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Adoption of AI in response to COVID-19—a configurational perspective
Although the importance of artificial intelligence (AI) has often been highlighted in strategic agility and decision outcomes, whether it helps firms strengthen their competitiveness and the means firms use to achieve such competitiveness are still under-researched. Our research thus joins the recen...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer London
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9904263/ https://www.ncbi.nlm.nih.gov/pubmed/36778529 http://dx.doi.org/10.1007/s00779-023-01711-6 |
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author | Mi, Lili Liu, Wei Yuan, Yu-Hsi Shao, Xuefeng Zhong, Yifan |
author_facet | Mi, Lili Liu, Wei Yuan, Yu-Hsi Shao, Xuefeng Zhong, Yifan |
author_sort | Mi, Lili |
collection | PubMed |
description | Although the importance of artificial intelligence (AI) has often been highlighted in strategic agility and decision outcomes, whether it helps firms strengthen their competitiveness and the means firms use to achieve such competitiveness are still under-researched. Our research thus joins the recent discussion on digitalization trends and strategic responses to COVID-19 to better understand how firms strengthen their competitiveness during such challenging times. Namely, this study incorporates the strategic responses to COVID-19 into the technology–organization–environment (TOE) framework by investigating the impacts of different configurations of TOE contexts and strategic responses on a firm’s competitive advantage. We used fuzzy-set qualitative comparative analysis to investigate how TOE contexts and strategic responses integrate into configurations and impact a firm’s competiveness. By applying a configurational approach with data from 514 exporting firms in China, we find a strong indication of the equifinality of different strategies, indicating that multiple strategic paths can be used to respond to crises. The adoption of AI, while important, is not sufficient to enhance a firm’s competitiveness. Our results stress the significance of data quality, organizational resources and capabilities, and digital business model innovation for AI adoption. We also identify successful strategic paths of AI adoption aversion and ambidextrous strategies. The findings have practical implications for firms seeking effective strategies to respond to future crises and sustain their competitive advantages. |
format | Online Article Text |
id | pubmed-9904263 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer London |
record_format | MEDLINE/PubMed |
spelling | pubmed-99042632023-02-07 Adoption of AI in response to COVID-19—a configurational perspective Mi, Lili Liu, Wei Yuan, Yu-Hsi Shao, Xuefeng Zhong, Yifan Pers Ubiquitous Comput Original Paper Although the importance of artificial intelligence (AI) has often been highlighted in strategic agility and decision outcomes, whether it helps firms strengthen their competitiveness and the means firms use to achieve such competitiveness are still under-researched. Our research thus joins the recent discussion on digitalization trends and strategic responses to COVID-19 to better understand how firms strengthen their competitiveness during such challenging times. Namely, this study incorporates the strategic responses to COVID-19 into the technology–organization–environment (TOE) framework by investigating the impacts of different configurations of TOE contexts and strategic responses on a firm’s competitive advantage. We used fuzzy-set qualitative comparative analysis to investigate how TOE contexts and strategic responses integrate into configurations and impact a firm’s competiveness. By applying a configurational approach with data from 514 exporting firms in China, we find a strong indication of the equifinality of different strategies, indicating that multiple strategic paths can be used to respond to crises. The adoption of AI, while important, is not sufficient to enhance a firm’s competitiveness. Our results stress the significance of data quality, organizational resources and capabilities, and digital business model innovation for AI adoption. We also identify successful strategic paths of AI adoption aversion and ambidextrous strategies. The findings have practical implications for firms seeking effective strategies to respond to future crises and sustain their competitive advantages. Springer London 2023-02-07 /pmc/articles/PMC9904263/ /pubmed/36778529 http://dx.doi.org/10.1007/s00779-023-01711-6 Text en © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Mi, Lili Liu, Wei Yuan, Yu-Hsi Shao, Xuefeng Zhong, Yifan Adoption of AI in response to COVID-19—a configurational perspective |
title | Adoption of AI in response to COVID-19—a configurational perspective |
title_full | Adoption of AI in response to COVID-19—a configurational perspective |
title_fullStr | Adoption of AI in response to COVID-19—a configurational perspective |
title_full_unstemmed | Adoption of AI in response to COVID-19—a configurational perspective |
title_short | Adoption of AI in response to COVID-19—a configurational perspective |
title_sort | adoption of ai in response to covid-19—a configurational perspective |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9904263/ https://www.ncbi.nlm.nih.gov/pubmed/36778529 http://dx.doi.org/10.1007/s00779-023-01711-6 |
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