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

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...

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Detalles Bibliográficos
Autores principales: Zamani, Efpraxia D., Griva, Anastasia, Conboy, Kieran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8889516/
https://www.ncbi.nlm.nih.gov/pubmed/35250366
http://dx.doi.org/10.1007/s10796-022-10255-8
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author Zamani, Efpraxia D.
Griva, Anastasia
Conboy, Kieran
author_facet Zamani, Efpraxia D.
Griva, Anastasia
Conboy, Kieran
author_sort Zamani, Efpraxia D.
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description 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.
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spelling pubmed-88895162022-03-02 Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure Zamani, Efpraxia D. Griva, Anastasia Conboy, Kieran Inf Syst Front Article 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. Springer US 2022-03-02 2022 /pmc/articles/PMC8889516/ /pubmed/35250366 http://dx.doi.org/10.1007/s10796-022-10255-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Zamani, Efpraxia D.
Griva, Anastasia
Conboy, Kieran
Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure
title Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure
title_full Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure
title_fullStr Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure
title_full_unstemmed Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure
title_short Using Business Analytics for SME Business Model Transformation under Pandemic Time Pressure
title_sort using business analytics for sme business model transformation under pandemic time pressure
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8889516/
https://www.ncbi.nlm.nih.gov/pubmed/35250366
http://dx.doi.org/10.1007/s10796-022-10255-8
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