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The prevalence of user innovation and free innovation transfers: Implications for statistical indicators and innovation policy Fred Gault, Visiting Fellow, International Development Research Centre, Ottawa, Canada and Eric von Hippel, MIT Sloan School of Management, Cambridge, MA, USA. January, 2009 MIT Sloan School of Management Working Paper #4722-09 Acknowledgements: We would like to express our appreciation to Susan Schaan of Statistics Canada for her help with the 2007 survey we report upo
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  1 The prevalence of user innovation and free innovation transfers:Implications for statistical indicators and innovation policy Fred Gault,Visiting Fellow, International Development Research Centre, Ottawa, CanadaandEric von Hippel,MIT Sloan School of Management, Cambridge, MA, USA.January, 2009  MIT Sloan School of Management Working Paper #4722-09 Acknowledgements: We would like to express our appreciation to Susan Schaan of Statistics Canada for her help with the 2007 survey we report upon here. Also we thank Mark Uhrback and Jeroen de Jong for their contribution to the development of the surveyquestions, and thank Statistics Canada colleagues for the testing of the resultingquestionnaires. Finally, we thank Joachim Henkel for his careful and critical reading of the final manuscript.  2 The prevalence of user innovation and free innovation transfers:Implications for statistical indicators and innovation policyABSTRACT Statistical indicators have not kept pace with innovation research. Today, it is wellunderstood that many industrial and consumer products are developed by users, and thatmany innovations developed at private cost are freely shared. New statistical indicatorswill empower policymakers to take advantage of the latest research findings in their innovation policymaking, and will enable them to benefit from improved measurement of resulting policy impacts.In this paper, we report upon a pilot project in which a novel set of statisticalindicators were deployed in a 2007 survey of 1,219 Canadian manufacturing plants. The plants all developed or modified “advanced” process technologies for in-house use.Responses to the survey showed that data on both user innovation and the transfers of these innovations could be reliably collected, and that novel findings important to policymaking would result. One such finding: About 20% of the user-innovatorssurveyed reported transferring their innovations to other users and/or equipment suppliers – and the majority of these at least sometimes did so at no charge to recipients. Sincecost-free sharing of innovations is understood to result in greater social welfare thanlicensing for a fee, innovation rates being equal, this finding has important public policyimplications. Current government innovation policies tend to favor and even to subsidizethe obtaining of intellectual property rights as a means of encouraging innovation. If asignificant fraction of user-innovators in the economy are already freely revealing their innovations - despite the availability of intellectual property grants - perhaps intellectual property rights policies should be reexamined.We propose that improved versions of the novel statistical indicators piloted hereshould be integrated into official statistics so that user innovation, and related matters suchas voluntary spillovers of innovation-related information, can be better monitored, better understood, and better managed.   3 The prevalence of user innovation and free innovation transfers:Implications for statistical indicators and innovation policy1. Introduction and overview Empirical research by innovation scholars has now clearly documented that manyof the innovative products we buy from producers are in fact developed and prototypedand tested and improved by “lead users.” These individuals and firms often innovate inorder to solve their own, ahead-of-market needs. Later, when a commercially-attractivemarket emerges for these products, producers adopt or learn from products that users havealready developed and used in the field as an important feedstock to their own productdevelopment and commercialization efforts. This user-centered innovation pattern has been shown to hold both in the case of user firms developing process innovations for in-house use, and in the case of innovative products developed for individual end users, likenovel sports equipment and foods. End user “consumers,” it has been found, workingindividually or in groups, are the actual developers of many consumer products later commercialized and sold to the general marketplace by producers.We define user-innovators as firms or individual consumers that benefit from using  a good or a service they develop. In contrast, producer-innovators are firms or individuals that benefit from  selling  a good or a service they develop. Lead users are asubset of all users. Their primary distinguishing feature is that they at the leading edge of important market trends, and so experience new emerging needs ahead of the bulk of themarket. As a result, lead users often innovate in order to solve their own, ahead-of-marketneeds – often before producers are even aware of those new needs (von Hippel, 1988,2005).Statistical indicators used in official surveys of innovation activities have notaddressed this new understanding of the central role of users in the innovation process. New indicators must be created to provide a clearer picture. This is especially important asresearch shows that user innovation is becoming steadily more important due to steadyimprovements in Internet communication tools and computer-based design and designcollaboration tools.  4In this paper, we report upon a first use of novel statistical indicators in a surveymeasuring important aspects of user development and diffusion of innovations. Thissurvey was undertaken by Statistics Canada in 2007, and utilized a sample of 1,219Canadian manufacturing plants. It was required that all survey participants haddeveloped new process equipment innovations for their own use, and/or had modified process equipment to better suit their needs. The authors participated in the developmentof the questions related to respondents’ innovation activities used in this survey.Analysis of survey responses showed that, on average, innovating user firms hadspent a significant amount of money and time developing process innovations andimprovements for in-house use. Analysis also showed that about 25% of these firmsknew that innovations they had developed had been adopted by process equipment producers. A similar fraction was aware that innovations they had developed had beenadopted by other user firms.When asked about the terms under which their innovations had been transferred toadopters, a significant fraction reported that they did not receive a fee or other consideration for the transfer of their intellectual property. User-innovators that hadtransferred their innovations without fee explained that they were motivated to do so because of expected benefits to themselves including: to allow a supplier to build a moresuitable final product; to gain feedback and expertise; and, to enhance reputation. These benefits are similar to the types of benefits claimed by contributors to open sourcesoftware projects – which supports the idea that the pathways to private returns from freerevealing are quite general in their basic nature. As we will discuss in section 5, thisfinding may justify significant changes in government policy related to intellectual property rights.We have been able to capture the innovation patterns just described because theexperimental Statistics Canada survey we report upon, to be described in detail later inthe paper, differs in two crucial respects from current official government surveys of theinnovation process: (1) innovation development  by users is better tracked; and, (2) the transfer  of user-developed innovations from users to producers is tracked for the firsttime in any government survey. As a result, what is actually occurring among innovatorsand adopters in the field is more accurately captured. We think that it is important to
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