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

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

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)3749-3768
Number of pages20
JournalBusiness Strategy and the Environment
Volume33
Issue number5
Early online date11 Jan 2024
DOIs
Publication statusPublished - Jul 2024

Keywords

  • AI-enabled drone
  • Industry 4.0
  • innovation resistance theory
  • mixed-method approach
  • process audit
  • theory of consumption values

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