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The Unexplored Effect of Skills and Technology on Firms' Performance


  • Silvia Rita Sedita


The aim of this paper is to add new findings to the knowledge based view of the firm, where the cross-learning ability of individuals and organizations plays a fundamental role in the determination of firms' superior performances. Collective, non formal - informal, formal types of learning (learning drivers) contribute to shape the competitiveness of firms, especially in the present knowledge-based economy, where the necessity to respond effectively to frequent external shock (demand, technology, competitive environment driven) emphasizes the importance of being flexible and quickly adaptive. Nevertheless, focusing on learning capacities, and particularly on human skills, often leads to forget or ignore industry effects, such as innovative intensity, which increase the explanatory power of the learning drivers. This work explores the conjoint effect of learning drivers and innovative intensity on firms' performance by showing some evidence from statistical data analysis on the Danish IDA (Integrated Database for Labour Market Research). A sample of firms belonging to the manufacturing industry is studied using data related to the year 1999. The paper proceeds as follows: firstly, the role and relevance of human resources in the determination of firm's performance is presented. Secondly, a missing ring in the knowledge based view of the firm is detected: the R&D investments intensity. Thirdly, the data analysis process and the methodology adopted are illustrated. Finally, the results are presented and discussed.

Suggested Citation

  • Silvia Rita Sedita, 2004. "The Unexplored Effect of Skills and Technology on Firms' Performance," DRUID Working Papers 04-06, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
  • Handle: RePEc:aal:abbswp:04-06

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    References listed on IDEAS

    1. Franco Malerba & Luigi Orsenigo, 2002. "Innovation and market structure in the dynamics of the pharmaceutical industry and biotechnology: towards a history-friendly model," Industrial and Corporate Change, Oxford University Press, vol. 11(4), pages 667-703, August.
    2. Mark Doms & Eric J. Bartelsman, 2000. "Understanding Productivity: Lessons from Longitudinal Microdata," Journal of Economic Literature, American Economic Association, vol. 38(3), pages 569-594, September.
    3. Romer, Paul, 1993. "Idea gaps and object gaps in economic development," Journal of Monetary Economics, Elsevier, vol. 32(3), pages 543-573, December.
    4. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    5. Metcalfe, J S, 1994. "Competition, Fisher's Principle and Increasing Returns in the Selection Process," Journal of Evolutionary Economics, Springer, vol. 4(4), pages 327-346, November.
    6. Ulrich Witt, 2006. "Evolutionary Economics," Papers on Economics and Evolution 2006-05, Philipps University Marburg, Department of Geography.
    7. Richard R. Nelson, 1995. "Recent Evolutionary Theorizing about Economic Change," Journal of Economic Literature, American Economic Association, vol. 33(1), pages 48-90, March.
    8. Malerba, Franco, et al, 1999. "'History-Friendly' Models of Industry Evolution: The Computer Industry," Industrial and Corporate Change, Oxford University Press, vol. 8(1), pages 3-40, March.
    9. Esben Sloth Andersen, 1999. "Multisectoral Growth and National Innovation Systems," Nordic Journal of Political Economy, Nordic Journal of Political Economy, vol. 25, pages 33-52.
    10. Young, Allyn A., 1928. "Increasing Returns and Economic Progress," History of Economic Thought Articles, McMaster University Archive for the History of Economic Thought, vol. 38, pages 527-542.
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    Cited by:

    1. Luciano PILOTTI & Silvia Rita SEDITA, 2005. "Human capital development in a complex learning system: the virtuous interaction between individuals, organizations and communities," Departmental Working Papers 2005-17, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

    More about this item


    Human capital; innovtive intensity; knowledge; learning; manufacturing; performance;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • L6 - Industrial Organization - - Industry Studies: Manufacturing

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