Exploring enablers and inhibitors of AI‐enabled drones for manufacturing process audits: A mixed‐method approach

Shankar, Amit; Behl, Abhishek; Pereira, Vijay; Chavan, Meena; Chirico, Francesco

Abstract

The objective of this study is to explore the enablers and inhibitors of AI-enabled drone adoption for manufacturing process audit using a mixed-method design. A qualitative study was performed to explore the enablers and inhibitors. Further, based on the findings of the qualitative studies, a framework was proposed, and proposed hypotheses were examined using a survey-based study. The results indicated that function, environmental, and epistemic values are major enablers, whereas vulnerability and sunk cost barriers are major inhibitors to adoption intention. The initial trust and inertia were crucial mediators, and organizations' technological innovativeness played a crucial moderating role. This study enriches the literature on technological adoption for sustainability and helps audit service providers design strategies to enhance AI-enabled drone adoption for process audits.

Citation

Shankar, A., Behl, A., Pereira, V., Chavan, M., & Chirico, F. (2024). Exploring enablers and inhibitors of AI‐enabled drones for manufacturing process audits: A mixed‐method approach. Business Strategy and the Environment, https://doi.org/10.1002/bse.3679

• Journal Article Type: Article
• Acceptance Date: Dec 20, 2023
• Online Publication Date: Jan 11, 2024
• Publication Date: Jan 11, 2024
• Deposit Date: Jun 24, 2024
• Journal: Business Strategy and the Environment
• Print ISSN: 0964-4733
• Electronic ISSN: 1099-0836
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1002/bse.3679
• Keywords: AI-enabled drone, Industry 4.0, innovation resistance theory, mixed-method approach, processaudit, theory of consumpt
• Public URL: https://keele-repository.worktribe.com/output/855823
• Publisher URL: https://onlinelibrary.wiley.com/doi/10.1002/bse.3679