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Role of big data analytics capabilities to improve sustainable competitive advantage of MSME service firms during COVID-19 – A multi-theoretical approach

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  • Behl, Abhishek
  • Gaur, Jighyasu
  • Pereira, Vijay
  • Yadav, Rambalak
  • Laker, Benjamin

Abstract

The extant literature suggests that digital technologies (big data analytics, artificial intelligence, blockchain) help firms gain a competitive advantage. However, the studies do not focus on the micro, small and medium enterprises (MSME) sector. Moreover, MSMEs face various challenges, including significant supply chain disruption due to the COVID-19 pandemic. Hence, there was an urgent requirement to shift to digital technologies to survive during this difficult time. In the context of MSME, various positive changes are discussed in the recent literature. However, a dearth of studies discusses the role of big data analytics capabilities (BDAC) to gain sustainable competitive advantage (SCA). Our study aims to fill this gap and answer this question – How do BDAC help MSMEs gain SCA? To understand the phenomenon, we receive theoretical support from organizational information processing theory (OIPT) and institutional theory (IT). We develop a conceptual framework that links BDAC and SCA through supply chain coordination, swift trust, and supply chain risk. Additionally, the age and size of the firm are used as control variables. The data is collected from Indian service sector employees of MSMEs, resulting in 497 usable responses. We use PLS-SEM using Warp PLS 7.0 to test the hypotheses. A critical finding is that the BDAC indirectly impacts the SCA. Finally, the other findings, limitations, and scope for future research are discussed.

Suggested Citation

  • Behl, Abhishek & Gaur, Jighyasu & Pereira, Vijay & Yadav, Rambalak & Laker, Benjamin, 2022. "Role of big data analytics capabilities to improve sustainable competitive advantage of MSME service firms during COVID-19 – A multi-theoretical approach," Journal of Business Research, Elsevier, vol. 148(C), pages 378-389.
    • Handle: RePEc:eee:jbrese:v:148:y:2022:i:c:p:378-389
    DOI: 10.1016/j.jbusres.2022.05.009
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