Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure

Efpraxia D. Zamani (), Anastasia Griva () and Kieran Conboy ()
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Efpraxia D. Zamani: The University of Sheffield
Anastasia Griva: National University of Ireland Galway
Kieran Conboy: National University of Ireland Galway

Information Systems Frontiers, 2022, vol. 24, issue 4, No 6, 1145-1166

Abstract: Abstract The COVID-19 pandemic has had an unprecedented impact on many industry sectors, forcing many companies and particularly Small Medium Enterprises (SMEs) to fundamentally change their business models under extreme time pressure. While there are claims that technologies such as analytics can help such rapid transitions, little empirical research exists that shows if or how Business Analytics (BA) supports the adaptation or innovation of SMEs’ business models, let alone within the context of extreme time pressure and turbulence. This study addresses this gap through an exemplar case, where the SME actively used location-based business analytics for rapid business model adaptation and innovation during the Covid-19 crisis. The paper contributes to existing theory by providing a set of propositions, an agenda for future research and a guide for SMEs to assess and implement their own use of analytics for business model transformation.

Keywords: Busines analytics; Busines model innovation; Business model adaptation; Exogenous shock; SMEs; Dynamic capabilities (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10796-022-10255-8

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