A Classification of Dutch Manufacturing based on a Model of Innovation

Summary The paper studies the degree of homogeneity of innovative behavior in order to determine empirically an industry classification of Dutch manufacturing that can be used for policy purposes. Defining homogeneity in terms of an economic model distinguishes our classification from existing taxonomies such as those of the OECD, Pavitt and the various classifications based on a principal components analysis. We use a two-limit tobit model with sample selection, which explains the decisions by business enterprises to innovate and the impact these decisions have on the share of innovative sales. The model is estimated for eleven industries based on the Dutch Standard Industrial Classification (SBI 1993). A likelihood ratio (LR) test is then performed to test for equality of the parameters across industries. We find that Dutch manufacturing consists of three groups of industries in terms of innovative behavior, a high-tech group, a low-tech group and the industry of wood. The same pattern shows up in the three Dutch Community Innovation Surveys. The empirical part of this study has been carried out at the Centre for Research of Economic Microdata at Statistics Netherlands. The authors wish to thank Statistics Netherlands, and in particular Bert Diederen, for helping us in accessing and using the Micronoom data set. The views expressed in this paper are solely those of the authors. The authors also wish to thank Fran?ois Laisney, Patrick Waelbroek and participants at presentations in Maastricht, Strasbourg, Leuven and Lille for their helpful comments. The first author acknowledges financial support from METEOR.     

Are you really doing good things in your boss's eyes? Interactive effects of employee innovative work behavior and leader–member exchange on supervisory performance ratings

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Sustainable technology development implies large changes in technological systems. The illustrative process ‘hydrogen fuel cell in a boat’ is used here as an example of a learning process concerning a transition towards a hydrogen economy. Theoretically the concepts of constructive technology assessment, back-casting and social niche management are combined in this approach.