Circular supply chain management with large scale group decision making in the big data era: The macro-micro model
Journal
Technological Forecasting and Social Change
Journal Volume
169
Date Issued
2021
Author(s)
Chen Y.
Abstract
Today, achieving the circular economy is a common goal for many enterprises and governments all around the world. In the big data era, decision making is well-supported and enhanced by a massive amount of data. In particular, large scale group decision making (LSGDM), which refers to the case in which a lot of decision makers join the decision making process, has emerged. Social network analyses are known to be relevant to LSGDM. In this paper, we examine the literature on LSGDM and highlight the current methodological advances in the area. We review the works focusing on applications of LSGDM. We study how big data can be used in circular supply chains. Based on the reviewed studies, we further construct the three-stage LSGDM CSCM micro framework as well as the five-step LSGDM CSCM macro framework (with a feedback loop) and form the Macro-Micro Model. We discuss how the Macro-Micro Model can help to support circular supply chain management (CSCM). We propose future research directions and areas. This paper contributes by being the first study uncovering systematically how LSGDM can be applied to support CSCM in the big data era using the Macro-Micro Model. ? 2021 Elsevier Inc.
Subjects
Circular supply chains; Frameworks; Large scale group decision making (LSGDM); Literature review; Macro-micro model; Research agenda
Other Subjects
Big data; Supply chain management; Chain management; Circular supply chain; Framework; Group Decision Making; Large scale group decision making; Large-scale group; Literature reviews; Macro micro; Macro-micro model; Research agenda; Decision making; decision making; literature review; numerical model; research work; supply chain management; technological change; technological development
Publisher
Elsevier Inc.
Type
journal article
