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Generative AI usage and sustainable supply chain performance: A practice-based view

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  • Li, Lixu
  • Zhu, Wenwen
  • Chen, Lujie
  • Liu, Yaoqi

Abstract

The emergence of generative AI presents numerous potential solutions to address challenges in sustainable supply chain management (SCM). However, not all firms can effectively master the methods of using generative AI and realize potential benefits. To address this dilemma, we adopt a practice-based view (PBV) to examine generative AI usage’s effect on sustainable supply chain performance (SSCP). Analyzing survey data from 213 Chinese manufacturing firms, we identify a positive relationship between generative AI usage and SSCP. Moreover, two types of sustainable supply chain practices—green supply chain collaboration (GSCC) and circular economy implementation (CEI)——emerge as serial mediators connecting this relationship. We contribute to existing AI-enabled SCM research by elucidating the potential mediation mechanisms underlying the link between generative AI usage and SSCP. We also offer insightful implications for firms adapting to new norms in global SCM.

Suggested Citation

  • Li, Lixu & Zhu, Wenwen & Chen, Lujie & Liu, Yaoqi, 2024. "Generative AI usage and sustainable supply chain performance: A practice-based view," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:transe:v:192:y:2024:i:c:s1366554524003521
    DOI: 10.1016/j.tre.2024.103761
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