Sustainable refrigeration technology selection: An innovative DEA-TOPSIS hybrid model

dc.contributor.authorArabi, Behrouz
dc.contributor.authorToloo, Mehdi
dc.contributor.authorYang, Zaoli
dc.contributor.authorZhang, Peihao
dc.contributor.authorXu, Bing
dc.date.accessioned2026-04-02T14:40:13Z
dc.date.available2026-04-02T14:40:13Z
dc.date.issued2024
dc.description.abstractThis study proposes a novel multiple criteria decision making (MCDM) framework aimed at selecting refrigeration technologies that are both carbon- and energy-efficient, aligning with the UK's net-zero policies and the UN's Sustainable Development Goals (SDGs). Addressing the challenge of a limited number of competing technologies and the need to incorporate diverse stakeholders' perspectives, we design a hybrid DEA-TOPSIS approach utilizing the Feasible Super-Efficiency Slacks-Based Algorithm (FSESBA). FSESBA proves invaluable, especially in scenarios involving super-efficiency or efficiency trend measurement, where addressing undesirable factors may lead to the well-known infeasibility problem. While we establish the theoretical soundness of the DEA-TOPSIS model, we validate the efficacy of our proposed approach through comparative analysis with conventional methods. Subsequently, we evaluate the choices of present and upcoming refrigeration technologies at a leading UK supermarket. Our findings reveal a shift from prevalent HFO-based technologies in 2020 to CO2-based technologies by 2050, attributed to their lower energy usage and GHG emissions. In addition, maintaining current refrigeration systems could contribute to achieving international and national targets to decrease F-Gas refrigerant usage, although net-zero targets will remain out of reach. In summary, our research findings underscore the potential of the introduced model to reinforce the adoption of novel refrigeration system technology, offering valuable support for the UK SDGs taskforces and net-zero policy formulation.
dc.description.firstpageart. no. 103780
dc.description.sourceWeb of Science
dc.description.volume158
dc.identifier.citationEnvironmental Science & Policy. 2024, vol. 158, art. no. 103780.
dc.identifier.doi10.1016/j.envsci.2024.103780
dc.identifier.issn1462-9011
dc.identifier.issn1873-6416
dc.identifier.urihttp://hdl.handle.net/10084/158356
dc.identifier.wos001264062800001
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofseriesEnvironmental Science & Policy
dc.relation.urihttps://doi.org/10.1016/j.envsci.2024.103780
dc.rights© 2024 The Author(s). Published by Elsevier Ltd.
dc.rights.accessopenAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectsustainable Development Goals (SDGs)
dc.subjectdata envelopment analysis (DEA)
dc.subjectrefrigeration technology
dc.subjecttechnology selection
dc.subjectTOPSIS (technique for order of preference by similarity to ideal solution)
dc.subjectfeasible super-efficiency slacks-based algorithm (FSESBA)
dc.titleSustainable refrigeration technology selection: An innovative DEA-TOPSIS hybrid model
dc.typearticle
dc.type.statusPeer-reviewed
dc.type.versionpublishedVersion
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local.files.size2977186
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