By Alfred Kleinknecht
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Additional resources for Determinants of Innovation: The Message from New Indicators
Fourth, with regard to technological opportunities, the contribution of science-orientated knowledge sources (variable SOURCE 1) to the innovation performance proves to be stronger for big than for small firms, a fact one can possibly explain with the higher capability of larger firms to absorb basic science-orientated knowledge because of their better endowment with R&D capital. ll On the other hand, small firms seem to use more successfully generally accessible knowledge (trade journals, conferences and so on) as well as know-how coming from customers and suppliers (variable SOURCE 3).
1. 15, includes only a subset of these indicators, primarily to secure a number of observations large enough to test the economic plausibility and the statistical quality of the aggregate innovation measure. 13 The statistically best performing factor solution is based on two factors depicting the technical (high loadings on INNR, INND, RDEQ, IASST) and the market dimension (high loadings primarily on SP 2 and NEW) of innovative activity in the case of new products and the input (INNR, INND, INNDC) and output side (IASST, IASSE) of the innovation process for new production techniques.
We also observe a weakening of the impact of TPOT. Results with Model 2 (not presented here) show similar effects for the overall appropriability measures APPRG and TPOT; in addition, owing to the interaction of SOURCE 1 (measuring the importance of science-orientated external knowledge sources) with size, the statistical significance of this variable disappears. Estimates with the output-orientated innovation measures SP 1, SP 2, NEW and NEWGROW also yield a reduced influence of the general technological potential (TPOT).
Determinants of Innovation: The Message from New Indicators by Alfred Kleinknecht