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Mapping pathways to responsible innovation: Configurations of digital economy, effectuation, and firm size in SMEs—A fuzzy set qualitative comparative analysis

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  • He, Liangxing
  • Zheng, Jianwen
  • Zhao, Meijuan
  • Li, Teng

Abstract

Digital technology has indubitably brought significant benefits, but has also triggered a series of social problems. Consequently, responsible innovation (RI) is essential to address these social concerns, and exploring mechanisms for corporations to achieve RI in the digital economy is urgently required. This study investigates the assessment of RI by 105 managers of small and medium-sized enterprises (SMEs) using a tracking survey and employs fuzzy set qualitative comparative analysis to uncover the various paths through which different principles of effectuation drive corporate RI. The findings indicate that digital-type, alliance-type, and larger firm exploratory-type contingent-driven configurations play equifinal roles in promoting corporate RI. While corporations remain contingent, they need to adopt different paths to achieve RI based on the digital economy environment and their own size. This study contributes to the literature on RI in three ways. First, it extends the research context of existing literature by incorporating the digital economy. Second, it provides new theoretical insights for RI by using different configurations to show the multiple paths corporations can take to achieve RI in the digital economy. Third, by using effectual principles as an intermediate path to bridge the digital economy and RI, this research expands the application scope of effectual principles.

Suggested Citation

  • He, Liangxing & Zheng, Jianwen & Zhao, Meijuan & Li, Teng, 2024. "Mapping pathways to responsible innovation: Configurations of digital economy, effectuation, and firm size in SMEs—A fuzzy set qualitative comparative analysis," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:tefoso:v:209:y:2024:i:c:s0040162524005766
    DOI: 10.1016/j.techfore.2024.123778
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