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

  • Lixu Li
  • , Wenwen Zhu*
  • , Lujie Chen
  • , Yaoqi Liu
  • *Corresponding author for this work
  • Xi'an University of Technology
  • Guangdong University of Finance & Economics
  • MBS School of Business

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)

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.

Original languageEnglish
Article number103761
JournalTransportation Research Part E: Logistics and Transportation Review
Volume192
DOIs
Publication statusPublished - Dec 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • Circular economy implementation
  • Generative AI usage
  • Green supply chain collaboration
  • Practice-based view
  • Sustainable supply chain performance

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