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On The consideration of carbon emissions in modelling-based supply chain literature: the state of the art, relevant features and research gaps

Author

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  • Amina Chelly

    (ENIT - Ecole Nationale d'Ingénieurs de Tunis - UTM - Université de Tunis El Manar, UGA [2016-2019] - Université Grenoble Alpes [2016-2019], CNRS - Centre National de la Recherche Scientifique, G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production - G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - CNRS - Centre National de la Recherche Scientifique - UGA [2016-2019] - Université Grenoble Alpes [2016-2019])

  • Imen Nouira

    (ESC [Rennes] - ESC Rennes School of Business)

  • Yannick Frein

    (G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production - G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - CNRS - Centre National de la Recherche Scientifique - UGA [2016-2019] - Université Grenoble Alpes [2016-2019], UGA [2016-2019] - Université Grenoble Alpes [2016-2019], CNRS - Centre National de la Recherche Scientifique)

  • Atidel Hadj-Alouane

    (ENIT - Ecole Nationale d'Ingénieurs de Tunis - UTM - Université de Tunis El Manar, ENIT - Ecole Nationale d'Ingénieurs de Tunis - UTM - Université de Tunis El Manar, UTM - Université de Tunis El Manar)

Abstract

This review paper provides the operations management (OM) community with an exhaustive analysis of the mathematical models developed for the problem of low-carbon supply chain management (LCSCM). Our paper belongs to the green supply chain management (GSCM) reviews but is distinguished by its specific interest in analysing research works on supply chain (SC) management regarding the reduction of carbon emissions and its related constraints. To facilitate our benchmarking of the 83 selected papers, we adopt a literature classification based on the logistic decisions studied within the developed models. We distinguish three categories of logistic decisions: operational management, technology investment and SC design coordination. Companies are currently facing great external pressures from governments and their conscientious customers to reduce their overall emissions. We analyse how these environmental constraints, which we believe are key drivers for low-carbon emissions management, have been incorporated into mathematical models. Analysing these external pressures in terms of concern about carbon emissions constitutes our main contribution through this literature review. In addition, companies are facing a challenge to reduce their carbon emissions, which are mainly generated from production, transport and storage activities. Consequently, the modelling of carbon emissions remains a crucial task when addressing the LCSCM problem. We suggest analysing the techniques used thus far to approximate those carbon emissions. Furthermore, to illustrate our literature classification and the features of the LCSCM problem, we provide the framework on which we based our analysis of the selected literature. We discuss the modelling aspects of this problem to highlight the limits of the existing literature and consequently suggest recommendations for future research. We believe that this issue will continue to be one of the top concerns of the OM community within the GSCM field as it continues to gain importance among business leaders, and political and social actors.

Suggested Citation

  • Amina Chelly & Imen Nouira & Yannick Frein & Atidel Hadj-Alouane, 2019. "On The consideration of carbon emissions in modelling-based supply chain literature: the state of the art, relevant features and research gaps," Post-Print hal-02285426, HAL.
  • Handle: RePEc:hal:journl:hal-02285426
    DOI: 10.1080/00207543.2018.1497310
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    Citations

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    Cited by:

    1. Kandil, Narjes & Hammami, Ramzi & Battaïa, Olga, 2022. "Insourcing versus outsourcing decision under environmental considerations and different contract arrangements," International Journal of Production Economics, Elsevier, vol. 253(C).
    2. Dong Yang & Qidong Liu & Jia Li & Yongji Jia, 2020. "Multi-Objective Optimization of Service Selection and Scheduling in Cloud Manufacturing Considering Environmental Sustainability," Sustainability, MDPI, vol. 12(18), pages 1-19, September.
    3. Asgari, Erfan & Hammami, Ramzi & Frein, Yannick & Nouira, Imen, 2021. "The effect of greenness- and price-based competition on a product's environmental performance," International Journal of Production Economics, Elsevier, vol. 234(C).
    4. Nan Li & Mingjiang Deng & Hanshu Mou & Deshan Tang & Zhou Fang & Qin Zhou & Changgao Cheng & Yingdi Wang, 2022. "Government Participation in Supply Chain Low-Carbon Technology R&D and Green Marketing Strategy Optimization," Sustainability, MDPI, vol. 14(14), pages 1-27, July.
    5. Yugang Yu & Xue Li & Xiaoping Xu, 2022. "Reselling or marketplace mode for an online platform: the choice between cap-and-trade and carbon tax regulation," Annals of Operations Research, Springer, vol. 310(1), pages 293-329, March.
    6. Maryam Shoaeinaeini & Kannan Govindan & Donya Rahmani, 2022. "Pricing policy in green supply chain design: the impact of consumer environmental awareness and green subsidies," Operational Research, Springer, vol. 22(4), pages 3989-4028, September.
    7. Dong Yang & Jia Li & Bill Wang & Yong-ji Jia, 2020. "Module-Based Product Configuration Decisions Considering Both Economical and Carbon Emission-Related Environmental Factors," Sustainability, MDPI, vol. 12(3), pages 1-13, February.
    8. Meng, Mingyou & Deng, Shiming & Zhou, Pin & Xu, He, 2023. "The effects of subsidy programs in byproduct synergy operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).

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