Evaluation of the smart reverse logistics development scenarios using a novel MCDM model

Abstract

The purpose of this study was to select the most promising smart reverse logistics system development scenario which would serve as a guideline for the decision-making in the process of building sustainable systems of circular economy and closed supply chains. Four development scenarios are defined in the study and evaluated by the representatives of the main stakeholders in relation to a broad set of sub-criteria classified within the six main criteria. To solve the defined problem, a novel multi-criteria decision-making model, combining the Delphi, Analytical Network Process (ANP) and COmprehensive distance Based RAnking (COBRA) methods in the fuzzy environment, was developed. The application of the developed model resulted in selecting the scenario which most effectively balances the wide application of Industry 4.0 technologies and the necessary resources. The scenarios imply the integration of the most effective Industry 4.0 technologies, such as the Internet of Things, Automated guided vehicles, Autonomous Vehicles, Artificial Intelligence, Big Data and Data Mining, Blockchain, Cloud Computing and Electronic/Mobile marketplaces, and their most realistic applications. The widest possible application of Industry 4.0 technologies does not necessarily guarantee the most acceptable development scenario and the solution should be sought in the area of common interest of all stakeholders. • Smart reverse logistics is a prerequisite for sustainable supply chains. • The application of Industry 4.0 technologies makes reverse logistics smart. • Various scenarios of smart reverse logistics development can be defined. • The selection of the most probable scenarios is a MCDM problem. • Novel fuzzy DANP-COBRA method is developed in the paper for solving this problem.