Digital supply network design: A circular economy 4.0 decision-making system for real-world challenges

Tsolakis, Naoum, Harrington, Tomás Seosamh ORCID: and Singh Srai, Jagjit (2023) Digital supply network design: A circular economy 4.0 decision-making system for real-world challenges. Production Planning & Control, 34 (10). pp. 941-966. ISSN 0953-7287

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This research introduces the idea of ‘Circular Economy 4.0’ to reflect the emergence of ‘digitalised’ sustainable supply networks. While often characterised by enhanced productivity and resource/energy efficiency, current perspectives are largely descriptive with limited practical relevance. A hierarchical decision-making framework and a multi-level simulation modelling and optimisation technique are constructed to explore the interplay between Circular Supply Chains and Industry 4.0. The real-world case of blue-green algae as renewable feedstock–to derive value-added omega-3 oils and biofertilisers–is investigated to develop ‘Circular Economy 4.0’ perspectives. The emerging circular supply network utilises micro-factories (i.e., photobioreactors), continuous manufacturing technologies (i.e., piezoelectric transducers), and drone operations for feedstock availability monitoring. This study contributes to theory and practice by building on the limited empirical research exploring determinants of successful transitions in Circular Economy-Industry 4.0 network contexts. Four design principles are proposed that capture the interplay between digital technologies and network design configurations, e.g., centralised–semi-centralised–decentralised. Modelling is developed across macro-, meso-, and micro-levels of analysis. Results demonstrate significant gains in terms of resources utilisation and market dynamics, enabled by the adoption of digital operations in a circular economy context, with initial insights on the evolution of such networks.

Item Type: Article
Uncontrolled Keywords: circular economy,hierarchical decision-making framework,industry 4.0,multi-level simulation modelling and optimisation technique,sustainable supply network design and management,industrial and manufacturing engineering,computer science applications,strategy and management,management science and operations research,sdg 7 - affordable and clean energy,sdg 8 - decent work and economic growth,sdg 12 - responsible consumption and production ,/dk/atira/pure/subjectarea/asjc/2200/2209
Faculty \ School: Faculty of Social Sciences > Norwich Business School
UEA Research Groups: Faculty of Social Sciences > Research Groups > Innovation, Technology and Operations Management
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Depositing User: LivePure Connector
Date Deposited: 29 Apr 2020 00:03
Last Modified: 10 Jul 2023 09:30
DOI: 10.1080/09537287.2021.1980907


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