Cross-functional group decision making with heterogeneous cooperation for digital transformation in supply chain resilience

IF 7.2 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Applied Soft Computing Pub Date : 2024-11-12 DOI:10.1016/j.asoc.2024.112463

Ming Tang , Huchang Liao

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引用次数: 0

Abstract

Supply chain resilience plays a critical role in gaining competitive advantages for companies. The resilience of supply chains can be achieved by leveraging emerging digital technologies to realize digital transformation. It is necessary to select an appropriate digitalization technology under such background. The wide-spanning of digital transformation and technology selection needs cross-functional integration of various expertise. However, in the process of making decisions by leveraging expert wisdom, differences in experts’ willingness to cooperate lead to difficulties in reaching a consensus. The existing literature fails to incorporate both non-cooperation and proactive-cooperation into the consensus reaching process. Thus, in this study, we introduce a cross-functional multi-attribute group decision making model for digitalization technology selection. To manage potential non-cooperative behaviors in the group consensus reaching process, the proposed model allows experts to have proactive cooperation, i.e., making more contributions than recommended feedback suggestions provided by the moderator. Proactive cooperation can make up for the loss caused by the non-cooperative behaviors of experts. A knowledge mining method is proposed to mine academic and practical preferences for attributes. Two consensus mechanisms are put forward for the meso decision-making process in functional teams and the macro decision-making process in the whole group, respectively. An illustrative example regarding the technology selection in shipbuilding industry is provided to verify the applicability of our model. Numerical experiments suggest that our model will improve the efficiency of consensus reaching process.

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跨职能小组决策与异质合作，促进供应链复原力的数字化转型

供应链的弹性在企业获得竞争优势方面发挥着至关重要的作用。利用新兴的数字化技术实现数字化转型，可以实现供应链的弹性。在此背景下，有必要选择合适的数字化技术。数字化转型和技术选择的跨度很大，需要跨部门整合各种专业知识。然而，在利用专家智慧进行决策的过程中，专家合作意愿的差异导致难以达成共识。现有文献没有将非合作和主动合作纳入共识达成过程。因此，在本研究中，我们引入了一个用于数字化技术选择的跨职能多属性群体决策模型。为了管理小组达成共识过程中潜在的非合作行为，所提出的模型允许专家进行主动合作，即做出比主持人推荐的反馈建议更多的贡献。主动合作可以弥补专家不合作行为造成的损失。提出了一种知识挖掘方法来挖掘学术和实践属性偏好。针对职能团队的中观决策过程和整个小组的宏观决策过程，分别提出了两种共识机制。为验证模型的适用性，提供了一个有关造船业技术选择的示例。数值实验表明，我们的模型可以提高达成共识过程的效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Soft Computing 工程技术-计算机：跨学科应用

CiteScore

15.80

自引率

6.90%

发文量

874

审稿时长

10.9 months

期刊介绍： Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities. Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.