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

IF 8.3 1区工程技术 Q1 ECONOMICS

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2024-09-11 DOI:10.1016/j.tre.2024.103761

Lixu Li , Wenwen Zhu , Lujie Chen , Yaoqi Liu

{"title":"Generative AI usage and sustainable supply chain performance: A practice-based view","authors":"Lixu Li , Wenwen Zhu , Lujie Chen , Yaoqi Liu","doi":"10.1016/j.tre.2024.103761","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"192 ","pages":"Article 103761"},"PeriodicalIF":8.3000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part E-Logistics and Transportation Review","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1366554524003521","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}

引用次数: 0

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.

查看原文本刊更多论文

生成式人工智能的使用与可持续供应链绩效：基于实践的观点

生成式人工智能的出现为应对可持续供应链管理（SCM）方面的挑战提供了众多潜在解决方案。然而，并非所有企业都能有效掌握生成式人工智能的使用方法并实现潜在效益。为了解决这一难题，我们采用基于实践的观点（PBV）来研究人工智能的使用对可持续供应链绩效（SSCP）的影响。通过分析来自 213 家中国制造企业的调查数据，我们发现人工智能的使用与可持续供应链绩效之间存在正相关关系。此外，两类可持续供应链实践--绿色供应链协作（GSCC）和循环经济实施（CEI）--成为连接这一关系的序列中介。我们阐明了生成性人工智能的使用与 SSCP 之间联系的潜在中介机制，为现有的人工智能支持的供应链管理研究做出了贡献。我们还为企业适应全球供应链管理新规范提供了深刻的启示。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Transportation Research Part E-Logistics and Transportation Review 工程技术-工程：土木

CiteScore

16.20

自引率

16.00%

发文量

285

审稿时长

62 days

期刊介绍： Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management. Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.