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Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry
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Xiaoning Chen,
Huilan Chen,
Sebastian Elgueta
Journal of Decision Systems, Volume: 35, Issue: 1
Swansea University Author:
Guoqing Zhao
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© 2026 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License.
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DOI (Published version): 10.1080/12460125.2026.2675048
Abstract
Grounded in dynamic capability theory, this study investigates how generative artificial intelligence (GenAI) adoption enhances organizational resilience through a qualitative single-case design based on 18 semi-structured interviews conducted within a world-leading logistics company. Our findings p...
| Published in: | Journal of Decision Systems |
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| ISSN: | 1246-0125 2116-7052 |
| Published: |
Informa UK Limited
2026
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa71882 |
| Abstract: |
Grounded in dynamic capability theory, this study investigates how generative artificial intelligence (GenAI) adoption enhances organizational resilience through a qualitative single-case design based on 18 semi-structured interviews conducted within a world-leading logistics company. Our findings provide novel insights into how GenAI supports resilience across the disruption lifecycle. First, we identify nine key dimensions of organizational functioning strengthened by GenAI adoption, including enhanced risk prediction, early warning alerts, real-time movement tracking, performance analytics, and action recommendations during the preparation; the provision of feasible action plans during the response; and continuous monitoring against planned performance through to the recovery. Second, these functional benefits are translated into individual- and organizational-level capabilities. At the individual level, GenAI strengthens sensemaking, decision-making capability, and flexibility. At the organizational level, it enhances cross-functional synchronization, proactive preparedness, and resource optimization. The interaction and collective alignment of these multi-level capabilities enable organizations to strengthen their resilience. |
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| Keywords: |
Generative artificial intelligence, organizational resilience, logistics industry, single case study, dynamic capability theory |
| College: |
Faculty of Humanities and Social Sciences |
| Funders: |
Swansea University |
| Issue: |
1 |