Shafique, Imran, Khan, Tamania, Rana, Sudhir and Ferraris, Alberto
ORCID: https://orcid.org/0000-0003-3125-1710
(2026)
The role of AI-powered big data analytics in enhancing firm ESG performance : mediating and moderating effects.
Behaviour and Information Technology
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DOI 10.1080/0144929X.2026.2641606
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Official URL: https://doi.org/10.1080/0144929X.2026.2641606
Abstract
This study addresses a key debate among leaders, policymakers, and researchers regarding the extent to which AI-powered big data analytics capabilities effectively support and enhance environmental, social and governance performance. We investigate the underlying mechanism and boundary condition through a moderated mediation model. The model tests the relationships between AI-powered big data analytics capabilities, AI-enabled green learning capability, responsible leadership and environmental, social and governance performance. Data were collected from senior-level managers in United Arab Emirates hospitality organisations using a survey questionnaire. Hypotheses were tested using Hayes’ PROCESS macro. The results reveal that AI-powered big data analytics capabilities have a significant positive impact on firm environmental, social and governance performance. Moreover, AI-enabled green learning capability mediates this primary relationship. Furthermore, responsible leadership positively moderates the link between AI-powered big data analytics capabilities and AI-enabled green learning capability. A significant moderated mediation effect was identified, demonstrating that the capabilities’ indirect influence on environmental, social and governance performance through green learning is strongest when responsible leadership is high. These findings highlight the strategic necessity of integrating advanced analytical capabilities with learning initiatives and fostering responsible leadership to maximise positive environmental, social and governance outcomes.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | AI-powered big data analytics capabilities; AI-enabled green learning capability; Responsible leadership; ESG performance |
| Divisions: | Corvinus Institute for Advanced Studies (CIAS) |
| Subjects: | Automatizálás, gépesítés Ecology Environmental economics Computer science |
| DOI: | 10.1080/0144929X.2026.2641606 |
| ID Code: | 12653 |
| Deposited By: | MTMT SWORD |
| Deposited On: | 25 Mar 2026 10:30 |
| Last Modified: | 25 Mar 2026 10:30 |
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