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Exploring enablers and inhibitors of AI-enabled drones for manufacturing process audits: A mixed-method approach
Indian Institute of Management Visakhapatnam, Visakhapatnam, India.
Management Development Institute, Gurgaon, India.
NEOMA Business School, Campus Reims, Reims, France.
Macquarie University, Sydney, Australia.
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2024 (English)In: Business Strategy and the Environment, ISSN 0964-4733, E-ISSN 1099-0836, Vol. 33, no 5, p. 3749-3768Article in journal (Refereed) Published
Abstract [en]

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. 

Place, publisher, year, edition, pages
John Wiley & Sons, 2024. Vol. 33, no 5, p. 3749-3768
Keywords [en]
AI-enabled drone, Industry 4.0, innovation resistance theory, mixed-method approach, process audit, theory of consumption values
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hj:diva-63485DOI: 10.1002/bse.3679ISI: 001139927600001Scopus ID: 2-s2.0-85181975235Local ID: ;intsam;935524OAI: oai:DiVA.org:hj-63485DiVA, id: diva2:1834886
Available from: 2024-02-06 Created: 2024-02-06 Last updated: 2025-01-12Bibliographically approved

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Chirico, Francesco

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