Unpacking complementarity in innovation ecosystems: A configurational analysis of knowledge transfer for achieving breakthrough innovation

Huan Wang, Leven J. Zheng, Justin Zuopeng Zhang, Ajay Kumar, Praveen Ranjan Srivastava

Research output: Contribution to journalArticlepeer-review

Abstract

To achieve breakthrough innovation, firms often need to acquire complementary knowledge from cross-industry actors in the innovation ecosystem, where unique and supermodular complementarities make knowledge exchange essential for value co-creation. This study examines the impact of the acquisition of knowledge transfer on breakthrough innovation by considering the complementors of unique and supermodular complementarity. We draw on data from 51 firms in the Chinese information and communication technology sector and apply the fuzzy set qualitative comparative analysis (fsQCA), in which we adopt factors on the complementor, relationship, and knowledge characteristics to determine the configurations that lead to firms' breakthrough innovation in the innovation ecosystem. The results show that several combinations of conditions drive firms' breakthrough innovation. Unique complementarities require conditions of explicit knowledge and cultural similarity within the realm of knowledge and complementors' characteristics. Conversely, supermodular complementarity underscores the importance of tacit knowledge, along with trust and tie strength within the characteristics of knowledge and relationships. Our study has practical and theoretical implications for complementors seeking breakthrough innovation in non-generic complementarities.

Original languageEnglish
Article number122974
JournalTechnological Forecasting and Social Change
Volume198
DOIs
Publication statusPublished - Jan 2024

Keywords

  • Breakthrough innovation
  • Complementarity
  • Innovation ecosystem
  • Knowledge transfer

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