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Big data-enabled large-scale group decision making for circular economy: An emerging market context

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  • Modgil, Sachin
  • Gupta, Shivam
  • Sivarajah, Uthayasankar
  • Bhushan, Bharat

Abstract

This study is focused on presenting a unique landscape for big data-enabled circular economy that involves stakeholders as important decision makers. This research is designed based on five case studies from emerging markets with a focus on circular models to propose a framework for large scale decision making. In these cases, different linear economy problems are addressed that further utilizes the integration of big data and large-scale group decision making by stakeholders to achieve circularity. The findings of our study indicate a four-step design (enabling technologies, business significance, deriving value, and circular goals) to implement the 10R's of the circular economy through emerging technologies such as big data and related mobile applications along with cloud-based platforms. The study highlights how cases from emerging markets can be useful for other firms and ecosystems, ranging from e-commerce to manufacturing, that employ large number of decision makers with the aim of creating a circular economy. At the end, the study presents theoretical and practical implications along with the scope for future research.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:tefoso:v:166:y:2021:i:c:s0040162521000391
    DOI: 10.1016/j.techfore.2021.120607
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    as
    1. Despeisse, M. & Baumers, M. & Brown, P. & Charnley, F. & Ford, S.J. & Garmulewicz, A. & Knowles, S. & Minshall, T.H.W. & Mortara, L. & Reed-Tsochas, F.P. & Rowley, J., 2017. "Unlocking value for a circular economy through 3D printing: A research agenda," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 75-84.
    2. Papadopoulos, Thanos & Stamati, Teta & Nikolaidou, Mara & Anagnostopoulos, Dimosthenis, 2013. "From Open Source to Open Innovation practices: A case in the Greek context in light of the debt crisis," Technological Forecasting and Social Change, Elsevier, vol. 80(6), pages 1232-1246.
    3. ., 2018. "The fourth industrial revolution," Chapters, in: Industrial Policy for the Manufacturing Revolution, chapter 3, pages 49-78, Edward Elgar Publishing.
    4. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    5. Jianjun Zhu & Shitao Zhang & Ye Chen & Lili Zhang, 2016. "A Hierarchical Clustering Approach Based on Three-Dimensional Gray Relational Analysis for Clustering a Large Group of Decision Makers with Double Information," Group Decision and Negotiation, Springer, vol. 25(2), pages 325-354, March.
    6. Müller, Julian Marius & Buliga, Oana & Voigt, Kai-Ingo, 2018. "Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 2-17.
    7. Garlapati, Vijay Kumar, 2016. "E-waste in India and developed countries: Management, recycling, business and biotechnological initiatives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 874-881.
    8. Rialti, Riccardo & Zollo, Lamberto & Ferraris, Alberto & Alon, Ilan, 2019. "Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    9. Jabbour, Charbel Jose Chiappetta & Jabbour, Ana Beatriz Lopes de Sousa & Sarkis, Joseph & Filho, Moacir Godinho, 2019. "Unlocking the circular economy through new business models based on large-scale data: An integrative framework and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 546-552.
    10. Min Xu & Jeanne M. David & Suk Hi Kim, 2018. "The Fourth Industrial Revolution: Opportunities and Challenges," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 9(2), pages 90-95, April.
    11. Gustavo Cattelan Nobre & Elaine Tavares, 2017. "Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 463-492, April.
    12. de Jesus, Ana & Mendonça, Sandro, 2018. "Lost in Transition? Drivers and Barriers in the Eco-innovation Road to the Circular Economy," Ecological Economics, Elsevier, vol. 145(C), pages 75-89.
    13. Liu, Bingsheng & Zhou, Qi & Ding, Ru-Xi & Palomares, Iván & Herrera, Francisco, 2019. "Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination," European Journal of Operational Research, Elsevier, vol. 275(2), pages 737-754.
    14. Ana Beatriz Lopes de Sousa Jabbour & Charbel Jose Chiappetta Jabbour & Moacir Godinho Filho & David Roubaud, 2018. "Industry 4.0 and the circular economy: a proposed research agenda and original roadmap for sustainable operations," Annals of Operations Research, Springer, vol. 270(1), pages 273-286, November.
    15. Bag, Surajit & Gupta, Shivam & Kumar, Sameer, 2021. "Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development," International Journal of Production Economics, Elsevier, vol. 231(C).
    16. Alan Murray & Keith Skene & Kathryn Haynes, 2017. "The Circular Economy: An Interdisciplinary Exploration of the Concept and Application in a Global Context," Journal of Business Ethics, Springer, vol. 140(3), pages 369-380, February.
    17. Hao, Han & Liu, Zongwei & Zhao, Fuquan & Geng, Yong & Sarkis, Joseph, 2017. "Material flow analysis of lithium in China," Resources Policy, Elsevier, vol. 51(C), pages 100-106.
    18. Yadegaridehkordi, Elaheh & Hourmand, Mehdi & Nilashi, Mehrbakhsh & Shuib, Liyana & Ahani, Ali & Ibrahim, Othman, 2018. "Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 199-210.
    19. Zhang, Yi & Huang, Ying & Porter, Alan L. & Zhang, Guangquan & Lu, Jie, 2019. "Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 795-807.
    20. Phillips, Robert & Freeman, R. Edward & Wicks, Andrew C., 2003. "What Stakeholder Theory is Not," Business Ethics Quarterly, Cambridge University Press, vol. 13(4), pages 479-502, October.
    21. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Papadopoulos, Thanos & Luo, Zongwei & Wamba, Samuel Fosso & Roubaud, David, 2019. "Can big data and predictive analytics improve social and environmental sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 534-545.
    22. Gupta, Shivam & Chen, Haozhe & Hazen, Benjamin T. & Kaur, Sarabjot & Santibañez Gonzalez, Ernesto D.R., 2019. "Circular economy and big data analytics: A stakeholder perspective," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 466-474.
    23. Iqbal, Rahat & Doctor, Faiyaz & More, Brian & Mahmud, Shahid & Yousuf, Usman, 2020. "Big data analytics: Computational intelligence techniques and application areas," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    24. Glen P. Peters & Oliver Geden, 2017. "Catalysing a political shift from low to negative carbon," Nature Climate Change, Nature, vol. 7(9), pages 619-621, September.
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    Cited by:

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    3. Stekelorum, Rebecca & Laguir, Issam & Lai, Kee-hung & Gupta, Shivam & Kumar, Ajay, 2021. "Responsible governance mechanisms and the role of suppliers’ ambidexterity and big data predictive analytics capabilities in circular economy practices improvements," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    4. Chauhan, Chetna & Parida, Vinit & Dhir, Amandeep, 2022. "Linking circular economy and digitalisation technologies: A systematic literature review of past achievements and future promises," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    5. Taiga Saito & Shivam Gupta, 2022. "Big Data Applications with Theoretical Models and Social Media in Financial Management," CIRJE F-Series CIRJE-F-1205, CIRJE, Faculty of Economics, University of Tokyo.
    6. Chowdhury, Naimur Rahman & Paul, Sanjoy Kumar & Sarker, Tapan & Shi, Yangyan, 2023. "Implementing smart waste management system for a sustainable circular economy in the textile industry," International Journal of Production Economics, Elsevier, vol. 262(C).
    7. Rosangela de Fátima Pereira Marquesone & Tereza Cristina Melo de Brito Carvalho, 2022. "Examining the Nexus between the Vs of Big Data and the Sustainable Challenges in the Textile Industry," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
    8. Taiga Saito & Shivam Gupta, 2022. "Big data applications with theoretical models and social media in financial management," CARF F-Series CARF-F-550, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    9. 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).
    10. Kristoffersen, Eivind & Mikalef, Patrick & Blomsma, Fenna & Li, Jingyue, 2021. "The effects of business analytics capability on circular economy implementation, resource orchestration capability, and firm performance," International Journal of Production Economics, Elsevier, vol. 239(C).
    11. Liang Dong & Zhaowen Liu & Yuli Bian, 2021. "Match Circular Economy and Urban Sustainability: Re-investigating Circular Economy Under Sustainable Development Goals (SDGs)," Circular Economy and Sustainability,, Springer.
    12. Ashkan Pakseresht & Sina Ahmadi Kaliji & Vilma Xhakollari, 2022. "How Blockchain Facilitates the Transition toward Circular Economy in the Food Chain?," Sustainability, MDPI, vol. 14(18), pages 1-22, September.
    13. Fabio De Felice & Antonella Petrillo, 2021. "Green Transition: The Frontier of the Digicircular Economy Evidenced from a Systematic Literature Review," Sustainability, MDPI, vol. 13(19), pages 1-26, October.
    14. Cheffi, Walid & Kaleem Zahir-ul-Hassan, Muhammad & Omer Farooq, Muhammad & Baqrain, Abdelrahman & Mohamed Habib Mansour, Mourad, 2023. "Ethical leadership, management control systems and circular economy in SMEs in an emerging economy, the UAE," Journal of Business Research, Elsevier, vol. 156(C).

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