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

Zamani, Efpraxia D.; Griva, Anastasia; Conboy, Kieran

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.

Citation

Zamani, E. D., Griva, A., & Conboy, K. (2022). Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure. Information Systems Frontiers, 24(4), 1145-1166. https://doi.org/10.1007/s10796-022-10255-8

• Journal Article Type: Article
• Acceptance Date: Jan 30, 2022
• Online Publication Date: Mar 2, 2022
• Publication Date: 2022-08
• Deposit Date: Aug 16, 2023
• Journal: Information Systems Frontiers
• Print ISSN: 1387-3326
• Electronic ISSN: 1572-9419
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 24
• Issue: 4
• Pages: 1145-1166
• DOI: https://doi.org/10.1007/s10796-022-10255-8
• Keywords: Computer Networks and Communications; Information Systems; Theoretical Computer Science; Software
• Public URL: https://durham-repository.worktribe.com/output/1718915