Handbook of Research on Innovation and Entrepreneurship
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Handbook of Research on Innovation and Entrepreneurship

Edited by David B. Audretsch, Oliver Falck, Stephan Heblich and Adam Lederer

Leading researchers use their outstanding expertise to investigate various aspects in the context of innovation and entrepreneurship such as growth, knowledge production and spillovers, technology transfer, the organization of the firm, industrial policy, financing, small firms and start-ups, and entrepreneurship education as well as the characteristics of the entrepreneur.
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Chapter 27: The Propensity to Patent an Innovation Comparing Entrepreneurial with Routinized Innovators

Alfred Kleinknecht and Gerben van der Panne


27 The propensity to patent an innovation: comparing entrepreneurial with routinized innovators Alfred Kleinknecht and Gerben van der Panne INTRODUCTION Patents are a frequently used innovation indicator as patent records are publicly available and easily accessible. Moreover, patent data are classified by technical fields, and patent time series allow for the convenient study of historical trends. As frequently argued, there are two major drawbacks associated with this indicator. First, not all patents relate to innovations, i.e. the market introduction of a product or service. Little is known about ‘sleeping’ patents that are never translated into commercial use. Second, many innovators do not seek patent protection. Often alternative mechanisms of protection are considered more efficient. Among the latter, secrecy and time-lead on competitors (Levin et al., 1987), and the protection of tacit knowledge by keeping qualified people in the firm (Brouwer and Kleinknecht, 1999) tend to rank higher than patents. In this chapter we explicitly address what F.M. Scherer once called the ‘propensity to patent’. This propensity might vary substantially across industries, types of innovation or other dimensions. When investigating interfirm differences in the propensity to patent, comparisons between R&D data and patents are less helpful since any deviation between the two may also be ascribed to a more or less efficient use of R&D inputs. Moreover, standard R&D data are a deficient indicator of innovation in small firms (Kleinknecht et al., 2002). This chapter therefore uses a direct measure of the ‘output’ of the innovative process: a...

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