人工智能在运营管理和供应链管理中的应用:一个探索性案例研究

IF 6.1 3区管理学 Q1 ENGINEERING, INDUSTRIAL

Production Planning & Control Pub Date : 2021-04-01 DOI:10.1080/09537287.2021.1882690

P. Helo, Yuqiuge Hao

{"title":"人工智能在运营管理和供应链管理中的应用:一个探索性案例研究","authors":"P. Helo, Yuqiuge Hao","doi":"10.1080/09537287.2021.1882690","DOIUrl":null,"url":null,"abstract":"Abstract With the development and evolution of information technology, competition has become more and more intensive on a global scale. Many companies have forecast that the future of operation and supply chain management (SCM) may change dramatically, from planning, scheduling, optimisation, to transportation, with the presence of artificial intelligence (AI). People will be more and more interested in machine learning, AI, and other intelligent technologies, in terms of SCM. Within this context, this particular research study provides an overview of the concept of AI and SCM. It then focuses on timely and critical analysis of AI-driven supply chain research and applications. In this exploratory research, the emerging AI-based business models of different case companies are analysed. Their relevant AI solutions and related values to companies are also evaluated. As a result, this research identifies several areas of value creation for the application of AI in the supply chain. It also proposes an approach to designing business models for AI supply chain applications.","PeriodicalId":20627,"journal":{"name":"Production Planning & Control","volume":"73 1","pages":"1573 - 1590"},"PeriodicalIF":6.1000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"74","resultStr":"{\"title\":\"Artificial intelligence in operations management and supply chain management: an exploratory case study\",\"authors\":\"P. Helo, Yuqiuge Hao\",\"doi\":\"10.1080/09537287.2021.1882690\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract With the development and evolution of information technology, competition has become more and more intensive on a global scale. Many companies have forecast that the future of operation and supply chain management (SCM) may change dramatically, from planning, scheduling, optimisation, to transportation, with the presence of artificial intelligence (AI). People will be more and more interested in machine learning, AI, and other intelligent technologies, in terms of SCM. Within this context, this particular research study provides an overview of the concept of AI and SCM. It then focuses on timely and critical analysis of AI-driven supply chain research and applications. In this exploratory research, the emerging AI-based business models of different case companies are analysed. Their relevant AI solutions and related values to companies are also evaluated. As a result, this research identifies several areas of value creation for the application of AI in the supply chain. It also proposes an approach to designing business models for AI supply chain applications.\",\"PeriodicalId\":20627,\"journal\":{\"name\":\"Production Planning & Control\",\"volume\":\"73 1\",\"pages\":\"1573 - 1590\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2021-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"74\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Production Planning & Control\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1080/09537287.2021.1882690\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Production Planning & Control","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1080/09537287.2021.1882690","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}

引用次数: 74

摘要

随着信息技术的发展和演变，全球范围内的竞争越来越激烈。许多公司预测，随着人工智能(AI)的出现，运营和供应链管理(SCM)的未来可能会发生巨大变化，从计划、调度、优化到运输。在SCM方面，人们将对机器学习、人工智能和其他智能技术越来越感兴趣。在此背景下，本研究概述了人工智能和供应链管理的概念。然后，它专注于对人工智能驱动的供应链研究和应用进行及时和批判性的分析。在这一探索性研究中，分析了不同案例公司基于人工智能的新兴商业模式。他们的相关人工智能解决方案和对企业的相关价值也被评估。因此，本研究确定了人工智能在供应链中应用的几个价值创造领域。它还提出了一种为人工智能供应链应用设计商业模式的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Artificial intelligence in operations management and supply chain management: an exploratory case study

Abstract With the development and evolution of information technology, competition has become more and more intensive on a global scale. Many companies have forecast that the future of operation and supply chain management (SCM) may change dramatically, from planning, scheduling, optimisation, to transportation, with the presence of artificial intelligence (AI). People will be more and more interested in machine learning, AI, and other intelligent technologies, in terms of SCM. Within this context, this particular research study provides an overview of the concept of AI and SCM. It then focuses on timely and critical analysis of AI-driven supply chain research and applications. In this exploratory research, the emerging AI-based business models of different case companies are analysed. Their relevant AI solutions and related values to companies are also evaluated. As a result, this research identifies several areas of value creation for the application of AI in the supply chain. It also proposes an approach to designing business models for AI supply chain applications.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Production Planning & Control 管理科学-工程：工业

CiteScore

19.30

自引率

9.60%

发文量

审稿时长

6-12 weeks

期刊介绍： Production Planning & Control is an international journal that focuses on research papers concerning operations management across industries. It emphasizes research originating from industrial needs that can provide guidance to managers and future researchers. Papers accepted by "Production Planning & Control" should address emerging industrial needs, clearly outlining the nature of the industrial problem. Any suitable research methods may be employed, and each paper should justify the method used. Case studies illustrating international significance are encouraged. Authors are encouraged to relate their work to existing knowledge in the field, particularly regarding its implications for management practice and future research agendas.