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Impact of open innovation on industries and firms – A dynamic complex systems view

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  • Sengupta, Abhijit
  • Sena, Vania

Abstract

This paper develops novel behavioural models of open innovation (OI) for competitive markets and uses them to compare the impact of two types of OI frameworks – open source (OS) and patent-licensing (PL). The dynamic consequences of OI, for both OS and PL, are studied using a complex adaptive systems approach. We examine how profits, technology levels, R&D investment, technology adoption and market structure evolve under each and are impacted by underlying market characteristics. While both OS and PL are found to be equivalent in technology outcomes, OS comes with additional advantages to participating firms. Firms in the OS framework earn higher profit and are more efficient with their R&D investments. The industry is less concentrated under OS than under PL, except when market size is very large. In both frameworks, consumer preference for new product adoption has a significant impact. When consumers adopt newly introduced products relatively quickly, market concentration is the higher and overall rate of technological progress slower. These results contribute towards a deeper theoretical understanding of OI, opening new avenues for future research.

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  • Sengupta, Abhijit & Sena, Vania, 2020. "Impact of open innovation on industries and firms – A dynamic complex systems view," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    • Handle: RePEc:eee:tefoso:v:159:y:2020:i:c:s0040162520310258
    DOI: 10.1016/j.techfore.2020.120199
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    Cited by:

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    2. Alexander Kuan Daiy & Kao-Yi Shen & Jim-Yuh Huang & Tom Meng-Yen Lin, 2021. "A Hybrid MCDM Model for Evaluating Open Banking Business Partners," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    3. Wu, Haizhen & Han, Zhao'an & Zhou, Yong, 2021. "Optimal degree of openness in open innovation: A perspective from knowledge acquisition & knowledge leakage," Technology in Society, Elsevier, vol. 67(C).

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