Not too close, not too far: testing the Goldilocks principle of ‘optimal’ distance in innovation networks

Rune Fitjar, Franz Huber and Andrés Rodríguez-Pose

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: This paper analyses how the formation of collaboration networks affects firm-level innovation by applying the ‘Goldilocks principle’. The ‘Goldilocks principle’ of optimal distance in innovation networks postulates that the best firm-level innovation results are achieved when the partners involved in the network are located at the ‘right’ distance, i.e. ‘not too close and not too far’ from one another, across non-geographical proximity dimensions. This principle is tested on a survey of 542 Norwegian firms conducted in 2013, containing information about firm-level innovation activities and key innovation partners. The results of the ordinal logit regression analysis substantiate the Goldilocks principle, as the most innovative firms are found among those that collaborate with partners at medium levels of proximity for all non-geographical dimensions. The analysis also underscores the importance of the presence of a substitution–innovation mechanism, with geographical distance problems being compensated by proximity in other dimensions as a driver of innovation, while there is no support for a potential overlap–innovation mechanism.

Keywords: proximities; innovation; collaboration; Goldilocks principle; Norway (search for similar items in EconPapers)
JEL-codes: J50 (search for similar items in EconPapers)
Date: 2016-08-17
New Economics Papers: this item is included in nep-cdm, nep-cse, nep-geo, nep-ino, nep-net, nep-sbm, nep-tid and nep-ure
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Citations: View citations in EconPapers (17)

Published in Industry and Innovation, 17, August, 2016, 23(6), pp. 465-487. ISSN: 1366-2716

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Related works:
Journal Article: Not too close, not too far: testing the Goldilocks principle of ‘optimal’ distance in innovation networks (2016)
Working Paper: Not too close, not too far: testing the Goldilocks principle of ‘optimal’ distance in innovation networks (2016)
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