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Cultivating competitive advantage for Chinese SMEs via big data analytics: The mediating role of data-driven innovation and antecedents of data governance and data-driven culture

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  • Song Rixin
  • Ramayah
  • Ma Xinrui

Abstract

This study explores how small and medium-sized enterprises (SMEs) can leverage big data analytics (BDA) to gain competitive advantage (CA), highlighting the mediating role of data-driven innovation (DDI) and the foundational importance of data governance (DG) and data-driven culture (DDC). Despite the transformative potential of BDA, SMEs often struggle to translate data insights into competitive outcomes due to inadequate governance, cultural barriers, and a lack of clarity on how to operationalize analytics through innovation. Drawing on the resource-based view (RBV) and dynamic capability view (DCV), this study adopts a quantitative approach and analyzes survey data from 287 Chinese SMEs using partial least squares structural equation modeling (PLS-SEM). The results show that DG and DDC significantly enhance BDA, which directly improves CA and strongly drives DDI. DDI further mediates 61% of the total effect of BDA on CA, highlighting its key role in translating data insights into market innovation. The study advances the theoretical framework by positioning DG and DDC as valuable, scarce, inimitable and non-substitutable (VRIN) resources and DDI as a dynamic “access” mechanism. Practical insights urge SMEs to prioritize governance protocols, cultural alignment, and innovation channels to bridge the gap between analytical and competitive outcomes. Limitations include geographic focus and cross-sectional design, prompting future longitudinal and cross-industry investigations. This study provides a roadmap for SMEs to leverage data-driven strategies in turbulent markets.

Suggested Citation

  • Song Rixin & Ramayah & Ma Xinrui, 2025. "Cultivating competitive advantage for Chinese SMEs via big data analytics: The mediating role of data-driven innovation and antecedents of data governance and data-driven culture," PLOS ONE, Public Library of Science, vol. 20(12), pages 1-21, December.
    • Handle: RePEc:plo:pone00:0337324
    DOI: 10.1371/journal.pone.0337324
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    References listed on IDEAS

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    1. JAHAN Sakila Akter & SAZU Mesbaul Haque, 2022. "Innovation Management: Is Big Data Necessarily Better Data?," Management of Sustainable Development, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 14(2), pages 27-33, December.
    2. Antonio Cimino & Vincenzo Corvello & Ciro Troise & Asha Thomas & Mario Tani, 2025. "Artificial Intelligence Adoption for Sustainable Growth in SMEs: An Extended Dynamic Capability Framework," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 32(5), pages 6120-6138, September.
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