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Heterogeneity of innovation strategies and firms’ performance

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Abstract

This work deals with two main issues: first, the possibility of identifying differences in firm economic returns (operating profit margins) for different groups of innovation strategy and second, the possibility of checking for factors explaining the probability of being within the best performers for each group of innovation strategy. It is an empirically based analysis using descriptive statistics (first part) and a probit econometric analysis (second part) where data are collected at firm level from two CIS surveys matched with economic accountability data for 902 Italian manufacturing firms for the period 1998-2000. The distribution analysis of profit margins by different populations of firms shows a better economic performance for groups characterized by more complex innovation strategies. Unexpectedly, the risk associated to economic returns is lower for groups where returns’ mean is higher. In this case skewness is higher too suggesting that reaching “excellence” is more difficult. The probit regressions account for the role played by different (market and firm) factors on the probability of being the best positioned for each firm population. This work gives two main messages: first, when studying the impact of R&D activity (both on firm productivity or competitiveness) it is worth to distinguish among different kinds of innovation strategy rather than limiting the analysis to aggregated results and second, it appears quite clear that competition awards more complex innovation strategies than simple R&D intra-muros activity.

Suggested Citation

  • Bianca Potì & Giovanni Cerulli, 2007. "Heterogeneity of innovation strategies and firms’ performance," CERIS Working Paper 200706, Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY -NOW- Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY.
  • Handle: RePEc:csc:cerisp:200706
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    References listed on IDEAS

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    1. Jacques Mairesse & Pierre Mohnen, 2002. "Accounting for Innovation and Measuring Innovativeness: An Illustrative Framework and an Application," American Economic Review, American Economic Association, vol. 92(2), pages 226-230, May.
    2. Orietta Marsili & Ammon Salter, 2005. "'Inequality' of innovation: skewed distributions and the returns to innovation in Dutch manufacturing," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(1-2), pages 83-102.
    3. repec:adr:anecst:y:1998:i:49-50 is not listed on IDEAS
    4. Dosi, Giovanni, 1988. "Sources, Procedures, and Microeconomic Effects of Innovation," Journal of Economic Literature, American Economic Association, vol. 26(3), pages 1120-1171, September.
    5. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
    6. F. M. Scherer, 1998. "The Size Distribution of Profits from Innovation," Annals of Economics and Statistics, GENES, issue 49-50, pages 495-516.
    7. Cohen, Wesley M. & Levin, Richard C., 1989. "Empirical studies of innovation and market structure," Handbook of Industrial Organization,in: R. Schmalensee & R. Willig (ed.), Handbook of Industrial Organization, edition 1, volume 2, chapter 18, pages 1059-1107 Elsevier.
    8. Jacques Mairesse & Mohamed Sassenou, 1991. "R&D Productivity: A Survey of Econometric Studies at the Firm Level," NBER Working Papers 3666, National Bureau of Economic Research, Inc.
    9. Elena Cefis & Matteo Ciccarelli, 2005. "Profit differentials and innovation," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(1-2), pages 43-61.
    10. Rivers, Douglas & Vuong, Quang H., 1988. "Limited information estimators and exogeneity tests for simultaneous probit models," Journal of Econometrics, Elsevier, vol. 39(3), pages 347-366, November.
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    Cited by:

    1. Cerina, Fabio & Mureddu, Francesco, 2014. "Is agglomeration really good for growth? Global efficiency, interregional equity and uneven growth," Journal of Urban Economics, Elsevier, vol. 84(C), pages 9-22.

    More about this item

    Keywords

    profitability; strategic heterogeneity; R&D and innovation; probit regression;

    JEL classification:

    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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