B. Andres , P. Urze , E. Araujo , L.M. Camarinha-Matos
{"title":"Artificial intelligence use in collaborative network processes","authors":"B. Andres , P. Urze , E. Araujo , L.M. Camarinha-Matos","doi":"10.1016/j.jii.2025.100883","DOIUrl":null,"url":null,"abstract":"<div><div>This paper reviews the literature to analyse the use of artificial intelligence (AI) in collaborative processes among supply chain (SC) partners, thereby forming a collaborative network (CN). Given the growth of AI and its limited exploration in many business strategies, especially when collaboration among SC partners’ is established, this paper focuses on defining the lines of research and application of AI in CN processes, by presenting insights into how AI can improve the resilience and the antifragility. It examines the integration of AI in CN processes from the following perspectives: (i) the collaborative processes addressed among the CN partners, (ii) the decision-making level of the collaborative processes performed, (iii) the SC partners involved in the collaboration; (iv) the technologies combined with AI to support CN processes; (v) the programming languages implemented to develop AI algorithms; (vi) the SC sectors in which AI is mainly implemented to perform collaborative processes; and (vii) the potential of implementing AI in CN processes, in an increasingly turbulent and disruptive business world. The study focuses on SC in various sectors, including food, transport, logistics, manufacturing, healthcare or electronics, among others. In addition, the review provides a comprehensive understanding of the interplay between collaborative processes and AI-driven advances, identifying the technologies that can merge with AI to support CN processes. The results have enabled the development of a conceptual framework for AI use collaborative processes and outline the benefits, risks and challenges associated with the use of AI in CN, while proposing future research directions in this area.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"47 ","pages":"Article 100883"},"PeriodicalIF":10.4000,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Industrial Information Integration","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2452414X25001062","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper reviews the literature to analyse the use of artificial intelligence (AI) in collaborative processes among supply chain (SC) partners, thereby forming a collaborative network (CN). Given the growth of AI and its limited exploration in many business strategies, especially when collaboration among SC partners’ is established, this paper focuses on defining the lines of research and application of AI in CN processes, by presenting insights into how AI can improve the resilience and the antifragility. It examines the integration of AI in CN processes from the following perspectives: (i) the collaborative processes addressed among the CN partners, (ii) the decision-making level of the collaborative processes performed, (iii) the SC partners involved in the collaboration; (iv) the technologies combined with AI to support CN processes; (v) the programming languages implemented to develop AI algorithms; (vi) the SC sectors in which AI is mainly implemented to perform collaborative processes; and (vii) the potential of implementing AI in CN processes, in an increasingly turbulent and disruptive business world. The study focuses on SC in various sectors, including food, transport, logistics, manufacturing, healthcare or electronics, among others. In addition, the review provides a comprehensive understanding of the interplay between collaborative processes and AI-driven advances, identifying the technologies that can merge with AI to support CN processes. The results have enabled the development of a conceptual framework for AI use collaborative processes and outline the benefits, risks and challenges associated with the use of AI in CN, while proposing future research directions in this area.
期刊介绍:
The Journal of Industrial Information Integration focuses on the industry's transition towards industrial integration and informatization, covering not only hardware and software but also information integration. It serves as a platform for promoting advances in industrial information integration, addressing challenges, issues, and solutions in an interdisciplinary forum for researchers, practitioners, and policy makers.
The Journal of Industrial Information Integration welcomes papers on foundational, technical, and practical aspects of industrial information integration, emphasizing the complex and cross-disciplinary topics that arise in industrial integration. Techniques from mathematical science, computer science, computer engineering, electrical and electronic engineering, manufacturing engineering, and engineering management are crucial in this context.