Building a data‐driven circular supply chain hierarchical structure: Resource recovery implementation drives circular business strategy

• Published in: Business strategy and the environment Vol. 31; no. 5; pp. 2082 - 2106
• Main Authors: Tseng, Ming‐Lang, Ha, Hien Minh, Tran, Thi Phuong Thuy, Bui, Tat‐Dat, Chen, Chih‐Cheng, Lin, Chun‐Wei
• Format: Journal Article
• Language: English
• Published: Chichester Wiley Periodicals Inc 01.07.2022
• Subjects: Artificial intelligence; Attributes; Big Data; Business; circular business strategy; circular supply chain; Cluster analysis; Criteria; data‐driven analysis; Decision analysis; Decision making; Delphi method; Digitization; Entropy; Entropy (statistics); Industry 4.0 and digitalization; Intelligence; Life cycle analysis; Life cycle assessment; Life cycles; Machine learning; Plastics recycling; Qualitative analysis; Recovery; Recycling; Resource recovery; reverse supply chain; Structural hierarchy; Supply; Supply chains; Waste to energy; Weighting methods

The circular supply chain has recently received more attention as a relevant solution to effectively tackle environmental issues while simultaneously achieving resource recovery and circular business strategy benefits. This study builds a hierarchical circular supply chain structure from big data in...