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The empirical part of this research has been carried out at the Centre for Research of Economic Microdata at Statistics Netherlands. The views expressed in this paper are those of the authors and do not necessarily reflect the policies of Statistics Netherlands. This paper has greatly benefited from comments by Stefano Brusoni, Elena Cefis, Keld Laursen and the late Keith Pavitt. An earlier version of the paper was presented at the ISS Conference 2002. Ammon Salter would like to acknowledge the financial support of the Ghoshal Research Fellowship of the Advanced Institute of Management (AIM) Research.
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There are some firms that carry out design activities that did not respond to the survey question. Since we have no way of differentiating those firms that did carry out design but who did not report these design activities from those who carried out no design at all, we assume a non-response to this question to be an indicator of a lack of design activity. This is a limitation of our study and data set.
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The distribution of innovative performance displays positive skewness (equal to 3.6 for products new to the market, 2.8 for products new to the firm and 1.7 for improved products). Positive skewness implies that the distribution is characterized by a large number of low-performing firms and a small number of high-performing firms. The kurtosis of the distribution is above the normality value (the difference is equal to 16.3 for products new to the market, 11.3 for products new to the firm and 3.0 for improved products). High kurtosis implies that the tails of the empirical distributions are 'fatter' than the tails of the normal distribution. That is, the relative presence of high-performing and low-performing firms is higher than under normality conditions.
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The sample is composed of firms that are 'innovators' according to a broad definition, which consists of firms that introduced either process or product innovations and firms that have carried out unsuccessful or uncompleted projects. Included within this definition are innovative firms with turnover for a specific category of product innovation equal to zero. These firms are also accounted for in the estimation of the model.
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Alternative versions of the hierarchical regression have been considered by entering the linear and interactive effects sequentially for the variables of marketing, first, and then machinery. The estimated coefficients of design and R&D expenditure did not change significantly, however.
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