| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 5036844 | Technological Forecasting and Social Change | 2017 | 11 Pages |
Abstract
The present paper studied regional innovative behavior in Iran through a spatial knowledge production function approach by employing the principal components analysis (PCA). To this end, the determinants of regional innovative behavior, as measured by the number of Iranian patents granted to resident applicants, were analyzed. In addition to the total number of patents, the effects of the innovative factors were examined on company patents, university patents, and personal patent, separately. Fourteen explanatory variables were converted by PCA into three components: contextual index, industrial index, and low-welfare index. The results showed that the low-welfare index was relatively more important in explaining innovative behaviors at the regional level, while company patents were more sensitive to contextual index. Moreover, the results pointed to the lack of knowledge spillover across Iranian regions.
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Authors
Mojgan Samandar Ali Eshtehardi, Seyed Kamran Bagheri, Alberto Di Minin,