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Sustainability dimensions and PM2.5 in supply chain logistics

Author

Listed:
  • Jiangtao Hong

    (Shanghai University of International Business and Economics)

  • Chaher Alzaman

    (Concordia University)

  • Ali Diabat

    (New York University Abu Dhabi
    New York University)

  • Akif Bulgak

    (Concordia University)

Abstract

Sustainable Supply Chain Management (SSCM) is a topic of growing interest among researchers. Many works have investigated the negative impact of CO2 emission, but have put less emphasis on other emission types. Many works have focused on the economic and environmental dimensions of sustainability but lacked content on the social dimension. Since SSCM is concerned with all aspects of sustainability, this work undertakes the three dimensions of sustainability and models particulate pollution (PM2.5) which has been cited in the literature to have a negative impact on human health. The paper constructs a mathematical programming model that minimizes the transportation costs and the undesirable social medical costs for remedying the release of PM2.5 into the atmosphere. The paper solves a model that evaluates different transportation modes, transportation costs, carbon emissions, PM2.5, medical costs, and capturing options. Moreover, the work utilizes a Monte Carlo simulation to best present the inherent variations in the model. Largely, the work provides stakeholders with transportation mode choices and greening opportunity investments to minimize the overall transportation costs while respecting physical and operational constraints.

Suggested Citation

  • Jiangtao Hong & Chaher Alzaman & Ali Diabat & Akif Bulgak, 2019. "Sustainability dimensions and PM2.5 in supply chain logistics," Annals of Operations Research, Springer, vol. 275(2), pages 339-366, April.
  • Handle: RePEc:spr:annopr:v:275:y:2019:i:2:d:10.1007_s10479-018-3077-7
    DOI: 10.1007/s10479-018-3077-7
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    References listed on IDEAS

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    Cited by:

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    2. Suthep Nimsai & Chanin Yoopetch & Polin Lai, 2020. "Mapping the Knowledge Base of Sustainable Supply Chain Management: A Bibliometric Literature Review," Sustainability, MDPI, vol. 12(18), pages 1-21, September.
    3. Xin Yao & Yuanyuan Cheng & Li Zhou & Malin Song, 2022. "Green efficiency performance analysis of the logistics industry in China: based on a kind of machine learning methods," Annals of Operations Research, Springer, vol. 308(1), pages 727-752, January.
    4. Mei, Qihuang & Li, Jianbin & Ursavas, Evrim & Zhu, Stuart X. & Luo, Xiaomeng, 2021. "Freight transportation planning in platform service supply chain considering carbon emissions," International Journal of Production Economics, Elsevier, vol. 240(C).
    5. Vitor W. B. Martins & Rosley Anholon & Osvaldo L. G. Quelhas & Walter Leal Filho, 2019. "Sustainable Practices in Logistics Systems: An Overview of Companies in Brazil," Sustainability, MDPI, vol. 11(15), pages 1-12, July.
    6. Karolina Werner-Lewandowska & Paulina Golinska-Dawson, 2021. "Sustainable Logistics Management Maturity—The Theoretical Assessment Framework and Empirical Results from Poland," Sustainability, MDPI, vol. 13(9), pages 1-19, May.

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