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Innovative performance of Iranian knowledge-based firms: Large firms or SMEs?

Noori, J ; Sharif University of Technology | 2016

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  1. Type of Document: Article
  2. DOI: 10.1016/j.techfore.2016.04.025
  3. Publisher: Elsevier Inc , 2016
  4. Abstract:
  5. The debate over innovativeness of large firms and SMEs, which was bolded by Schumpeter, still continues under mixed empirical evidences. There are several implications for this debate including policy orientation in support of large firms or SMEs. But there is a scarce of studies in developing countries and no such study in Iran yet. The present study has explored the proportionality of increase of innovation activity versus firm size within 522 Iranian knowledge-based firms categorized in 9 industries. Innovation activity was measured by R&D expenditure while firm size stood for number of employees. Using log-log regression in the first phase, it was found that R&D expenditure confirms a significantly more than proportionate relationship with firm size, on a continuous spectrum of size, which is in line with Schumpeter's idea in favor of large firms. The second phase of the study utilized analysis of covariance to treat firm size categorically using quantitative covariate of physical capital structure. The second results complemented the first, in the sense that categories of small-, medium-, and large-sized firms had significantly different mean innovation activity under a same physical capital structure. It should be noted that these conclusive results were derived just for the industries that sufficiently had a large number of observations (firms); otherwise, the results seem mixed. Of course, the results should be interpreted within the features of the database and measurement indicators
  6. Keywords:
  7. Logarithmic regression ; R&D expenditure ; Developing countries ; Regression analysis ; Analysis of covariances ; ANCOVA ; Continuous spectrum ; Firm size ; Innovative performance ; Measurement indicators ; Knowledge based systems
  8. Source: Technological Forecasting and Social Change ; May , 2016 ; 00401625 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0040162516300555