectly acceptable to install a precisely right and very cheap
computer controller made and prominently labeled by Lego, a manufacturer of
children's toys. (Lego provides computer controllers for some of its children's
building kit products.) But if that same engineer saw a Lego controller in a
million-dollar process machine his firm was purchasing from a specialist
high-end manufacturer, he might not know enough about the design details to
know that the Lego controller was precisely right for the application. In that
case, the engineer and his managers might well regard the seemingly
inappropriate brand name as an indirect signal of bad quality.

Manufacturers are often so concerned about a reputation for quality that they
refuse to take shortcuts that a customer specifically requests and that might
make sense for a particular customer, lest others get wind of what was done and
take it as a negative signal about the general quality of the firm's products.
For example, you may say to a maker of luxury custom cars: "I want to have a
custom car of your brand in my driveway---my friends will admire it. But I only
plan to drive it to the grocery store once in a while, so I only want a cheap
little engine. A luxury exterior combined with cheap parts is the best solution
for me in this application---just slap something together and keep the price
low." The maker is likely to respond: "We understand your need, but we cannot
be associated with any product of low quality. Someone else may look under the
hood some day, and that would damage our reputation as a maker of fine cars.
You must look elsewhere, or decide you are willing to pay the price to keep one
of our fine machines idle on your driveway."

!_ Differing Legal and Regulatory Requirements

Users that innovate do not generally face legal risk if the product they
develop fails and causes costs to themselves but not to others. In contrast,
manufacturers that develop and sell new products are regarded under US law as
also providing an implied warranty of "fitness for the intended use." If a
product does not meet this criterion, and if a different, written warranty is
not in place, manufacturers can be found liable for negligence with respect to
providing a defective design and failure to warn buyers (Barnes and Ulin 1984).
This simple difference can cause a large difference in exposure to liability by
innovators and so can drive up the costs of manufacturer-provided solutions
relative to user-provided ones.
={ Barnes, B. ;
   Ulin, D. ;
   Transaction costs +51 ;
   Users :
     transaction costs and +23
}

For example, a user firm that builds a novel process controller to improve its
plant operations must pay its own actual costs if the self-built controller
fails and ruins expensive materials being processed. On the other hand, if a
controller manufacturer designed the novel controller product and sold it to
customers, and a failure then occurred and could be traced back to a fault in
the design, the controller manufacturer is potentially liable for actual user
costs and punitive damages. It may also incur significant reputational losses
if the unhappy user broadcasts its complaints. The logical response of a
controller manufacturer to this higher risk is to charge more and/or to be much
more careful with respect to running exhaustive, expensive, and lengthy tests
before releasing a new product. The resulting increase in cost and delay for
obtaining a manufacturer-developed product can tend to tip users toward
building their own, in-house solutions.
={ Custom products :
     manufacturers and +2 ;
   Economic benefit, expectations of by lead users :
     by manufacturers +4 | by users +7 ;
   Manufacturers :
     expectations of economic benefit by +4
}

!_ Net Result

A net result of the foregoing considerations is that manufacturers often find
that developing a custom product for only one or a few users will be
unprofitable. In such cases, the transaction costs involved can make it cheaper
for users with appropriate capabilities to develop the product for themselves.
In larger markets, in contrast, fixed transaction costs will be spread over
many customers, and the economies of scale obtainable by producing for the
whole market may be substantial. In that case, it will likely be cheaper for
users to buy than to innovate. As a result, manufacturers, when contacted by a
user with a very specific request, will be keenly interested in how many others
are likely to want this solution or elements of it. If the answer is "few," a
custom manufacturer will be unlikely to accept the project.

Of course, manufacturers have an incentive to /{make}/ markets attractive from
their point of view. This can be done by deviating from precisely serving the
needs of a specific custom client in order to create a solution that will be
"good enough" for that client but at the same time of more interest to others.
Manufacturers may do this openly by arranging meetings among custom buyers with
similar needs, and then urging the group to come up with a common solution that
all will find acceptable. "After all," as the representative will say, "it is
clear that we cannot make a special product to suit each user, so all of you
must be prepared to make really difficult compromises!" More covertly,
manufacturers may simply ignore some of the specific requests of the specific
user client and make something that they expect to be a more general solution
instead.

The contrasting incentives of users and manufacturers with respect to
generality of need being served---and also with respect to the solution choice
issue discussed earlier---can result in a very frustrating and cloudy
interaction in which each party hides its best information and attempts to
manipulate others to its own advantage. With respect to generality of need,
sophisticated users understand custom suppliers' preference for a larger market
and attempt to argue convincingly that "everyone will want precisely what I am
asking you for." Manufacturers, in turn, know users have this incentive and so
will generally prefer to develop custom products for which they themselves have
a reasonable understanding of demand. Users are also aware of manufacturers'
strong preference for only producing products that embody their existing
solution expertise. To guard against the possibility that this incentive will
produce biased advice, they may attempt to shop around among a number of
suppliers offering different solution types and/or develop internal expertise
on solution possibilities and/or attempt to write better contracts. All these
attempts to induce and guard against bias involve agency costs.
={ Custom products :
     manufacturers and
}

!_ An Illustrative Case

A case study by Sarah Slaughter (1993) illustrates the impact of some of the
transaction costs discussed above related to users' innovate-or-buy decisions.
Slaughter studied patterns of innovation in stressed-skin panels, which are
used in some housing construction. The aspects of the panels studied were
related to installation, and so the users of these features were home builders
rather than home owners. When Slaughter contrasted users' costs of innovating
versus buying, she found that it was always much cheaper for the builder to
develop a solution for itself at a construction site than to ask a panel
manufacturer to do so.
={ Slaughter, S. +16 ;
   Stressed-skin panels +16
}

A stressed-skin panel can be visualized as a large 4-by-8-foot sandwich
consisting of two panels made of plywood with a layer of plastic foam glued in
between. The foam, about 4 inches thick, strongly bonds the two panels together
and also acts as a layer of thermal insulation. In 1989, manufacturing of
stressed-skin panels was a relatively concentrated industry; the four largest
manufacturers collectively having a 77 percent share of the market. The user
industry was much less concentrated: the four largest constructors of panelized
housing together had only 1 percent of the market for such housing in 1989.

In housing construction, stressed-skin panels are generally attached to strong
timber frames to form the outer shell of a house and to resist shear loads
(such as the force of the wind). To use the panels in this way, a number of
subsidiary inventions are required. For example, one must find a practical,
long-lasting way to attach panels to each other and to the floors, the roof,
and the frame. Also, one has to find a new way to run pipes and wires from
place to place because there are no empty spaces in the walls to put
them---panel interiors are filled with foam.

Stressed-skin panels were introduced into housing construction after World War
II. From then till 1989, the time of Slaughter's study, 34 innovations were
made in 12 functionally important areas to create a complete building system
for this type of construction. Slaughter studied the history of each of these
innovations and found that 82 percent had been developed by users of the
stressed-skin panels---residential builders---and only 18 percent by
manufacturers of stressed-skin panels. Sometimes more than one user developed
and implemented different approaches to the same functional problem (table
4.1). Builders freely revealed their innovations rather than protecting them
for proprietary advantage. They were passed from builder to builder by word of
mouth, published in trade magazines, and diffused widely. All were replicated
at building sites for years before any commercial panel manufacturer developed
and sold a solution to accomplish the same function.

Histories of the user-developed improvements to stressed-skin panel
construction showed that the user-innovator construction firms did not engage
in planned R&D projects. Instead, each innovation was an immediate response to
a problem encountered in the course of a construction project. Once a problem
was encountered, the innovating builder typically developed and fabricated a
solution at great speed, using skills, materials, and equipment on hand at the
construction site. Builders reported that the average time from discovery of
the problem to installation of the completed solution on the site was only half
a day. The total cost of each innovation, including time, equipment, and
materials, averaged $153.

!_ Example: Installing Wiring in a Stressed-Skin Panel

A builder was faced with the immediate problem of how to route wires through
the foam interior of panels to wall switches located in the middle of the
panels. He did not want cut grooves or channels through the surfaces of the
panels to these locations---that would dangerously reduce the panels'
structural strength. His inventive solution was to mount an electrically heated
wire on the tip of a long pole and simply push the heated tip through the
center insulation layer of the panel. As he pushed, the electrically heated tip
quickly melted a channel through the foam plastic insulation from the edge of
the panel to the desired spot. Wires were then pulled through this channel.

!_ Table 4.1
Users would have found it much more costly to get custom solutions from
manufacturers. The costs of user-developed innovations in stressed-skin panels
were very low.

table{~h c5; 40; 17; 17; 6; 20;

Function
Average user development time (days)
Average user development cost
N
Minimimum cost of waiting for manufacturer to deliver

Framing of openings in panels
0.1
$20
1
$1,400

Structural connection between panels
0.1
30
2
$1,400

Ventilation of panels on roof
0.1
32
2
$28,000

Insulated connection between panels
0.1
41
3
$2,800

Corner connection between panels
0.2
60
1
$2,800

Installation of HVAC in panels
0.2
60
2
$2,800

Installation of wiring in panels
0.2
79
7
$2,800

Connection of panels to roof
0.2
80
1
$2,800

Add insect repellency to panels
0.4
123
3
$70,000

Connect panels to foundation
0.5
160
1
$1,400

Connect panels to frames
1.2
377
3
$2,800

Development of curved panels
5.0
1,500
1
$28,000

Average for all innovations
0.5
$153
~
$12,367

}table

N represents number of innovations developed by /{users}/ to carry out each
listed function. Source: Slaughter 1993, tables 4 and 5. Costs and times shown
are averaged for all user-developed innovations in each functional category.
(The six /{manufacturer}/-developed innovations in Slaughter's sample are not
included in this table.)

The builder-innovator reported that the total time to develop the innovation
was only an hour, and that the total cost for time and materials equaled $40.
How could it cost so little and take so little time? The builder explained that
using hot wires to slice sheets of plastic foam insulation into pieces of a
required length is a technique known to builders. His idea as to how to modify
the slicing technique to melt channels instead came to him quickly. To test the
idea, he immediately sent a worker to an electrical supply house to get some
nichrome wire (a type of high-resistance wire often used as an electrical
heating element), attached the wire to a tip of a pole, and tried the solution
on a panel at the building site---and it worked!

This solution was described in detail in an article in a builder's magazine and
was widely imitated. A panel manufacturer's eventual response (after the user
solution had spread for a number of years) was to manufacture a panel with a
channel for wires pre-molded into the plastic foam interior of the panel. This
solution is only sometimes satisfactory. Builders often do not want to locate
switch boxes at the height of the premolded channel. Also, sometimes
construction workers will install some panels upside down in error, and the
preformed channels will then not be continuous between one panel and the next.
In such cases, the original, user-developed solution is again resorted to.

!_ Example: Creating a Curved Panel
={ Manufacturers :
     transaction costs and +8
}

A builder was constructing a custom house with large, curved windows. Curved
stressed-skin panels were needed to fill in the space above and below these
windows, but panel manufacturers only sold flat panels at that time. The
builder facing the problem could not simply buy standard flat panels and bend
them into curved ones at the construction site---completed panels are rigid by
design. So he bought plywood and plastic foam at a local building supply house
and slowly bent each panel component separately over a curved frame quickly
built at the construction site. He then bonded all three elements together with
glue to create strong curved panels that would maintain their shape over time.

To determine whether users' decisions to innovate rather than buy made economic
sense for them, Slaughter calculated, in a very conservative way, what it would
have cost users to buy a manufacturer-developed solution embodied in a
manufactured panel rather than build a solution for themselves. Her estimates
included only the cost of the delay a user-builder would incur while waiting
for delivery of a panel incorporating a manufacturer's solution. Delay in
obtaining a solution to a problem encountered at a construction site is costly
for a builder, because the schedule of deliveries, subcontractors, and other
activities must then be altered. For example, if installation of a panel is
delayed, one must also reschedule the arrival of the subcontractor hired to run
wires through it, the contractor hired to paint it, and so on. Slaughter
estimated the cost of delay to a builder at $280 per crew per day of delay
(Means 1989). To compute delay times, she assumed that a manufacturer would
always be willing to supply the special item a user requested. She also assumed
that no time elapsed while the manufacturer learned about the need, contracted
to do the job, designed a solution, and obtained needed regulatory approvals.
She then asked panel manufacturers to estimate how long it would take them to
simply construct a panel with the solution needed and deliver it to the
construction site. Delay times computed in this manner ranged from 5 days for
some innovations to 250 days for the longest-term one and averaged 44 days.
={ Means, R. ;
   Economic benefit, expectations of by lead users :
     by manufacturers +2 | by users +2 ;
   Manufacturers :
     expectations of economic benefit by +2 | innovation and +5
}

The conservative nature of this calculation is very clear. For example,
Slaughter points out that the regulatory requirements for building components,
not included, are in fact much more stringent for manufacturers than for
user-builders in the field of residential construction. Manufacturers
delivering products can be required to provide test data demonstrating
compliance with local building codes for each locality served. Testing new
products for compliance in a locality can take from a month to several years,
and explicit code approval often takes several additional years. In contrast, a
builder that innovates need only convince the local building inspector that
what he has done meets code or performance requirements--- often a much easier
task (Ehrenkrantz Group 1979; Duke 1988).
={ Duke, R. ;
   Ehrenkrantz Group
}

Despite her very conservative method of calculation, Slaughter found the costs
to users of obtaining a builder solution to be at least 100 times the actual
costs of developing a solution for themselves (table 4.1). Clearly, users'
decisions to innovate rather than buy made economic sense in this case.

!_ Modeling Users' Innovate-or-Buy Decisions

In this section I summarize the core of the argument discussed in this chapter
via a simple quantitative model developed with Carliss Baldwin. Our goal is to
offer additional clarity by trading off the richness of the qualitative
argument for simplicity.
={ Baldwin, C. +24 }

Whether a user firm should innovate or buy is a variant of a well-known
problem: where one should place an activity in a supply chain. In any
real-world case many complexities enter. In the model that follows, Baldwin and
I ignore most of these and consider a simple base case focused on the impact of
transaction costs on users' innovate-or-buy considerations. The model deals
with manufacturing firms and user firms rather than individual users. We assume
that user firms and manufacturer firms both will hire designers from the same
homogeneous pool if they elect to solve a user problem. We also assume that
both user firms and manufacturer firms will incur the same costs to solve a
specific user problem. For example, they will have the same costs to monitor
the performance of the designer employees they hire. In this way we simplify
our innovate-or-buy problem to one of transaction costs only.

If there are no transaction costs (for example, no costs to write and enforce a
contract), then by Coase's theorem a user will be indifferent between making or
buying a solution to its problem. But in the real world there are transaction
costs, and so a user will generally prefer to either make or buy. Which, from
the point of view of minimizing overall costs of obtaining a problem solution,
is the better choice under any given circumstances?
={ Coase, R. }

Let V,{ij}, be the value of a solution to problem j for user i. Let N,{j}, be
the number of users having problem j. Let Wh,{j}, be the cost of solving
problem j, where W = hourly wage and h,{j}, = hours required to solve it. Let
P,{j}, be the price charged by a manufacturer for a solution to problem j. Let
T be fixed or "setup" transaction costs, such as writing a general contract for
buyers of a solution to problem j. Let t be variable or "frictional"
transaction costs, such as tailoring the general contract to a specific
customer.

To explore this problem we make two assumptions. First, we assume that a user
firm knows its own problems and the value of a solution to itself, V,{ij},.
Second, we assume that a manufacturer knows the number of users having each
problem, N,{j},, and the value of solutions for each problem for all users,
V,{ij},.

These assumptions are in line with real-world incentives of users and
manufacturers, although information stickiness generally prevents firms from
getting full information. That is, users have a high incentive to know their
own problems and the value to them of a solution. Manufacturers, in turn, have
an incentive to invest in understanding the nature of problems faced by users
in the target market, the number of users affected, and the value that the
users would attach to getting a solution in order to determine the potential
profitability of markets from their point of view.
={ Sticky information :
     innovation and
}

We first consider the user's payoff for solving a problem for itself. A user
has no transaction costs in dealing with itself, so a user's payoff for solving
problem j will be V,{ij}, - Wh,{j},. Therefore, a user will buy a solution from
an upstream manufacturer rather than develop one for itself if and only if P ≤
Wh,{j},.

Next we consider payoffs to a manufacturer for solving problem j. In this case,
transaction costs such as those discussed in earlier sections will be
encountered. With respect to transaction costs assume first that t = 0 but T >
0. Then, the manufacturer's payoff for solving problem j will be V,{ij}, -
Wh,{j},, which needs to be positive in order for the manufacturer to find
innovation attractive:

N,{j}, P,{j}, - Wh,{j}, - T > 0.

But, as we saw, P,{j}, ≤ Wh,{j}, if the user is to buy, so we may substitute
Wh,{j}, for P,{j}, in our inequality. Thus we obtain the following inequality
as a condition for the user to buy:

N,{j}, (Wh,{j},) - Wh,{j}, - T > 0,

or

N,{j}, > (T / Wh,{j},) + 1.

In other words, Baldwin and I find that the absolute lower bound on N is
greater than 1. This means that a single user will always prefer to solve a
unique problem j for itself (except in Coase's world, where T = 0, and the user
will be indifferent). If every problem is unique to a single user, users will
never choose to call on upstream manufacturers for solutions.
={ Coase, R. }

Now assume that T = 0 but t > 0. Then the condition for the user to buy rather
than to innovate for itself becomes

N,{j}, (Wh,{j}, - t) - Wh,{j}, > 0,

or equivalently (provided Wh,{j}, > t)

N,{j}, > Wh,{j}, / (Wh,{j}, - t) > 1.

Again, users will not call on upstream manufacturers to solve problems unique
to one user.

The findings from the simplified model, then, are the following: Problems
unique to one user will always be solved efficiently by users hiring designers
to work for them in house. In contrast, problems affecting more than a moderate
number of users, n, which is a function of the transaction costs, will be
efficiently solved by the manufacturer hiring designers to develop the needed
new product or service and then selling that solution to all users affected by
the problem. However, given sufficient levels of T and/or of t, problems
affecting more than one but fewer than n users will not be solved by a
manufacturer, and so there will be a market failure: Assuming an institutional
framework consisting only of independent users and manufacturers, multiple
users will have to solve the same problem independently.

As illustration, suppose that t = 0.25Wh,{j}, and T = 10Wh,{j},. Then,
combining the two expressions and solving for n yields

n = (11Wh,{j}, /0.75Wh,{j},) = 14.66.

The condition for the user to buy the innovation rather than innovate itself
becomes N,{j}, ≥ 15. For a number of users less than 15 but greater than 1,
there will be a wasteful multiplication of user effort: several users will
invest in developing the same innovation independently.

In a world that consists entirely of manufacturers and of users that do not
share the innovations they develop, the type of wasteful duplicative innovation
investment by users just described probably will occur often. As was discussed
earlier in this chapter, and as was illustrated by Slaughter's study,
substantial transaction costs might well be the norm. In addition, low numbers
of users having the same need---situations where N,{j}, is low---might also be
the norm in the case of functionally novel innovations. Functionally novel
innovations, as I will show later, tend to be developed by lead users, and lead
users are by definition at the leading (low-N,{j},) edge of markets.
={ Slaughter, S. ;
   Stressed-skin panels
}

When the type of market failure discussed above does occur, users will have an
incentive to search for institutional forms with a lower T and/or a lower t
than is associated with assignment of the problem to an upstream manufacturer.
One such institutional form involves interdependent innovation development
among multiple users (for example, the institutional form used successfully in
open source software projects that I will discuss in chapter 7). Baldwin and
Clark (2003) show how this form can work to solve the problem of wasteful user
innovation investments that were identified in our model. They show that, given
modularity in the software's architecture, it will pay for users participating
in open source software projects to generate and freely reveal some components
of the needed innovation, benefiting from the fact that other users are likely
to develop and reveal other components of that innovation. At the limit, the
wasteful duplication of users' innovative efforts noted above will be
eliminated; each innovation component will have been developed by only one
user, but will be shared by many.
={ Clark, K. }

!_ Benefiting from the Innovation Process
={ Innovation process +4 ;
   Users :
     innovation process and +4
}

Some individual users (not user firms) may decide to innovate for themselves
rather than buy even if a traditional accounting evaluation would show that
they had made a major investment in time and materials for an apparently minor
reward in product functionality. The reason is that individual users may gain
major rewards from the process of innovating, in addition to rewards from the
product being developed. Make-or-buy evaluations typically include factors such
as the time and materials that must be invested to develop a solution. These
costs are then compared with the likely benefits produced by the project's
"output"---the new product or service created---to determine whether the
project is worth doing. This was the type of comparison made by Slaughter, for
example, in assessing whether it would be better for the users to make or to
buy the stressed-skin panel innovations in her sample. However, in the case of
individual user-innovators, this type of assessment can provide too narrow a
perspective on what actually constitutes valuable project output. Specifically,
there is evidence that individuals sometimes greatly prize benefits derived
from their participation in the process of innovation. The process, they say,
can produce learning and enjoyment that is of high value to them.
={ Slaughter, S. ;
   Stressed-skin panels
}

In the introductory chapter, I pointed out that some recreational activities,
such as solving crossword puzzles, are clearly engaged in for process rewards
only: very few individuals value the end "product" of a completed puzzle. But
process rewards have also been found to be important for innovators that are
producing outputs that they and others do value (Hertel, Niedner, and Herrmann
2003; Lakhani and Wolf 2005). Lakhani and Wolf studied a sample of individuals
(n = 684, response rate = 34 percent) who had written new software code and
contributed it to an open source project. They asked the programmers to list
their three most important reasons for doing this. Fifty-eight percent of
respondents said that an important motivation for writing their code was that
they had a work need (33 percent), or a non-work need (30 percent) or both (5
percent) for the code itself. That is, they valued the project's "output" as
this is traditionally viewed. However, 45 percent said that one of their top
three reasons for writing code was intellectual stimulation, and 41 percent
said one of their top three reasons was to improve their own programming skills
(Lakhani and Wolf 2005, table 6). Elaborating on these responses, 61 percent of
respondents said that their participation in the open source project was their
most creative experience or was as creative as their most creative experience.
Also, more than 60 percent said that "if there were one more hour in the day"
they would always or often dedicate it to programming.
={ Herrmann, S. ;
   Hertel, G. ;
   Lakhani, K. ;
   Niedner, S. ;
   Wolf, B.
}

Csikszentmihalyi (1975, 1990, 1996) systematically studied the characteristics
of tasks that individuals find intrinsically rewarding, such as rock climbing.
He found that a level of challenge somewhere between boredom and fear is
important, and also that the experience of "flow" gained when one is fully
engaged in a task is intrinsically rewarding. Amabile (1996) proposes that
intrinsic motivation is a key determining factor in creativity. She defines a
creative task as one that is heuristic in nature (with no predetermined path to
solution), and defines a creative outcome as a novel and appropriate (useful)
response to such a task. Both conditions certainly can apply to the task of
developing a product or a service.
={ Amiable, T. ;
   Csikszentmihalyi, M.
}

In sum, to the extent that individual user-innovators benefit from the process
of developing or modifying a product as well as from the product actually
developed, they are likely to innovate even when the benefits expected from the
product itself are relatively low. (Employees of a firm may wish to experience
this type of intrinsic reward in their work as well, but managers and
commercial constraints may give them less of an opportunity to do so. Indeed,
"control over my own work" is cited by many programmers as a reason that they
enjoy creating code as volunteers on open source projects more than they enjoy
coding for their employers for pay.)

1~ 5 Users' Low-Cost Innovation Niches
={ Users :
     innovation and +50 | low-cost innovation niches of +50
}

!_ The Problem-Solving Process
={ Trial-and-error problem solving +11 }

Product and service development is at its core a problem-solving process.
Research into the nature of problem solving shows it to consist of trial and
error, directed by some amount of insight as to the direction in which a
solution might lie (Baron 1988). Trial and error has also been found to be
prominent in the problem-solving work of product and process development
(Marples 1961; Allen 1966; von Hippel and Tyre 1995; Thomke 1998, 2003).
={ Allen, T. ;
   Baron, J. ;
   Marples, D. ;
   Thomke, S. ;
   Tyre, M. ;
   von Hippel, E.
}

Trial-and-error problem solving can be envisioned as a four-phase cycle that is
typically repeated many times during the development of a new product or
service. Problem solvers first conceive of a problem and a related solution
based on their best knowledge and insight. Next, they build a physical or
virtual prototype of both the possible solution they have envisioned and the
intended use environment. Third, they run the experiment---that is, they
operate their prototyped solution and see what happens. Fourth and finally,
they analyze the result to understand what happened in the trial and to assess
the "error information" that they gained. (In the trial-and-error formulation
of the learning process, error is the new information or learning derived from
an experiment by an experimenter: it is the aspect(s) of the outcome that the
experimenter did not predict.) Developers then use the new learning to modify
and improve the solution under development before building and running a new
trial (figure 5.1).

Trial-and-error experimentation can be informal or formal; the underlying
principles are the same. As an example on the informal side, consider a user
experiencing a need and then developing what eventually turns out to be a new
product: the skateboard. In phase 1 of the cycle, the user combines need and
solution information into a product idea: "I am bored with roller skating. How
can I get down this hill in a more exciting way? Maybe it would be fun to put
my skates' wheels under a board and ride down on that." In phase 2, the user
builds a prototype by taking his skates apart and hammering the wheels onto the
underside of a board. In phase 3, he runs the experiment by climbing onto the
board and heading down the hill. In phase 4, he picks himself up from an
inaugural crash and thinks about the error information he has gained: "It is
harder to stay on this thing than I thought. What went wrong, and how can I
improve things before my next run down the hill?"

% (2) BUILD
% (3) RUN
% (4) ANALYZE
% (1) DESIGN
% DONE
% DESIGN REQUIREMENTS
% DESIGN ACTIVITY
% Changes in
% exogenous
% information
% Use learning from previous
% cycle(s) to conceive and design
% an improved solution.
% .
% Develop models and/or build
% prototypes to be used in
% running experiments.
% .
% Test model/prototype in real
% or simulated use environment.
% .
% Analyze findings from
% previous step and learn.
% .
% Figure 5.1
% The trial-and-error cycle of product development.

{di_evh_f5-1.png}image

!_ Figure 5.1
The trial-and-error cycle of product development.

As an example of more formal experimentation, consider a product-development
engineer working in a laboratory to improve the performance of an automobile
engine. In phase 1, need and solution information are again combined into a
design idea: "I need to improve engine fuel efficiency. I think that a more
even expansion of the flame in the cylinders is a possible solution direction,
and I think that changing the shape of the spark plug electrodes will improve
this." In phase 2, the engineer builds a spark plug incorporating her new idea.
In phase 3, she inserts the new spark plug into a lab test engine equipped with
the elaborate instrumentation needed to measure the very rapid propagation of a
flame in the cylinders of an auto engine and runs the test. In phase 4, she
feeds the data into a computer and analyzes the results. She asks: "Did the
change in spark plug design change the flame front as expected? Did it change
fuel efficiency? How can I use what I have learned from this trial to improve
things for the next one?"

In addition to the difference in formality, there is another important
difference between these two examples. In the first example, the skateboard
user was conducting trial and error with a full prototype of the intended
product in a real use environment---his own. In the second example, the
experimental spark plug might have been a full prototype of a real product, but
it probably consisted only of that portion of a real spark plug that actually
extends into a combustion chamber. Also, only /{aspects}/ of the use
environment were involved in the lab experiment. That is, the test engine was
not a real auto engine, and it was not being operated in a real car traveling
over real roads.

Experimentation is often carried out using simplified versions---models--- of
the product being designed and its intended use environment. These models can
be physical (as in the example just given), or they can be virtual (as in the
case of thought experiments or computer simulations). In a computer simulation,
both the product and the environment are represented in digital form, and their
interaction is tested entirely within a computer. For example, one might make a
digital model of an automobile and a crash barrier. One could then use a
computer to simulate the crash of the model car into the model barrier. One
would analyze the results by calculating the effects of that crash on the
structure of the car.

The value of using models rather than the real thing in experimentation is
twofold. First, it can reduce the cost of an experiment---it can be much
cheaper to crash a simulated BMW than a real one. Second, it can make
experimental results clearer by making them simpler or otherwise different than
real life. If one is trying to test the effect of a small change on car safety,
for example, it can be helpful to remove everything not related to that change
from the experiment. For example, if one is testing the way a particular wheel
suspension structure deforms in a crash, one does not have to know (or spend
time computing) how a taillight lens will react in the crash. Also, in a real
crash things happen only once and happen very fast. In a virtual crash executed
by computer, on the other hand, one can repeat the crash sequence over and
over, and can stretch time out or compress it exactly as one likes to better
understand what is happening (Thomke 2003).
={ Thomke, S. +2 }

Users and others experimenting with real prototypes in real use environments
can also modify things to make tests simpler and clearer. A restaurant chef,
for example, can make slight variations in just a small part of a recipe each
time a customer calls for it, in order to better understand what is happening
and make improvements. Similarly, a process machine user can experiment with
only a small portion of machine functioning over and over to test changes and
detect errors.

Sometimes designers will test a real experimental object in a real experimental
context only after experimenting with several generations of models that
isolate different aspects of the real and/or encompass increasing amounts of
the complexity of the real. Developers of pharmaceuticals, for example, might
begin by testing a candidate drug molecule against just the purified enzyme or
receptor it is intended to affect, then test it again and again against
successively more complex models of the human organism (tissue cultures, animal
models, etc.) before finally seeking to test its effect on real human patients
during clinical trials (Thomke, von Hippel, and Franke 1998).
={ Franke, N. ;
   von Hippel, E.
}

!_ Sticky Information
={ Sticky information +11 :
     innovation and +11
}

Any experiment is only as accurate as the information that is used as inputs.
If inputs are not accurate, outcomes will not be accurate: "garbage in, garbage
out."

The goal of product development and service development is to create a solution
that will satisfy needs of real users within real contexts of use. The more
complete and accurate the information on these factors, the higher the fidelity
of the models being tested. If information could be transferred costlessly from
place to place, the quality of the information available to problem solvers
would or could be independent of location. But if information is costly to
transfer, things are different. User-innovators, for example, will then have
better information about their needs and their use context than will
manufacturers. After all, they create and live in that type of information in
full fidelity! Manufacturer-innovators, on the other hand, must transfer that
information to themselves at some cost, and are unlikely to be able to obtain
it in full fidelity at any cost. However, manufacturers might well have a
higher-fidelity model of the solution types in which they specialize than users
have.
={ Information asymmetries +31 ;
   Local information +35 ;
   Users :
     information asymmetries of +31
}

It turns out that much information needed by product and service designers is
"sticky." In any particular instance, the stickiness of a unit of information
is defined as the incremental expenditure required to transfer that unit of
information to a specified location in a form usable by a specified information
seeker. When this expenditure is low, information stickiness is low; when it is
high, stickiness is high (von Hippel 1994). That information is often sticky
has been shown by studying the costs of transferring information regarding
fully developed process technology from one location to another with full
cooperation on both sides. Even under these favorable conditions, costs have
been found to be high---leading one to conclude that the costs of transferring
information during product and service development are likely to be at least as
high. Teece (1977), for example, studied 26 international technology-transfer
projects and found that the costs of information transfer ranged from 2 percent
to 59 percent of total project costs and averaged 19 percent---a considerable
fraction. Mansfield et al. (1982) also studied a number of projects involving
technology transfer to overseas plants, and also found technology-transfer
costs averaging about 20 percent of total project costs. Winter and Suzlanski
(2001) explored replication of well-known organizational routines at new sites
and found the process difficult and costly.
={ Mansfield, E. ;
   Suzlanski, G. ;
   Teece, D. ;
   Winter, S. ;
   von Hippel, E. +63
}

Why is information transfer so costly? The term "stickiness" refers only to a
consequence, not to a cause. Information stickiness can result from causes
ranging from attributes of the information itself to access fees charged by an
information owner. Consider tacitness---a lack of explicit encoding. Polanyi
(1958, pp. 49--53) noted that many human skills are tacit because "the aim of a
skilful performance is achieved by the observance of a set of rules which are
not known as such to the person following them." For example, swimmers are
probably not aware of the rules they employ to keep afloat (e.g., in exhaling,
they do not completely empty their lungs), nor are medical experts generally
aware of the rules they follow in order to reach a diagnosis of a disease.
"Indeed," Polanyi says, "even in modern industries the indefinable knowledge is
still an essential part of technology." Information that is tacit is also
sticky because it cannot be transferred at low cost. As Polanyi points out, "an
art which cannot be specified in detail cannot be transmitted by prescription,
since no prescription for it exists. It can be passed on only by example from
master to apprentice. . . ." Apprenticeship is a relatively costly mode of
transfer.
={ Polanyi, M. }

Another cause of information stickiness is related to absorptive capacity. A
firm's or an individual's capacity to absorb new, outside technical information
is largely a function of prior related knowledge (Cohen and Levinthal 1990).
Thus, a firm knowing nothing about circuit design but seeking to apply an
advanced technique for circuit engineering may be unable to apply it without
first learning more basic information. The stickiness of the information about
the advanced technique for the firm in question is therefore higher than it
would be for a firm that already knows that basic information. (Recall that the
stickiness of a unit of information is defined as the incremental expenditure
required to transfer a unit of information to a specified site in a form usable
by a /{specific}/ information seeker.)
={ Cohen, W. ;
   Levinthal, D.
}

Total information stickiness associated with solving a specific problem is also
determined by the amount of information required by a problem solver. Sometimes
a great deal is required, for two reasons. First, as Rosenberg (1976, 1982) and
Nelson (1982, 1990) point out, much technological knowledge deals with the
specific and the particular. Second, one does not know in advance of problem
solving which particular items will be important.
={ Nelson, R. ;
   Rosenberg, N.
}

An example from a study by von Hippel and Tyre (1995) illustrates both points
nicely. Tyre and I studied how and why novel production machines failed when
they were first introduced into factory use. One of the machines studied was an
automated machine used by a computer manufacturing firm to place large
integrated circuits onto computer circuit boards. The user firm had asked an
outside group to develop what was needed, and that group had developed and
delivered a robot arm coupled to a machine-vision system. The arm, guided by
the vision system, was designed to pick up integrated circuits and place them
on a circuit board at precise locations.
={ Tyre, M. +4 }

Upon being installed in the factory, the new component-placing machine failed
many times as a result of its developers' lack of some bit of information about
the need or use environment. For example, one day machine operators reported
that the machine was malfunctioning---again---and they did not know why.
Investigation traced the problem to the machine-vision system. This system used
a small TV camera to locate specific metalized patterns on the surface of each
circuit board being processed. To function, the system needed to "see" these
metalized patterns clearly against the background color of the board's surface.
The vision system developed by the machine-development group had functioned
properly in their lab when tested with sample boards from the user factory.
However, the field investigation showed that in the factory it failed when
boards that were light yellow in color were being processed.

The fact that some of the boards being processed were sometimes light yellow
was a surprise to the machine developers. The factory personnel who had set the
specifications for the machine knew that the boards they processed varied in
color; however, they had not volunteered the information, because they did not
know that the developers would be interested. Early in the machine-development
process, they had simply provided samples of boards used in the factory to the
machine-development group. And, as it happened, these samples were green. On
the basis of the samples, developers had then (implicitly) assumed that all
boards processed in the field were green. It had not occurred to them to ask
users "How much variation in board color do you generally experience?" Thus,
they had designed the vision system to work successfully with boards that were
green.

In the case of this field failure, the item of information needed to understand
or predict this problem was known to the users and could easily have been
provided to the machine developers---had the developers thought to ask and/or
had users thought to volunteer it. But in the actual evolution of events this
was not done. The important point is that this omission was not due to poor
practice; it was due to the huge amount of information about the need and the
use environment that was /{potentially}/ relevant to problem solvers. Note that
the use environment and the novel machine contain many highly specific
attributes that could potentially interact to cause field problems. Note also
that the property of the board causing this particular type of failure was very
narrow and specific. That is, the problem was not that the board had physical
properties, nor that it had a color. The problem was precisely that some boards
were yellow, and a particular shade of yellow at that. Since a circuit board,
like most other components, has many attributes in addition to color (shape,
size, weight, chemical composition, resonant frequency, dielectric constant,
flexibility, and so on), it is likely that problem solvers seeking to learn
everything they might need to know about the use and the use environment would
have to collect a very large (perhaps unfeasibly large) number of very specific
items of information.

Next, consider that the information items the problem solver will actually need
(of the many that exist) are contingent on the solution path taken by the
engineer designing the product. In the example, the problem caused by the
yellow color of the circuit board was contingent on the design solution to the
component-placing problem selected by the engineer during the development
process. That is, the color of the circuit boards in the user factory became an
item the problem solvers needed to know only when engineers, in the course of
their development of the component placer, decided to use a vision system in
the component-placing machine they were designing, and the fact that the boards
were yellow became relevant only when the engineers chose a video camera and
lighting that could not distinguish the metalized patterns on the board against
a yellow background. Clearly, it can be costly to transfer the many items of
information that a product or service developer might require---even if each
individual item has low stickiness---from one site to another.

!_ How Information Asymmetries Affect User Innovation vs. Manufacturer Innovation
={ Manufacturers :
     information asymmetries of +11 | innovation and +25
}

An important consequence of information stickiness is that it results in
information asymmetries that cannot be erased easily or cheaply. Different
users and manufacturers will have different stocks of information, and may find
it costly to acquire information they need but do not have. As a result, each
innovator will tend to develop innovations that draw on the sticky information
it already has, because that is the cheapest course of action (Arora and
Gambardella 1994; von Hippel 1994). In the specific case of product
development, this means that users as a class will tend to develop innovations
that draw heavily on their own information about need and context of use.
Similarly, manufacturers as a class will tend to develop innovations that draw
heavily on the types of solution information in which they specialize.
={ Arora, A. ;
   Gambardella, A.
}

This effect is visible in studies of innovation. Riggs and von Hippel (1994)
studied the types of innovations made by users and manufacturers that improved
the functioning of two major types of scientific instruments.
={ Riggs, W. ;
   Scientific instruments +9 ;
   Sticky information :
     and scientific instruments +1
}

They found that users tended to develop innovations that enabled the
instruments to do qualitatively new types of things for the first time. In
contrast, manufacturers tended to develop innovations that enabled users to do
the same things they had been doing, but to do them more conveniently or
reliably (table 5.1). For example, users were the first to modify the
instruments to enable them to image and analyze magnetic domains at
sub-microscopic dimensions. In contrast, manufacturers were the first to
computerize instrument adjustments to improve ease of operation. Sensitivity,
resolution, and accuracy improvements fall somewhere in the middle, as the data
show. These types of improvements can be driven by users seeking to do specific
new things, or by manufacturers applying their technical expertise to improve
the products along known dimensions of merit, such as accuracy.

!_ Table 5.1
Users tend to develop innovations that deliver novel functions.

% Innovation developed by

table{~h c4; 60; 15; 15; 10;

Type of improvement provided by innovation
User
Manufacturer
n

New functional capability
82%
18%
17

Sensitivity, resolution, or accuracy improvement
48%
52%
23

Convenience or reliability improvement
13%
87%
24

Total sample size
~
~
64

}table

Source: Riggs and von Hippel 1994, table 3.

The variation in locus of innovation for different types of innovations, seen
in table 5.1 does fit our expectations from the point of view of sticky
information considerations. But these findings are not controlled for
profitability, and so it might be that profits for new functional capabilities
are systematically smaller than profits obtainable from improvements made to
existing functionality. If so, this could also explain the patterns seen.

Ogawa (1998) took the next necessary step and conducted an empirical study that
did control for profitability of innovation opportunities. He too found the
sticky-information effect---this time visible in the division of labor
/{within}/ product-development projects. He studied patterns in the development
of a sample of 24 inventory-management innovations. All were jointly developed
by a Japanese equipment manufacturer, NEC, and by a user firm, Seven-Eleven
Japan (SEJ). SEJ, the leading convenience-store company in Japan, is known for
its inventory management. Using innovative methods and equipment, it is able to
turn over its inventory as many as 30 times a year, versus 12 times a year for
competitors (Kotabe 1995). An example of such an innovation jointly developed
by SEJ and NEC is just-in-time reordering, for which SEJ created the procedures
and NEC the hand-held equipment to aid store clerks in carrying out their newly
designed tasks. Equipment sales to SEJ are important to NEC: SEJ has thousands
of stores in Japan.
={ Kotabe, M. ;
   Ogawa, S. +1
}

The 24 innovations studied by Ogawa varied in the amount of sticky need
information each required from users (having to do with store inventory-
management practices) and the amount of sticky solution information required
from manufacturers (having to do with new equipment technologies). Each also
varied in terms of the profit expectations of both user and manufacturer. Ogawa
determined how much of the design for each was done by the user firm and how
much by the manufacturer firm. Controlling for profit expectations, he found
that increases in the stickiness of user information were associated with a
significant increase in the amount of need-related design undertaken by the
user (Kendall correlation coefficient = 0.5784, P < 0.01). Conversely he found
that increased stickiness of technology-related information was associated in a
significant reduction in the amount of technology design done by the user
(Kendall correlation coefficients = 0.4789, P < 0.05). In other words,
need-intensive tasks within product-development projects will tend to be done
by users, while solution-intensive ones will tend to be done by manufacturers.

!_ Low-Cost Innovation Niches

Just as there are information asymmetries between users and manufacturers as
classes, there are also information asymmetries among individual user firms and
individuals, and among individual manufacturers as well. A study of mountain
biking by Lüthje, Herstatt, and von Hippel (2002) shows that information held
locally by individual user-innovators strongly affects the type of innovations
they develop. Mountain biking involves bicycling on rough terrain such as
mountain trails. It may also involve various other extreme conditions, such as
bicycling on snow and ice and in the dark (van der Plas and Kelly 1998).
={ Kelly, C. ;
   Lüthje, C. ;
   Van der Plas, R. ;
   Herstatt, C. +12 ;
   Lüthje, C. +12 ;
   Mountain biking +12 ;
   Users :
     innovate-or-buy decisions by +12
}

Mountain biking began in the early 1970s when some young cyclists started to
use their bicycles off-road. Existing commercial bikes were not suited to this
type of rough use, so early users put together their own bikes. They used
strong bike frames, balloon tires, and powerful drum brakes designed for
motorcycles. They called their creations "clunkers" (Penning 1998; Buenstorf
2002).
={ Buenstorf, G. ;
   Penning, C.
}

Commercial manufacture of mountain bikes began about 1975, when some of the
early users of mountain bikes began to also build bikes for others. A tiny
cottage industry developed, and by 1976 a half-dozen small assemblers existed
in Marin County, California. In 1982, a small firm named Specialized, an
importer of bikes and bike parts that supplied parts to the Marin County
mountain bike assemblers, took the next step and brought the first
mass-produced mountain bike to market. Major bike manufacturers then followed
and started to produce mountain bikes and sell them at regular bike shops
across the United States. By the mid 1980s the mountain bike was fully
integrated in the mainstream bike market, and it has since grown to significant
size. In 2000, about $58 billion (65 percent) of total retail sales in the US
bicycle market were generated in the mountain bike category (National Sporting
Goods Association 2002).

Mountain biking enthusiasts did not stop their innovation activities after the
introduction of commercially manufactured mountain bikes. They kept pushing
mountain biking into more extreme environmental conditions, and they continued
to develop new sports techniques involving mountain bikes (/{Mountain Bike}/
1996). Thus, some began jumping their bikes from house roofs and water towers
and developing other forms of acrobatics. As they did so, they steadily
discovered needs for improvements to their equipment. Many responded by
developing and building the improvements they needed for themselves.

Our sample of mountain bikers came from the area that bikers call the North
Shore of the Americas, ranging from British Columbia to Washington State.
Expert mountain bikers told us that this was a current "hot spot" where new
riding styles were being developed and where the sport was being pushed toward
new limits. We used a questionnaire to collect data from members of North Shore
mountain biking clubs and from contributors to the mailing lists of two North
Shore online mountain biking forums. Information was obtained from 291 mountain
bikers. Nineteen percent of bikers responding to the questionnaire reported
developing and building a new or modified item of mountain biking equipment for
their own use. The innovations users developed were appropriate to the needs
associated with their own riding specialties and were heterogeneous in
function.
={ Custom products :
     heterogeneity of user needs and +6 ;
   User need +6 ;
   Users :
     needs of +6
}

We asked mountain bikers who had innovated about the sources of the need and
solution information they had used in their problem solving. In 84.5 percent of
the cases respondents strongly agreed with the statement that their need
information came from /{personal needs they had frequently experienced}/ rather
than from information about the needs of others. With respect to solution
information, most strongly agreed with the statement that /{they used solution
information they already had}/, rather than learning new solution information
in order to develop their biking equipment innovation (table 5.2).

!_ Table 5.2
Innovators tended to use solution information they already had "in stock" to
develop their ideas. Tabulated here are innovators' answers to the question
"How did you obtain the information needed to develop your solution?"
={ Lüthje, C. }

table{~h c4; 55; 15; 15; 15;

.
Mean
Median
Very high or high agreement

"I had it due to my professional background."
4.22
4
47.5%

"I had it from mountain biking or another hobby."
4.56
5
52.4%

"I learned it to develop this idea."
2.11
2
16%

}table

Source: Lüthje et al. 2003. N = 61. Responses were rated on a seven-point
scale, with 1 = not at all true and 7 = very true.

!_ Discussion

To the extent that users have heterogeneous and sticky need and solution
information, they will have heterogeneous low-cost innovation niches. Users can
be sophisticated developers within those niches, despite their reliance on
their own need information and solution information that they already have in
stock. On the need side, recall that user-innovators generally are lead users
and generally are expert in the field or activity giving rise to their needs.
With respect to solution information, user firms have specialties that may be
at a world-class level. Individual users can also have high levels of solution
expertise. After all, they are students or employees during the day, with
training and jobs ranging from aerospace engineering to orthopedic surgery.
Thus, mountain bikers might not want to /{learn}/ orthopedic surgery to improve
their biking equipment, but if they already /{are}/ expert in that field they
could easily draw on what they know for relevant solution information. Consider
the following example drawn from the study of mountain biking discussed
earlier:

I'm a human movement scientist working in ergonomics and biomechanics. I used
my medical experience for my design. I calculated a frame design suitable for
different riding conditions (downhill, climb). I did a CAD frame design on
Catia and conceived a spring or air coil that can be set to two different
heights. I plan to build the bike next year.

Users' low-cost innovation niches can be narrow because their development
"labs" for such experimentation often consist largely of their individual use
environment and customary activities. Consider, for example, the low-cost
innovation niches of individual mountain bikers. Serious mountain bikers
generally specialize in a particular type of mountain biking activity. Repeated
specialized play and practice leads to improvement in related specialized
skills. This, in turn, may lead to a discovery of a problem in existing
mountain biking equipment and a responsive innovation. Thus, an innovating user
in our mountain biking study reported the following: "When doing tricks that
require me to take my feet off the bike pedals in mid-air, the pedals often
spin, making it hard to put my feet back onto them accurately before landing."
Such a problem is encountered only when a user has gained a high level of skill
in the very specific specialty of jumping and performing tricks in mid-air.
Once the problem has been encountered and recognized, however, the skilled
specialist user can re-evoke the same problematic conditions at will during
ordinary practice. The result is the creation of a low-cost laboratory for
testing and comparing different solutions to that problem. The user is
benefiting from enjoyment of his chosen activity and is developing something
new via learning by doing at the same time.

In sharp contrast, if that same user decides to stray outside his chosen
activity in order to develop innovations of interest to others with needs that
are different from his own, the cost properly assignable to innovation will
rise. To gain an equivalent-quality context for innovation, such a user must
invest in developing personal skill related to the new innovation topic. Only
in this way will he gain an equivalently deep understanding of the problems
relevant to practitioners of that skill, and acquire a "field laboratory"
appropriate to developing and testing possible solutions to those new problems.

Of course, these same considerations apply to user firms as well as to
individual users. A firm that is in the business of polishing marble floors is
a user of marble polishing equipment and techniques. It will have a low-cost
learning laboratory with respect to improvements in these because it can
conduct trial-and-error learning in that "lab" during the course of its
customary business activities. Innovation costs can be very low because
innovation activities are paid for in part by rewards unrelated to the novel
equipment or technique being developed. The firm is polishing while
innovating---and is getting paid for that work (Foray 2004). The low cost
innovation niche of the marble polishing firm may be narrow. For example, it is
unlikely to have any special advantage with respect to innovations in the
polishing of wood floors, which requires different equipment and techniques.
={ Foray, D. }

1~ 6 Why Users Often Freely Reveal Their Innovations
={ Free revealing of innovation information :
     evidence of +10 | users and +50 ;
   Information commons +13 ;
   Intellectual property rights :
     free revealing and +50 ;
   Users :
     free revealing by +50
}

Products, services, and processes developed by users become more valuable to
society if they are somehow diffused to others that can also benefit from them.
If user innovations are not diffused, multiple users with very similar needs
will have to invest to (re)develop very similar innovations, which would be a
poor use of resources from the social welfare point of view. Empirical research
shows that new and modified products developed by users often do diffuse
widely---and they do this by an unexpected means: user-innovators themselves
often voluntarily publicly reveal what they have developed for all to examine,
imitate, or modify without any payment to the innovator.

In this chapter, I first review evidence that free revealing is frequent. Next,
I discuss the case for free revealing from an innovators' perspective, and
argue that it often can be the best /{practical}/ route for users to increase
profit from their innovations. Finally, I discuss the implications of free
revealing for innovation theory.

!_ Evidence of Free Revealing
={ Free revealing of innovation information }

When my colleagues and I say that an innovator "freely reveals" proprietary
information, we mean that all intellectual property rights to that information
are voluntarily given up by that innovator and all parties are given equal
access to it---the information becomes a public good (Harhoff, Henkel, and von
Hippel 2003). For example, placement of non-patented information in a publicly
accessible site such as a journal or public website would be free revealing as
we define it. Free revealing as so defined does not mean that recipients
necessarily acquire and utilize the revealed information at no cost to
themselves. Recipients may, for example, have to pay for a subscription to a
journal or for a field trip to an innovation site to acquire the information
being freely revealed. Also, some may have to obtain complementary information
or other assets in order to fully understand that information or put it to use.
However, if the possessor of the information does not profit from any such
expenditures made by its adopters, the information itself is still freely
revealed, according to our definition. This definition of free revealing is
rather extreme in that revealing with some small constraints, as is sometimes
done, would achieve largely the same economic effect. Still, it is useful to
discover that innovations are often freely revealed even in terms of this
stringent definition.
={ Harhoff, D. ;
   Henkel, J.
}

Routine and intentional free revealing among profit-seeking firms was first
described by Allen (1983). He noticed the phenomenon, which he called
collective invention, in historical records from the nineteenth-century English
iron industry. In that industry, ore was processed into iron by means of large
furnaces heated to very high temperatures. Two attributes of the furnaces used
had been steadily improved during the period 1850--1875: chimney height had
been increased and the temperature of the combustion air pumped into the
furnace during operation had been raised. These two technical changes
significantly and progressively improved the energy efficiency of iron
production---a very important matter for producers. Allen noted the surprising
fact that employees of competing firms publicly revealed information on their
furnace design improvements and related performance data in meetings of
professional societies and in published material.
={ Allen, R. ;
   Free revealing of innovation information :
     collective invention and
}

After Allen's initial observation, a number of other authors searched for free
revealing among profit-seeking firms and frequently found it. Nuvolari (2004)
studied a topic and time similar to that studied by Allen and found a similar
pattern of free revealing in the case of improvements made to steam engines
used to pump out mines in the 1800s. At that time, mining activities were
severely hampered by water that tended to flood into mines of any depth, and so
an early and important application of steam engines was for the removal of
water from mines. Nuvolari explored the technical history of steam engines used
to drain copper and tin mines in England's Cornwall District. Here, patented
steam engines developed by James Watt were widely deployed in the 1700s. After
the expiration of the Watt patent, an engineer named Richard Trevithick
developed a new type of high-pressure engine in 1812. Instead of patenting his
invention, he made his design available to all for use without charge. The
engine soon became the basic design used in Cornwall. Many mine engineers
improved Trevithick's design further and published what they had done in a
monthly journal, /{Leans Engine Reporter}/. This journal had been founded by a
group of mine managers with the explicit intention of aiding the rapid
diffusion of best practices among these competing firms.
={ Nuvolari, A. ;
   Trevithick, R. ;
   Watt, J.
}

Free revealing has also been documented in the case of more recent industrial
equipment innovations developed by users. Lim (2000) reports that IBM was first
to develop a process to manufacture semiconductors that incorporated copper
interconnections among circuit elements instead of the traditionally used
aluminum ones. After some delay, IBM revealed increasing amounts of proprietary
process information to rival users and to equipment suppliers. Widespread free
revealing was also found in the case of automated clinical chemistry analyzers
developed by the Technicon Corporation for use in medical diagnosis. After
commercial introduction of the basic analyzer, many users developed major
improvements to both the analyzer and to the clinical tests processed on that
equipment. These users, generally medical personnel, freely revealed their
improvements via publication, and at company-sponsored seminars (von Hippel and
Finkelstein 1979). Mishina (1989) found free, or at least selective no-cost
revealing in the lithographic equipment industry. He reported that innovating
equipment users would sometimes reveal what they had done to machine
manufacturers. Morrison, Roberts, and I, in our study of library IT search
software (discussed in chapter 2 above), found that innovating users freely
revealed 56 percent of the software modifications they had developed. Reasons
given for not revealing the remainder had nothing to do with considerations of
intellectual property protection. Rather, users who did not share said they had
no convenient users' group forum for doing so, and/or they thought their
innovation was too specialized to be of interest to others.
={ IBM ;
   Finkelstein, S. ;
   Lim, K. ;
   Mishina, K. ;
   Morrison, Pamela ;
   Roberts, J. ;
   Technicon Corporation ;
   Free revealing of innovation information :
     and library information search system ;
   Lead users :
     library information search system and ;
   Library information search system
}

Innovating users of sports equipment also have been found to freely reveal
their new products and product modifications. Franke and Shah (2003), in their
study of four communities of serious sports enthusiasts described in chapter 2,
found that innovating users uniformly agreed with the statement that they
shared their innovation with their entire community free of charge---and
strongly disagreed with the statement that they sold their innovations (p <
0.001, t-test for dependent samples). Interestingly, two of the four
communities they studied engaged in activities involving significant
competition among community members. Innovators in these two communities
reported high but significantly less willingness to share, as one might expect
in view of the potentially higher level of competitive loss free revealing
would entail.
={ Franke, N. ;
   Shah, S. ;
   Free revealing of innovation information :
     and sports equipment ;
   Sporting equipment :
     free revealing and
}

Contributors to the many open source software projects extant (more than 83,000
were listed on SourceForge.net in 2004) also routinely make the new code they
have written public. Well-known open source software products include the Linux
operating system software and the Apache web server computer software. Some
conditions are attached to open source code licensing to ensure that the code
remains available to all as an information commons. Because of these added
protections, open source code does not quite fit the definition of free
revealing given earlier in this chapter. (The licensing of open source software
will be discussed in detail in chapter 7.)
={ Linux +1 ;
   Apache web server software ;
   Free revealing of innovation information :
     and open source software +1 ;
   Open source software :
     free revealing and +1
}

Henkel (2003) showed that free revealing is sometimes practiced by directly
competing manufacturers. He studied manufacturers that were competitors and
that had all built improvements and extensions to a type of software known as
embedded Linux. (Such software is "embedded in" and used to operate equipment
ranging from cameras to chemical plants.) He found that these manufacturers
freely revealed improvements to the common software platform that they all
shared and, with a lag, also revealed much of the equipment-specific code they
had written.
={ Henkel, J. ;
   Free revealing of innovation information :
     manufacturers and ;
   Manufacturers :
     free revealing and
}

!_ The Practical Case for Free Revealing
={ Free revealing of innovation information :
     case for +2
}

The "private investment model" of innovation assumes that innovation will be
supported by private investment if and as innovators can make attractive
profits from doing so. In this model, any free revealing or uncompensated
"spillover" of proprietary knowledge developed by private investment will
reduce the innovator's profits. It is therefore assumed that innovators will
strive to avoid spillovers of innovation-related information. From the
perspective of this model, then, free revealing is a major surprise: it seems
to make no sense that innovators would intentionally give away information for
free that they had invested money to develop.

In this subsection I offer an explanation for the puzzle by pointing out that
free revealing is often the best /{practical}/ option available to user
innovators. Harhoff, Henkel, and von Hippel (2003) found that it is in practice
very difficult for most innovators to protect their innovations from direct or
approximate imitation. This means that the practical choice is typically
/{not}/ the one posited by the private investment model: should innovators
voluntarily freely reveal their innovations, or should they protect them?
Instead, the real choice facing user innovators often is whether to voluntarily
freely reveal or to arrive at the same end state, perhaps with a bit of a lag,
via involuntary spillovers. The practical case for voluntary free revealing is
further strengthened because it can be accomplished at low cost, and often
yields private benefits to the innovators. When benefits from free revealing
exceed the benefits that are /{practically}/ obtainable from holding an
innovation secret or licensing it, free revealing should be the preferred
course of action for a profit-seeking firm or individual.
={ Harhoff, D. ;
   Henkel, J. ;
   Free revealing of innovation information :
     and information diffusion +9
}

!_ Others Often Know Something Close to "Your" Secret

Innovators seeking to protect innovations they have developed as their
intellectual property must establish some kind of monopoly control over the
innovation-related information. In practice, this can be done either by
effectively hiding the information as a trade secret, or by getting effective
legal protection by patents or copyrights. (Trademarks also fall under the
heading of intellectual property, but we do not consider those here.) In
addition, however, it must be the case that /{others}/ do not know substitute
information that skirts these protections and that they /{are}/ willing to
reveal. If multiple individuals or firms have substitutable information, they
are likely to vary with respect to the competitive circumstances they face. A
specific innovator's ability to protect "its" innovation as proprietary
property will then be determined for all holders of such information by the
decision of the one having the least to lose by free revealing. If one or more
information holders expect no loss or even a gain from a decision to freely
reveal, then the secret will probably be revealed despite other innovators'
best efforts to avoid this fate.
={ Intellectual property rights :
     copyrights and | patents and | trade secrets and
}

Commonly, firms and individuals have information that would be valuable to
those seeking to imitate a particular innovation. This is because innovators
and imitators seldom need access to a specific version of an innovation.
Indeed, engineers seldom even want to see a solution exactly as their
competitors have designed it: specific circumstances differ even among close
competitors, and solutions must in any case be adapted to each adopter's
precise circumstances. What an engineer does want to extract from the work of
others is the principles and the general outline of a possible improvement,
rather than the easily redevelopable details. This information is likely to be
available from many sources.

For example, suppose you are a system developer at a bank and you are tasked
with improving in-house software for checking customers' credit online. On the
face of it, it might seem that you would gain most by studying the details of
the systems that competing banks have developed to handle that same task. It is
certainly true that competing banks may face market conditions very similar to
your bank, and they may well not want to reveal the valuable innovations they
have developed to a competitor. However, the situation is still by no means
bleak for an imitator. There are also many non-bank users of online credit
checking systems in the world---probably millions. Some will have innovated and
be willing to reveal what they have done, and some of these will have the
information you need. The likelihood that the information you seek will be
freely revealed by some individual or firm is further enhanced by the fact that
your search for novel basic improvements may profitably extend far beyond the
specific application of online credit checking. Other fields will also have
information on components of the solution you need. For example, many
applications in addition to online credit checking use software components
designed to determine whether persons seeking information are authorized to
receive it. Any can potentially be a provider of information for this element
of your improved system.

A finding by Lakhani and von Hippel (2003) illustrates the possibility that
many firms and individuals may have similar information. Lakhani and von Hippel
studied Apache help-line websites. These sites enable users having problems
with Apache software to post questions, and others to respond with answers. The
authors asked those who provided answers how many other help-line participants
they thought also knew a solution to specific and often obscure problems they
had answered on the Apache online forum. Information providers generally were
of the opinion that some or many other help-line participants also knew a
solution, and could have provided an answer if they themselves had not done so
(table 6.1).
={ Lakhani, K ;
   Apache web server software +2
}

!_ Table 6.1
Even very specialized information is often widely known. Tabulated here are
answers to a question asked of help-line information providers: "How many
others do you think knew the answer to the question you answered?"
={ Lakhani, K }

table{~h c3; 40; 30; 30;

~
Frequent providers (n = 21)

Other providers (n = 67)

Many
38%
61%

A few with good Apache knowledge
38%
18%

A few with specific problem experience
24%
21%

}table

Source: Lakhani and von Hippel 2003, table 10.

Even in the unlikely event that a secret is held by one individual, that
information holder will not find it easy to keep a secret for long. Mansfield
(1985) studied 100 American firms and found that "information concerning
development decisions is generally in the hands of rivals within about 12 to 18
months, on the average, and information concerning the detailed nature and
operation of a new product or process generally leaks out within about a year."
This observation is supported by Allen's previously mentioned study of free
revealing in the nineteenth-century English iron industry. Allen (1983, p. 17)
notes that developers of improved blast furnace designs were unlikely to be
able to keep their valuable innovations secret because "in the case of blast
furnaces and steelworks, the construction would have been done by contractors
who would know the design." Also, "the designs themselves were often created by
consulting engineers who shifted from firm to firm."
={ Allen, R. ;
   Mansfield, E. +4 ;
   Free revealing of innovation information :
     evidence of
}

!_ Low Ability to Profit from Patenting
={ Free revealing of innovation information :
     patent protection and +12 ;
   Intellectual property rights :
     patents and +12
}

Next, suppose that a single user-innovator is the only holder of a particular
unit of innovation-related information, and that for some reason there are no
easy substitutes. That user actually does have a real choice with respect to
disposing of its intellectual property: it can keep the innovation secret and
profit from in-house use only, it can license it, or it can choose to freely
reveal the innovation. We have just seen that the practical likelihood of
keeping a secret is low, especially when there are multiple potential providers
of very similar secrets. But if one legally protects an innovation by means of
a patent or a copyright, one need not keep an innovation secret in order to
control it. Thus, a firm or an individual that freely reveals is forgoing any
chance to get a profit via licensing of intellectual property for a fee. What,
in practical terms, is the likelihood of succeeding at this and so of forgoing
profit by choosing to freely reveal?
={ Intellectual property rights :
     copyrights and +1 | patents and +4
}

In most subject matters, the relevant form of legal protection for intellectual
property is the patent, generally the "utility" patent. (The notable exception
is the software industry, where material to be licensed is often protected by
copyright.) In the United States, utility patents may be granted for inventions
related to composition of matter and/or a method and/or a use. They may not be
granted for ideas per se, mathematical formulas, laws of nature, and anything
repugnant to morals and public policy. Within subject matters potentially
protectable by patent, protection will be granted only when the intellectual
property claimed meets additional criteria of usefulness, novelty, and
non-obviousness to those skilled in the relevant art. (The tests for whether
these criteria have been met are based on judgement. When a low threshold is
used, patents are easier to get, and vice-versa (Hall and Harhoff 2004).)
={ Hall, B. ;
   Harhoff, D.
}

The real-world value of patent protection has been studied for more than 40
years. Various researchers have found that, with a few exceptions, innovators
do /{not}/ think that patents are very useful either for excluding imitators or
for capturing royalties in most industries. (Fields generally cited as
exceptions are pharmaceuticals, chemicals, and chemical processes, where
patents do enable markets for technical information (Arora et al. 2001).) Most
respondents also say that the availability of patent protection does not induce
them to invest more in research and development than they would if patent
protection did not exist. Taylor and Silberston (1973) reported that 24 of 32
firms said that only 5 percent or less of their R&D expenditures were dependent
on the availability of patent protection. Levin et al. (1987) surveyed 650 R&D
executives in 130 different industries and found that all except respondents
from the chemical and pharmaceutical industries judged patents to be
"relatively ineffective." Similar findings have been reported by Mansfield
(1968, 1985), by Cohen et al. (2000, 2002), by Arundel (2001), and by Sattler
(2003).
={ Arora, A. ;
   Arundel, A. ;
   Cohen, W. ;
   Gambardella, A. ;
   Levin, R. ;
   Sattler, H. ;
   Silberston, Z. ;
   Taylor, C.
}

% Slaughter, S., 83--85

% ={Fosfuri, A.;Goto, A.}

Despite recent governmental efforts to strengthen patent enforcement, a
comparison of survey results indicates only a modest increase between 1983 and
1994 in large firms' evaluations of patents' effectiveness in protecting
innovations or promoting innovation investments. Of course, there are notable
exceptions: some firms, including IBM and TI, report significant income from
the licensing of their patented technologies.

% ={IBM}

Obtaining a patent typically costs thousands of dollars, and it can take years
(Harhoff, Henkel, and von Hippel 2003). This makes patents especially
impractical for many individual user-innovators, and also for small and
medium-size firms of limited means. As a stark example, it is hard to imagine
that an individual user who has developed an innovation in sports equipment
would find it appealing to invest in a patent and in follow-on efforts to find
a licensee and enforce payment. The few that do attempt this, as Shah (2000)
has shown, seldom gain any return from licensees as payment for their time and
expenditures.
={ Harhoff, D. ;
   Henkel, J. ;
   Shah, S. ;
   Intellectual property rights :
     licensing of +1
}

Copyright is a low-cost and immediate form of legal protection that applies to
original writings and images ranging from software code to movies. Authors do
not have to apply for copyright protection; it "follows the author's pen across
the page." Licensing of copyrighted works is common, and it is widely practiced
by commercial software firms. When one buys a copy of a non-custom software
product, one is typically buying only a license to use the software, not buying
the intellectual property itself. However, copyright protection is also limited
in an important way. Only the specific original writing itself is protected,
not the underlying invention or ideas. As a consequence, copyright protections
can be circumvented. For example, those who wish to imitate the function of a
copyrighted software program can do so by writing new software code to
implement that function.
={ Intellectual property rights :
     copyrights and ;
   Free revealing of innovation information :
     copyright protection and
}

Given the above, we may conclude that in practice little profit is being
sacrificed by many user-innovator firms or individuals that choose to forgo the
possibility of legally protecting their innovations in favor of free revealing.

!_ Positive Incentives for Free Revealing
={ Free revealing of innovation information :
     incentives for +7 ;
   Information commons +7
}

As was noted earlier, when we say that an innovator "freely reveals"
proprietary information we mean that all existing and potential intellectual
property rights to that information are voluntarily given up by that innovator
and that all interested parties are given access to it---the information
becomes a public good. These conditions can often be met at a very low cost.
For example, an innovator can simply post information about the innovation on a
website without publicity, so those potentially interested must discover it. Or
a firm that has developed a novel process machine can agree to give a factory
tour to any firm or individual that thinks to ask for one, without attempting
to publicize the invention or the availability of such tours in any way.
However, it is clear that many innovators go beyond basic, low-cost forms of
free revealing. They spend significant money and time to ensure that their
innovations are seen in a favorable light, and that information about them is
effectively and widely diffused. Writers of computer code may work hard to
eliminate all bugs and to document their code in a way that is very easy for
potential adopters to understand before freely revealing it. Plant owners may
repaint their plant, announce the availability of tours at a general industry
meeting, and then provide a free lunch for their visitors.

Innovators' /{active}/ efforts to diffuse information about their innovations
suggest that there are positive, private rewards to be obtained from free
revealing. A number of authors have considered what these might be. Allen
(1983) proposed that reputation gained for a firm or for its managers might
offset a reduction in profits for the firm caused by free revealing. Raymond
(1999) and Lerner and Tirole (2002) elaborated on this idea when explaining
free revealing by contributors to open source software development projects.
Free revealing of high-quality code, they noted, can increase a programmer's
reputation with his peers. This benefit can lead to other benefits, such as an
increase in the programmer's value on the job market. Allen has argued that
free revealing might have effects that actually increase a firm's profits if
the revealed innovation is to some degree specific to assets owned by the
innovator (see also Hirschleifer 1971).
={ Allen, R. +1 ;
   Hirschleifer, J. ;
   Lerner, J. ;
   Raymond, E. ;
   Tirole, J. ;
   Free revealing of innovation information :
     and open source software ;
   Open source software :
     free revealing and
}

Free revealing may also increase an innovator's profit in other ways. When an
innovating user freely reveals an innovation, the direct result is to increase
the diffusion of that innovation relative to what it would be if the innovation
were either licensed at a fee or held secret. The innovating user may then
benefit from the increase in diffusion via a number of effects. Among these are
network effects. (The classic illustration of a network effect is that the
value of each telephone goes up as more are sold, because the value of a phone
is strongly affected by the number of others who can be contacted in the
network.) In addition, and very importantly, an innovation that is freely
revealed and adopted by others can become an informal standard that may preempt
the development and/or commercialization of other versions of the innovation.
If, as Allen suggested, the innovation that is revealed is designed in a way
that is especially appropriate to conditions unique to the innovator, this can
result in creating a permanent source of advantage for that innovator.

Being first to reveal a certain type of innovation increases a user firm's
chances of having its innovation widely adopted, other things being equal. This
may induce innovators to race to reveal first. Firms engaged in a patent race
may disclose information voluntarily if the profits from success do not go only
to the winner of the race. If being second quickly is preferable to being first
relatively late, there will be an incentive for voluntary revealing in order to
accelerate the race (de Fraja 1993).
={ de Fraja, G. }

Incentives to freely reveal have been most deeply explored in the specific case
of open source software projects. Students of the open source software
development process report that innovating users have a number of motives for
freely revealing their code to open source project managers and open source
code users in general. If they freely reveal, others can debug and improve upon
the modules they have contributed, to everyone's benefit. They are also
motivated to have their improvement incorporated into the standard version of
the open source software that is generally distributed by the volunteer open
source user organization, because it will then be updated and maintained
without further effort on the innovator's part. This volunteer organization is
the functional equivalent of a manufacturer with respect to inducing
manufacturer improvements, because a user-developed improvement will be assured
of inclusion in new "official" software releases only if it is approved and
adopted by the coordinating user group. Innovating users also report being
motivated to freely reveal their code under a free or open source license by a
number of additional factors. These include giving support to open code and
"giving back" to those whose freely revealed code has been of value to them
(Lakhani and Wolf 2005).
={ Lakhani, K. ;
   Lakhani, K. ;
   Wolf, B. ;
   Free revealing of innovation information :
     and open source software +4 ;
   Open source software :
     free revealing and +4
}

By freely revealing information about an innovative product or process, a user
makes it possible for manufacturers to learn about that innovation.
Manufacturers may then improve upon it and/or offer it at a price lower than
users' in-house production costs (Harhoff et al. 2003). When the improved
version is offered for sale to the general market, the original user-innovator
(and other users) can buy it and gain from in-house use of the improvements.
For example, consider that manufacturers often convert user-developed
innovations ("home-builts") into a much more robust and reliable form when
preparing them for sale on the commercial market. Also, manufacturers offer
related services, such as field maintenance and repair programs, that
innovating users must otherwise provide for themselves.
={ iHarhoff, D. +1 }

A variation of this argument applies to the free revealing among competing
manufacturers documented by Henkel (2003). Competing developers of embedded
Linux systems were creating software that was specifically designed to run the
hardware products of their specific clients. Each manufacturer could freely
reveal this equipment-specific code without fear of direct competitive
repercussions: it was applicable mainly to specific products made by a
manufacturer's client, and it was less valuable to others. At the same time,
all would jointly benefit from free revealing of improvements to the underlying
embedded Linux code base, upon which they all build their proprietary products.
After all, the competitive advantages of all their products depended on this
code base's being equal to or better than the proprietary software code used by
other manufacturers of similar products. Additionally, Linux software was a
complement to hardware that many of the manufacturers in Henkel's sample also
sold. Improved Linux software would likely increase sales of their
complementary hardware products. (Complement suppliers' incentives to innovate
have been modeled by Harhoff (1996).)
={ Linux ;
   Henkel, J. }

!_ Free Revealing and Reuse
={ Free revealing of innovation information +2 }

Of course, free revealing is of value only if others (re)use what has been
revealed. It can be difficult to track what visitors to an information commons
take away and reuse, and there is as yet very little empirical information on
this important matter. Valuable forms of reuse range from the gaining of
general ideas of development paths to pursue or avoid to the adoption of
specific designs. For example, those who download software code from an open
source project repository can use it to learn about approaches to solving a
particular software problem and/or they may reuse portions of the downloaded
code by inserting it directly into a software program of their own. Von Krogh
et al. (2004) studied the latter type of code reuse in open source software and
found it very extensive. Indeed, they report that /{most}/ of the lines of
software code in the projects they studied were taken from the commons of other
open source software projects and software libraries and reused.
={ von Krogh, G. +10 }

% Spaeth, S., 88,?

In the case of academic publications, we see evidence that free revealing does
increase reuse---a matter of great importance to academics. A citation is an
indicator that information contained in an article has been reused: the article
has been read by the citing author and found useful enough to draw to readers'
attention. Recent empirical studies are finding that articles to which readers
have open access---articles available for free download from an author's
website, for example---are cited significantly more often than are equivalent
articles that are available only from libraries or from publishers' fee-based
websites. Antelman (2004) finds an increase in citations ranging from 45
percent in philosophy to 91 percent in mathematics. She notes that "scholars in
diverse disciplines are adopting open-access practices at a surprisingly high
rate and are being rewarded for it, as reflected in [citations]."
={ Antelman, K. }

!_ Implications for Theory

We have seen that in practice free revealing may often be the best practical
course of action for innovators. How can we tie these observations back to
theory, and perhaps improve theory as a result? At present there are two major
models that characterize how innovation gets rewarded. The private investment
model is based on the assumption that innovation will be supported by private
investors expecting to make a profit. To encourage private investment in
innovation, society grants innovators some limited rights to the innovations
they generate via patents, copyrights, and trade secrecy laws. These rights are
intended to assist innovators in getting private returns from their
innovation-related investments. At the same time, the monopoly control that
society grants to innovators and the private profits they reap create a loss to
society relative to the free and unfettered use by all of the knowledge that
the innovators have created. Society elects to suffer this social loss in order
to increase innovators' incentives to invest in the creation of new knowledge
(Arrow 1962; Dam 1995).
={ Arrow, K. ;
   Dam, K. ;
   Intellectual property rights :
     copyrights and | trade secrets and ;
   Free revealing of innovation information :
     copyright protection and | patents and | trade secrecy and
}

The second major model for inducing innovation is termed the collective action
model. It applies to the provision of public goods, where a public good is
defined by its non-excludability and non-rivalry: if any user consumes it, it
cannot be feasibly withheld from other users, and all consume it on the same
terms (Olson 1967). The collective action model assumes that innovators are
/{required}/ to relinquish control of knowledge or other assets they have
developed to a project and so make them a public good. This requirement enables
collective action projects to avoid the social loss associated with the
restricted access to knowledge of the private investment model. At the same
time, it creates problems with respect to recruiting and motivating potential
contributors. Since contributions to a collective action project are a public
good, users of that good have the option of waiting for others to contribute
and then free riding on what they have done (Olson 1967).
={ Olson, M. +1 ;
   Free revealing of innovation information :
     collective action model for +6 ;
   Social welfare :
     free revealing and
}

The literature on collective action deals with the problem of recruiting
contributors to a task in a number of ways. Oliver and Marwell (1988) and
Taylor and Singleton (1993) predict that the description of a project's goals
and the nature of recruiting efforts should matter a great deal. Other
researchers argue that the creation and deployment of selective incentives for
contributors is essential to the success of collective action projects. For
example, projects may grant special credentials to especially productive
project members (Friedman and McAdam 1992; Oliver 1980). The importance of
selective incentives suggests that small groups will be most successful at
executing collective action projects. In small groups, selective incentives can
be carefully tailored for each group member and individual contributions can be
more effectively monitored (Olson 1967; Ostrom 1998).
={ Friedman, D. ;
   Marwell, G. ;
   McAdam, D. ;
   Oliver, P. ;
   Ostrom, E. ;
   Singleton, S. ;
   Taylor, M.
}

Interestingly, successful open source software projects do not appear to follow
any of the guidelines for successful collective action projects just described.
With respect to project recruitment, goal statements provided by successful
open source software projects vary from technical and narrow to ideological and
broad, and from precise to vague and emergent (for examples, see goal
statements posted by projects hosted on Sourceforge.net).~{ As a specific
example of a project with an emergent goal, consider the beginnings of the
Linux open source software project. In 1991, Linus Torvalds, a student in
Finland, wanted a Unix operating system that could be run on his PC, which was
equipped with a 386 processor. Minix was the only software available at that
time but it was commercial, closed source, and it traded at US$150. Torvalds
found this too expensive, and started development of a Posix-compatible
operating system, later known as Linux. Torvalds did not immediately publicize
a very broad and ambitious goal, nor did he attempt to recruit contributors. He
simply expressed his private motivation in a message he posted on July 3, 1991,
to the USENET newsgroup comp.os.minix (Wayner 2000): /{Hello netlanders, Due to
a project I'm working on (in minix), I'm interested in the posix standard
definition.}/ [Posix is a standard for UNIX designers. A software using POSIX
is compatible with other UNIX-based software.] /{Could somebody please point me
to a (preferably) machine-readable format of the latest posix-rules? Ftp-sites
would be nice.}/ In response, Torvalds got several return messages with Posix
rules and people expressing a general interest in the project. By the early
1992, several skilled programmers contributed to Linux and the number of users
increased by the day. Today, Linux is the largest open source development
project extant in terms of number of developers. }~ Further, such projects may
engage in no active recruiting beyond simply posting their intended goals and
access address on a general public website customarily used for this purpose
(for examples, see the Freshmeat.net website). Also, projects have shown by
example that they can be successful even if large groups---perhaps
thousands---of contributors are involved. Finally, open source software
projects seem to expend no effort to discourage free riding. Anyone is free to
download code or seek help from project websites, and no apparent form of moral
pressure is applied to make a compensating contribution (e.g., "If you benefit
from this code, please also contribute . . .").
={ Free revealing of innovation information :
     open source software and
}

What can explain these deviations from expected practice? What, in other words,
can explain free revealing of privately funded innovations and enthusiastic
participation in projects to produce a public good? From the theoretical
perspective, Georg von Krogh and I think the answer involves revisiting and
easing some of the basic assumptions and constraints conventionally applied to
the private investment and collective action models of innovation. Both, in an
effort to offer "clean" and simple models for research, have excluded from
consideration a very rich and fertile middle ground where incentives for
private investment and collective action can coexist, and where a
"private-collective" innovation model can flourish. More specifically, a
private-collective model of innovation occupies the middle ground between the
private investment model and the collective action model by:
={ Free revealing of innovation information :
     private-collective model for +3 ;
   Private-collective model +3 ;
   Social welfare :
     private-collective model and +3
}

_* Eliminating the assumption in private investment models that free revealing
of innovations developed with private funds will represent a loss of private
profit for the innovator and so will not be engaged in voluntarily. Instead the
private-collective model proposes that under common conditions free revealing
of proprietary innovations may increase rather than decrease innovators'
private profit.

_* Eliminating the assumption in collective action models that a free rider
obtains benefits from the completed public good that are equal to those a
contributor obtains. Instead, the private-collective model proposes that
contributors to a public good can /{inherently}/ obtain greater private
benefits than free riders. These provide incentives for participation in
collective action projects that need not be managed by project personnel (von
Hippel and von Krogh 2003).
={ von Hippel, E. }

In summation: Innovations developed at private cost are often revealed freely,
and this behavior makes economic sense for participants under commonly
encountered conditions. A private-collective model of innovation incentives can
explain why and when knowledge created by private funding may be offered freely
to all. When the conditions are met, society appears to have the best of both
worlds---new knowledge is created by private funding and then freely revealed
to all.

1~ 7 Innovation Communities
={ Innovation communities +56 :
     innovation and +56
}

It is now clear that users often innovate, and that they often freely reveal
their innovations. But what about informal cooperation among users? What about
/{organized}/ cooperation in development of innovations and other matters? The
answer is that both flourish among user-innovators. Informal user-to-user
cooperation, such as assisting others to innovate, is common. Organized
cooperation in which users interact within communities, is also common.
Innovation communities are often stocked with useful tools and infrastructure
that increase the speed and effectiveness with which users can develop and test
and diffuse their innovations.

In this chapter, I first show that user innovation is a widely distributed
process and so can be usefully drawn together by innovation communities. I next
explore the valuable functions such communities can provide. I illustrate with
a discussion of free and open source software projects, a very successful form
of innovation community in the field of software development. Finally, I point
out that innovation communities are by no means restricted to the development
of information products such as software, and illustrate with the case of a
user innovation community specializing in the development of techniques and
equipment used in the sport of kitesurfing.
={ Free software ;
   Kitesurfing ;
   Open source software :
     innovation communities and
}

!_ User Innovation Is Widely Distributed
={ Users :
     innovation and +8 ;
   Innovation :
     distributed process of +8
}

When users' needs are heterogeneous and when the information drawn on by
innovators is sticky, it is likely that product-development activities will be
widely distributed among users, rather than produced by just a few prolific
user-innovators. It should also be the case that different users will tend to
develop different innovations. As was shown in chapter 5, individual users and
user firms tend to develop innovations that serve their particular needs, and
that fall within their individual "low-cost innovation niches." For example, a
mountain biker who specializes in jumping from high platforms and who is also
an orthopedic surgeon will tend to develop innovations that draw on both of
these types of information: he might create a seat suspension that reduces
shock to bikers' spines upon landing from a jump. Another mountain biker
specializing in the same activity but with a different background---say
aeronautical engineering---is likely to draw on this different information to
come up with a different innovation. From the perspective of Fleming (2001),
who has studied innovations as consisting of novel combinations of pre-existing
elements, such innovators are using their membership in two distinct
communities to combine previously disparate elements. Baldwin and Clark (2003)
and Henkel (2004a) explore this type of situation in theoretical terms.
={ Baldwin, C. ;
   Clark, K. ;
   Fleming, L. ;
   Henkel, J. ;
   User need ;
   Custom products :
     heterogeneity of user needs and +3 ;
   Sticky information :
     innovation and +3 ;
   Users :
     low-cost innovation niches of +3 ;
   Scientific instruments ;
   Sporting equipment :
     innovation communities and ;
   Mountain biking ;
   Local information +1 ;
   Users :
     innovate-or-buy decisions by
}

The underlying logic echoes that offered by Eric Raymond regarding "Linus's
Law" in software debugging. In software, discovering and repairing subtle code
errors or bugs can be very costly (Brooks 1979). However, Raymond argued, the
same task can be greatly reduced in cost and also made faster and more
effective when it is opened up to a large community of software users that each
may have the information needed to identify and fix some bugs. Under these
conditions, Raymond says, "given a large enough beta tester and co-developer
base, almost every problem will be characterized quickly and the fix obvious to
someone. Or, less formally, `given enough eyeballs, all bugs are shallow."' He
explains: "More users find more bugs because adding more users adds more ways
of stressing the program. . . . Each [user] approaches the task of bug
characterization with a slightly different perceptual set and analytical
toolkit, a different angle on the problem. So adding more beta-testers . . .
increases the probability that someone's toolkit will be matched to the problem
in such a way that the bug is shallow to /{that person}/." (1999, pp. 41--44)
={ Brooks, F. ;
   Raymond, E. ;
   Free software ;
   Open source software :
     innovation communities and ;
   Innovation communities :
     and sources of innovation +2
}

The analogy to distributed user innovation is, of course, that each user has a
different set of innovation-related needs and other assets in place which makes
a particular type of innovation low-cost ("shallow") to /{that user}/. The
assets of /{some}/ user will then generally be found to be a just-right fit to
many innovation development problems. (Note that this argument does not mean
that /{all}/ innovations will be cheaply done by users, or even done by users
at all. In essence, users will find it cheaper to innovate when manufacturers'
economies of scale with respect to product development are more than offset by
the greater scope of innovation assets held by the collectivity of individual
users.)

Available data support these expectations. In chapter 2 we saw evidence that
users tended to develop very different innovations. To test whether
commercially important innovations are developed by just a few users or by
many, I turn to studies documenting the functional sources of important
innovations later commercialized. As is evident in table 7.1, most of the
important innovations attributed to users in these studies were done by
/{different}/ users. In other words, user innovation does tend to be widely
distributed in a world characterized by users with heterogeneous needs and
heterogeneous stocks of sticky information.
={ Innovation :
     functional sources of
}

!_ Table 7.1
User innovation is widely distributed, with few users developing more than one
major innovation. NA: data not available.
={ Riggs, W. ;
   Shah, S. ;
   von Hippel, E. ;
   Scientific instruments ;
   Sporting equipment :
     innovation communities and
}

Number of users developing this number of major innovations

table{~h c7; 30; 10; 10; 10; 10; 10; 20;

~
1
2
3
6
NA
Sample (n)

Scientific Instruments^{a}^
28
0
1
0
1
32

Scientific Instruments^{b}^
20
1
0
1
0
28

Process equipment^{c}^
19
1
0
0
8
29

Sports equipment^{d}^
7
0
0
0
0
7

}table

a. Source: von Hippel 1988, appendix: GC, TEM, NMR Innovations. \\
b. Source: Riggs and von Hippel, Esca and AES. \\
c. Source: von Hippel 1988, appendix: Semiconductor and pultrusion process equipment innovations. \\
d. Source: Shah 2000, appendix A: skateboarding, snowboarding, and windsurfing innovations.

!_ Innovation Communities
={ Innovation communities :
     and sources of innovation
}

User-innovators may be generally willing to freely reveal their information.
However, as we have seen, they may be widely distributed and each may have only
one or a few innovations to offer. The practical value of the "freely revealed
innovation commons" these users collectively offer will be increased if their
information is somehow made conveniently accessible. This is one of the
important functions of "innovation communities."
={ Information commons +3 }

I define "innovation communities" as meaning nodes consisting of individuals or
firms interconnected by information transfer links which may involve
face-to-face, electronic, or other communication. These can, but need not,
exist within the boundaries of a membership group. They often do, but need not,
incorporate the qualities of communities for participants, where "communities"
is defined as meaning"networks of interpersonal ties that provide sociability,
support, information, a sense of belonging, and social identity" (Wellman et
al. 2002, p. 4).~{ When they do not incorporate these qualities, they would be
more properly referred to as networks---but communities is the term commonly
used, and I follow that practice here. }~
={ Wellman, B. }

Innovation communities can have users and/or manufacturers as members and
contributors. They can flourish when at least some innovate and voluntarily
reveal their innovations, and when others find the information revealed to be
of interest. In previous chapters, we saw that these conditions do commonly
exist with respect to user-developed innovations: users innovate in many
fields, users often freely reveal, and the information revealed is often used
by manufacturers to create commercial products---a clear indication many users,
too, find this information of interest.

Innovation communities are often specialized, serving as collection points and
repositories for information related to narrow categories of innovations. They
may consist only of information repositories or directories in the form of
physical or virtual publications. For example, userinnovation.mit.edu is a
specialized website where researchers can post articles on their findings and
ideas related to innovation by users. Contributors and non-contributors can
freely access and browse the site as a convenient way to find such information.

Innovation communities also can offer additional important functions to
participants. Chat rooms and email lists with public postings can be provided
so that contributors can exchange ideas and provide mutual assistance. Tools to
help users develop, evaluate, and integrate their work can also be provided to
community members---and such tools are often developed by community members
themselves.

All the community functionality just mentioned and more is visible in
communities that develop free and open source software programs. The emergence
of this particular type of innovation community has also done a great deal to
bring the general phenomenon to academic and public notice, and so I will
describe them in some detail. I first discuss the history and nature of free
and open source software itself (the product). Next I outline key
characteristics of the free and open source software development projects
typically used to create and maintain such software (the community-based
development process).
={ Free software +10 ;
   Innovation communities :
     open source software and +22 ;
   Open source software :
     innovation communities and +22
}

!_ Open Source Software
={ Open source software :
     innovation and +21
}

In the early days of computer programming, commercial "packaged" software was a
rarity---if you wanted a particular program for a particular purpose, you
typically wrote the code yourself or hired someone to write it for you. Much of
the software of the 1960s and the 1970s was developed in academic and corporate
laboratories by scientists and engineers. These individuals found it a normal
part of their research culture to freely give and exchange software they had
written, to modify and build on one another's software, and to freely share
their modifications. This communal behavior became a central feature of "hacker
culture." (In communities of open source programmers, "hacker" is a positive
term that is applied to talented and dedicated programmers.~{ !{hacker}! n.
[originally, someone who makes furniture with an axe] 1. A person who enjoys
exploring the details of programmable systems and how to stretch their
capabilities, as opposed to most users, who prefer to learn only the minimum
necessary. 2. One who programs enthusiastically (even obsessively) or who
enjoys programming rather than just theorizing about programming. 3. A person
capable of appreciating !{hack value}!. 4. A person who is good at programming
quickly. . . . 8. [deprecated] A malicious meddler who tries to discover
sensitive information by poking around. Hence /{password hacker}/, /{network
hacker}/. The correct term for this sense is !{cracker}! (Raymond 1996). }~ )
={ Hackers +4 ;
   Raymond, E.
}

In 1969, the Defense Advanced Research Projects Agency, a part of the US
Department of Defense, established the ARPANET, the first transcontinental
high-speed computer network. This network eventually grew to link hundreds of
universities, defense contractors, and research laboratories. Later succeeded
by the Internet, it also allowed hackers to exchange software code and other
information widely, easily, and cheaply---and also enabled them to spread
hacker norms of behavior.

The communal hacker culture was very strongly present among a group of
programmers---software hackers---housed at MIT's Artificial Intelligence
Laboratory in the 1960s and the 1970s (Levy 1984). In the 1980s this group
received a major jolt when MIT licensed some of the code created by its hacker
employees to a commercial firm. This firm, in accordance with normal commercial
practice, then promptly restricted access to the "source code"~{ Source code is
a sequence of instructions to be executed by a computer to accomplish a
program's purpose. Programmers write computer software in the form of source
code, and also document that source code with brief written explanations of the
purpose and design of each section of their program. To convert a program into
a form that can actually operate a computer, source code is translated into
machine code using a software tool called a compiler. The compiling process
removes program documentation and creates a binary version of the program---a
sequence of computer instructions consisting only of strings of ones and zeros.
Binary code is very difficult for programmers to read and interpret. Therefore,
programmers or firms that wish to prevent others from understanding and
modifying their code will release only binary versions of the software. In
contrast, programmers or firms that wish to enable others to understand and
update and modify their software will provide them with its source code.
(Moerke 2000, Simon 1996). }~ of that software, and so prevented non-company
personnel---including the MIT hackers who had been instrumental in developing
it---from continuing to use it as a platform for further learning and
development.
={ Levy, S. ;
   MIT Artificial Intelligence Laboratory +1 ;
   Innovation communities :
     open source software and ;
   Open source software :
     innovation communities and
}

Richard Stallman, a brilliant programmer in MIT's Artificial Intelligence
Laboratory, was especially distressed by the loss of access to communally
developed source code. He also was offended by a general trend in the software
world toward development of proprietary software packages and the release of
software in forms that could not be studied or modified by others. Stallman
viewed these practices as morally wrong impingements on the rights of software
users to freely learn and create. In 1985, in response, he founded the Free
Software Foundation and set about to develop and diffuse a legal mechanism that
could preserve free access for all to the software developed by software
hackers. Stallman's pioneering idea was to use the existing mechanism of
copyright law to this end. Software authors interested in preserving the status
of their software as "free" software could use their own copyright to grant
licenses on terms that would guarantee a number of rights to all future users.
They could do this by simply affixing a standard license to their software that
conveyed these rights. The basic license developed by Stallman to implement
this seminal idea was the General Public License or GPL (sometimes referred to
as copyleft, in a play on the word "copyright"). Basic rights transferred to
those possessing a copy of free software include the right to use it at no
cost, the right to study its source code, the right to modify it, and the right
to distribute modified or unmodified versions to others at no cost. Licenses
conveying similar rights were developed by others, and a number of such
licenses are currently used in the open source field. Free and open source
software licenses do not grant users the full rights associated with free
revealing as that term was defined earlier. Those who obtain the software under
a license such as the GPL are restricted from certain practices. For example,
they cannot incorporate GPL software into proprietary software that they then
sell.~{ See www.gnu.org/licenses/licenses.html#GPL }~ Indeed, contributors of
code to open source software projects are very concerned with enforcing such
restrictions in order to ensure that their code remains accessible to all
(O'Mahony 2003).
={ Stallman, R. +2 ;
   Intellectual property rights :
     copyrights and | licensing of +1
}

The idea of free software did not immediately become mainstream, and industry
was especially suspicious of it. In 1998, Bruce Perens and Eric Raymond agreed
that a significant part of the problem resided in Stallman's term "free"
software, which might understandably have an ominous ring to the ears of
businesspeople. Accordingly, they, along with other prominent hackers, founded
the open source software movement (Perens 1999). Open source software uses the
licensing practices pioneered by the free software movement. It differs from
that movement primarily on philosophical grounds, preferring to emphasize the
practical benefits of its licensing practices over issues regarding the moral
importance of granting users the freedoms offered by both free and open source
software. The term "open source" is now generally used by both practitioners
and scholars to refer to free or open source software, and that is the term I
use in this book.
={ Perens, B. ;
   Raymond, E.
}

Open source software has emerged as a major cultural and economic phenomenon.
The number of open source software projects has been growing rapidly. In mid
2004, a single major infrastructure provider and repository for open source
software projects, Sourceforge.net,~{ http://www.sourceforge.net }~ hosted
83,000 projects and had more than 870,000 registered users. A significant
amount of software developed by commercial firms is also being released under
open source licenses.

!_ Open Source Software Development Projects

Software can be termed "open source" independent of how or by whom it has been
developed: the term denotes only the type of license under which it is made
available. However, the fact that open source software is freely accessible to
all has created some typical open source software development practices that
differ greatly from commercial software development models---and that look very
much like the "hacker culture" behaviors described above.
={ Hackers +1 }

Because commercial software vendors typically wish to sell the code they
develop, they sharply restrict access to the source code of their software
products to firm employees and contractors. The consequence of this restriction
is that only insiders have the information required to modify and improve that
proprietary code further (Meyer and Lopez 1995; Young, Smith, and Grimm 1996;
Conner and Prahalad 1996). In sharp contrast, all are offered free access to
the source code of open source software if that code is distributed by its
authors. In early hacker days, this freedom to learn and use and modify
software was exercised by informal sharing and co-development of code---often
by the physical sharing and exchange of computer tapes and disks on which the
code was recorded. In current Internet days, rapid technological advances in
computer hardware and software and networking technologies have made it much
easier to create and sustain a communal development style on ever-larger
scales. Also, implementing new projects is becoming progressively easier as
effective project design becomes better understood, and as prepackaged
infrastructural support for such projects becomes available on the Web.
={ Conner, K. ;
   Grimm, C. ;
   Meyer, M. ;
   Lopez, L. ;
   Prahalad, C. ;
   Smith, G. ;
   Young, G.
}

Today, an open source software development project is typically initiated by an
individual or a small group seeking a solution to an individual's or a firm's
need. Raymond (1999, p. 32) suggests that "every good work of software starts
by scratching a developer's personal itch" and that "too often software
developers spend their days grinding away for pay at programs they neither need
nor love. But not in the (open source) world. . . ." A project's initiators
also generally become the project's "owners" or "maintainers" who take on
responsibility for project management.~{ "The owner(s) [or `maintainers'] of an
open source software project are those who have the exclusive right, recognized
by the community at large, to redistribute modified versions. . . . According
to standard open source licenses, all parties are equal in the evolutionary
game. But in practice there is a very well-recognized distinction between
`official' patches [changes to the software], approved and integrated into the
evolving software by the publicly recognized maintainers, and `rogue' patches
by third parties. Rogue patches are unusual and generally not trusted."
(Raymond 1999, p. 89) }~ Early on, this individual or group generally develops
a first, rough version of the code that outlines the functionality envisioned.
The source code for this initial version is then made freely available to all
via downloading from an Internet website established by the project. The
project founders also set up infrastructure for the project that those
interested in using or further developing the code can use to seek help,
provide information or provide new open source code for others to discuss and
test. In the case of projects that are successful in attracting interest,
others do download and use and "play with" the code---and some of these do go
on to create new and modified code. Most then post what they have done on the
project website for use and critique by any who are interested. New and
modified code that is deemed to be of sufficient quality and of general
interest by the project maintainers is then added to the authorized version of
the code. In many projects the privilege of adding to the authorized code is
restricted to only a few trusted developers. These few then serve as
gatekeepers for code written by contributors who do not have such access (von
Krogh and Spaeth 2002).
={ Spaeth, S. ;
   von Krogh, G. ;
   Raymond, E.
}

Critical tools and infrastructure available to open source software project
participants includes email lists for specialized purposes that are open to
all. Thus, there is a list where code users can report software failures
("bugs") that they encounter during field use of the software. There is also a
list where those developing the code can share ideas about what would be good
next steps for the project, good features to add, etc. All of these lists are
open to all and are also publicly archived, so anyone can go back and learn
what opinions were and are on a particular topic. Also, programmers
contributing to open source software projects tend to have essential tools,
such as specific software languages, in common. These are generally not
specific to a single project, but are available on the web. Basic toolkits held
in common by all contributors tends to greatly ease interactions. Also, open
source software projects have version-control software that allows contributors
to insert new code contributions into the existing project code base and test
them to see if the new code causes malfunctions in existing code. If so, the
tool allows easy reversion to the status quo ante. This makes "try it and see"
testing much more practical, because much less is at risk if a new contribution
inadvertently breaks the code. Toolkits used in open source projects have been
evolved through practice and are steadily being improved by user-innovators.
Individual projects can now start up using standard infrastructure sets offered
by sites such as Sourceforge.net.
={ Toolkits :
     open source software and
}

Two brief case histories will help to further convey the flavor of open source
software development.

!_ Apache Web Server Software
={ Apache web server software +3 ;
   Innovation communities :
     Apache web server software and +3
}

Apache web server software is used on web server computers that host web pages
and provide appropriate content as requested by Internet browsers. Such 7
computers are a key element of the Internet-based World Wide Web
infrastructure.

The web server software that evolved into Apache was developed by University of
Illinois undergraduate Rob McCool for, and while working at, the National
Center for Supercomputing Applications (NCSA). The source code as developed and
periodically modified by McCool was posted on the web so that users at other
sites could download it, use it, modify it, and develop it further. When McCool
departed NCSA in mid 1994, a small group of webmasters who had adopted his web
server software for their own sites decided to take on the task of continued
development. A core group of eight users gathered all documentation and bug
fixes and issued a consolidated patch. This "patchy" web server software
evolved over time into Apache. Extensive user feedback and modification yielded
Apache 1.0, released on December 1, 1995.
={ McCool, Rob }

In 4 years, after many modifications and improvements contributed by many
users, Apache became the most popular web server software on the Internet,
garnering many industry awards for excellence. Despite strong competition from
commercial software developers such as Microsoft and Netscape, it is currently
used by over 60 percent of the world's millions of websites. Modification and
updating of Apache by users and others continues, with the release of new
versions being coordinated by a central group of 22 volunteers.
={ Microsoft }

!_ Fetchmail---An Internet Email Utility Program
={ Fetchmail +4 ;
   Innovation communities :
     fetchmail and +4
}

Fetchmail is an Internet email utility program that "fetches" email from
central servers to a local computer. The open source project to develop,
maintain, and improve this program was led by Eric Raymond (1999).
={ Raymond, E. +3 }

Raymond first began to puzzle about the email delivery problem in 1993 because
he was personally dissatisfied with then-existing solutions. "What I wanted,"
Raymond recalled (1999, p. 31), "was for my mail to be delivered on snark, my
home system, so that I would be notified when it arrived and could handle it
using all my local tools." Raymond decided to try and develop a better
solution. He began by searching databases in the open source world for an
existing, well-coded utility that he could use as a development base. He knew
it would be efficient to build on others' related work if possible, and in the
world of open source software (then generally called free software) this
practice is understood and valued. Raymond explored several candidate open
source programs, and settled on one in small-scale use called "popclient." He
developed a number of improvements to the program and proposed them to the then
maintainer of popclient. It turned out that this individual had lost interest
in working further on the program, and so his response to Raymond's suggestions
was to offer his role to Raymond so that he could evolve the popclient further
as he chose.

Raymond accepted the role of popclient's maintainer, and over the next months
he improved the program significantly in conjunction with advice and
suggestions from other users. He carefully cultivated his more active beta list
of popclient users by regularly communicating with them via messages posted on
an public electronic bulletin board set up for that purpose. Many responded by
volunteering information on bugs they had found and perhaps fixed, and by
offering improvements they had developed for their own use. The quality of
these suggestions was often high because "contributions are received not from a
random sample, but from people who are interested enough to use the software,
learn about how it works, attempt to find solutions to the problems they
encounter, and actually produce an apparently reasonable fix. Anyone who passes
all these filters is highly likely to have something useful to contribute."
(ibid., p. 42)

Eventually, Raymond arrived at an innovative design that he knew worked well
because he and his beta list of co-developers had used it, tested it and
improved it every day. Popclient (now renamed fetchmail) became standard
software used by millions users. Raymond continues to lead the group of
volunteers that maintain and improve the software as new user needs and
conditions dictate.

!_ Development of Physical Products by Innovation Communities
={ Innovation communities :
     physical products and +14
}

User innovation communities are by no means restricted to the development of
information products like software. They also are active in the development of
physical products, and in very similar ways. Just as in the case of communities
devoted to information product, communities devoted to physical products can
range from simple information exchange sites to sites well furnished with tools
and infrastructure. Within sports, Franke and Shah's study illustrates
relatively simple community infrastructure. Thus, the boardercross community
they studied consisted of semi-professional athletes from all over the world
who meet in up to 10 competitions a year in Europe, North America, and Japan.
Franke and Shah report that community members knew one another well, and spent
a considerable amount of time together. They also assisted one another in
developing and modifying equipment for their sport. However, the community had
no specialized sets of tools to support joint innovation development.
={ Franke, N. ;
   Shah, S. ;
   Innovation communities :
     sporting equipment and +2
}

More complex communities devoted to the development of physical products often
look similar to open source software development communities in terms of tools
and infrastructure. As an example, consider the recent formation of a community
dedicated to the development and diffusion of information regarding novel
kitesurfing equipment. Kitesurfing is a water sport in which the user stands on
a special board, somewhat like a surfboard, and is pulled along by holding onto
a large, steerable kite. Equipment and technique have evolved to the point that
kites can be guided both with and against the wind by a skilled kitesurfer, and
can lift rider and board many meters into the air for tens of seconds at a
time.
={ Innovation communities :
     kitesurfing and +1 ;
   Kitesurfing +1
}

Designing kites for kitesurfing is a sophisticated undertaking, involving
low-speed aerodynamical considerations that are not yet well understood. Early
kites for kitesurfing were developed and built by user-enthusiasts who were
inventing both kitesurfing techniques and kitesurfing equipment
interdependently. In about 2001, Saul Griffith, an MIT PhD student with a
long-time interest in kitesurfing and kite development, decided that
kite-surfing would benefit from better online community interaction.
Accordingly, he created a site for the worldwide community of user-innovators
in kitesurfing (www.zeroprestige.com). Griffith began by posting patterns for
kites he had designed on the site and added helpful hints and tools for kite
construction and use. Others were invited to download this information for free
and to contribute their own if they wished. Soon other innovators started to
post their own kite designs, improved construction advice for novices, and
sophisticated design tools such as aerodynamics modeling software and rapid
prototyping software. Some kitesurfers contributing innovations to the site had
top-level technical skills; at least one was a skilled aerodynamicist employed
by an aerospace firm.
={ Griffith, S. ;
   Zeroprestige.com
}

Note that physical products are information products during the design stage.
In earlier days, information about an evolving design was encoded on large
sheets of paper, called blueprints, that could be copied and shared. The
information on blueprints could be understood and assessed by fellow designers,
and could also be used by machinists to create the actual physical products
represented. Today, designs for new products are commonly encoded in
computer-aided design (CAD) files. These files can be created and seen as
two-dimensional and three-dimensional renderings by designers. The designs they
contain can also be subjected to automated analysis by various engineering
tools to determine, for example, whether they can stand up to stresses to which
they will be subjected. CAD files can then be downloaded to computer-controlled
fabrication machinery that will actually build the component parts of the
design.

The example of the kitesurfing group's methods of sharing design information
illustrates the close relationship between information and physical products.
Initially, users in the group exchanged design ideas by means of simple
sketches transferred over the Internet. Then group members learned that
computerized cutters used by sail lofts to cut sails from large pieces of cloth
are suited to cutting cloth for surfing kites. They also learned that sail
lofts were interested in their business. Accordingly, innovation group members
began to exchange designs in the form of CAD files compatible with sail lofts'
cutting equipment. When a user was satisfied with a design, he would transmit
the CAD file to a local sail loft for cutting. The pieces were then sewn
together by the user or sent to a sewing facility for assembly. The total time
required to convert an information product into a physical one was less than a
week, and the total cost of a finished kite made in this way was a few hundred
dollars---much less than the price of a commercial kite.
={ Innovation communities :
     kitesurfing and ;
   Kitesurfing
}

!_ User-to-User Assistance
={ Innovation communities :
     user-to-user assistance and +9 ;
   Users :
     innovation communities and +9
}

Clearly, user innovation communities can offer sophisticated support to
individual innovators in the form of tools. Users in these innovation
communities also tend to behave in a collaborative manner. That is, users not
only distribute and evaluate completed innovations; they also volunteer other
important services, such as assisting one another in developing and applying
innovations.

Franke and Shah (2003) studied the frequency with which users in four sporting
communities assisted one another with innovations, and found that such
assistance was very common (table 7.2). They also found that those who assisted
were significantly more likely to be innovators themselves (table 7.3). The
level of satisfaction reported by those assisted was very high. Seventy-nine
percent agreed strongly with the statement "If I had a similar problem I would
ask the same people again." Jeppesen (2005) similarly found extensive
user-to-user help being volunteered in the field of computer gaming.
={ Franke, N. ;
   Jeppesen, L. ;
   Shah, S. ;
   Innovation communities :
     sporting equipment and ;
   Sporting equipment :
     innovation communities and +7 | user-to-user assistance and +7
}

!_ Table 7.2
Number of people from whom innovators received assistance.
={ Franke, N. ;
   Shah, S.
}

table{~h c3; 34; 33; 33;

Number of people
Number of cases
Percentage

0
0
0

1
3
6

2
14
26

3--5
25
47

6--10
8
15

> 10
3
6

Total
53
100

}table

Source: Franke and Shah 2003, table 4.

!_ Table 7.3
Innovators tended to be the ones assisting others with their innovations (p <
0.0001).
={ Franke, N. ;
   Shah, S.
}

table{~h c4; 40; 20; 20; 20;

~
Innovators
Non-innovators
Total

Gave assistance
28
13
41

Did not give assistance
32
115
147

Total
60
128
~

}table

Source: Franke and Shah 2003, table 7.

Such helping activity is clearly important to the value contributed by
innovation communities to community participants. Why people might voluntarily
offer assistance is a subject of analysis. The answers are not fully in, but
the mysteries lessen as the research progresses. An answer that appears to be
emerging is that there are private benefits to assistance providers, just as
there are for those who freely reveal innovations (Lakhani and von Hippel
2003). In other words, provision of free assistance may be explicable in terms
of the private-collective model of innovation-related incentives discussed
earlier.
={ Lakhani, K. ;
   Free revealing of innovation information :
     in information communities | private-collective model for ;
   Private-collective model ;
   Social welfare :
     private-collective model and
}

1~ 8 Adapting Policy to User Innovation
={ Government policy +44 :
     user innovation and +19 ;
   Innovation :
     and government policy +44 ;
   Manufacturers :
     innovation and +44 ;
   Users :
     government policy and +44 | innovation and +44
}

Government policy makers generally wish to encourage activities that increase
social welfare, and to discourage activities that reduce it. Therefore, it is
important to ask about the social welfare effects of innovation by users.
Henkel and von Hippel (2005) explored this matter and concluded that social
welfare is likely to be higher in a world in which both users and manufacturers
innovate than in a world in which only manufacturers innovate.
={ Henkel, J. ;
   Government policy :
     manufacturer innovation and +1 ;
   Manufacturers :
     government policy and +1 ;
   Government policy :
     social welfare and +21 ;
   Social welfare :
     government policy +4 ;
   Users :
     social welfare and +4
}

In this chapter, I first explain that innovation by users complements
manufacturer innovation and can also be a source of success-enhancing new
product ideas for manufacturers. Next, I note that innovation by users does not
exhibit several welfare-reducing effects associated with innovation by
manufacturers. Finally, I evaluate the effects of public policies on user
innovation, and suggest modifications to those that---typically
unintentionally---discriminate against innovation by users.

!_ Social Welfare Effects of User Innovation

Social welfare functions are used in welfare economics to provide a measure of
the material welfare of society, using economic variables as inputs. A social
welfare function can be designed to express many social goals, ranging from
population life expectancies to income distributions. Much of the literature on
product diversity, innovation, and social welfare evaluates the impact of
economic phenomena and policy on social welfare from the perspective of total
income of a society without regard to how that income is distributed. We will
take that viewpoint here.

!_ User Innovation Improves Manufacturers' Success Rates
={ Government policy :
     manufacturer innovation and +5 ;
   Manufacturers :
     government policy and +5
}

It is striking that most new products developed and introduced to the market by
manufacturers are commercial failures. Mansfield and Wagner (1975) found the
overall probability of success for new industrial products to be only 27
percent. Elrod and Kelman (1987) found an overall probability of success of 26
percent for consumer products. Balachandra and Friar (1997), Poolton and
Barclay (1998), and Redmond (1995) found similarly high failure rates in new
products commercialized. Although there clearly is some recycling of knowledge
from failed projects to successful ones, much of the investment in product
development is highly specific. This high failure rate therefore represents a
huge inefficiency in the conversion of R&D investment to useful output, and a
corresponding reduction in social welfare.
={ Balachandra, R ;
   Barclay, I. ;
   Elrod, T. ;
   Kelman, A. ;
   Friar, J. ;
   Mansfield, E. +1 ;
   Poolton, J. ;
   Redmond, W. ;
   Wagner, S. +1
}

% Robertson, A., 108

Research indicates that the major reason for the commercial failure of
manufacturer-developed products is poor understanding of users' needs by
manufacturer-innovators. The landmark SAPPHO study showed this in a very clear
and convincing way. This study was based on a sample of 31 product pairs.
Members of each pair were selected to address the same function and market.
(For example, one pair consisted of two "roundness meters," each developed by a
separate company.) One member of each pair was a commercial success (which
showed that there was a market for the product type); the other was a
commercial failure. The development process for each successful and failing
product was then studied in detail. The primary factor found to distinguish
success from failure was that a deeper understanding of the market and the need
was associated with successful projects (Achilladelis et al. 1971; Rothwell et
al. 1974). A study by Mansfield and Wagner (1975) came to the same conclusion.
More recent studies of information stickiness and the resulting asymmetries of
information held by users and manufacturers, discussed in chapter 3, support
the reasonableness of this general finding. Users are the generators of
information regarding their needs. The decline in accuracy and completeness of
need information after transfer from user to manufacturer is likely to be
substantial because important elements of this information are likely to be
sticky (von Hippel 1994; Ogawa 1998).
={ Achilladelis, B. ;
   Ogawa, S. ;
   Rothwell, R. ;
   Project SAPPHO ;
   SAPPHO study ;
   Sticky information :
     innovation and
}

Innovations developed by users can improve manufacturers' information on users'
needs and so improve their new product introduction success rates. Recall from
previous chapters that innovation by users is concentrated among lead users.
These lead users tend, as we have seen, to develop functionally novel products
and product modifications addressing their own needs at the leading edge of
markets where potential sales are both small and uncertain. Manufacturers, in
contrast, have poorer information on users' needs and use contexts, and will
prefer to manufacture innovations for larger, more certain markets. In the
short term, therefore, user innovations will tend to /{complement}/ rather than
substitute for products developed by manufacturers. In the longer term, the
market as a whole catches up to the needs that motivated the lead user
developments, and manufacturers will begin to find production of similar
innovations to be commercially attractive. At that point, innovations by lead
users can provide very useful information to manufacturers that they would not
otherwise have.

As lead users develop and test their solutions in their own use environments,
they learn more about the real nature of their needs. They then often freely
reveal information about their innovations. Other users then may adopt the
innovations, comment on them, modify and improve them, and freely reveal what
they have done in turn. All of this freely revealed activity by lead users
offers manufacturers a great deal of useful information about both needs
embodied in solutions and about markets. Given access to a user-developed
prototype, manufacturers no longer need to understand users' needs very
accurately and richly. Instead they have the much easier task of replicating
the function of user prototypes that users have already demonstrated are
responsive to their needs. For example, a manufacturer seeking to commercialize
a new type of surgical equipment and coming upon prototype equipment developed
by surgeons need not understand precisely why the innovators want this product
or even precisely how it is used; the manufacturer need only understand that
many surgeons appear willing to pay for it and then reproduce the important
features of the user-developed prototypes in a commercial product.
={ Free revealing of innovation information :
     lead users and +35 | users and ;
   Surgical equipment
}

Observation of innovation by lead users and adoption by follow-on users also
can give manufacturers a better understanding of the size of the potential
market. Projections of product sales have been shown to be much more accurate
when they are based on actual customer behavior than when they are based on
potential buyers' pre-use expectations. Monitoring of field use of user-built
prototypes and of their adoption by other users can give manufacturers rich
data on precisely these matters and so should improve manufacturer's commercial
success. In net, user innovation helps to reduce information asymmetries
between users and manufacturers and so increases the efficiency of the
innovation process.
={ Information asymmetries ;
   Users :
     information asymmetries of
}

!_ User Innovation and Provisioning Biases

The economic literature on the impact of innovation on social welfare generally
seeks to understand effects that might induce society to create too many
product variations (overprovisioning) or too few (underprovisioning) from the
viewpoint of net social economic income (Chamberlin 1950). Greater variety of
products available for purchase is assumed to be desirable, in that it enables
consumers to get more precisely what they want and/or to own a more diverse
array of products. However, increased product diversity comes at a cost:
smaller quantities of each product will be produced on average. This in turn
means that development-related and production-related economies of scale are
likely to be less. The basic tradeoff between variety and cost is what creates
the possibility of overprovisioning or underprovisioning product variety.
Innovations such as flexible manufacturing may reduce fixed costs associated
with increased diversity and so shift the optimal degree of diversity upward.
Nonetheless, the conflict still persists.
={ Chamberlin, E. ;
   Social welfare :
     innovation and +11
}

Henkel and I studied the welfare impact of adding users as a source of
innovation to existing analyses of product diversity, innovation, and social
welfare. Existing models uniformly contained the assumption that new products
and services were supplied to the economy by manufacturers only. We found that
the addition of innovation by users to these analyses largely avoids the
welfare-reducing biases that had been identified. For example, consider
"business stealing" (Spence 1976). This term refers to the fact that commercial
manufacturers benefit by diverting business from their competitors. Since they
do not take this negative externality into account, their private gain from
introducing new products exceeds society's total gain, tilting the balance
toward overprovision of variety. In contrast, a freely revealed user innovation
may also reduce incumbents' business, but not to the innovator's benefit.
Hence, innovation incentives are not socially excessive.
={ Henkel, J. ;
   Spence, M. ;
   Free revealing of innovation information :
     intellectual property rights and +11 | social welfare and +5 ;
   Government policy :
     free revealing and +10 ;
   Government policy :
     provisioning biases and ;
   Intellectual property rights :
     free revealing and +11 ;
   Users :
     social welfare and +5
}

Freely revealed innovations by users are also likely to reduce deadweight loss
caused by pricing of products above their marginal costs. (Deadweight loss is a
reduction in social welfare that occurs when goods are sold at a price above
their marginal cost of production.) When users make information about their
innovations available for free, and if the marginal cost of revealing that
information is zero, an imitator only has to bear the cost of adoption. This is
statically efficient. The availability of free user innovations can also induce
sellers of competing commercial offerings to reduce their prices, thus
indirectly leading to another reduction in dead-weight loss.

Reducing prices toward marginal costs can also reduce incentives to
over-provision variety (Tirole 1988).
={ Tirole, J. }

Henkel and I also explored a few special situations where social welfare might
be /{reduced}/ by the availability of freely revealed user innovations. One of
these was the effect of reduced pricing power on manufacturers that create
"platform" products. Often, a manufacturer of such a product will want to sell
the platform---a razor, an ink-jet printer, a video-game player---at a low
margin or a loss, and then price necessary add-ons (razor blades, ink
cartridges, video games) at a much higher margin. If the possibility of freely
revealed add-ons developed by users makes development of a platform
unprofitable for a manufacturer, social welfare can thereby be reduced.
However, it is only the razor-vs.-blade pricing scheme that may become
unprofitable. Indeed, if the manufacturer makes positive margins on the
platform, then the availability of user-developed add-ons can have a positive
effect: it can increase the value of the platform to users, and so allow
manufacturers to charge higher margins on it and/or sell more units. Jeppesen
(2004) finds that this is in fact the outcome when users introduce free game
modifications (called mods) operating on proprietary game software platform
products (called engines) sold by game manufacturers. Even though the game
manufacturers also sell mods commercially that compete with free user mods,
many provide active support for the development and diffusion of user mods
built on their proprietary game engines, because they find that the net result
is increased sales and profits.
={ Henkel, J. ;
   Jeppesen, L. ;
   Government policy :
     intellectual property rights and | trade secrets and ;
   Intellectual property rights :
     trade secrets and
}

!_ Public Policy Choices

If innovation by users is welfare enhancing and is also significant in amount
and value, then it makes sense to consider the effects of public policy on user
innovation. An important first step would be to collect better data. Currently,
much innovation by users---which may in aggregate turn out to be a very large
fraction of total economic investment in innovation--- goes uncounted or
undercounted. Thus, innovation effort that is volunteered by users, as is the
case with many contributions to open source software, is currently not recorded
by governmental statistical offices. This is also the case for user innovation
that is integrated with product and service production. For example, much
process innovation by manufacturers occurs on the factory floor as they produce
goods and simultaneously learn how to improve their production processes.
Similarly, many important innovations developed by surgeons are woven into
learning by doing as they deliver services to patients.
={ Open source software :
     innovation communities and
}

Next, it will be important to review innovation-related public policies to
identify and correct biases with respect to sources of innovation. On a level
playing field, users will become a steadily more important source of
innovation, and will increasingly substitute for or complement manufacturers'
innovation-related activities. Transitions required of policy making to support
this ongoing evolution are important but far from painless. To illustrate, we
next review issues related to the protection intellectual property, related to
policies restricting product modifications, related to source-biased subsidies
for R&D, and related to control over innovation diffusion channels.
={ Government policy :
     provisioning biases and | intellectual property rights and +16 | patents and +8 ;
   Intellectual property rights :
     patents and +8
}

!_ Intellectual Property

Earlier, when we explored why users might freely reveal their innovations, we
concluded that it was often their best /{practical}/ choice in view of how
intellectual property law actually functions (or, often, does not function) to
protect innovations today. For example, recall from chapter 6 that most
innovators do not judge patents to be very effective, and that the availability
of patent grant protection does not appear to increase innovation investments
in most fields. Recall also that patent protection is costly to obtain, and
thus of little value to developers of minor innovations---with most innovations
being minor. We also saw that in practice it was often difficult for innovators
to protect their innovations via trade secrecy: it is hard to keep a secret
when many others know similar things, and when some of these information
holders will lose little or nothing from freely revealing what they know.
={ Intellectual property rights :
     trade secrets and ;
   Government policy :
     trade secrets and ;
   Intellectual property rights :
     trade secrets and
}

These findings show that the characteristics of present-day intellectual
property regimes as actually experienced by innovators are far from the
expectations of theorists and policy makers. The fundamental reason that
societies elect to grant intellectual property rights to innovators is to
increase private investment in innovation. At the same time, economists have
long known that there will be social welfare losses associated with these
grants: owners of intellectual property will generally restrict the use of
their legally protected information in order to increase private profits. In
other words, intellectual property rights are thought to be good for innovation
and bad for competition. The consensus view has long been that the good
outweighs the bad, but Foray (2004) explains that this consensus is now
breaking down. Some---not all---are beginning to think that intellectual
property rights are bad for innovation too in many cases.
={ oray, D. ;
   Government policy :
     intellectual commons and +13
}

The need to grant private intellectual property rights to achieve socially
desirable levels of innovation is being questioned in the light of apparent
counterexamples. Thus, as we saw earlier, open source software communities do
not allow contributing innovators to use their intellectual property rights to
control the use of their code. Instead, contributors use their authors'
copyright to assign their code to a common pool to which all--- contributors
and non-contributors alike---are granted equal access. Despite this regime,
innovation seems to be flourishing. Why? As we saw in our earlier discussions
of why innovators might freely reveal their innovations, researchers now
understand that significant private rewards to innovation can exist independent
of intellectual property rights grants. As a general principle, intellectual
property rights grants should not be offered if and when developers would seek
protection but would innovate without it.
={ Intellectual property rights :
     copyrights and ;
   Open source software :
     innovation communities and +1 ;
   Innovation :
     open source software and +1
}

The debate rages. Gallini and Scotchmer (2002) assert that "intellectual
property is the foundation of the modern information economy" and that "it
fuels the software, lifesciences and computer industries, and pervades most
other products we consume." They also conclude that the positive or negative
effect of intellectual property rights on innovation depends centrally on "the
ease with which innovators can enter into agreements for rearranging and
exercising those rights." This is precisely the rub from the point of view of
those who urge that present intellectual property regimes be reconsidered: it
is becoming increasingly clear that in practice rearranging and exercising
intellectual property rights is often difficult rather than easy. It is also
becoming clear that the protections afforded by existing intellectual property
law can be strategically deployed to achieve private advantage at the expense
of general innovative progress (Foray 2004).
={ oray, D. ;
   Gallini, N. ;
   Scotchmer, S.
}

Consider an effect first pointed out by Merges and Nelson (1990) and further
explored as the "tragedy of the anticommons" by Heller (1998) and Heller and
Eisenberg (1998). A resource such as innovation-related information is prone to
underuse---a tragedy of the anticommons---when multiple owners each have a
right to exclude others and no one has an effective privilege of use. The
nature of the patent grant can lead to precisely this type of situation. Patent
law is so arranged that an owner of a patent is not granted the right to
practice its invention---it is only granted the right to exclude others from
practicing it. For example, suppose you invent and patent the chair. I then
follow by inventing and patenting the rocking chair---implemented by building
rockers onto a chair covered by your patent. In this situation I cannot
manufacture a rocking chair without getting a license from you for the use of
your chair patent, and you cannot build rocking chairs either without a license
to my rocker patent. If we cannot agree on licensing terms, no one will have
the right to build rocking chairs.
={ Eisenberg, R. +1 ;
   Heller, M. +1 ;
   Merges, Robert ;
   Nelson, R. ;
   Government policy :
     user innovation and +19
}

In theory and in a world of costless transactions, people could avoid tragedies
of the anticommons by licensing or trading their intellectual property rights.
In practice the situation can be very different. Heller and Eisenberg point
specifically to the field of biomedical research, and argue that conditions for
anticommons effects do exist there. In that field, patents are routinely
allowed on small but important elements of larger research problems, and
upstream research is increasingly likely to be private. "Each upstream patent,"
Heller and Eisenberg note, "allows its owner to set up another tollbooth on the
road to product development, adding to the cost and slowing the pace of
downstream biomedical innovation."
={ Transaction costs }

A second type of strategic behavior based on patent rights involves investing
in large portfolios of patents to create "patent thickets"---dense networks of
patent claims across a wide field (Merges and Nelson 1990; Hall and Ham
Ziedonis 2001; Shapiro 2001; Bessen 2003). Patent thickets create plausible
grounds for patent infringement suits across a wide field. Owners of patent
thickets can use the threat of such suits to discourage others from investing
research dollars in areas of technical advance relevant to their products. Note
that this use of patents is precisely opposite to policy mak' intentions to
stimulate innovation by providing ways for innovators to assert intellectual
property rights. Indeed, Bessen and Hunt (2004) have found in the field of
software that, on average, as firm's investments in patent protection go up,
their investments in research and development actually go down. If this
relationship proves causal, there is a reasonable explanation from the
viewpoint of private profit: corporations that can use a patent thicket to
deter others' research in a field might well decide that there is less need to
do research of their own.
={ Bessen, J. ;
   Hall, B. ;
   Hunt, R. ;
   Merges, Robert ;
   Nelson, R. ;
   Shapiro, C. ;
   Ziedonis, R. ;
   Government policy :
     patent thickets and ;
   Intellectual property rights :
     patent thickets and
}

Similar innovation-retarding strategies can be applied by owners of large
collections of copyrighted work in the movie, publishing, and software fields.
Copyright owners can prevent others from building new works on characters (e.g.
Mickey Mouse) that are already familiar to customers. The result is that owners
of large portfolios of copyrighted work can gain an advantage over those with
no or small portfolios in the creation of derivative works. Indeed, Benkler
(2002) argues that institutional changes strengthening intellectual property
protection tend to foster concentration of information production in general.
Lessig (2001) and Boldrin and Levine (2002) arrive at a similarly negative
valuation of overly strong and lengthy copyright protection.
={ Benkler, Y. ;
   Boldrin, M. ;
   Levine, D. ;
   Lessig, L. ;
   Intellectual property rights :
     copyrights and ;
   Government policy :
     copyrights and
}

These types of innovation-discouraging effects can affect innovation by users
especially strongly. The distributed innovation system we have documented
consists of users each of whom might have only a few innovations and a small
amount of intellectual property. Such innovators are clearly hurt
differentially by a system that gives advantage to the owners of large shares
of the intellectual property in a field.

What can be done? A solution approach open to policy makers is to change
intellectual property law so as to level the playing field. But owners of large
amounts of intellectual property protected under the present system are often
politically powerful, so this type of solution will be difficult to achieve.

Fortunately, an alternative solution approach may be available to innovators
themselves. Suppose that many elect to contribute the intellectual property
they individually develop to a commons in a particular field. If the commons
then grows to contain reasonable substitutes for much of the proprietary
intellectual property relevant to the field, the relative advantage accruing to
large holders of this information will diminish and perhaps even disappear. At
the same time and for the same reason, the barriers that privately held stocks
of intellectual property currently may raise to further intellectual advance
will also diminish. Lessig supports this possibility with his creation and
publication of standard "Creative Commons" licenses on the website
creativecommons.org. Authors interested in contributing their work to the
commons, perhaps with some restrictions, can easily find and adopt an
appropriate license at that site.
={ Lessig, L. ;
   Intellectual commons +13 ;
   Intellectual property rights :
     intellectual commons and +13 ;
   Open source software :
     intellectual commons and +13 | intellectual property rights and +13 ;
   Intellectual property rights :
     licensing of
}

Reaching agreement on conditions for the formation of an intellectual commons
can be difficult. Maurer (2005) makes this clear in his cautionary tale of the
struggle and eventual failure to create a commons for data on human mutations.
However, success is possible. For example, an extensive intellectual commons of
software code is contained and maintained in the many open source software
projects that now exist.
={ Maurer, S. ;
   Innovation communities +2
}

Interesting examples also exist regarding on the impact a commons can have on
the value of intellectual property innovators seek to hold apart from it. Weber
(2004) recounts the following anecdote: In 1988, Linux developers were building
new graphical interfaces for their open source software. One of the most
promising of these, KDE, was offered under the General Public License. However,
Matthias Ettrich, its developer, had built KDE using a proprietary graphical
library called Qt. He felt at the time that this could be an acceptable
solution because Qt was of good quality and Troll Tech, owner of Qt, licensed
Qt at no charge under some circumstances. However, Troll Tech did require a
developer's fee be paid under other circumstances, and some Linux developers
were concerned about having code not licensed under the GPL as part of their
code. They tried to convince Troll Tech to change the Qt license so that it
would be under the GPL when used in free software. But Troll Tech, as was fully
within its rights, refused to do this. Linux developers then, as was fully
within their rights, began to develop open source alternatives to Qt that could
be licensed under the GPL. As those projects moved toward success, Troll Tech
recognized that Qt might be surpassed and effectively shut out of the Linux
market. In 2000 the company therefore decided to license Qt under the GPL.
={ Ettrich, M. ;
   Linux ;
   Weber, S. ;
   Intellectual property rights :
     licensing of +1 ;
}

Similar actions can keep conditions for free access to materials held within a
commons from degrading and being lost over time. Chris Hanson, a Principal
Research Scientist at MIT, illustrates this with an anecdote regarding an open
source software component called ipfilter. The author of ipfilter attempted to
"lock" the program by changing licensing terms of his program to disallow the
distribution of modified versions. His reasoning was that Ipfilter, a
network-security filter, must be as bug-free as possible, and that this could
best be ensured by his controlling access. His actions ignited a flame war in
which the author was generally argued to be selfish and overreaching. His
program, then an essential piece of BSD operating systems, was replaced by
newly written code in some systems within the year. The author, Hanson notes,
has since changed his licensing terms back to a standard BSD-style
(unrestricted) license.
={ Hanson, C. }

We will learn over time whether and how widely the practice of creating and
defending intellectual commons diffuses across fields. There obviously can be
cases where it will continue to make sense for innovators, and for society as
well, to protect innovations as private intellectual property. However, it is
likely that many user innovations are kept private not so much out of rational
motives as because of a general, not-thought-through attitude that "we do not
give away our intellectual property," or because the administrative cost of
revealing is assumed to be higher than the benefits. Firms and society can
benefit by rethinking the benefits of free revealing and (re)developing
policies regarding what is best kept private and what is best freely revealed.
={ Government policy :
     social welfare and +9 | trade secrets and +3 ;
   Intellectual property rights :
     trade secrets and +3
}

!_ Constraints on Product Modification
={ Custom products :
     manufacturers and +2 ;
   Government policy :
     manufacturer innovation and +8 ;
   Manufacturers :
     government policy and +8
}

Users often develop prototypes of new products by buying existing commercial
products and modifying them. Current efforts by manufacturers to build
technologies into the products they sell that restrict the way these products
are used can undercut users' traditional freedom to modify what they purchase.
This in turn can raise the costs of innovation development by users and so
lessen the amount of user innovation that is done. For example, makers of
ink-jet printers often follow a razor-and-blade strategy, selling printers at
low margins and the ink cartridges used in them at high margins. To preserve
this strategy, printer manufacturers want to prevent users from refilling ink
cartridges with low-cost ink and using them again. Accordingly, they may add
technical modifications to their cartridges to prevent them from functioning if
users have refilled them. This manufacturer strategy can potentially cut off
both refilling by the economically minded and modifications by user-innovators
that might involve refilling (Varian 2002). Some users, for example, have
refilled cartridges with special inks not sold by printer manufacturers in
order to adapt ink-jet printing to the printing of very high-quality
photographs. Others have refilled cartridges with food colorings instead of
inks in order to develop techniques for printing images on cakes. Each of these
applications might have been retarded or prevented by technical measures
against cartridge refilling.
={ Varian, H. }

The Digital Millennium Copyright Act, a legislative initiative intended to
prevent product copying, may negatively affect users' abilities to change and
improve the products they own. Specifically, the DMCA makes it a crime to
circumvent anti-piracy measures built into most commercial software. It also
outlaws the manufacture, sale, or distribution of code-cracking devices used to
illegally copy software. Unfortunately, code cracking is also a needed step for
modification of commercial software products by user-innovators. Policy makers
should be aware of "collateral damage" that may be inflicted on user innovation
by legislation aimed at other targets, as is likely in this case.
={ Digital Millennium Copyright Act }

!_ Control over Distribution Channels
={ Government policy :
     distribution channels and +1
}

Users that innovate and wish to freely diffuse innovation-related information
are able to do so cheaply in large part because of steady advances in Internet
distribution capabilities. Controls placed on such infrastructural factors can
threaten and maybe even totally disable distributed innovation systems such as
the user innovation systems documented in this book. For example, information
products developed by users are commonly distributed over the Internet by
peer-to-peer sharing networks. A firm that owns both a channel and content
(e.g., a cable network) may have a strong incentive to shut out or discriminate
against content developed by users or others in favor of its own content. The
transition from the chaotic, fertile early days of radio in the United States
when many voices were heard, to an era in which the spectrum was dominated by a
few major networks---a transition pushed by major firms and enforced by
governmental policy making--- provides a sobering example of what could happen
(Lessig 2001). It will be important for policy makers to be aware of this kind
of incentive problem and address it---in this case perhaps by mandating that
ownership of content and ownership of channel be separated, as has long been
the case for other types of common carriers.
={ Lessig, L. }

!_ R&D Subsidies and Tax Credits
={ Government policy :
     R&D subsidies and +3
}

In many countries, manufacturing firms are rewarded for their innovative
activity by R&D subsidies and tax credits. Such measures can make economic
sense if average social returns to innovation are significantly higher than
average private returns, as has been found by Mansfield et al. (1977) and
others. However, important innovative activities carried out by users are often
not similarly rewarded, because they tend to not be documentable as formal R&D
activities. As we have seen, users tend to develop innovations in the course of
"doing" in their normal use environments. Bresnahan and Greenstein (1996a) make
a similar point. They investigate the role of "co-invention" in the move by
users from mainframe to client-server architecture.~{ See also Bresnahan and
Greenstein 1996b; Bresnahan and Saloner 1997; Saloner and Steinmueller 1996. }~
By "co-invention" Bresnahan and Greenstein mean organizational changes and
innovations developed and implemented by users that are required to take full
advantage of a new invention. They point out the high importance that
co-invention has for realizing social returns from innovation. They consider
the federal government's support for creating "national information
infrastructures" insufficient or misallocated, since they view co-invention is
the bottleneck for social returns and likely the highest value locus for
invention.
={ Bresnahan, T. ;
   Greenstein, S. ;
   Mansfield, E. ;
   Users :
     co-invention and
}

Efforts to level the playing field for user innovation and manufacturer
innovation could, of course, also go in the direction of lessening R&D
subsidies or tax credits for all rather than attempting to increase
user-innovators' access to subsidies. However, if directing subsidies to
user-innovators seems desirable, social welfare will be best served if policy
makers link them to free revealing by user-innovators as well as or instead of
tying them to users' private investments in the development of products for
exclusive in-house use. Otherwise, duplication of effort by users interested in
the same innovation will reduce potential welfare gains.
={ Free revealing of innovation information :
     government policy and +1 | social welfare and +1
}

In sum, the welfare-enhancing effects found for freely revealed user
innovations suggest that policy makers should consider conditions required for
user innovation when creating policy and legislation. Leveling the playing
field for user-innovators and manufacturer-innovators will doubtless force more
rapid change onto manufacturers. However, as will be seen in the next chapter,
manufacturers can adapt to a world in which user innovation is at center stage.

1~ 9 Democratizing Innovation
={ Social welfare :
     innovation and +45 ;
   von Hippel, E. +45
}

We have learned that lead users sometimes develop and modify products for
themselves and often freely reveal what they have done. We have also seen that
many users can be interested in adopting the solutions that lead users have
developed. Taken together, these findings offer the basis for user-centered
innovation systems that can entirely supplant manufacturer-based innovation
systems under some conditions and complement them under most. User-centered
innovation is steadily increasing in importance as computing and communication
technologies improve.
={ Free revealing of innovation information :
     lead users and ;
   Manufacturers :
     innovation and +44 ;
   Custom products :
     users and ;
   Innovation :
     lead users and ;
   Lead users :
     innovation and ;
   User need +3 ;
   Users :
   innovation and +4
}

I begin this chapter with a discussion of the ongoing democratization of
innovation. I then describe some of the patterns in user-centered innovation
that are emerging. Finally, I discuss how manufacturers can find ways to
profitably participate in emerging, user-centered innovation processes.

!_ The Trend toward Democratization

Users' abilities to develop high-quality new products and services for
themselves are improving radically and rapidly. Steady improvements in computer
software and hardware are making it possible to develop increasingly capable
and steadily cheaper tools for innovation that require less and less skill and
training to use. In addition, improving tools for communication are making it
easier for user innovators to gain access to the rich libraries of modifiable
innovations and innovation components that have been placed into the public
domain. The net result is that rates of user innovation will increase even if
users' heterogeneity of need and willingness to pay for "exactly right"
products remain constant.
={ Custom products :
     users and +1 ;
   Users :
     paying for innovations and
}

The radical nature of the change that is occurring in design capabilities
available to even individual users is perhaps difficult for those without
personal innovation experience to appreciate. An anecdote from my own
experience may help as illustration. When I was a child and designed new
products that I wanted to build and use, the ratio of not-too-pleasurable (for
me) effort required to actually build a prototype relative to the very
pleasurable effort of inventing it and use-testing it was huge. (That is, in
terms of the design, build, test, evaluate cycle illustrated in figure 5.1, the
effort devoted to the "build" element of the cycle was very large and the rate
of iteration and learning via trial and error was very low.)

In my case it was especially frustrating to try to build anything sophisticated
from mechanical parts. I did not have a machine shop in which I could make good
parts from scratch, and it often was difficult to find or buy the components I
needed. As a consequence, I had to try to assemble an approximation of my ideas
out of vacuum cleaner parts and other bits of metal and plastic and rubber that
I could buy or that were lying around. Sometimes I failed at this and had to
drop an exciting project. For example, I found no way to make the combustion
chamber I needed to build a large pulse-jet engine for my bicycle (in
retrospect, perhaps a lucky thing!). Even when I succeeded, the result was
typically "unaesthetic": the gap between the elegant design in my mind and the
crude prototype that I could realize was discouragingly large.

Today, in sharp contrast, user firms and increasingly even individual hobbyists
have access to sophisticated design tools for fields ranging from software to
electronics to musical composition. All these information-based tools can be
run on a personal computer and are rapidly coming down in price. With
relatively little training and practice, they enable users to design new
products and services---and music and art---at a satisfyingly sophisticated
level. Then, if what has been created is an information product, such as
software or music, the design is the actual product---software you can use or
music you can play.

If one is designing a physical product, it is possible to create a design and
even conduct some performance testing by computer simulation. After that,
constructing a real physical prototype is still not easy. However, today users
do have ready access to kits that offer basic electronic and mechanical
building blocks at an affordable price, and physical product prototyping is
becoming steadily easier as computer-driven 3-D parts printers continue to go
up in sophistication while dropping in price. Very excitingly, even today
home-built prototypes need not be poorly fashioned items that will fall apart
with a touch in the wrong place---the solution components now available to
users are often as good as those available to professional designers.

Functional equivalents of the resources for innovation just described have long
been available within corporations to a lucky few. Senior designers at firms
have long been supported by engineers and designers under their direct control,
and also with other resources needed to quickly construct and test prototype
designs. When I took a job as R&D manager at a start-up firm after college, I
was astounded at the difference professional-quality resources made to both the
speed and the joy of innovation. Product development under these conditions
meant that the proportion of one's effort that could be focused on the design
and test portions of the innovation cycle rather than on prototype building was
much higher, and the rate of progress was much faster.
={ Innovation process +3 }

The same story can be told in fields from machine design to clothing design:
just think of the staffs of seamstresses and models supplied by clothing
manufacturers to their "top designers" so that these few can quickly realize
and test many variations on their designs. In contrast, think of the time and
effort that equally talented designers without such staff assistance must
engage in to stitch together even a single high-quality garment prototype on
their own.

But, as we learned in chapter 7, the capability and the information needed to
innovate in important ways are in fact widely distributed. Given this finding,
we can see that the traditional pattern of concentrating innovation-support
resources on just a few pre-selected potential innovators is hugely
inefficient. High-cost resources for innovation support cannot be allocated to
"the right people," because one does not know who they are until they develop
an important innovation. When the cost of high-quality resources for design and
prototyping becomes very low---which is the trend we have described---these
resources can be diffused widely, and the allocation problem then diminishes in
significance. The net result is and will be to democratize the opportunity to
create.

Democratization of the opportunity to create is important beyond giving more
users the ability to make exactly right products for themselves. As we saw in a
previous chapter, the joy and the learning associated with creativity and
membership in creative communities are also important, and these experiences
too are made more widely available as innovation is democratized. The
aforementioned Chris Hanson, a Principal Research Scientist at MIT and a
maintainer in the Debian Linux community, speaks eloquently of this in his
description of the joy and value he finds from his participation in an open
source software community:
={ Hanson, C. ;
   Linux ;
   Users :
     innovate-or-buy decisions by +3 | innovation process and +3 ;
   Free revealing of innovation information :
     innovation and +3 ;
   Innovation communities :
     open source software and ;
   Linux ;
   Open source software :
     innovation communities and +3
}

_1 Creation is unbelievably addictive. And programming, at least for skilled
programmers, is highly creative. So good programmers are compelled to program
to feed the addiction. (Just ask my wife!) Creative programming takes time, and
careful attention to the details. Programming is all about expressing intent,
and in any large program there are many areas in which the programmer's intent
is unclear. Clarification requires insight, and acquiring insight is the
primary creative act in programming. But insight takes time and often requires
extensive conversation with one's peers.

_1 Free-software programmers are relatively unconstrained by time. Community
standards encourage deep understanding, because programmers know that
understanding is essential to proper function. They are also programming for
themselves, and naturally they want the resulting programs to be as good as
they can be. For many, a free software project is the only context in which
they can write a program that expresses their own vision, rather than
implementing someone else's design, or hacking together something that the
marketing department insists on. No wonder programmers are willing to do this
in their spare time. This is a place where creativity thrives.

_1 Creativity also plays a role in the programming community: programming, like
architecture, has both an expressive and a functional component. Unlike
architecture, though, the expressive component of a program is inaccessible to
non-programmers. A close analogy is to appreciate the artistic expression of a
novel when you don't know the language in which it is written, or even if you
know the language but are not fluent. This means that creative programmers want
to associate with one another: only their peers are able to truly appreciate
their art. Part of this is that programmers want to earn respect by showing
others their talents. But it's also important that people want to share the
beauty of what they have found. This sharing is another act that helps build
community and friendship.

!_ Adapting to User-Centered Innovation---Like It or Not
={ Innovation process +5 ;
   Free revealing of innovation information :
     innovation and +5
}

User-centered innovation systems involving free revealing can sometimes
supplant product development carried out by manufacturers. This outcome seems
reasonable when manufacturers can obtain field-tested user designs at no cost.
As an illustration, consider kitesurfing (previously discussed in chapter 7).
The recent evolution of this field nicely shows how manufacturer-based product
design may not be able to survive when challenged by a user innovation
community that freely reveals leading-edge designs developed by users. In such
a case, manufacturers may be obliged to retreat to manufacturing only,
specializing in modifying user-developed designs for producibility and
manufacturing these in volume.
={ Free revealing of innovation information :
     users and ;
   Kitesurfing +4
}

Recall that equipment for kitesurfing was initially developed and built by
user-enthusiasts who were inventing both kitesurfing techniques and kitesurfing
equipment interdependently. Around 1999, the first of several small
manufacturers began to design and sell kitesurfing equipment commercially. The
market for kitesurfing equipment then began to grow very rapidly. In 2001 about
5,000 kite-and-board sets were sold worldwide. In 2002 the number was about
30,000, and in 2003 it was about 70,000. With a basic kite-and-board set
selling for about $1,500, total sales in 2003 exceeded $100 million. (Many
additional kites, home-made by users, are not included in this calculation.) As
of 2003, about 40 percent of the commercial market was held by a US firm called
Robbie Naish (Naishkites.com).

Recall also that in 2001 Saul Griffith, an MIT graduate student, established an
Internet site called Zeroprestige.com as a home for a community of kitesurfing
users and user-innovators. In 2003, the general consensus of both site
participants and manufacturers was that the kite designs developed by users and
freely revealed on Zeroprestige.com were at least as advanced as those
developed by the leading manufacturers. There was also a consensus that the
level of engineering design tools and aggregate rate of experimentation by kite
users participating on the Zeroprestige.com site was superior to that within
any kite manufacturer. Indeed, this collective user effort was probably
superior in quality and quantity to the product-development work carried out by
all manufacturers in the industry taken together.
={ Griffith, S. ;
   Zeroprestige.com +1
}

In late 2003, a perhaps predictable event occurred: a kite manufacturer began
downloading users' designs from Zeroprestige.com and producing them for
commercial sale. This firm had no internal kitesurfing product-development
effort and offered no royalties to user-innovators---who sought none. It also
sold its products at prices much lower than those charged by companies that
both developed and manufactured kites.

It is not clear that manufacturers of kitesurfing equipment adhering to the
traditional developer-manufacturer model can---or should---survive this new and
powerful combination of freely revealed collaborative design and prototyping
effort by a user innovation community combined with volume production by a
specialist manufacturer. In effect, free revealing of product designs by users
offsets manufacturers' economies of scale in design with user communities'
economies of scope. These economies arise from the heterogeneity in information
and resources found in a user community.
={ Custom products :
     heterogeneity of user needs and ;
   User need +2
}

!_ Manufacturers' Roles in User-Centered Innovation

Users are not required to incorporate manufacturers in their
product-development and product-diffusion activities. Indeed, as open source
software projects clearly show, horizontal innovation communities consisting
entirely of users can develop, diffuse, maintain, and consume software and
other /{information}/ products by and for themselves---no manufacturer is
required. Freedom from manufacturer involvement is possible because information
products can be "produced" and distributed by users essentially for free on the
web (Kollock 1999). In contrast, production and diffusion of physical products
involves activities with significant economies of scale. For this reason, while
product development and early diffusion of copies of physical products
developed by users can be carried out by users themselves and within user
innovation communities, mass production and general diffusion of physical
products incorporating user innovations are usually carried out by
manufacturing firms.
={ Innovation communities :
     open source software and +5 ;
   Open source software :
     innovation and +5 | innovation communities and +5
}

For information products, general distribution is carried out within and beyond
the user community by the community itself; no manufacturer is required:

Innovating lead users ➔ All users.

For physical products, general distribution typically requires manufacturers:

Innovating lead users ➔ Manufacturer ➔ All users.

In light of this situation, how can, should, or will manufacturers of products,
services, and processes play profitable roles in user-centered innovation
systems? Behlendorf (1999), Hecker (1999) and Raymond (1999) explore what might
be possible in the specific context of open source software. More generally,
many are experimenting with three possibilities: (1) Manufacturers may produce
user-developed innovations for general commercial sale and/or offer a custom
manufacturing service to specific users. (2) Manufacturers may sell kits of
product-design tools and/or "product platforms" to ease users'
innovation-related tasks. (3) Manufacturers may sell products or services that
are complementary to user-developed innovations.
={ Behlendorf, B. ;
   Hecker, F. ;
   Raymond, E.
}

!_ Producing User-Developed Products

Firms can make a profitable business from identifying and mass producing
user-developed innovations or developing and building new products based on
ideas drawn from such innovations. They can gain advantages over competitors by
learning to do this better than other manufacturers. They may, for example,
learn to identify commercially promising user innovations more effectively that
other firms. Firms using lead user search techniques such as those we will
describe in chapter 10 are beginning to do this systematically rather than
accidentally---surely an improvement. Effectively transferring user-developed
innovations to mass manufacture is seldom as simple as producing a product
based on a design by a single lead user. Often, a manufacturer combines
features developed by several independent lead users to create an attractive
commercial offering. This is a skill that a company can learn better than
others in order to gain a competitive advantage.
={ Lead users :
     innovation and | manufacturers and +1 ;
   Manufacturers :
     lead users and +1
}

The decision as to whether or when to take the plunge and commercialize a lead
user innovation(s) is also not typically straightforward, and companies can
improve their skills at inviting in the relevant information and making such
assessments. As was discussed previously, manufacturers often do not understand
emerging user needs and markets nearly as well as lead users do. Lead users
therefore may engage in entrepreneurial activities, such as "selling" the
potential of an idea to potential manufacturers and even lining up financing
for a manufacturer when they think it very important to rapidly get widespread
diffusion of a user-developed product. Lettl, Herstatt, and Gemünden (2004),
who studied the commercialization of major advances in surgical equipment,
found innovating users commonly engaging in these activities. It is also
possible, of course, for innovating lead users to become manufacturers and
produce the products they developed for general commercial sale. This has been
shown to occur fairly frequently in the field of sporting goods (Shah 2000;
Shah and Tripsas 2004; Hienerth 2004).
={ Gemünden, H. ;
   Lettl, C. ;
   Herstatt, C. ;
   Hienerth, C. ;
   Shah, S. ;
   Tripsas, M. ;
   Lead users :
     surgical equipment and ;
   Windsurfing ;
   Custom products :
     innovation and +1 | manufacturers and +1 ;
   users and +1 ;
   Users :
     custom products and +1
}

Manufacturers can also elect to provide custom production or "foundry" services
to users, differentiating themselves by producing users' designs faster,
better, and/or cheaper than competitors. This type of business model is already
advanced in many fields. Custom machine shops specialize in manufacturing
mechanical parts to order; electronic assembly shops produce custom electronic
products, chemical manufacturers offer "toll" manufacturing of custom products
designed by others, and so on. Suppliers of custom integrated circuits offer an
especially good example of custom manufacture of products designed by users.
More than $15 billion worth of custom integrated circuits were produced in
2002, and the cumulative average growth rate of that market segment was 29
percent. Users benefit from designing their own circuits by getting exactly
what they want more quickly than manufacturer-based engineers could supply what
they need, and manufacturers benefit from producing the custom designs for
users (Thomke and von Hippel 2002).
={ Thomke, S. ;
   von Hippel, E. ;
   Custom products :
     suppliers and +2 ;
   Suppliers +2 ;
   Economic benefit, expectations of by lead users :
     by manufacturers | by users
}

!_ Supplying Toolkits and/or Platform Products to Users
={ Custom products :
     product platforms and +7 ;
   Toolkits +7 :
     platform products and +7
}

Users interested in designing their own products want to do it efficiently.
Manufacturers can therefore attract them to kits of design tools that ease
their product-development tasks and to products that can serve as "platforms"
upon which to develop and operate user-developed modifications. Some are
supplying users with proprietary sets of design tools only. Cadence, a supplier
of design tools for corporate and even individual users interested in designing
their own custom semiconductor chips, is an example of this. Other
manufacturers, including Harley-Davidson in the case of motorcycles and
Microsoft in the case of its Excel spreadsheet software, sell platform products
intentionally designed for post-sale modification by users.
={ Microsoft }

Some firms that sell platform products or design tools to users have learned to
systematically incorporate valuable innovations that users may develop back
into their commercial products. In effect, this second strategy can often be
pursued jointly with the manufacturing strategy described above. Consider, for
example, StataCorp of College Station, Texas. StataCorp produces and sells
Stata, a proprietary software program designed for statistics. It sells the
basic system bundled with a number of families of statistical tests and with
design tools that enable users to develop new tests for operation on the Stata
platform. Advanced customers, many of them statisticians and social science
researchers, find this capability very important to their work and do develop
their own tests. Many then freely reveal tests they have developed on Internet
websites set up by the users themselves. Other users then visit these sites to
download and use, and perhaps to test, comment on, and improve these tests,
much as users do in open source software communities.
={ StataCorp statistical software +2 ;
   Toolkits :
     StataCorp and +2 ;
   Free revealing of innovation information :
     innovation and +3 | intellectual property rights and +3 ;
   Government policy :
     free revealing and +3 | intellectual property rights and +3 | trade secrets and +3 ;
   Innovation communities +3 :
     open source software and +3 | and sources of innovation +3 ;
   Intellectual property rights :
     free revealing and +3 | trade secrets and +3 ;
   Open source software :
     innovation and +10 | innovation communities and +10
}

StataCorp personnel monitor the activity at user sites, and note the new tests
that are of interest to many users. They then bring the most popular tests into
their product portfolio as Stata modules. To do this, they rewrite the user's
software code while adhering to the principles pioneered by the user-innovator.
They then subject the module to extensive validation testing---a very important
matter for statisticians. The net result is a symbiotic relationship.
User-innovators are publicly credited by Stata for their ideas, and benefit by
having their modules professionally tested. StataCorp gains a new commercial
test module, rewritten and sold under its own copyright. Add-ons developed by
users that are freely revealed will increase StataCorp's profits more than will
equivalent add-ons developed and sold by manufacturers (Jokisch 2001). Similar
strategies are pursued by manufacturers of simulator software (Henkel and Thies
2003).
={ Henkel, J. ;
   Jokisch, M. ;
   Thies, S. ;
   Economic benefit, expectations of by lead users :
     by manufacturers | by users
}

Note, however, that StataCorp, in order to protect its proprietary position,
does not reveal the core of its software program to users, and does not allow
any user to modify it. This creates problems for those users who need to make
modifications to the core in order to solve particular problems they encounter.
Users with problems of this nature and users especially concerned about price
have the option of turning to non-proprietary free statistical software
packages available on the web, such as the "R" project (www.r-project.org).
These alternatives are developed and supported by user communities and are
available as open source software. The eventual effect of open source software
alternatives on the viability of the business models of commercial vendors such
as StataCorp and its competitors remains to be seen.

A very similar pattern exists in the online gaming industry. Vendors of early
online computer games were surprised to discover that sophisticated users were
deciphering their closed source code in order to modify the games to be more to
their liking. Some of these "mods" attracted large followings, and some game
vendors were both impressed and supportive. Manufacturers also discovered that
the net effect of user-developed mods was positive for them: mods actually
increased the sales of their basic software, because users had to buy the
vendors' proprietary software engine code in order to play the mods.
Accordingly, a number of vendors began to actively support user-developers by
supplying them with design tools to make it easier for them to build mods on
their proprietary engine platforms (Jeppesen and Molin 2003).
={ Jeppesen, L. +1 ;
   Molin, M.
}

Both manufacturers and users involved with online gaming are experimenting with
the possibilities of user-manufacturer symbiosis in a number of additional
ways. For example, some vendors are experimenting with creating
company-supported distribution channels through which users---who then become
vendors---can sell their mods rather than simply offering them as free
downloads (Jeppesen 2004). At the same time, some user communities are working
in the opposite direction by joining together to develop open source software
engines for video games. If the latter effort is successful, it will offer mod
developers a platform and design tools that are entirely non-proprietary for
the first time. As in the case of statistical software, the eventual outcomes
of all these experiments are not yet clear.

As a final example of a strategy in which manufacturers offer a platform to
support user innovation of value to them, consider General Electric's
innovation pattern with respect to the magnetic-resonance imaging machines it
sells for medical use. Michael Harsh (GE's Director of R&D in the division that
produces MRI machines) and his colleagues realized that nearly all the major,
commercially important improvements to these machines are developed by
leading-edge users rather than by GE or by competing machine producers. They
also knew that commercialization of user-developed improvements would be easier
and faster for GE if the users had developed their innovations using a GE MRI
machine as a platform rather than a competitor's machine. Since MRI machines
are expensive, GE developed a policy of selectively supplying machines at a
very low price to scientists GE managers judged most likely to develop
important improvements. These machines are supplied with restrictive interlocks
removed so that the users can easily modify them. In exchange for this research
support, the medical researchers give GE preferred access to innovations they
develop. Over the years, supported researchers have provided a steady flow of
significant improvements that have been first commercialized by GE. Managers
consider the policy a major source of GE's commercial success in the MRI field.
={ General Electric ;
   Harsh, M. ;
   Toolkits :
     GE and
}

!_ Providing Complementary Products or Services

Many user innovations require or benefit from complementary products or
services, and manufacturers can often supply these at a profit. For example,
IBM profits from user innovation in open source software by selling the
complement of computer hardware. Specifically, it sells computer servers with
open source software pre-installed, and as the popularity of that software goes
up, so do server sales and profits. A firm named Red Hat distributes a version
of the open source software computer operating system Linux, and also sells the
complementary service of Linux technical support to users. Opportunities to
provide profitable complements are not necessarily obvious at first glance, and
providers often reap benefits without being aware of the user innovation for
which they are providing a complement. Hospital emergency rooms, for example,
certainly gain considerable business from providing medical care to the users
and user-developers of physically demanding sports, but may not be aware of
this.
={ IBM ;
   Linux ;
   Users :
     innovation and +3 ;
   Innovation communities :
     open source software and ;
   Linux ;
   Innovation communities :
     sources of innovation and
}

!_ Discussion
={ Government policy :
     intellectual property rights and +2
}

All the examples above explore how manufacturers can integrate themselves into
a user-centered innovation system. However, manufacturers will not always find
user innovations based on or related to their products to be in their interest.
For example, manufacturers may be concerned about legal liabilities and costs
sometimes associated with "unauthorized user tinkering." For example, an
automaker might legitimately worry about the user-programmed engine controller
chips that racing aficionados and others often install to change their cars'
performance. The result can be findings of eventual commercial value as users
explore new performance regimes that manufacturers' engineers might not have
considered. However, if users choose to override manufacturers' programming to
increase engine performance, there is also a clear risk of increased warrantee
costs for manufacturers if engines fail as a consequence (Mollick 2004).
={ Mollick, Ethan }

We have seen that manufacturers can often find ways to profit from user
innovation. It is also the case, however, that user innovators and user
innovation communities can provide many of these same functions for themselves.
For example, StataCorp is successfully selling a proprietary statistical
software package. User-developed alternatives exist on the web that are
developed and maintained by user-innovators and can be downloaded at no charge.
Which ownership model will prove more robust under what circumstances remains
to be seen. Ultimately, since users are the customers, they get to choose.
={ StataCorp statistical software ;
   Toolkits :
     StataCorp and ;
   Users :
     innovation communities and ;
   Innovation communities
}

1~ 10 Application: Searching for Lead User Innovations
={ Users :
     innovation and +59 ;
   Lead users +59 :
     innovation and +59 | identification of +49
}

Users and manufacturers can apply the insights developed in this book to
improve their innovation processes. In this chapter, I illustrate by showing
how firms can profit by /{systematically}/ searching for innovations developed
by lead users. I first explain how this can be done. I then present findings of
a study conducted at 3M to assess the effectiveness of lead user
idea-generation techniques. Finally, I briefly review other studies reporting
systematic searches for lead users by manufacturers, and the results obtained.
={ Lead users :
     idea generation and | 3M and ;
   Manufacturers :
     innovation and | lead users and +16 ;
   3M Corporation
}

!_ Searching for Lead Users

Product-development processes traditionally used by manufacturers start with
market researchers who study customers in their target markets to learn about
unsatisfied needs. Next, the need information they uncover is transferred to
in-house product developers who are charged with developing a responsive
product. In other words, the approach is to find a user need and to fill it by
means of in-house product development.
={ Marketing research +2 }

These traditional processes cannot easily be adapted to systematic searching
for lead user innovations. The focus on target-market customers means that lead
users are regarded as outliers of no interest. Also, traditional
market-research analyses focus on collecting and analyzing need information and
not on possible solutions that users may have developed. For example, if a user
says "I have developed this new product to make task X more convenient,"
market-research analyses typically will note that more convenience is wanted
but not record the user-developed solution. After all, product development is
the province of in-house engineers!

We are therefore left with a question: How can manufacturers build a
product-development process that systematically searches for and evaluates lead
user-generated innovations? (See figure 10.1.) It turns out that the answer
differs depending on whether the lead users sought are at the leading edge of
"advanced analog" fields or at the leading edge of target markets. Searching
for the former is more difficult, but experience shows that the user-developed
innovations that are most radical (and profitable) relative to conventional
thinking often come from lead users in "advanced analog" fields.
={ Manufacturers :
     innovation and ;
   Lead users :
     characteristics of +1 ;
   Marketing research +1
}

% Only lead user
% prototypes available
% Time
% Commercial versions of product available
% Number
% of users
% perceiving
% need
% Figure 10.1
% Innovations by lead users precede equivalent commercial products.

{di_evh_f10-1.png}image

!_ Figure 10.1
Innovations by lead users precede equivalent commercial products.

!_ Identifying Lead Users in Advanced Analog Fields

Lead users in advanced analog fields experience needs that are related to but
more extreme than those being faced by /{any}/ users, including lead users,
within the target market. They also often face a different set of constraints
than those affecting users in the target market. These differences can force
them to develop solutions that are entirely new from the perspective of the
target market.

As an example, consider the relationship between the braking requirements faced
by users of automobiles (let's call auto users the target market) and the
braking requirements faced by large commercial airplanes as they land on an
airport runway (the advanced analog market). Clearly, the braking demands on
large airplanes are much more extreme. Airplanes are much heavier than autos
and land at higher speeds: their brakes must rapidly dissipate hundreds of
times more energy to bring the vehicle to a stop. Also, the situational
constraints are different. For example, auto drivers are often assisted in
braking in winter by the application of salt or sand to icy roads. These aids
cannot be applied in the case of aircraft: salt would damage aircraft bodies,
and sand would be inhaled into jet engines and damage them.

The result of the more extreme demands and additional constraints placed on
solutions to aircraft braking was the development of antilock braking systems
(ABS) for aircraft. Auto firms conducting searches for valuable lead user
innovations regarding auto braking were able to learn about this out-of-field
innovation and adapt if for use in autos---where it is common today. Before the
development of ABS for autos, an automobile firm could have learned about the
underlying concept by studying the practices of users with a strong need for
controlling skidding while braking such as stock car auto racing teams. These
lead users had learned to manually "pump" their brakes to help control this
problem. However, auto company engineers were able to learn much more by
studying the automated solutions developed in the "advanced analog" field of
aerospace.~{ ABS braking is intended to keep a vehicle's wheels turning during
braking. ABS works by automatically and rapidly "pumping" the brakes. The
result is that the wheels continue to revolve rather than "locking up," and the
operator continues to have control over steering. }~

Finding lead users in advanced analog markets can be difficult because
discovering the relevance of a particular analog can itself be a creative act.
One approach that has proven effective is to ask the more easily identified
lead users in target markets for nominations. These lead users tend to know
about useful advanced analogs, because they have been struggling with their
leading-edge problems for a long time, and often have searched beyond the
target market for information.

Networking from innovators to more advanced innovators in this way is called
pyramiding (von Hippel, Thomke, and Sonnack 1999). Pyramiding is a modified
version of the "snowballing" technique sometimes used by sociologists to
identify members of a group or accumulate samples of rare respondents (Bijker
1995). Snowballing relies on the fact that people with rare interests or
attributes tend to know others like themselves. Pyramiding modifies this idea
by assuming that people with a strong interest in a topic or field can direct
an enquiring researcher to people /{more}/ expert than themselves. Experiments
have shown that pyramiding can identify high-quality informants much more
efficiently than can mass-screening techniques under many conditions (von
Hippel, Franke, and Prügl 2005). Pyramiding was made into a practical
industrial process by Mary Sonnack, a Division Scientist at 3M, and Joan
Churchill, a psychologist specializing in the development of industrial
training programs.
={ Bijker, W. ;
   Churchill, J. ;
   Franke, N. ;
   Prügl, R. ;
   Thomke, S. ;
   von Hippel, E. +46
}

!_ Identifying Lead Users in Target Markets

In general it is easier to identify users at the leading edge of target markets
than it is to identify users in advanced analog fields. Screening for users
with lead user characteristics can be used. When the desired type of lead user
is so rare as to make screening impractical---often the case---pyramiding can
be applied. In addition, manufacturers can take advantage of the fact that
users at the leading edge of a target market often congregate at specialized
sites or events that manufacturers can readily identify. At such sites, users
may freely reveal what they have done and may learn from others about how to
improve their own practices still further. Manufacturers interested in learning
from these lead users can easily visit the sites and listen in. For example,
sports equipment companies can go to sporting meets where lead users are known
to compete, observe user innovations in action, and compare notes.
={ Manufacturers :
     innovation and
}

Essentially the same thing can be done at virtual sites. For example, recall
the practices of StataCorp, a supplier of statistical software. Stata sells a
set of standard statistical tests and also a language and tools that
statisticians can use to design new tests to serve their own evolving needs.
Some Stata users (statisticians) took the initiative to set up a few
specialized websites, unaffiliated with StataCorp, where they post their
innovations for others to download, use, comment on, and improve. StataCorp
personnel visit these sites, learn about the user innovations, and observe
which tests seem to be of interest to many users. They then develop proprietary
versions of the more generally useful tests as commercial products.
={ Lead users :
     StataCorp statistical software and ;
   StataCorp statistical software
}

When specialized rendezvous sites for lead users don't exist in a particular
field, manufacturers may be able to create them. Technicon Corporation, for
example, set up a series of seminars at which innovating users of their medical
equipment got together and exchanged information on their innovations.
Technicon engineers were free to listen in, and the innovations developed by
these users were the sources of most of Technicon's important new product
improvements (von Hippel and Finkelstein 1979).
={ Finkelstein, S. ;
   Technicon Corporation
}

!_ The 3M Experiment
={ Lead users :
     3M and +32 ;
   3M Corporation +32
}

To test whether lead users in advanced analog fields can in fact generate
information that leads to commercially valuable new products, Lilien, Morrison,
Searls, Sonnack, and von Hippel (2002) studied a natural experiment at 3M. That
firm was carrying out both lead user projects and traditional market
research-based idea-generation projects in the same divisions at the same time,
and in sufficient numbers to make statistical comparisons of outcomes possible.
={ Lilien, G. +26 ;
   Morrison, Pamela +26 ;
   Searls, K. +26 ;
   Sonnack, M. +26 ;
   Lead users :
     idea generation and +45
}

!_ Methods

3M first began using the lead user method in one division in 1996. By May 2000,
when data collection began, five divisions of 3M had completed seven lead user
(LU) idea-generation projects and had funded further development of the product
concepts generated by five of these. These same five divisions also had 42
contemporaneously funded projects that used "find a need and fill it"
idea-generation methodologies that were traditional practice at 3M. We used
these two samples of funded ideas to compare the performance of lead user
idea-generation projects with traditional idea-generation projects. Although 3M
cooperated in the study and permitted access to company records and to members
of the product-development teams, the firm did not offer a controlled
experimental setting. Rather, we as researchers were required to account for
any naturally occurring differences after the fact.

Our study methodology required a pre-post/test-control situation, with at least
quasi-random assignments to treatment cells (Cook and Campbell 1979). In other
words, our goal was to compare samples of development projects in 3M divisions
that differed with respect to their use of lead user idea-generation methods,
but that were as similar as possible in other respects. Identifying,
understanding, and controlling for the many potential sources of difference
that could affect the natural experiment involved careful field explorations.
Thus, possible differences between project staffing and performance incentives
applied to LU and non-LU idea-generation projects were assessed. We looked for
(and did not find) differences in the capabilities or motivation of LU and
non-LU project team members with respect to achieving a major new product
advance. 3M managers also said that there was no difference in these matters,
and a content analysis of formal annual performance goals set for the
individual LU and non-LU team members in a division that allowed access to
these data supported their views.
={ Campbell, D. ;
   Cook, T.
}

We also found no major differences in the innovation opportunities teams faced.
They also looked for Hawthorne or placebo effects that might affect the project
teams differentially, and found none. (The Hawthorne effect can be described as
"I do better because extra attention is being paid to me or to my performance."
The placebo effect can be described as "I expect this process will work and
will strive to get the results I have been told are likely.") We concluded that
the 3M samples of funded LU and non-LU idea-generation projects, though not
satisfying the random assignment criterion for experimental design, appeared to
satisfy rough equivalence criteria in test and control conditions associated
with natural or quasi-experimentation. Data were collected by interviews and by
survey instruments.

With respect to the intended difference under study---the use of lead user
methods within projects---all lead user teams employed an identical lead user
process taught to them with identical coaching materials and with coaching
provided by members of the same small set of internal 3M coaches. Each lead
user team consisted of three or four members of the marketing and technical
departments of the 3M division conducting the project. Teams began by
identifying important market trends. Then, they engaged in pyramiding to
identify lead users with respect to each trend both within the target market
and in advanced analog markets. Information from a number of innovating lead
users was then combined by the team to create a new product concept and
business plan---an "LU idea" (von Hippel, Thomke, and Sonnack 1999).
={ Thomke, S. }

% ={Sonnack, M.}

Non-lead-user idea-generation projects were conducted in accordance with
traditional 3M practices. I refer to these as non-LU idea generation methods
and to teams using them as non-LU teams. Non-LU teams were similar to lead user
teams in terms of size and make-up. They used data sources for idea generation
that varied from project to project. Market data collected by outside
organizations were sometimes used, as were data from focus groups with major
customers and from customer panels, and information from lab personnel. Non-LU
teams collected market information from target markets users but not from lead
users.

!_ Findings

Our research compared all funded product concepts generated by LU and non-LU
methods from February 1999 to May 2000 in each of the five 3M divisions that
had funded one or more lead-user-developed product concepts. During that time,
five ideas generated by lead user projects were being funded, along with 42
ideas generated by non-LU idea-generation methods. The results of these
comparisons can be seen in table 10.1. Product concepts generated by seeking
out and learning from lead users were found to be significantly more novel than
those generated by non-LU methods. They were also found to address more
original or newer customer needs, to have significantly higher market share, to
have greater potential to develop into an entire product line, and to be more
strategically important. The lead-user-developed product concepts also had
projected annual sales in year 5 that were greater than those of ideas
generated by non-LU methods by a factor of 8---an average of $146 million
versus an average of $18 million in forecast annual sales. Thus, at 3M, lead
user idea-generation projects clearly did generate new product concepts with
much greater commercial potential than did traditional, non-LU methods (p <
0.005).

!_ Table 10.1
Concepts for new products developed by lead user project teams had far more
commercial promise than those developed by non-lead-user project teams.

table{~h c4; 40; 20; 20; 20;

~
LU product concepts (n =5)
Non-LU product concepts (n = 42)
Significance

Factors related to value of concept
~
~
~

Novelty compared with competition a
9.6
6.8
0.01

Originality/newness of customer needs addressed
8.3
5.3
0.09

% market share in year 5
68%
33%
0.01

Estimated sales in year 5 (deflated for forecast error)
$146m
$18m
0.00

Potential for entire product family a
10.0
7.5
0.03

Operating profit
22%
24.0%
0.70

Probability of success
80%
66%
0.24

Strategic importance a
9.6
7.3
0.08

Intellectual property protection a
7.1
6.7
0.80

Factors related to organizational fit of concept
~
~
~

Fit with existing distribution channels a
8.8
8.0
0.61

Fit with existing manufacturing capabilities a
7.8
6.7
0.92

Fit with existing strategic plan a
9.8
8.4
0.24

}table

Source: Lilien et al. 2002, table 1. \\
a. Rated on a scale from 1 to 10.

Note that the sales data for both the LU and non-LU projects are forecasts. To
what extent can we rely on these? We explored this matter by collecting both
forecast and actual sales data from five 3M division controllers. (Division
controllers are responsible for authorizing new product-development investment
expenditures.) We also obtained data from a 1995 internal study that compared
3M's sales forecasts with actual sales. We combined this information to develop
a distribution of forecast errors for a number of 3M divisions, as well as
overall forecast errors across the entire corporation. Those errors range from
forecast/actual of +30 percent (over-forecast) to --13 percent (underforecast).
On the basis of the information just described, and in consultation with 3M
management, we deflated all sales forecast data by 25 percent. That deflator is
consistent with 3M's historical experience and, we think, provides conservative
sales forecasts.~{ In the general literature, Armstrong's (2001) review on
forecast bias for new product introduction indicates that sales forecasts are
generally optimistic, but that that upward bias decreases as the magnitude of
the sales forecast increases. Coller and Yohn (1998) review the literature on
bias in accuracy of management earnings forecasts and find that little
systematic bias occurs. Tull's (1967) model calculates $15 million in revenue
as a level above which forecasts actually become pessimistic on average. We
think it reasonable to apply the same deflator to LU vs. non-LU project sales
projections. Even if LU project personnel were for some reason more likely to
be optimistic with respect to such projections than non-LU project personnel,
that would not significantly affect our findings. Over 60 percent of the total
dollar value of sales forecasts made for LU projects were actually made by
personnel not associated with those projects (outside consulting firms or
business analysts from other divisions). }~ Deflated data appear in table 10.1
and in the following tables.

Rather strikingly, all five of the funded 3M lead user projects created the
basis for major new product lines for 3M (table 10.2). In contrast, 41 of 42
funded product concepts generated by non-LU methods were improvements or
extensions of existing product lines (χ^{2}^ test, p < 0.005).

Following tt, p < 0.005).e advice of 3M divisional controllers, major product
lines were defined as those separately reported in divisional financial
statements. In 1999 in the 3M divisions we studied, sales of individual major
product lines ranged from 7 percent to 73 percent of total divisional sales.
The sales projections for funded lead user project ideas all fell well above
the lower end of this range: projected sales five years after introduction for
funded LU ideas, conservatively deflated as discussed above, ranged from 25
percent to over 300 percent of current total divisional sales.

!_ Table 10.2
Lead user project teams developed concepts for major new product lines.
Non-lead-user project teams developed concepts for incremental product
improvements.

table{~h c3; 34; 33; 33;

~
Incremental product improvements
Major new product lines

LU method
0
5

Non-LU method
41
1

}table

Source: Lilien et al. 2002, table 2.

To illustrate what the major product line innovations that the LU process teams
generated at 3M were like, I briefly describe four (one is not described for 3M
proprietary reasons):

_* A new approach to the prevention of infections associated with surgical
operations. The new approach replaced the traditional "one size fits all"
approach to infection prevention with a portfolio of patient-specific measures
based on each patient's individual biological susceptibilities. This innovation
involved new product lines plus related business and strategy innovations made
by the team to bring this new approach to market successfully and profitably.

_* Electronic test and communication equipment for telephone field repair
workers that pioneered the inclusion of audio, video, and remote data access
capabilities. These capabilities enabled physically isolated workers to carry
out their problem-solving work as a virtual team with co-workers for the first
time.

_* A new approach, implemented via novel equipment, to the application of
commercial graphics films that cut the time of application from 48 hours to
less than 1 hour. (Commercial graphics films are used, for example, to cover
entire truck trailers, buses, and other vehicles with advertising or decorative
graphics.) The LU team's solutions involved technical innovations plus related
channel and business model changes to help diffuse the innovation rapidly.

_* A new approach to protecting fragile items in shipping cartons that replaces
packaging materials such as foamed plastic. The new product lines implementing
the approach were more environmentally friendly and much faster and more
convenient for both shippers and package recipients than other products and
methods on the market.

Lilien, Morrison, Searls, Sonnack, and I also explored to see whether the major
product lines generated by the lead user projects had characteristics similar
to those of the major product lines that had been developed at 3M in the past,
including Scotch Tape. To determine this we collected data on all major new
product lines introduced to the market between 1950 and 2000 by the five 3M
divisions that had executed one or more lead user studies. (The year 1950 was
as far back as we could go and still find company employees who could provide
some data about the innovation histories of these major products lines.)
Examples from our 1950--2000 sample include the following:
={ Lilien, G. ;
   Morrison, Pamela ;
   Searls, K.
}

% ={Sonnack, M.}

_* Scotch Tape: A line of transparent mending tapes that was first of its type
and a major success in many household and commercial applications.

_* Disposable patient drapes for operating room use: A pioneering line of
disposable products for the medical field now sold in many variations.

_* Box sealing tapes: The first type of tape strong enough to reliably seal
corrugated shipping boxes, it replaced stapling in most "corrugated shipper"
applications.

_* Commercial graphics films: Plastic films capable of withstanding outdoor
environments that could be printed upon and adhered to large surfaces on
vehicles such as the sides of trailer trucks. This product line changed the
entire approach to outdoor signage.

Table 10.3 provides profiles of the five LU major product lines and the 16
non-LU major product lines for which we were able to collect data. As can be
seen, innovations generated with inputs from lead users are similar in many
ways to the major innovations developed by 3M in the past.

!_ Table 10.3
Major new product lines (MNPLs) generated by lead-user methods are similar to
MNPLs generated by 3M in the past.

table{~h c4; 55; 15; 15; 15;

~
LU MNPLs (n = 5)
Past 3M MNPLs (n = 16)
Significance

Novelty a compared with competition
9.6
8.0
0.21

Originality/newness of customer needs addressed^{a}^
8.3
7.9
0.78

% market share in year 5
68%
61%
0.76

Estimated sales in year 5 (deflated for forecast error)
146m^{b}^
$62m^{b}^
0.04

Potential for entire product family^{a}^
10.0
9.4
0.38

Operating profit
22%
27%
0.41

Probability of success
80%
87%
0.35

Strategic importance*
9.6
8.5
0.39

Intellectual property protection^{a}^
7.1
7.4
0.81

Fit with distribution channels^{a}^
8.8
8.4
0.77

Fit with manufacturing capabilities^{a}^
7.8
6.7
0.53

Fit with strategic plan^{a}^
9.8
8.7
0.32

}table

Source: Lilien et al. 2002, table 4. \\
a. Measured on a scale from 1 to 10. \\
b. Five-year sales forecasts for all major product lines commercialized in 1994
or later (5 LU and 2 non-LU major product lines) have been deflated by 25% in
line with 3M historical forecast error experience (see text). Five-year sales
figures for major product lines commercialized before 1994 are actual
historical sales data. This data has been converted to 1999 dollars using the
Consumer Price Index from the Economic Report of the President (Council of
Economic Advisors 2000).

!_ Discussion

The performance comparison between lead user and "find a need and fill it"
idea-generation projects at 3M showed remarkably strong advantages associated
with searching for ideas among lead users in advanced analog fields with needs
similar to, but even more extreme than, needs encountered in the intended
target market. The direction of this outcome is supported by findings from
three other real-world industrial applications of lead user idea-generation
methods that studied lead users in the target market but not in advanced analog
markets. I briefly describe these three studies next. They each appear to have
generated primarily next-generation products--- valuable for firms, but not the
basis for radically new major product lines.

%%

_* Recall that Urban and von Hippel (1988) tested the relative commercial
attractiveness of product concepts developed in the field of computer-aided
systems for the design of printed circuit boards (PC-CAD). One of the concepts
they tested contained novel features proposed by lead users that had innovated
in the PC-CAD field in order to serve in-house need. The attractiveness of the
"lead user concept" was then evaluated by a sample of 173 target-market users
of PC-CAD systems relative to three other concept choices---one of which was a
description of the best system then commercially available. Over 80 percent of
the target-market users were found to prefer the concept incorporating the
features developed by innovating lead users. Their reported purchase
probability for a PC-CAD system incorporating the lead user features was 51
percent, over twice as high as the purchase probability indicated for any other
system. The target-market users were also found willing to pay twice as much
for a product embodying the lead user features than for PC-CAD products that
did not incorporate them.
={ Urban, G. ;
   Printed circuit CAD software
}

_* Herstatt and von Hippel (1992) documented a lead user project seeking to
develop a new line of pipe hangers---hardware used to attach pipes to the
ceilings of commercial buildings. Hilti, a major manufacturer of
construction-related equipment and products, conducted the project. The firm
introduced a new line of pipe hanger products based on the lead user concept
and a post-study evaluation has shown that this line has become a major
commercial success for Hilti.
={ Herstatt, C. ;
   Pipe hanger hardware
}

_* Olson and Bakke (2001) report on two lead user studies carried out by Cinet,
a leading IT systems integrator in Norway, for the firm's two major product
areas, desktop personal computers, and Symfoni application GroupWare. These
projects were very successful, with most of the ideas incorporated into
next-generation products having been collected from lead users.
={ Bakke, G. ;
   Olson, E.
}

Active search for lead users that have innovated enables manufacturers to more
rapidly commercialize lead user innovations. One might think that an
alternative approach would be to identify lead users before they have
innovated. Alert manufacturers could then make some prior arrangements to get
preferred access to promising user-developed innovations by, for example,
purchasing promising lead user organizations. I myself think that such vertical
integration approaches are not practical. As was shown earlier, the character
and attractiveness of innovations lead users may develop is based in part on
the particular situations faced by and information stocks held by individual
lead users. User innovation is therefore likely to be a widely distributed
phenomenon, and it would be difficult to predict in advance which users are
most likely to develop very valuable innovations.
={ Manufacturers :
     lead users and +8
}

How do we square these findings with the arguments, put forth by Christensen
(1997), by Slater and Narver (1998), and by others, that firms are likely to
miss radical or disruptive innovations if they pay close attention to requests
from their customers? Christensen (1997, p. 59, n. 21) writes: "The research of
Eric von Hippel, frequently cited as evidence of the value of listening to
customers, indicates that customers originate a large majority of new product
ideas. . . . The [Christensen] value network framework would predict that the
innovations toward which the customers in von Hippel's study led their
suppliers would have been sustaining innovations. We would expect disruptive
innovations to have come from other sources."
={ Christensen, C. +2 ;
   Narver, J. ;
   Slater, S.
}

Unfortunately, the above contains a basic misunderstanding of my research
findings. My findings, and related findings by others as well, deal with
innovations by lead users, not customers, and /{lead users are a much broader
category than customers of a specific firm}/. Lead users that generate
innovations of interest to manufacturers can reside, as we have seen, at the
leading edges of target markets, and also in advanced analog markets. The
innovations that some lead users develop are certainly disruptive from the
viewpoint of some manufacturers---but the lead users are unlikely to care about
this. After all, they are developing products to serve their own needs. Tim
Berners-Lee, for example, developed the World Wide Web as a lead user working
at CERN---a user of that software. The World Wide Web was certainly disruptive
to the business models of many firms, but this was not Berners-Lee's concern.
Lead users typically have no reason to lead, mislead, or even contact
manufacturers that might eventually benefit from or be disrupted by their
innovations. Indeed, the likely absence of a preexisting customer relationship
is the reason that manufacturing firms must search for lead user innovations
/{outside}/ their customer lists---as 3M did in its lead user idea generation
studies. "Listening to the voice of the customer" is /{not}/ the same thing as
seeking out and learning from lead users (Danneels 2004).
={ Berners-Lee, T. ;
   Danneels, E. ;
   Lead users :
     3M and ;
   3M Corporation ;
   Custom products :
     manufacturers and +2 | users and +2 ;
   Innovation :
     distributed process of +2 | functional sources of +2
}

That basic misunderstanding aside, I do agree with Christensen and others that
a manufacturer may well receive mainly requests for sustaining innovations from
its /{customers}/. As was discussed in chapter 4, manufacturers have an
incentive to develop innovations that utilize their existing
capabilities---that are "sustaining" for them. Customers know this and, when
considering switching to a new technology, are unlikely to request it from a
manufacturer that would consider it to be disruptive: they know that such a
manufacturer is unlikely to respond positively. The net result is that
manufacturers' inputs from their existing customers may indeed be biased
towards requests for sustaining innovations.

I conclude this chapter by reminding the reader that studies of the sources of
innovation show clearly that users will tend to develop some types of
innovations but not all. It therefore makes sense for manufacturers to
partition their product-development strategies and portfolios accordingly. They
may wish, for example, to move away from actual new product development and
search for lead users' innovations in the case of functionally novel products.
At the same time manufacturers may decide to continue to develop products that
do /{not}/ require high-fidelity models of need information and use
environments to get right. One notable category of innovations with this
characteristic is dimension-of-merit improvements to existing products.
Sometimes users state their needs for improved products in terms of dimensions
on which improvements are desired---dimensions of merit. As an example,
consider that users may say "I want a computer that is as fast and cheap as
possible." Similarly, users of medical imaging equipment may say "I want an
image that is of as high a resolution as is technically possible." If
manufacturers (or users) cannot get to the end point desired by these users
right away, they will instead progressively introduce new product generations
that move along the dimension of merit as rapidly and well as they can. Their
rate of progress is determined by the rate at which /{solution}/ technologies
improve over time. This means that sticky solution information rather than
sticky need information is central to development of dimension-of-merit
improvements. Manufacturers will tend to have the information they need to
develop dimension of merit innovations internally.
={ Manufacturers :
     dimensions-of-merit product improvements and ;
   Sticky information :
     dimensions-of-merit product improvements and | innovation and
}

1~ 11 Application: Toolkits for User Innovation and Custom Design
={ Users :
     innovation and +62 ;
   Custom products :
     manufacturers and +62 | toolkits and +62 ;
   Manufacturers :
     innovation and +62 ;
   Toolkits +62 :
     innovation and +62 ;
   Users :
     toolkits and +62
}

An improved understanding of the relative innovation capabilities of users and
manufacturers can enable designs for more effective joint innovation processes.
Toolkits for user innovation and custom design illustrate this possibility. In
this new innovation process design, manufacturers actually /{abandon}/ their
efforts to understand users' needs accurately and in detail. Instead, they
outsource only /{need-related}/ innovation tasks to their users, who are
equipped with appropriate toolkits. This process change differs from the lead
user search processes discussed earlier in an interesting way. Lead user
searchs identify existing innovations, but do nothing to change the conditions
affecting user-innovators at the time a new product or service is being
developed. Toolkits for users, in contrast, do change the conditions potential
innovators face. By making innovation cheaper and quicker for users, they can
increase the volume of user innovation. They also can channel innovative effort
into directions supported by toolkits.
={ Toolkits :
     characteristics of +3
}

In this chapter, I first explore why toolkits are useful. Next, I describe how
to create an appropriate setting for toolkits and how toolkits function in
detail. Finally, I discuss the conditions under which toolkits are likely to be
of most value.

!_ Benefits from Toolkits

Toolkits for user innovation and design are integrated sets of product-design,
prototyping, and design-testing tools intended for use by end users. The goal
of a toolkit is to enable non-specialist users to design high-quality,
producible custom products that exactly meet their needs. Toolkits often
contain "user-friendly" features that guide users as they work. They are
specific to a type of product or service and a specific production system. For
example, a toolkit provided to customers interested in designing their own,
custom digital semiconductor chips is tailored precisely for that purpose--- it
cannot be used to design other types of products. Users apply a toolkit in
conjunction with their rich understanding of their own needs to create a
preliminary design, simulate or prototype it, evaluate its functioning in their
own use environment, and then iteratively improve it until they are satisfied.
={ Toolkits :
     manufacturers and +58 | user-friendly tools for ;
   Information asymmetries +10
}

A variety of manufacturers have found it profitable to shift the tasks of
custom product design to their customers along with appropriate toolkits for
innovation. Results to date in the custom semiconductor field show development
time cut by 2/3 or more for products of equivalent complexity and development
costs cut significantly as well via the use of toolkits. In 2000, more than $15
billion worth of custom integrated circuits were sold that had been designed
with the aid of toolkits---often by circuit users---and produced in the
"silicon foundries" of custom semiconductor manufacturers such as LSI (Thomke
and von Hippel 2002). International Flavors and Fragrances (IFF), a global
supplier of specialty flavors to the food industry, has built a toolkit that
enables its customers to modify flavors for themselves, which IFF then
manufactures. In the materials field, GE provides customers with Web-based
tools for designing better plastic products. In software, a number of consumer
product companies provide toolkits that allow people to add custom-designed
modules to their standard products. For example, Westwood Studios provides its
customers with toolkits that enable them to design important elements of their
own video games (Jeppesen 2005).
={ Jeppesen, L. ;
   Thomke, S. ;
   von Hippel, E. +9 ;
   Toolkits :
     GE and | International Flavors and Fragrances and
}

The primary function of toolkits for user design is to co-locate
product-development and service-development tasks with the sticky information
needed to execute them. Need-intensive tasks involved in developing a
particular type of product or service are assigned to users, along with the
tools needed to carry those tasks out. At the same time, solution-intensive
tasks are assigned to manufacturers.
={ Toolkits :
     users and +55 | sticky information and +8 ;
   Sticky information :
     toolkits and +8
}

As was discussed in chapter 5, problem solving in general, and product and
service development in particular, is carried out via repeated cycles of
learning by trial and error. When each cycle of a trial-and-error process
requires access to sticky information located at more than one site, colocation
of problem-solving activity with sticky information is achieved by repeatedly
shifting problem solving to the relevant sticky information sites as product
development proceeds.
={ Trial-and-error problem solving ;
   Toolkits :
     trial-and-error learning in
}

For example, suppose that need information is sticky at the site of the
potential product user and that solution information is sticky at the site of
the manufacturer. A user may initiate a development project by drawing on local
user-need information to specify a desired new product or service (figure
11.1). This information is likely to be sticky at least in part. Therefore, the
user, even when exerting best efforts, will supply only partial and partially
correct need and use-context information to the manufacturer. The manufacturer
then applies its solution information to the partially accurate user
information and creates a prototype that it thinks is responsive to the need
and sends it to the user for testing. If the prototype is not satisfactory (and
it often is not), the product is returned to the manufacturer for refinement.
Typically, as empirical studies show (Tyre and von Hippel 1997; Kristensen
1992), sites of sticky need and / or solution information are repeatedly
revisited as problem solvers strive to reach a satisfactory product design
(figure 11.2).
={ Kristensen, P. ;
   Tyre, M.
}

%% Figure 11.1
% Toolkits 149
% Manufacturer
% activity
% User
% activity
% User iterates until satisfied.
% User draws on local need
% information to specify
% desired product or service.
% User draws on local need and
% context of use information to
% evaluate prototype.
% User changes specifications as
% needed.
% Manufacturer draws on
% local capability information
% to develop prototype
% responsive to specifications.
% Manufacturer iterates until
% user is satisfied.
% User-manufacturer
% boundary
% Figure 11.1
% A pattern of problem solving often encountered in product and service development.


{di_evh_f11-1.png}image

Figure 11.1

%% Figure 11.2
% 0 1 2 3 4 5 6
% 7
% 0
% 22
% 7
% 15
% 30
% Number of shifts
% Percent
% of
% sample
% Figure 11.2
% Shifts in the location of problem solving from user site to lab observed during process
% machine debugging. Source: Tyre and von Hippel 1993, figure 2.

{di_evh_f11-2.png}image

Figure 11.2

Explicit management of user-manufacturer iterations has been built into a
number of modern product-development processes. In the rapid application
development method (Martin 1991), manufacturers learn to respond to initial
user need inputs by quickly developing a partial prototype of a planned product
containing the features likely to be most important to users. They deliver this
to users, who apply it in their own setting to clarify their needs. Users then
relay requests for changes or new features to the product developers, and this
process is repeated until an acceptable fit between need and solution is found.
Such iteration has been found to "better satisfy true user requirements and
produce information and functionality that is more complete, more accurate, and
more meaningful" (Connell and Shafer 1989).
={ Connell, J. ;
   Martin, J. ;
   Shafer, L.
}

Even with careful management, however, iterative shifts in problem solving
between users and manufacturer-based developers involve significant
coordination costs. For example, a manufacturer's development team may be
assigned to other tasks while it waits for user feedback, and so will not be
immediately able to resume work on a project when needed feedback is received.
It would be much better still to eliminate the need for cross-boundary
iteration between user and manufacturer sites during product development, and
this is what toolkits for user design are intended to do. The basic idea behind
toolkits for user design is, as was mentioned earlier, to partition an overall
product-development task into subproblems, each drawing on only one locus of
sticky information. Then, each task is assigned to the party already having the
sticky information needed to solve it. In this approach, both the user and the
manufacturer still engage in iterative, trial-and-error problem solving to
solve the problems assigned to them. But this iteration is internal to each
party---no costly and time-consuming cross-boundary iteration between user and
manufacturer is required (von Hippel 1998, 2001; Thomke and von Hippel 2002;
von Hippel and Katz 2002).
={ Katz, R. ;
   Thomke, S. ;
   Task partitioning +10
}

To appreciate the major advantage in problem-solving speed and efficiency that
concentrating problem solving within a single locus can create, consider a
familiar example: the contrast between conducting financial strategy
development with and without "user-operated" financial spreadsheet software:

_* Before the development of easy-to-use financial spreadsheet programs such as
Lotus 1-2-3 and Microsoft Excel, a firm's chief financial officer might have
carried out a financial strategy development exercise as follows. First, the
CFO would have asked an assistant to develop an analysis incorporating a list
of assumptions. A few hours or days might elapse before the result was
delivered. Then the CFO would use her rich understanding of the firm and its
goals to study the analysis. She would typically almost immediately spot some
implications of the patterns developed, and would then ask for additional
analyses to explore these implications. The assistant would take the new
instructions and go back to work while the CFO switched to another task. When
the assistant returned, the cycle would repeat until a satisfactory outcome was
found.
={ Microsoft }

_* After the development of financial spreadsheet programs, a CFO might begin
an analysis by asking an assistant to load up a spreadsheet with corporate
data. The CFO would then "play with" the data, trying out various ideas and
possibilities and "what if" scenarios. The cycle time between trials would be
reduced from days or hours to minutes. The CFO's full, rich information would
be applied immediately to the effects of each trial. Unexpected
patterns---suggestive to the CFO but often meaningless to a less knowledgeable
assistant---would be immediately identified and explored further.

It is generally acknowledged that spreadsheet software that enables expert
users to "do it themselves" has led to better outcomes that are achieved faster
(Levy 1984; Schrage 2000). The advantages are similar in the case of product
and service development. Learning by doing via trial and error still occurs, of
course, but the cycle time is much faster because the complete cycle of
need-related learning is carried out at a single (user) site earlier in the
development process.
={ Levy, S. ;
   Schrage, M. ;
   Trial-and-error problem solving +15
}

!_ Repartitioning of Development Tasks
={ Toolkits :
     task partitioning +5
}

To create the setting for a toolkit, one must partition the tasks of product
development to concentrate need-related information in some and
solution-related information in others. This can involve fundamental changes to
the underlying architecture of a product or service. As illustration, I first
discuss the repartioning of the tasks involved in custom semiconductor chip
development. Then, I show how the same principles can be applied in the less
technical context of custom food design.

Traditionally, fully customized integrated circuits were developed in an
iterative process like that illustrated in figure 11.1. The process began with
a user specifying the functions that the custom chip was to perform to a
manufacturer of integrated circuits. The chip would then be designed by
manufacturer employees, and an (expensive) prototype would be produced and sent
to the user. Testing by the user would typically reveal faults in the chip
and/or in the initial specification, responsive changes would be made, a new
prototype would be built. This cycle would continue until the user was
satisfied. In this traditional manufacturer-centered development process,
manufacturers' development engineers typically incorporated need-related
information into the design of both the fundamental elements of a circuit---
such as transistors, and the electrical "wiring" that interconnected those
elements into a functioning circuit.

The brilliant insight that allowed custom design of integrated circuits to be
partitioned into solution-related and need-related subtasks was made by Mead
and Conway (1980). They determined that the design of a digital chip's
fundamental elements, such as its transistors, could be made standard for all
circuits. This subtask required rich access to the manufacturer's sticky
solution information regarding how semiconductors are fabricated, but did not
require detailed information on users' specific needs. It could therefore be
assigned to manufacturer-based chip-design and chip-fabrication engineers. It
was also observed that the subtask of interconnecting standard circuit elements
into a functioning integrated circuit required only sticky, need-related
information about a chip's function---for example, whether it was to function
as a microprocessor for a calculator or as a voice chip for a robotic dog. This
subtask was therefore assigned to users along with a toolkit that enabled them
to do it properly. In sum, this new type of chip, called a gate array, had a
novel architecture created specifically to separate the problem-solving tasks
requiring access to a manufacturer's sticky solution information from those
requiring access to users' sticky need information.
={ Conway, C. ;
   Mead, L. ;
   Toolkits :
     characteristics of
}

The same basic principle can be illustrated in a less technical context: food
design. In this field, manufacturer-based designers have traditionally
undertaken the entire job of developing a novel food, and so they have freely
blended need-specific design into any or all of the recipe-design elements
wherever convenient. For example, manufacturer-based developers might find it
convenient to create a novel cake by both designing a novel flavor and texture
for the cake body, and designing a complementary novel flavor and texture into
the frosting. However, it is possible to repartition these same tasks so that
only a few draw on need-related information, and these can then be more easily
transferred to users.

The architecture of the pizza pie illustrates how this can be done. Many
aspects of the design of a pizza, such as the dough and the sauce, have been
made standard. User choice has been restricted to a single task: the design of
toppings. In other words, all need-related information that is unique to a
particular user has been linked to the toppings-design task only. Transfer of
this single design task to users can still potentially offer creative
individuals a very large design space to play in (although pizza shops
typically restrict it sharply). Any edible ingredient one can think of, from
eye of newt to edible flowers, is a potential topping component. But the fact
that need-related information has been concentrated within only a single
product-design task makes it much easier to transfer design freedom to the
user.

!_ The Functionality of Toolkits
={ Toolkits :
     characteristics of +2
}

If a manufacturer outsources need-intensive design tasks to users, it must also
make sure that users have the information they need to carry out those tasks
effectively. This can be done via a toolkit for user innovation. Toolkits are
not new as a general concept---every manufacturer equips its own engineers with
a set of tools suitable for developing the type of products or services it
wishes to produce. Toolkits for users also are not new---many users have
personal collections of tools that they have assembled to help them create new
items or modify standard ones. For example, some users have woodworking tools
ranging from saws to glue which can be used to create or modify furniture---in
very novel or very standard ways. Others may have a kit of software tools
needed to create or modify software. What is new, however, is integrated
toolkits enabling users to create /{and}/ test designs for custom products or
services that can then be produced "as is" by manufacturers.

Present practice dictates that a high-quality toolkit for user innovation will
have five important attributes. (1) It will enable users to carry out complete
cycles of trial-and-error learning. (2) It will offer users a solution space
that encompasses the designs they want to create. (3) It will be user friendly
in the sense of being operable with little specialized training. (4) It will
contain libraries of commonly used modules that users can incorporate into
custom designs. (5) It will ensure that custom products and services designed
by users will be producible on a manufacturer's' production equipment without
modification by the manufacturer.

!_ Learning through Trial and Error
={ Toolkits :
     trial-and-error learning in +5
}


It is crucial that user toolkits for innovation enable users to go through
complete trial-and-error cycles as they create their designs. Recall that
trial-and-error problem solving is essential to product development. For
example, suppose that a user is designing a new custom telephone answering
system for her firm, using a software-based computer-telephony integration
(CTI) design toolkit provided by a vendor. Suppose also that the user decides
to include a new rule to "route all calls of X nature to Joe" in her design. A
properly designed toolkit would allow her to temporarily place the new rule
into the telephone system software, so that she could actually try it out (via
a real test or a simulation) and see what happened. She might discover that the
solution worked perfectly. Or she might find that the new rule caused some
unexpected form of trouble---for example, Joe might be flooded with too many
calls---in which case it would be "back to the drawing board" for another
design and another trial.

In the same way, toolkits for innovation in the semiconductor design field
allow users to design a circuit that they think will meet their needs and then
test the design by "running" it in the form of a computer simulation. This
quickly reveals errors that the user can then quickly and cheaply fix using
toolkit-supplied diagnostic and design tools. For example, a user might
discover by testing a simulated circuit design that a switch needed to adjust
the circuit had been forgotten and make that discovery simply by trying to make
a needed adjustment. The user could then quickly and cheaply design in the
needed switch without major cost or delay.

One can appreciate the importance of giving the user the capability for
trial-and-error learning by doing in a toolkit by thinking about the
consequences of not having it. When users are not supplied with toolkits that
enable them to draw on their local, sticky information and engage in
trial-and-error learning, they must actually order a product and have it built
to learn about design errors---typically a very costly and unsatisfactory way
to proceed. For example, automobile manufacturers allow customers to select a
range of options for their cars, but they do not offer the customer a way to
learn during the design process and before buying. The cost to the customer is
unexpected learning that comes too late: "That wide-tire option did look great
in the picture. But now that the car has been delivered, I discover that I
don't like the effect on handling. Worse, I find that my car is too wide to fit
into my garage!"

Similar disasters are often encountered by purchasers of custom computers. Many
custom computer manufacturers offer a website that allows users to "design your
own computer online." However, these websites do not allow users to engage in
trial-and-error design. Instead, they simply allow users to select computer
components such as processor chips and disk drives from lists of available
options. Once these selections have been made, the design transaction is
complete and the computer is built and shipped. The user has no way to test the
functional effects of these choices before purchase and first field
use---followed by celebration or regret.

In contrast, a sophisticated toolkit for user innovation would allow the user
to conduct trial-and-error tests to evaluate the effects of initial choices
made and to improve on them. For example, a computer design site could add this
capability by enabling users to actually test and evaluate the hardware
configuration they specify on their own programs and computing tasks before
buying. To do this, the site might, for example, provide access to a remote
computer able to simulate the operation of the computer that the user has
specified, and provide performance diagnostics and related choices in terms
meaningful to the user (e.g., "If you add option x at cost y, the time it takes
to complete your task will decrease by z seconds"). The user could then modify
or confirm initial design choices according to trade-off preferences only he or
she knows.

!_ Appropriate Solution Spaces
={ Toolkits :
     solution spaces and +3
}

Economical production of custom products and services is achievable only when a
custom design falls within the pre-existing capability and degrees of freedom
built into a particular manufacturer's production system. My colleagues and I
call this the /{solution space}/ offered by that system. A solution space may
vary from very large to small, and if the output of a toolkit is tied to a
particular production system, then the design freedom that a toolkit can offer
a user will be accordingly large or small. For example, the solution space
offered by the production process of a manufacturer of custom integrated
circuits offers a huge solution space to users---it will produce any
combination of logic elements interconnected in any way that a user-designer
might desire, with the result that the user can invent anything from a novel
type of computer processor to a novel silicon organism within that space.
However, note that the semiconductor production process also has stringent
limits. It will only implement product designs expressed in terms of
semiconductor logic---it will not implement designs for bicycles or houses.
Also, even within the arena of semiconductors, it will only be able to produce
semiconductors that fit within a certain range with respect to size and other
properties. Another example of a production system offering a very large
solution space to designers---and, potentially to user-designers via
toolkits---is the automated machining center. Such a device can basically
fashion any shape out of any machinable material that can be created by any
combination of basic machining operations such as drilling and milling. As a
consequence, toolkits for innovation intended to create designs that can be
produced by automated machining centers can offer users access to that very
large solution space.

Large solution spaces can typically be made available to user-designers when
production systems and associated toolkits allow users to manipulate and
combine relatively basic and general-purpose building blocks and operations, as
in the examples above. In contrast, small solution spaces typically result when
users are only allowed to combine a relatively few pre-designed options. Thus,
users who want to design their own custom automobiles are restricted to a
relatively small solution space: they can only make choices from lists of
options regarding such things as engines, transmissions, and paint colors.
Similarly, purchasers of eyeglasses are restricted to combining "any frame from
this list" of pre-designed frames, with "any lens type from that list" of
pre-designed options.

The reason producers of custom products or services enforce constraints on the
solution space that user-designers may use is that custom products can be
produced at reasonable prices only when custom user designs can be implemented
by simply making low-cost adjustments to the production process. This condition
is met within the solution space on offer. However, responding to requests that
fall outside that space will require small or large additional investments by
the manufacturer. For example, a producer of integrated circuits may have to
invest many millions of dollars and rework an entire production process in
order to respond to a customer's request for a larger chip that falls outside
the solution space associated with its present production equipment.

!_ User-Friendly Tools
={ Toolkits :
     user-friendly tools for +6
}

User toolkits for innovation are most effective and successful when they are
made "user friendly" by enabling users to use the skills they already have and
to work in their own customary and well-practiced design language. This means
that users don't have to learn the---typically different---design skills and
language customarily used by manufacturer-based designers, and so they will
require much less training to use the toolkit effectively.

For example, in the case of custom integrated circuit design, the users of
toolkits are typically electrical engineers who are designing electronic
systems that will incorporate custom semiconductor chips. The digital design
language normally used by electrical engineers is Boolean algebra. Therefore,
user-friendly toolkits for custom semiconductor design are provided that allow
toolkit users to design in this language. That is, users can create a design,
test how it works, and make improvements using only their own, customary design
language. At the conclusion of the design process, the toolkit then translates
the user's logical design into the design inputs required by the semiconductor
manufacturer's production system.

A design toolkit based on a language and skills and tools familiar to the user
is only possible to the extent that the user /{has}/ familiarity with some
appropriate and reasonably complete language and set of skills and tools.
Interestingly, this is the case more frequently than one might initially
suppose, at least in terms of the /{function}/ that a user wants a product or
service to perform---because functionality is the face that the product or a
service presents to the user. (Indeed, an expert user of a product or service
may be much more familiar with that functional face than manufacturer-based
experts.) Thus, the user of a custom semiconductor is the expert in what he or
she wants that custom chip to /{do}/, and is skilled at making complex
tradeoffs among familiar functional elements to achieve a desired end: "If I
increase chip clock speed, I can reduce the size of my cache memory and. . . ."

As a less technical example, consider the matter of designing a custom
hairstyle. There is certainly a great deal of information known to hairstylists
that even an expert user may not know, such as how to achieve a certain look by
means of layer cutting, or how to achieve a certain streaked color pattern by
selectively dying some strands of hair. However, an expert user is often very
well practiced at the skill of examining the shape of his or her face and
hairstyle as reflected in a mirror, and visualizing specific improvements that
might be desirable in matters such as curls, shape, or color. In addition, the
user will be very familiar with the nature and functioning of everyday tools
used to shape hair, such as scissors and combs.

A user-friendly toolkit for hairstyling innovation can be built upon these
familiar skills and tools. For example, a user can be invited to sit in front
of a computer monitor, and study an image of her face and hairstyle as captured
by a video camera. Then, she can select from a palette of colors and color
patterns offered on the screen, can superimpose the effect on her existing
hairstyle, can examine it, and can repeatedly modify it in a process of
trial-and-error learning. Similarly, the user can select and manipulate images
of familiar tools, such as combs and scissors, to alter the image of the length
and shape of her own hairstyle as projected on the computer screen, can study
and further modify the result achieved, and so forth. Note that the user's new
design can be as radically new as is desired, because the toolkit gives the
user access to the most basic hairstyling variables and tools such as hair
color and scissors. When the user is satisfied, the completed design can be
translated into technical hairstyling instructions in the language of a
hairstyling specialist---the intended production system in this instance.

In general, steady improvements in computer hardware and software are enabling
toolkit designers to provide information to users in increasingly friendly
ways. In earlier days, information was often provided to users in the form of
specification sheets or books. The user was then required to know when a
particular bit of information was relevant to a development project, find the
book, and look it up. Today, a large range of potentially needed information
can be embedded in a computerized toolkit, which is programmed to offer the
user items of information only if and as a development being worked on makes
them relevant.

!_ Module Libraries
={ Toolkits :
     module libraries for +1
}

Custom designs seldom are novel in all their parts. Therefore, a library of
standard modules will be a valuable part of a toolkit for user innovation.
Provision of such standard modules enables users to focus their creative work
on those aspects of their product or service designs that cannot be implemented
via pre-designed options. For example, architects will find it very useful to
have access to a library of standard components, such as a range of standard
structural support columns with pre-analyzed structural characteristics, that
they can incorporate into their novel building designs. Similarly, users who
want to design custom hairstyles will often find it helpful to begin by
selecting a hairstyle from a toolkit library. The goal is to select a style
that has some elements of the desired look. Users can then proceed to develop
their own desired style by adding to and subtracting from that starting point.

!_ Translating Users' Designs for Production

The "language" of a toolkit for user innovation must be convertible without
error into the language of the intended production system at the conclusion of
the user's design work. If it is not, the entire purpose of the toolkit will be
lost---because a manufacturer receiving a user design will essentially have to
do the design work over again. Error-free translation need not emerge as a
major problem---for example, it was never a major problem during the
development of toolkits for integrated circuit design, because both chip
designers and chip producers already used a language based on digital logic. In
contrast, in some fields, translating from the design language preferred by
users to the language required by intended production systems can be /{the}/
central problem in toolkit design. As an illustration, consider a recent
toolkit test project managed by Ernie Gum, the Director of Food Product
Development for the USA FoodServices Division of Nestlé.
={ Gum, E. +5 ;
   Toolkits :
     Nestlé and +5
}

One major business of Nestlé FoodServices is producing custom food products,
such as custom Mexican sauces, for major restaurant chains. Custom foods of
this type have traditionally been developed by or modified by the chains'
executive chefs, using what are in effect design and production toolkits taught
by culinary schools: recipe development procedures based on food ingredients
available to individuals and restaurants, and processed with restaurant-style
equipment. After using their traditional toolkits to develop or modify a recipe
for a new menu item, executive chefs call in Nestlé Foodservices or another
custom food producer and ask that firm to manufacture the product they have
designed---and this is where the language translation problem rears its head.

There is no error-free way to translate a recipe expressed in the language of a
traditional restaurant-style culinary toolkit into the language required by a
food-manufacturing facility. Food factories must use ingredients that can be
obtained in quantity at consistent quality. These are not the same as, and may
not taste quite the same as, the ingredients used by the executive chef during
recipe development. Also, food factories use volume production equipment, such
as huge-steam-heated retorts. Such equipment is very different from
restaurant-style stoves and pots and pans, and it often cannot reproduce the
cooking conditions created by the executive chef on a stove-top---for example,
very rapid heating. Therefore, food-production factories cannot simply produce
a recipe developed by or modified by an executive chef "as is" under factory
conditions---it will not taste the same.

As a consequence, even though an executive chef creates a prototype product
using a traditional chef's toolkit, food manufacturers find most of that
information---the information about ingredients and processing
conditions---useless because it cannot be straightforwardly translated into
factory-relevant terms. The only information that can be salvaged is the
information about taste and texture contained in the prototype. And so,
production chefs carefully examine and taste the customer's custom food
prototype, then try to make something that tastes the same using factory
ingredients and methods. But an executive chef's taste buds are not necessarily
the same as production chef taste buds, and so the initial factory
version---and the second and the third---is typically not what the customer
wants. So the producer must create variation after variation until the customer
is finally satisfied.

To solve the translation problem, Gum created a novel toolkit of pre-processed
food ingredients to be used by executive chefs during food development. Each
ingredient in the toolkit was the Nestlé factory version of an ingredient
traditionally used by chefs during recipe development: That is, it was an
ingredient commercially available to Nestlé that had been processed as an
independent ingredient on Nestlé factory equipment. Thus, a toolkit designed
for developing Mexican sauces would contain a chili puree ingredient processed
on industrial equipment identical to that used to produce food in
commercial-size lots. (Each ingredient in such a toolkit also contains traces
of materials that will interact during production---for example, traces of
tomato are included in the chili puree---so that the taste effects of such
interactions will also be apparent to toolkit users.)

Chefs interested in using the Nestlé toolkit to prototype a novel Mexican sauce
would receive a set of 20--30 ingredients, each in a separate plastic pouch.
They would also be given instructions for the proper use of these ingredients.
Toolkit users would then find that each component differs slightly from the
fresh components he or she is used to. But such differences are discovered
immediately through direct experience. The chef can then adjust ingredients and
proportions to move to the desired final taste and texture that is desired.
When a recipe based on toolkit components is finished, it can be immediately
and precisely reproduced by Nestlé factories--- because now the executive chef
is using the same language as the factory. In the Nestlé case, field testing by
Food Product Development Department researchers showed that adding the
error-free translation feature to toolkit-based design by users reduced the
time of custom food development from 26 weeks to 3 weeks by eliminating
repeated redesign and refinement interactions between Nestlé and purchasers of
its custom food products.

!_ Discussion

A toolkit's success in the market is significantly correlated with that
toolkit's quality and with industry conditions. Thus, Prügl and Franke (2005)
studied the success of 100 toolkits offered in a single industry: computer
gaming. They found that success, evaluated by independent experts, was
significantly correlated with the quality of execution of the attributes of
toolkits that have been discussed in this chapter. That is, success was found
to be significantly affected by the quality of trial-and-error learning enabled
by a toolkit, by the quality of fit of the solution space offered to users'
design problems, by the user friendliness of the tools provided, and by the
quality of module libraries offered with the toolkit. Schreier and Franke
(2004) also obtained information on the importance of toolkit quality in a
study of the value that users placed on consumer products (scarves, T shirts,
cell phone covers) customized with a simple, manufacturer-supplied toolkit.
They found user willingness to pay for custom designs, as measured by Vickrey
auctions, was significantly negatively affected by the difficulty of creating
custom designs with a toolkit. In contrast, willingness to pay was
significantly positively affected by enjoyment experienced in using a toolkit.
={ Franke, N. ;
   Prügl, R. ;
   Schreier, M. ;
   Trial-and-error problem solving ;
   Custom products :
     heterogeneity of user needs and +3 ;
   User need +3
}

With respect to industry and market conditions, the toolkit-for-user innovation
approach to product design is likely to be most appealing to toolkit suppliers
when the heterogeneous needs of /{many}/ users can be addressed by a standard
solution approach encoded in a toolkit. This is because it can be costly to
encode all the solution and production information relevant to users' design
decisions. For example, a toolkit for custom semiconductor design must contain
information about the semi-conductor production process needed to ensure that
product designs created by users are in fact producible. Encoding such
information is a one-time cost, so it makes the best economic sense for
solution approaches that many will want to use.

Toolkits for user innovation are not an appropriate solution for all product
needs, even when heterogeneous needs can be addressed by a common solution
approach. Specifically, toolkits will not be the preferred approach when the
product being designed requires the highest achievable performance. Toolkits
incorporate automated design rules that cannot, at least at present, translate
designs into products or software as skillfully as a human designer can. For
example, a design for a gate array generated with a toolkit will typically take
up more physical space on a silicon chip than would a fully custom-developed
design of similar complexity. Even when toolkits are on offer, therefore,
manufacturers may continue to design certain products (those with difficult
technical demands) while customers take over the design of others (those
involving complex or rapidly evolving user needs).

Toolkits can be designed to offer a range of capabilities to users. At the high
end, with toolkits such as those used to design custom integrated circuits,
users can truly innovate, creating anything implementable in digital
electronics, from a dishwasher controller to a novel supercomputer or form of
artificial life. At the low end, the product configurators commonly offered by
manufacturers of mass-customized products enable, for example, a watch
purchaser to create a custom watch by selecting from lists of pre-designed
faces, hands, cases, and straps. (Mass-customized production systems can
manufacture a range of product variations in single-unit quantities at near
mass-production costs (Pine 1993). In the United States, production systems
used by these manufacturers are generally based on computerized production
equipment.)
={ Pine, J. }

The design freedom provided by toolkits for user innovation may not be of
interest to all or even to most users in a market characterized by
heterogeneous needs. A user must have a great enough need for something
different to offset the costs of putting a toolkit to use for that approach to
be of interest. Toolkits may therefore be offered only to a subset of users. In
the case of software, toolkits may be provided to all users along with a
standard, default version of the product or service, because the cost of
delivering the extra software is essentially zero. In such a case, the
toolkit's capability will simply lie unused in the background unless and until
a user has sufficient incentive to evoke and employ it.
={ Lead users :
     toolkits and +3 ;
   Toolkits :
     lead users and +3
}

Provision of toolkits to customers can be a complement to lead user
idea-generation methods for manufacturers. Some users choosing to employ a
toolkit to design a product precisely right for their own needs will be lead
users, whose present strong need foreshadows a general need in the market.
Manufacturers can find it valuable to identify and acquire the generally useful
improvements made by lead users of toolkits, and then supply these to the
general market. For this reason, manufacturers may find it valuable implement
toolkits for innovation even if the portion of the target market that can
directly use them is relatively small.

Toolkits can affect existing business models in a field in ways that may or may
not be to manufacturers' competitive advantage in the longer run. For example,
consider that many manufacturers of products and services profit from both
their design capabilities and their production capabilities. A switch to
user-based customization via toolkits can affect their ability to do this over
the long term. Thus, a manufacturer that is early in introducing a toolkit
approach to custom product or service design may initially gain an advantage by
tying that toolkit to its particular production facility. However, when
toolkits are made available to customer designers, this tie often weakens over
time. Customers and independent tool developers can eventually learn to design
toolkits applicable to the processes of several manufacturers. Indeed, this is
precisely what has happened in the custom integrated circuit industry. The
toolkits revealed to users by the initial innovator, LSI, and later by rival
producers were producer-specific. Over time, however, Cadance and other
specialist toolkit supply firms emerged and developed toolkits that could be
used to make designs producible by a number of vendors. The end result is that
manufacturers that previously benefited from selling their product-design
skills and their production skills can be eventually forced by the shifting of
design tasks to customers via toolkits to a position of benefiting from their
production skills only.

Manufacturers that think long-term disadvantages may accrue from a switch to
toolkits for user innovation and design will not necessarily have the luxury of
declining to introduce toolkits. If any manufacturer introduces a high-quality
toolkit into a field favoring its use, customers will tend to migrate to it,
forcing competitors to follow. Therefore, a firm's only real choice in a field
where conditions are favorable to the introduction of toolkits may be whether
to lead or to follow.

1~ 12 Linking User Innovation to Other Phenomena and Fields

This final chapter is devoted to describing links between user-centered
innovation and other phenomena and literatures. Of course, innovation writ
large is related to anything and everything, so the phenomena and the
literatures I will discuss here are only those hanging closest on the
intellectual tree. My goal is to enable interested readers to migrate to
further branches as they wish, assisted by the provision of a few important
references. With respect to phenomena, I will first point out the relationship
of user innovation to /{information}/ communities---of which user innovation
communities are a subset. With respect to related fields, I begin by linking
user-centric innovation phenomena explored in this book to the literature on
the economics of knowledge, and to the competitive advantage of nations. Next I
link it to research on the sociology of technology. Finally, I point out how
findings regarding user innovation could---but do not yet---link to and
complement the way that product development is taught to managers.
={ Information commons ;
   Information communities ;
   Product development ;
   Technical communities
}

!_ Information Communities
={ Information commons +8 ;
   Information communities +8
}

Many of the considerations I have discussed with respect to user innovation
communities apply to /{information}/ communities as well---a much more general
category of which user innovation communities are a subset. I define
information communities as communities or networks of individuals and/or
organizations that rendezvous around an information commons, a collection of
information that is open to all on equal terms.
={ Technical communities +1 }

In close analogy to our discussions of innovation communities, I propose that
commons-based information communities or networks will form when the following
conditions hold: (1) Some have information that is not generally known. (2)
Some are willing to freely reveal what they know. (3) Some beyond the
information source have uses for what is revealed. On an intuitive basis, one
can immediately see that these conditions are often met. Of course, people and
firms know different things. Of course there are many things that one would not
be averse to freely revealing; and of course others would often be interested
in what is freely revealed. After all, as individuals we all regularly freely
reveal information not generally known to people who ask, and presumably these
people value at least some of the information we provide.
={ Free revealing of innovation information :
     in information communities +3
}

The economics of information communities can be much simpler than that of the
user innovation communities discussed earlier, because valuable proprietary
information is often not at center stage. When the service provided by
information communities is to offer non-proprietary "content" in a more
convenient and accessible form, one need consider only the costs and benefits
associated with information diffusion. One need not also consider potential
losses associated with the free revealing of proprietary innovation-related
information.

It is likely that information communities are getting steadily more pervasive
for the same reasons that user innovation communities are: the costs of
diffusing information are getting steadily lower as computing and communication
technologies improve. As a result, information communities may have a rapidly
increasing impact on the economy and on the landscape of industry. They are and
will be especially empowering to fragmented groups, whose members may for the
first time gain low-cost access to a great deal of rich and fresh information
of mutual interest. As is the case for user innovation networks, information
networks can actually store content that participants freely reveal and make it
available for free downloading. (Wikipedia is an example of this.) And/or,
information networks can function to link information seekers and information
holders rather than actually storing information. In the latter case,
participants post to the network, hoping that someone with the requested
information will spot their request and provide an answer (Lakhani and von
Hippel 2003). Prominent examples can be found in the medical field in the form
of specialized websites where patients with relatively rare conditions can for
the first time find each other and also find specialists in those conditions.
Patients and specialists who participate in these groups can both provide and
get access to information that previously was scattered and for most practical
purposes inaccessible.
={ Lakhani, K ;
   Wikipedia ;
   von Hippel, E.
}

Just as is the case in user innovation groups, open information communities are
developing rapidly, and the behaviors and infrastructure needed for success are
being increasingly learned and codified. These communities are by no means
restricted to user-participants. Thus, both patients and doctors frequently
participate in medical information communities. Also, information communities
can be run by profit-making firms and/or on a non-profit basis for and by
information providers and users themselves--- just as we earlier saw was the
case with innovation communities. Firms and users are developing many versions
of open information communities and testing them in the market. As an example
of a commercially supported information commons, consider e-Bay, where
information is freely revealed by many under a structure provided by a
commercial firm. The commercial firm then extracts a profit from commissions on
transactions consummated between information providers and information seekers.
As an example of an information community supported by users themselves, again
consider Internet sites specializing in specific diseases---for example,
childrenfacingillness.com.
={ Marketing research +1 }

Information communities can have major effects on established ways of doing
business. For example, markets become more efficient as the information
provided to transaction participants improves. Thus, product and service
manufacturers benefit from good information on the perceptions and preferences
of potential buyers. Similarly, product and service purchasers benefit from
good information on the characteristics of the various offerings in the market.
Traditionally, firms have collected information on users' needs and on
products' characteristics by means of face-to-face interviewing and (in the
case of mass markets) questionnaires. Similar information of high quality now
can be collected nearly without cost and can be posted on special Internet
sites by users themselves and/or by for-profit enterprises. Dellarocas, Awad,
and Zhang (2004) show that volunteered online movie reviews provide information
that is just as accurate as that collected by surveys of representative samples
of respondents. This emerging new approach to data aggregation will clearly
affect the established business models of firms specializing in information
collection, with websites like www.ciao.co.uk illustrating new possibilities.
If the quality of information available to transaction participants goes up and
the information price is low, transaction quality should go up. With the aid of
online product-evaluation sites, it is likely that consumers will be able to
apply much better information even to small buying decisions, such as the
choice of a restaurant for tonight's dinner.
={ Awad, N. ;
   Dellarocas C. ;
   Zhang, X.
}

What Paul David and colleagues call "open science" is a type of information
community that is closely related to the innovation communities discussed
earlier (David 1992; Dasgupta and David 1994; David 1998). Free revealing of
findings is, of course, a characteristic of modern science. Academic scientists
publish regularly and so freely reveal information that may have high
proprietary value. This raises the same question explored in the case of
innovation communities: Why, in view of the potential of free ridership, do
scientists freely reveal the information they have developed at private cost?
The answer overlaps with but also differs from the answers provided in the case
of free revealing of proprietary innovations by innovation users. With respect
to similarities, sociologists of science have found that reputation among peers
is important to scientists, and that priority in the discovery of new knowledge
is a major component of reputation. Because of the importance of priority,
scientists generally rush their research projects to completion and then rush
to freely reveal their new findings. This dynamic creates a great advantage
from the point of view of social welfare (Merton 1973).
={ Dasgupta, P. ;
   David, P. ;
   Merton, Robert ;
   Free revealing of innovation information :
     in information communities +1 ;
   Intellectual property rights :
     information communities and ;
   Users :
     free revealing by +1 | information communities and +1
}

With respect to major differences, it is public policy in many countries to
subsidize research with public funds. These policies are based on the
assumption that only inadequate amounts of scientific research can be drawn
forth by reputational inducements alone. Recall that, in contrast, innovations
developed and freely revealed by innovation users are not subsidized from any
source. Users, unlike "scientists," by definition have a personal or corporate
use for the innovation-related knowledge they generate. This additional source
of private reward may explain why user innovation communities can flourish
without subsidy.
={ Knowledge, production and distribution of }

!_ The Economics of Knowledge
={ Knowledge, production and distribution of +7 ;
   Users :
     knowledge and +7
}

In this field, Foray (2004) provides a rich road map regarding the economics of
knowledge and the central role played by users. Foray argues that the radical
changes in information and communication technologies (ICT) are creating major
changes in the economics of knowledge production and distribution. Economists
have traditionally reduced knowledge production to the function of research and
development, defined as the activity specifically devoted to invention and
innovation. Starting with Machlup (1962), economists also have identified the
knowledge-based economy as consisting of specialized sectors focused on
activities related to communication, education, the media, and computing and
information-related services. Foray argues that these simplifications, although
providing a rationale for a way to measure knowledge-generation activities,
were never appropriate and now are totally misleading.
={ Machlup, F. ;
   Foray, D. +2
}

Knowledge generation, Foray says, is now a major activity across all industrial
sectors and is by no means restricted to R&D laboratories: we are in the age of
the knowledge economy. He makes a central distinction between R&D that is
conducted in laboratories remote from doing, and learning by doing at the site
of production. He argues that both are important, and have complementary
advantages and drawbacks. Laboratory research can ignore some of the
complexities involved in production in search of basic understanding. Learning
by doing has the contrasting advantage of being in the full fidelity of the
real production process. The drawback to learning by doing, however, is that
one is attempting to do two things at once---producing and learning---and this
can force compromises onto both.

Foray positions users at the heart of knowledge production. He says that one
major challenge for management is to capture the knowledge being generated by
users "on line" during the process of doing and producing, and to integrate it
with knowledge created "off line" in laboratories. He discusses implications of
the distributed nature of knowledge production among users and others, and
notes that the increased capabilities of information and communication
technologies tend to reduce innovators' ability to control the knowledge they
create. He proposes that the most effective knowledge-management policies and
practices will be biased toward knowledge sharing.

Weber (2004, pp. 72--73) explores similar ideas in the specific context of open
source software. "The conventional language of industrial-era economics," he
notes, "identifies producers and consumers, supply and demand. The open source
process scrambles these categories. Open source software users are not
consumers in the conventional sense. . . . Users integrate into the production
process itself in a profound way." Weber's central thesis is that the open
source process is a new way of organizing production:
={ Weber, S. ;
   Open source software :
     knowledge and
}

_1 One solution is the familiar economy that depends upon a blend of exclusive
property rights, divisions of labor, reduction of transaction costs, and the
management of principal-agent problems. The success of open source demonstrates
the importance of a fundamentally different solution, built on top of an
unconventional understanding of property rights configured around distribution.
. . . And it relies on a set of organizational structures to coordinate
behavior around the problem of managing distributed innovation, which is
different from the division of labor. (ibid., p. 224)

Weber details the property-rights regime used by open source projects, and also
the nature of open source innovation communities and incentives acting on
participants. He then argues that this new mode of production can extend beyond
the development of open source software, to an extent and a degree that are not
yet understood:
={ Weber, S. ;
   Open source software :
     knowledge and
}

One important direction in which the open source experiment points is toward
moving beyond the discussion of transaction as a key determinant of
institutional design. . . . The elegant analytics of transaction cost economics
do very interesting work in explaining how divisions of labor evolve through
outsourcing of particular functions (the decision to buy rather than make
something). But the open source process adds another element. The notion of
open-sourcing as a strategic organizational decision can be seen as an
efficiency choice around distributed innovation, just as outsourcing was an
efficiency choice around transactions costs. . . . As information about what
users want and need to do becomes more fine-grained, more individually
differentiated, and harder to communicate, the incentives grow to shift the
locus of innovation closer to them by empowering them with freely modifiable
tools. (ibid., pp. 265--267)

!_ National Competitive Advantage
={ Government policy :
     and national competitive advantage +6 ;
   Manufacturers :
     and national competitive advantage +6 ;
   National competitive advantage +6 :
     See also Government policy ;
   Users :
     national competitive advantage and +6
}

Understanding national innovation systems and the competitive advantage of a
nation's firms is an important matter for national policy makers (Nelson 1993).
Can what we have learned in this book shed any light on their concerns? Porter
(1991), assessing national competitive advantage through the intellectual lens
of competitive strategy, concludes that one of four major factors determining
the competitive advantage of nations is demand conditions. "A nation's firms,"
he argues, "gain competitive advantage if domestic buyers are, or are among,
the world's most sophisticated and demanding buyers for the product or service.
Such buyers provide a window into the most advanced buyer needs. . . . Buyers
are demanding where home product needs are especially stringent or challenging
because of local circumstances." For example: "The continental United States
has been intensely drilled, and wells are being drilled in increasingly
difficult and marginal fields. The pressure has been unusually great for
American oil field equipment suppliers to perfect techniques that minimize the
cost of difficult drilling and ensure full recovery from each field. This has
pushed them to advance the state of the art and sustain strong international
positions." (ibid., pp. 89--90)
={ Nelson, R. ;
   Porter, M. +5
}

Porter also argues that /{early}/ domestic demand is also important: "Provided
it anticipates buyer needs in other nations, early local demand for a product
or service in a nation helps local firms to move sooner than foreign rivals to
become established in an industry. They get the jump in building large-scale
facilities and accumulating experience. . . . Only if home demand is
anticipatory of international need will home demand contribute to advantage."
(ibid., p. 95)

From my perspective, Porter is making the case for the value of a nation's
domestic lead users to national competitive advantage. However, he is also
assuming that it is /{manufacturers}/ that innovate in response to advanced or
stringent user demand. On the basis of the findings reported on in this book, I
would modify this assumption by noting that, often, domestic manufacturers'
links to /{innovating lead users}/ have the impacts on national competitive
advantage that he describes---but that the lead users' input to favored
domestic firms would include innovations as well as needs.

Domestic lead users make a difference to national competitive advantage, Porter
argues, because "local firms often enjoy some natural advantages in serving
their home market compared to foreign firms, a result of proximity as well as
language, regulation, and cultural affinities (even, frequently, if foreign
firms are staffed with local nationals)." Porter continues: "Preferred access
to a large domestic customer base can be a spur to investment by local firms.
Home demand may be perceived as more certain and easier to forecast, while
foreign demand is seen as uncertain even if firms think they have the ability
to fill it." (ibid., p. 93)

What new insights and research questions can the work of this book contribute
to this analysis of national competitive advantage? On the one hand, I
certainly see the pattern Porter describes in some studies of lead user
innovation. For example, early in the history of the US semiconductor industry,
AT&T, the inventor of the transistor and an early innovator, developed a number
of novel types of production equipment as a user organization. AT&T engineers
went to local machine shops to have these machines produced in volume to meet
AT&T's in-house production needs. A side effect of this procurement strategy
was to put many of these previously undistinguished firms into the business of
producing advanced semi-conductor equipment to the world (von Hippel 1977,
1988).
={ von Hippel, E. }

On the other hand, the findings of this book suggest that the "natural
advantages" Porter proposes that domestic manufacturers will have with respect
to filling the needs of local lead users may be eroding in the Internet age. As
has been seen in the case of open source software, and by extension in the
cases of other information-based products, users are capable of developing
complex products in a coordinated way without geographic proximity.
Participants in a particular open source project, for example, may come from a
number of countries and may never meet face to face. In the case of physical
products, the emergence of a pattern of user-based design followed by
"foundry-style" production may also reduce the importance of propinquity
between innovating lead users and manufacturers. As in the cases of integrated
circuits and kitesurfing discussed earlier in this book, users can transmit CAD
product-design information files from anywhere to any suitably equipped
manufacturer for production. Probably only in the case of physical products
where the interaction between product and production methods are not clear will
geography continue to matter deeply in the age of the Internet. Nations may be
able to create comparative advantages for domestic manufacturers with respect
to profiting from innovation by lead users; however, they cannot assume that
such advantages will continue to exist simply because of propinquity.
={ Custom products :
     product platforms and | users and ;
   Innovation communities :
     open source software and ;
   Kitesurfing ;
   Open source software ;
   Printed circuit CAD software ;
   Open source software :
     innovation communities and ;
   Toolkits :
     platform products and ;
   Users :
     custom products and
}

!_ The Sociology of Technical Communities
={ Information commons +8 ;
   Innovation communities :
     sociology of +8 ;
   Technical communities +8
}

Relevant elements of this field include studies in the sociology of technology
in general and studies of the sociology of open source software communities in
particular. Historical accounts of the evolution of a technology have often
taken a linear view of their subject. In the linear view, a technology such as
aerodynamics and related technological artifacts such as the airplane start at
point A and then naturally evolve to end point B. In other words, it is
implicitly assumed that the airplane will evolve from the artifact of wood and
fabric and wire developed by the Wright brothers to the characteristics we
associate with aircraft today. Nothing much to explain about that.
={ Open source software ;
   Open source software :
     innovation communities and
}

In the Social Construction of Technology (SCOT) model of technological
evolution (Pinch and Bijker 1987), the direction in which an artifact (a
product, for example) evolves depends very much on the meanings that different
"groups with a problem" construct for it. These meanings, in turn, affect which
of the many possible variations of a product are developed, how they evolve,
and whether and how they eventually die. Groups that construct the meanings of
a product centrally include, but are not restricted to, product users. For
example, in the case of the bicycle, some relevant groups were users of various
types---people who wanted to travel from place to place via bicycle, people who
wanted to race bicycles, etc. Relevant non-user groups included "anticyclists,"
who had a negative view of the bicycle in its early days and wanted it to fail
(Bijker 1995).
={ Bijker, W. ;
   Pinch, T. +4 ;
   Custom products :
     users and
}

When one takes the views of all relevant groups into account, one gets a much
richer view of the "socially constructed" evolution of a technology. As a
relatively recent example, consider the supersonic transport plane (SST)
planned in the United States during the 1970s. Airlines, and potential
passengers were "groups with a problem" who presumably wanted the technology
for different reasons. Other relevant groups with a problem included people who
expected to be negatively affected by the sonic boom the SST would cause,
people who were concerned about the pollution its engines would cause in the
stratosphere, and people who had other reasons for opposing or supporting the
SST. Proposed designs evolved in an attempt to satisfy the various contending
interest groups. Eventually it became clear that the SST designers could not
arrive at a generally acceptable compromise solution and so the project failed
(Horwich 1982).
={ Horwich, M. }

Pinch and Kline (1996, pp. 774--775) elaborated on the original SCOT model by
pointing out that the way a product is interpreted is not restricted to the
design stage of a technology, but also can continue during the product's use.
They illustrated with the case of the automobile: . . .
={ Kline, R. +2 }

_1 although [automobile] manufacturers may have ascribed a particular meaning
to the artifact they were not able to control how that artifact was used once
it got into the hands of the users. Users precisely as users can embed new
meanings into the technology. This happened with the adaptation of the car into
rural life. As early as 1903, farm families started to define the car as more
than a transportation device. In particular, they saw it as a general source of
power. George Schmidt, a Kansas farmer, advised readers of the /{Rural New
Yorker}/ in 1903 to "block up the hind axle and run a belt over the one wheel
of the automobile and around the wheel on a [corn] sheller, grinder, saw, pump,
or any other machine that the engine is capable of running, and see how the
farmer can save money and be in style with any city man." T. A. Pottinger, an
Illinois farm man, wrote in /{Wallace's Farmer}/ in 1909 that "the ideal farm
car should have a detachable backseat, which could turn the vehicle into a
small truck." Other Phenomena and Fields 173
={ Pottinger, T. ;
   Schmidt, G.
}

Of course, user innovations and modifications are involved in these cases along
with users' reinterpretation of product uses. Kline and Pinch report that
manufacturers adopted some of the rural users' innovations, generally after a
lag. For example, a car that could also serve as a small truck was eventually
offered as a commercial product.
={ Users :
     innovation and +13 ;
   Manufacturers :
     innovation and
}

Research on communities of practice offers another link between studies of user
innovation and sociology (Brown and Duguid 1991; Wenger 1998). The focus of
this research is on the functioning of specialist communities. Researchers find
that experts in a field spontaneously form interest groups that communicate to
exchange their views and learnings on how to carry out and improve the
practices of their profession. Members of communities of practice exchange help
in informal ways that seem similar to the practices described above as
characteristic of open source software projects and communities of sports
innovators.
={ Brown, J. ;
   Duguid, P. ;
   Wenger, E. ;
   Open source software
}

Research on brand communities is still another related research thread (Muniz
and O'Guinn 2001). Brand communities form around commercial brands and products
(e.g., Lego construction toys) and even around products discontinued by their
manufacturers e.g., Apple's Newton personal digital assistant). Brand
communities can be intensely meaningful to participants and can involve user
innovation. In Newton groups, for example, users develop new applications and
exchange information about how to repair aging equipment (Muniz and Schau
2004). In Lego communities, lead users develop new products, new building
techniques, and new offline and online multiplayer building projects that later
prove to be of interest to the manufacturer (Antorini 2005).
={ Antorini, Y. ;
   Brand communities ;
   Muniz, A. ;
   O'Guinn, T. ;
   Schau, H. ;
   Innovation communities :
     brand and
}

!_ The Management of Product Development
={ Product development +10 }

Finally, I turn to links between user-centered innovation and teaching on the
management of product development. Information on lead users as a source of new
product ideas now appears in most marketing textbooks. There also should be a
link to other elements of user-centered innovation processes in the literature
on product-development management---but there really isn't much of one yet.
Although much of the research on user innovation cited in this book is going on
in schools of management and business economics, little of this information has
moved into teaching related to the product-development process as of yet.

Clearly, it would be useful to provide managers of both user firms and
manufacturing firms with a better understanding of the management of
user-centered innovation. It is a curious fact that even managers of firms that
have built major product lines upon user-developed innovations may hold the
manufacturer-centric view that "we developed that." For example, an early study
of innovation in scientific instruments documented that nearly 80 percent of
the major improvements commercialized by instrument manufacturers had been
developed by users (von Hippel 1976). When I later discussed this finding with
managers in instrument firms, most of them were astonished. They insisted that
all the innovations in the study sample had been developed within manufacturing
firms. They could be convinced otherwise only when supplied with actual
publications by user-scientists describing user-built prototypes of those
instrument improvements---prototypes developed from 5 to 7 years before any
instrument firm had sold a functionally equivalent commercial product.
={ von Hippel, E. }

My inquiries into why managers in this field and others held---and largely
still hold---such contrary-to-fact beliefs identified several contributing
factors. First, manufacturers seldom track where the major new products and
product improvements they sell actually came from. Managers see no need to set
up a tracking system, because the conventional wisdom is clear: "Everyone knows
new products are developed by manufacturers such as ourselves based on user
needs identified by market research." Further, the manufacturing firms have
market-research and product-development departments in place, and innovations
are somehow being produced. Thus, it is easy to conclude that the
manufacturers' innovation processes must be working as expected.

In fact, however, important, functionally novel innovations are often brought
into manufacturers by informal channels. Product-development engineers may
attend conferences and learn about important user innovations, salesmen and
technical service personnel discover user-modified equipment on field visits,
and so on. Once the basic innovation-related information is in house, the
operating principles of a user's prototype will often be adopted, but the
detailed design of the device will be changed and improved for production.
After a while, the user's prototype, if remembered at all, will begin to look
quite primitive to the firm's engineers relative to the much better product
they have designed. Finally, when sales begin, the firm's advertising will urge
customers to buy "/{our}/ wonderful new product." Other Phenomena and Fields
175

The net result is understandable: the user roots of many new commercial
products, never widely known in manufacturing firms, are forgotten. And when it
is time to develop the next innovation, management again turns to the
conventional methods that "worked so well for us last time." Eventually,
information about new user innovations will again arrive by pathways unnoticed
and unmanaged---and with an unnecessary lag.

To improve matters, managers must learn when it is appropriate to follow
user-centered and manufacturer-centered innovation process paradigms and how
user-centered innovation can best be managed when it is the method of choice.
Managers in user firms and in manufacturing firms need tools with which to
understand the innovate-or-buy decisions they face---to understand which
product needs or which service needs users (rather than manufacturers) should
invest in developing. Managers in user firms also need to learn how their firms
can best carry out development work in their low-cost innovation niches: how
they can best deploy their information-related advantages of being actual users
and residing in the context of use to cheaply learn by doing. Managers in
manufacturing firms will want to learn how they can best play a profitable role
in user-centered innovation patterns when these play a role in the markets they
serve.
={ Sticky information :
     toolkits and +1 ;
   Users :
     innovate-or-buy decisions by | low-cost innovation niches of
}

Innovating users may also want to learn whether and how to diffuse their
innovations by becoming manufacturers. This may be a fairly common practice in
some fields. Shah (2000) found that users of sports equipment sometimes became
manufacturers by a very natural process. The users would demonstrate the
performance and value of their innovations as they used them in public sporting
events. Some of the participants in the meets would then ask "Can you make one
of those for me too?" Informal hobby-level production would then sometimes
become the basis of a major company. Lettl, Herstatt, and Gemünden (2004)
report on case histories in which user-innovators became heavily involved in
promoting the commercialization of important innovations in surgical equipment.
These innovations tended to be developed by surgeons, who then often made major
efforts to induce manufacturers to commercialize them. Hienerth (2004)
documents how user-innovators in "rodeo kayaking" build their own boats,
discover that kayak manufacturers (even those established by a previous
generation of user-innovators) are unwilling to manufacture what they want, and
so are driven to become manufacturers themselves.
={ Gemünden, H. ;
   Lettl, C. ;
   Herstatt, C. ;
   Hienerth, C. ;
   Shah, S. ;
   Sporting equipment :
     lead users and ;
   Windsurfing ;
   Surgical equipment
}

Managers must learn that no single locus of innovation is the "right" one for
either user firms or manufacturer firms. The locus of innovation varies between
user firms and manufacturing firms according to market-related and
information-related conditions. These conditions may well vary predictably over
product life cycles. Utterback and Abernathy (1975) proposed that innovation by
users is likely to be more important in the early stages of such cycles. Early
in the life of a new product, there is a "fluid" stage in which the nature and
the use of a product are unclear. Here, Utterback and Abernathy say, users play
a big part in sorting the matter out, in part through innovation. Later, a
dominant product design will emerge---a shared sense of exactly what a
particular product is, what features and components it should include, and how
it should function. (We all know, for example, that a car has four wheels and
moves along the ground in directions determined by a steering wheel.) After
that time, if the market for the product grows, innovation will shift from
product to process as firms shift from the problem of what to produce to the
problem of how to produce a well-understood product in ever greater volumes.
From a lead user innovation perspective, of course, both functionally novel
products and functionally novel processes are likely to be developed by
users---in the first case users of the product, and in the second by
manufacturing firms that use the process.
={ Albernathy, W. ;
   Utterback, J.
}

!_ In Conclusion

In this book I have explored how and why users, individually and in firms and
in communities, develop and freely reveal innovations. I have also argued that
there is a general trend toward a open and distributed innovation process
driven by steadily better and cheaper computing and communications. The net
result is an ongoing shift toward the democratization of innovation. This
welfare-enhancing shift is forcing major changes in user and manufacturer
innovation practices, and is creating the need for change in government
policies. It also, as I noted at the start of the book, presents major new
opportunities for us all. Other Phenomena and Fields 177

1~ Notes

!_ Chapter 2

1. LES contains four types of measures. Three ("benefits recognized early,"
"high benefits expected," and "direct elicitation of the construct") contain
the core components of the lead user construct. The fourth ("applications
generation") is a measure of a number of innovation-related activities in which
users might engage: they "suggest new applications," they "pioneer those
applications," and (because they have needs or problems earlier than their
peers) they may be "used as a test site" (Morrison, Midgely, and Roberts 2004).

!_ Chapter 3

1. Cluster analysis does not specify the "right" number of clusters---it simply
segments a sample into smaller and smaller clusters until the analyst calls a
halt. Determining an appropriate number of clusters within a sample can be done
in different ways. Of course, it always possible to say that "I only want to
deal with three market segments, so I will stop my analysis when my sample has
been segmented into three clusters." More commonly, analysts will examine the
increase of squared error sums of each step, and generally will view the
optimal number of clusters as having been reached when the plot shows a sudden
"elbow" (Myers 1996). Since this technique does not incorporate information on
remaining within-cluster heterogeneity, it can lead to solutions with a large
amount of within-cluster variance. The "cubic clustering criterion" (CCC)
partially addresses this concern by measuring the within-cluster homogeneity
relative to the between-cluster heterogeneity. It suggests choosing the number
of clusters where this value peaks (Milligan and Cooper 1985). However, this
method appears to be rarely used: Ketchen and Shook (1996) found it used in
only 5 of 45 segmentation studies they examined.

2. http://groups-beta.google.com/group/comp.infosystems.www.servers.unix

3. http://modules.apache.org/

4. To measure heterogeneity, Franke and I analyzed the extent to which j
standards, varying from [1; i], meet the needs of the i individuals in our
sample. Conceptually, we first locate a product in multi-dimensional need space
(dimensions = 45 in the case of our present study) that minimizes the distances
to each individual's needs. (This step is analogous to the Ward's method in
cluster analysis that also minimizes within cluster variation; see Punj and
Stewart 1983.) The "error" is then measured as the sum of squared Euclidean
distances. We then repeated these steps to determine the error for two
optimally positioned products, three products, and so on up to a number
equaling I -- 1. The sum of squared errors for all cases is then a simple
coefficient that measures how much the needs of i individuals can be satisfied
with j standard products. The "coefficient of heterogeneity" just specified is
sensitive both to the (average) distance between the needs and for the
configuration of the needs: when the needs tend to form clusters the
heterogeneity coefficient is lower than if they are evenly spread. To make the
coefficient comparable across different populations, we calibrate it using a
bootstrapping technique (Efron 1979) involving dividing the coefficient by the
expected value (this value is generated by averaging the heterogeneity of many
random distributions of heterogeneity of the same kind). The average random
heterogeneity coefficient is then an appropriate value for calibration
purposes: it assumes that there is no systematic relationship between the needs
of the individuals or between the need dimensions.

5. Conceptually, it can be possible to generate "one perfect product" for
everyone--- in which case heterogeneity of demand is zero---by simply creating
all the features wanted by anyone (45 + 92 features in the case of this study),
and incorporating them in the "one perfect product." Users could then select
the features they want from a menu contained in the one perfect product to
tailor it to their own tastes. Doing this is at least conceptually possible in
the case of software, but less so in the case of a physical product for two
reasons: (1) delivering all possible physical options to everyone who buys the
product would be expensive for physical goods (while costing nothing extra in
the case of information products); (2) some options are mutually exclusive (an
automobile cannot be both red and green at the same time).

6. The difference between actual willingness to pay and expressed willingness
to pay is much lower for private goods (our case) than for public goods. In the
case of private goods, Loomis et al. (1996) found the expressed willingness to
pay for art prints to be twice the actual WTP. Willis and Powe (1998) found
that among visitors to a castle the expressed WTP was 60 percent lower than the
actual WTP. In the case of public goods, Brown et al. (1996), in a study of
willingness to pay for removal of a road from a wilderness area, found the
expressed WTP to be 4--6 times the actual WTP. Lindsey and Knaap (1999), in a
study of WTP for a public urban greenway, found the expressed WTP to be 2-10
times the actual WPT. Neil et al. (1994) found the expressed WTP for conserving
an original painting in the desert to be 9 times the actual WTP. Seip and
Strand (1992) found that less than 10 percent of those who expressed interest
in paying to join an environmental organization actually joined.

!_ Chapter 6

1. As a specific example of a project with an emergent goal, consider the
beginnings of the Linux open source software project. In 1991, Linus Torvalds,
a student in Finland, wanted a Unix operating system that could be run on his
PC, which was equipped with a 386 processor. Minix was the only software
available at that time but it was commercial, closed source, and it traded at
US$150. Torvalds found this too expensive, and started development of a
Posix-compatible operating system, later known as Linux. Torvalds did not
immediately publicize a very broad and ambitious goal, nor did he attempt to
recruit contributors. He simply expressed his private motivation in a message
he posted on July 3, 1991, to the USENET newsgroup comp.os.minix (Wayner 2000):
Hello netlanders, Due to a project I'm working on (in minix), I'm interested in
the posix standard definition. [Posix is a standard for UNIX designers. A
software using POSIX is compatible with other UNIX-based software.] Could
somebody please point me to a (preferably) machine-readable format of the
latest posix-rules? Ftp-sites would be nice. In response, Torvalds got several
return messages with Posix rules and people expressing a general interest in
the project. By the early 1992, several skilled programmers contributed to
Linux and the number of users increased by the day. Today, Linux is the largest
open source development project extant in terms of number of developers.
={ Linux }

!_ Chapter 7

1. When they do not incorporate these qualities, they would be more properly
referred to as networks---but communities is the term commonly used, and I
follow that practice here.

2. hacker n. [originally, someone who makes furniture with an axe] 1. A person
who enjoys exploring the details of programmable systems and how to stretch
their capabilities, as opposed to most users, who prefer to learn only the
minimum necessary. 2. One who programs enthusiastically (even obsessively) or
who enjoys programming rather than just theorizing about programming. 3. A
person capable of appreciating hack value. 4. A person who is good at
programming quickly. . . . 8. [deprecated] A malicious meddler who tries to
discover sensitive information by poking around. Hence password hacker, network
hacker. The correct term for this sense is cracker (Raymond 1996).

3. Source code is a sequence of instructions to be executed by a computer to
accomplish a program's purpose. Programmers write computer software in the form
of source code, and also document that source code with brief written
explanations of the purpose and design of each section of their program. To
convert a program into a form that can actually operate a computer, source code
is translated into machine code using a software tool called a compiler. The
compiling process removes program documentation and creates a binary version of
the program---a sequence of computer instructions consisting only of strings of
ones and zeros. Binary code is very difficult for programmers to read and
interpret. Therefore, programmers or firms that wish to prevent others from
understanding and modifying their code will release only binary versions of the
software. In contrast, programmers or firms that wish to enable others to
understand and update and modify their software will provide them with its
source code. (Moerke 2000, Simon 1996).

4. See www.gnu.org/licenses/licenses.html#GPL

5. http://www.sourceforge.net

6. "The owner(s) [or `maintainers'] of an open source software project are
those who have the exclusive right, recognized by the community at large, to
redistribute modified versions. . . . According to standard open source
licenses, all parties are equal in the evolutionary game. But in practice there
is a very well-recognized distinction between `official' patches [changes to
the software], approved and integrated into the evolving software by the
publicly recognized maintainers, and `rogue' patches by third parties. Rogue
patches are unusual and generally not trusted." (Raymond 1999, p. 89)

!_ Chapter 8

1. See also Bresnahan and Greenstein 1996b; Bresnahan and Saloner 1997; Saloner and Steinmueller 1996.

!_ Chapter 10

1. ABS braking is intended to keep a vehicle's wheels turning during braking.
ABS works by automatically and rapidly "pumping" the brakes. The result is that
the wheels continue to revolve rather than "locking up," and the operator
continues to have control over steering.

2. In the general literature, Armstrong's (2001) review on forecast bias for
new product introduction indicates that sales forecasts are generally
optimistic, but that that upward bias decreases as the magnitude of the sales
forecast increases. Coller and Yohn (1998) review the literature on bias in
accuracy of management earnings forecasts and find that little systematic bias
occurs. Tull's (1967) model calculates $15 million in revenue as a level above
which forecasts actually become pessimistic on average. We think it reasonable
to apply the same deflator to LU vs. non-LU project sales projections. Even if
LU project personnel were for some reason more likely to be optimistic with
respect to such projections than non-LU project personnel, that would not
significantly affect our findings. Over 60 percent of the total dollar value of
sales forecasts made for LU projects were actually made by personnel not
associated with those projects (outside consulting firms or business analysts
from other divisions).

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%% index di.eric_von_hippel_index.txt democratizing_innovation.eric_von_hippel_index.txt