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What drives or derails AI in supply chains? An investigation from the behavioral reasoning theory (BRT) perspective
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DOI：10.1007/s12063-026-00609-9.png)
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Abstract
En 中文
The exponential growth of Artificial Intelligence (AI) technologies offers significant transformative opportunities for modern supply chains to address disruptions, but its adoption remains difficult, particularly in developing countries. The present study investigates the patterns influencing AI adoption for supply chain management using the Behavioral Reasoning Theory (BRT). It examines how values, reasons for and against, attitudes, and intentions influence organizational decision-making regarding AI adoption in SCM. The presented research collected data from 392 respondents across various manufacturing sectors in India. The study uses Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess a conceptual model underpinning the research and to test eight direct and four mediation hypotheses. The results indicate that ‘reasons for’ AI adoption, including economic, social, and environmental benefits, significantly impact attitudes and intentions. Besides this, ‘reasons against’ do not significantly affect intention, indicating that perceived benefits outweigh concerns. In addition, values significantly shape attitudes and intentions, directly or indirectly through mediating effects. The results highlight the crucial role of contextual and psychological factors in the adoption of AI for supply chain management (SCM). The paper contributes to the rapid adoption of AI by extending the application of BRT in technology-driven SCM. From a practical standpoint, the paper provides managers and policymakers with crucial insights into perspectives that may facilitate or hinder the effective adoption of digital transformation in existing supply chains.
Keywords:
Artificial intelligence
Supply chain management
Behavioral reasoning theory
Technology adoption
PLS-SEM
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5.3
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46
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0
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