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

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  • Fitjar, Rune Dahl
  • Huber, Franz
  • Rodríguez-Pose, Andrés

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.

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  • Fitjar, Rune Dahl & Huber, Franz & Rodríguez-Pose, Andrés, 2016. "Not too close, not too far: testing the Goldilocks principle of ‘optimal’ distance in innovation networks," LSE Research Online Documents on Economics 84304, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:84304
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    Cited by:

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    2. Kang, Meiling & Li, Yucheng & Zhao, Zhongkuang & Song, Min & Yi, Jun, 2023. "Travel costs and inter-city collaborative innovation: Evidence of high-speed railway in China," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 286-302.
    3. Maria Tsouri, 2022. "Knowledge networks and strong tie creation: the role of relative network position," Journal of Geographical Systems, Springer, vol. 24(1), pages 95-114, January.
    4. Godlewska Malgorzata & Mackiewicz Marta, 2023. "Local context of local government participation in the innovation networks: Evidence from Poland," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 59(3), pages 243-263, September.
    5. Utku Ali Rıza Alpaydın & Rune Dahl Fitjar, 2021. "Proximity across the distant worlds of university–industry collaborations," Papers in Regional Science, Wiley Blackwell, vol. 100(3), pages 689-711, June.
    6. Susanne Hinzmann & Uwe Cantner & Holger Graf, 2019. "The role of geographical proximity for project performance: evidence from the German Leading-Edge Cluster Competition," The Journal of Technology Transfer, Springer, vol. 44(6), pages 1744-1783, December.
    7. Marte C.W. Solheim & Ron Boschma & Sverre Herstad, 2018. "Related variety, unrelated variety and the novelty content of firm innovation in urban and non-urban locations," Papers in Evolutionary Economic Geography (PEEG) 1836, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Oct 2018.
    8. Frank Crowley & Declan Jordan, 2022. "Do local start-ups and knowledge spillovers matter for firm-level R&D investment?," Urban Studies, Urban Studies Journal Limited, vol. 59(5), pages 1085-1102, April.
    9. Hilda Bø Lyng & Eric Christian Brun, 2018. "Knowledge Transition: A Conceptual Model of Knowledge Transfer for Cross-Industry Innovation," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(05), pages 1-23, October.
    10. Lopolito, Antonio & Falcone, Pasquale Marcello & Sica, Edgardo, 2022. "The role of proximity in sustainability transitions: A technological niche evolution analysis," Research Policy, Elsevier, vol. 51(3).
    11. den Hamer, Pieter & Frenken, Koen, 2021. "A network-based model of exploration and exploitation," Journal of Business Research, Elsevier, vol. 129(C), pages 589-599.
    12. Blanca L. Delgado-Márquez & Nuria E. Hurtado-Torres & Luis E. Pedauga & Eulogio Cordón-Pozo, 2018. "A network view of innovation performance for multinational corporation subsidiaries," Regional Studies, Taylor & Francis Journals, vol. 52(1), pages 47-67, January.
    13. Grzegorz Micek, 2019. "Geographical Proximity Paradox Revisited: The Case of IT Service SMEs in Poland," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
    14. MaÅ‚gorzata Runiewicz-Wardyn, 2020. "The role proximity plays in university-driven social networks. The case of the US and EU life-science clusters," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 16(3), pages 167-196.
    15. Tsouri, Maria & Hansen, Teis & Hanson, Jens & Steen, Markus, 2022. "Knowledge recombination for emerging technological innovations: The case of green shipping," Technovation, Elsevier, vol. 114(C).
    16. Viktor Květoň & Josef Novotný & Jiří Blažek & David Marek, 2022. "The role of geographic and cognitive proximity in knowledge networks: The case of joint R&D projects," Papers in Regional Science, Wiley Blackwell, vol. 101(2), pages 351-372, April.
    17. Anna Maria Lis, 2020. "Development of proximity in cluster organizations," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(2), pages 116-132, December.
    18. Hilda Bø Lyng & Eric Christian Brun, 2020. "Innovating with Strangers; Managing Knowledge Barriers Across Distances in Cross-Industry Innovation," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-33, February.
    19. Lo, Jade Y. & Li, Haiyang, 2018. "In the eyes of the beholder: The effect of participant diversity on perceived merits of collaborative innovations," Research Policy, Elsevier, vol. 47(7), pages 1229-1242.
    20. Wallin, Tina, 2017. "An empirical study of firms’ absorptive capacity and export diversification," Working Paper Series in Economics and Institutions of Innovation 452, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.

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    Keywords

    proximities; innovation; collaboration; Goldilocks principle; Norway;
    All these keywords.

    JEL classification:

    • J50 - Labor and Demographic Economics - - Labor-Management Relations, Trade Unions, and Collective Bargaining - - - General

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