AI-Driven Risk Management and Sustainable Decision-Making: Role of Perceived Environmental Responsibility

Author:

Khalid Jamshed1ORCID,Chuanmin Mi1ORCID,Altaf Fasiha2,Shafqat Muhammad Mobeen3,Khan Shahid Kalim45,Ashraf Muhammad Umair6

Affiliation:

1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210007, China

2. Department of Education, Government College Women University Sialkot, Sialkot 51260, Pakistan

3. Department of Business Administration, Government College Women University Sialkot, Sialkot 51260, Pakistan

4. Department of Business Administration, Thal University Bhakkar, Bhakkar 30000, Pakistan

5. Noon Business School, University of Sargodha, Sargodha 40162, Pakistan

6. Department of Sociology, Government College Women University Sialkot, Sialkot 51260, Pakistan

Abstract

Risk management driven by AI has the potential to play an important role in sustainable decision-making by offering predictive insights and scenario modeling capabilities. This proactive approach empowers top management to align informed decisions in accordance with sustainability goals while optimizing resource allocation and mitigating risks. While existing research examined the benefits of AI risk management, this study addresses the underexplored question of how AI risk management impacts sustainable decision-making, particularly when considering the mediating role of perceived environmental responsibility. A structural equation modeling (SEM) technique was employed on a dataset comprising 428 senior managers from the Pakistani construction sector. The results revealed that AI-driven risk management is highly relevant to sustainable decision-making. Further, perceived environmental responsibility was found to have a partial mediating effect. These results hold a significant promise for organizations seeking to integrate AI for environmental sustainability goals. The findings of the study enhance the understanding of how AI-driven risk management is a driving mechanism empowering decision-makers to make more sustained decisions in the construction sector.

Publisher

MDPI AG

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