Decision-Support Tools for Smart Transition to Circular Economy

Open Access
Authors
Publication date 2022
Host editors
  • T. Bondarouk
  • M.R. Olivas-Luján
Book title Smart Industry – Better Management
ISBN
  • 9781801177153
ISBN (electronic)
  • 9781801177122
  • 9781801177146
Series Advanced Series in Management
Pages (from-to) 151-169
Number of pages 19
Publisher United Kingdom: Emerald Publishing
Organisations
  • Faculty of Economics and Business (FEB) - Amsterdam Business School Research Institute (ABS-RI)
Abstract

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.


Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

Document type Chapter
Language English
Published at https://doi.org/10.1108/S1877-636120220000028010
Other links https://www.scopus.com/pages/publications/85133661546
Downloads
10-1108_S1877-636120220000028010 (Final published version)
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