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A comprehensive minimum cost consensus model for large scale group decision making for circular economy measurement

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  • Rodríguez, Rosa M.
  • Labella, Álvaro
  • Nuñez-Cacho, Pedro
  • Molina-Moreno, Valentin
  • Martínez, Luis

Abstract

Since the first report on the Circular Economy (CE) appeared in 2013, there has been an explosion of interest in the subject by society and the business world. Thus, a base of academic literature has been developed, seeking the establishment of principles that serve as a theoretical foundation for the concept of CE. Governments demand to know how organizations are evolving in the transition towards the new production model. However, despite the efforts of researchers and companies to develop effective measurement systems, it is not easy to decide which aspects to measure, nor to determine the degree of intensity in which an organization implements the CE model. The measurement proposals combine different methodologies that are costly and time consuming procedures. We propose a comprehensive minimum cost consensus model for large scale group decision making, in which the initial experts’ preferences are automatically adjusted to obtain the measurement and cost of indicators, so that they might agree on the measurements implemented. The main aim of this research is not only to provide a quick, useful and correct method for measuring the CE, but also to show its correctness, advantages and usefulness by comparing its performance with a real case.

Suggested Citation

  • Rodríguez, Rosa M. & Labella, Álvaro & Nuñez-Cacho, Pedro & Molina-Moreno, Valentin & Martínez, Luis, 2022. "A comprehensive minimum cost consensus model for large scale group decision making for circular economy measurement," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
  • Handle: RePEc:eee:tefoso:v:175:y:2022:i:c:s0040162521008222
    DOI: 10.1016/j.techfore.2021.121391
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    References listed on IDEAS

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    1. Modgil, Sachin & Gupta, Shivam & Sivarajah, Uthayasankar & Bhushan, Bharat, 2021. "Big data-enabled large-scale group decision making for circular economy: An emerging market context," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    2. Patrik Eklund & Agnieszka Rusinowska & Harrie Swart, 2008. "A consensus model of political decision-making," Annals of Operations Research, Springer, vol. 158(1), pages 5-20, February.
    3. Pedro Núñez-Cacho & Valentín Molina-Moreno & Francisco A. Corpas-Iglesias & Francisco J. Cortés-García, 2018. "Family Businesses Transitioning to a Circular Economy Model: The Case of “Mercadona”," Sustainability, MDPI, vol. 10(2), pages 1-19, February.
    4. Gong, Zaiwu & Zhang, Huanhuan & Forrest, Jeffrey & Li, Lianshui & Xu, Xiaoxia, 2015. "Two consensus models based on the minimum cost and maximum return regarding either all individuals or one individual," European Journal of Operational Research, Elsevier, vol. 240(1), pages 183-192.
    5. Stephen Polasky & Gretchen Daily, 2021. "An Introduction to the Economics of Natural Capital," Review of Environmental Economics and Policy, University of Chicago Press, vol. 15(1), pages 87-94.
    6. Pei Wang & Xuanhua Xu & Shuai Huang, 2019. "An Improved Consensus-Based Model for Large Group Decision Making Problems Considering Experts with Linguistic Weighted Information," Group Decision and Negotiation, Springer, vol. 28(3), pages 619-640, June.
    7. Sabina Scarpellini & Pilar Portillo-Tarragona & Alfonso Aranda-Usón & Fernando Llena-Macarulla, 2019. "Definition and measurement of the circular economy’s regional impact," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 62(13), pages 2211-2237, November.
    8. Cheng, Dong & Zhou, Zhili & Cheng, Faxin & Zhou, Yanfang & Xie, Yujing, 2018. "Modeling the minimum cost consensus problem in an asymmetric costs context," European Journal of Operational Research, Elsevier, vol. 270(3), pages 1122-1137.
    9. Hayes, Samantha & Desha, Cheryl & Baumeister, Dayna, 2020. "Learning from nature – Biomimicry innovation to support infrastructure sustainability and resilience," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    10. Nasir, Mohammed Haneef Abdul & Genovese, Andrea & Acquaye, Adolf A. & Koh, S.C.L. & Yamoah, Fred, 2017. "Comparing linear and circular supply chains: A case study from the construction industry," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 443-457.
    11. Pedro Núñez-Cacho & Juan Carlos Leyva-Díaz & Jorge Sánchez-Molina & Rody Van der Gun, 2020. "Plastics and sustainable purchase decisions in a circular economy: The case of Dutch food industry," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-16, September.
    12. Eklund, Patrik & Rusinowska, Agnieszka & De Swart, Harrie, 2007. "Consensus reaching in committees," European Journal of Operational Research, Elsevier, vol. 178(1), pages 185-193, April.
    13. Andreas Mayer & Willi Haas & Dominik Wiedenhofer & Fridolin Krausmann & Philip Nuss & Gian Andrea Blengini, 2019. "Measuring Progress towards a Circular Economy: A Monitoring Framework for Economy‐wide Material Loop Closing in the EU28," Journal of Industrial Ecology, Yale University, vol. 23(1), pages 62-76, February.
    14. Mateusz Lewandowski, 2016. "Designing the Business Models for Circular Economy—Towards the Conceptual Framework," Sustainability, MDPI, vol. 8(1), pages 1-28, January.
    15. Witjes, Sjors & Lozano, Rodrigo, 2016. "Towards a more Circular Economy: Proposing a framework linking sustainable public procurement and sustainable business models," Resources, Conservation & Recycling, Elsevier, vol. 112(C), pages 37-44.
    16. Labella, Álvaro & Liu, Hongbin & Rodríguez, Rosa M. & Martínez, Luis, 2020. "A Cost Consensus Metric for Consensus Reaching Processes based on a comprehensive minimum cost model," European Journal of Operational Research, Elsevier, vol. 281(2), pages 316-331.
    17. Guzzo, Daniel & Rodrigues, Vinicius Picanço & Mascarenhas, Janaina, 2021. "A systems representation of the Circular Economy: Transition scenarios in the electrical and electronic equipment (EEE) industry," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    18. Pedro Nuñez-Cacho & Jaroslaw Górecki & Valentín Molina-Moreno & Francisco A. Corpas-Iglesias, 2018. "What Gets Measured, Gets Done: Development of a Circular Economy Measurement Scale for Building Industry," Sustainability, MDPI, vol. 10(7), pages 1-22, July.
    19. Iakovou, E. & Moussiopoulos, N. & Xanthopoulos, A. & Achillas, Ch. & Michailidis, N. & Chatzipanagioti, M. & Koroneos, C. & Bouzakis, K.-D. & Kikis, V., 2009. "A methodological framework for end-of-life management of electronic products," Resources, Conservation & Recycling, Elsevier, vol. 53(6), pages 329-339.
    20. Zhang, Bowen & Dong, Yucheng & Zhang, Hengjie & Pedrycz, Witold, 2020. "Consensus mechanism with maximum-return modifications and minimum-cost feedback: A perspective of game theory," European Journal of Operational Research, Elsevier, vol. 287(2), pages 546-559.
    21. Jiménez Rivero, Ana & Sathre, Roger & García Navarro, Justo, 2016. "Life cycle energy and material flow implications of gypsum plasterboard recycling in the European Union," Resources, Conservation & Recycling, Elsevier, vol. 108(C), pages 171-181.
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