- Title
- Adoption of AI in response to COVID-19—a configurational perspective
- Creator
- Mi, Lili; Liu, Wei; Yuan, Yu-Hsi; Shao, Xuefeng; Zhong, Yifan
- Relation
- Personal and Ubiquitous Computing Vol. 27, Issue 7 February 2023, p. 1455-1467
- Publisher Link
- http://dx.doi.org/10.1007/s00779-023-01711-6
- Publisher
- Springer
- Resource Type
- journal article
- Date
- 2023
- 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.
- Subject
- artifical intelligence; technology-organization-environment framework; fuzzy-set qualitative comparative analysis; strategic responses to COVID-19; SDG 3; SDG 17; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1484875
- Identifier
- uon:51425
- Identifier
- ISSN:1617-4909
- Language
- eng
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