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Using Fuzzy DEA for Green Suppliers Selection Considering Carbon Footprints

Author

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  • Min-Chun Yu

    (Department of Business Administration, National Kaohsiung University of Applied Sciences, Kaohsiung City 807, Taiwan)

  • Min-Hong Su

    (Department of Business Administration, National Kaohsiung University of Applied Sciences, Kaohsiung City 807, Taiwan)

Abstract

Due to increasing global environmental awareness, supply chains that consider environmental protection tend to be favored by green-minded customers. In addition to adapting to the technology required for green supply chains and developing contingency plans, organizations must consider reducing their carbon footprint to meet corporate objectives and reducing their carbon footprint. To address this issue, this paper aims at establishing a decision-making process for buyers with sustainability in mind. A fuzzy data envelopment analysis (FDEA) model was developed to select the most suitable supplier. Production costs, lead time, and supply chain carbon footprints were used as the input criteria, and quality and demand quantity were used as the output criteria. Buyer-seller supply chains and non-cooperative and cooperative models were employed separately to calculate associative efficiency. Sensitivity analysis was conducted to understand the effects carbon footprints have on efficiency. This study found that suppliers with low carbon footprints exhibited poor efficiency, which may be attributed to the additional effort required to select raw materials. Additionally, suppliers with different supply chain operation models exhibited differing efficiencies. Therefore, suppliers must consider the balance between carbon footprint reduction and costs, and buyers must consider environmental criteria when selecting green suppliers.

Suggested Citation

  • Min-Chun Yu & Min-Hong Su, 2017. "Using Fuzzy DEA for Green Suppliers Selection Considering Carbon Footprints," Sustainability, MDPI, vol. 9(4), pages 1-11, March.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:4:p:495-:d:94112
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    References listed on IDEAS

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    1. J. Reilly & R. Prinn & J. Harnisch & J. Fitzmaurice & H. Jacoby & D. Kicklighter & J. Melillo & P. Stone & A. Sokolov & C. Wang, 1999. "Multi-gas assessment of the Kyoto Protocol," Nature, Nature, vol. 401(6753), pages 549-555, October.
    2. Thomas Wiedmann & John Barrett, 2010. "A Review of the Ecological Footprint Indicator—Perceptions and Methods," Sustainability, MDPI, vol. 2(6), pages 1-49, June.
    3. Liang Liang & Feng Yang & Wade Cook & Joe Zhu, 2006. "DEA models for supply chain efficiency evaluation," Annals of Operations Research, Springer, vol. 145(1), pages 35-49, July.
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    Cited by:

    1. Ankit Kumrawat & Seema Unnikrishnan, 2025. "Life Cycle Sustainability Assessment Integrated Data‐Driven Methodological Framework for Sustainable Supplier Selection," Business Strategy and the Environment, Wiley Blackwell, vol. 34(6), pages 7368-7388, September.
    2. Wei Song & Zhiya Chen & Aijun Liu & Qiuyun Zhu & Wei Zhao & Sang-Bing Tsai & Hui Lu, 2018. "A Study on Green Supplier Selection in Dynamic Environment," Sustainability, MDPI, vol. 10(4), pages 1-22, April.
    3. Xiaolu Zhang & Xiaoming Xing, 2017. "Probabilistic Linguistic VIKOR Method to Evaluate Green Supply Chain Initiatives," Sustainability, MDPI, vol. 9(7), pages 1-18, July.
    4. Ibrahim Yilmaz, 2023. "A Hybrid DEA–Fuzzy COPRAS Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    5. Lívia Mariana Lopes de Souza Torres & Francisco de Sousa Ramos, 2026. "Data envelopment analysis and game theory: Where are we? Where are we going?," Annals of Operations Research, Springer, vol. 358(2), pages 929-983, March.
    6. Youngbok Ryu & Toshiyuki Sueyoshi, 2021. "Examining the Relationship between the Economic Performance of Technology-Based Small Suppliers and Socially Sustainable Procurement," Sustainability, MDPI, vol. 13(13), pages 1-23, June.
    7. Katerina Fotova Čiković & Ivana Martinčević & Joško Lozić, 2022. "Application of Data Envelopment Analysis (DEA) in the Selection of Sustainable Suppliers: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(11), pages 1-30, May.
    8. Xiangshuo He & Jian Zhang, 2018. "Supplier Selection Study under the Respective of Low-Carbon Supply Chain: A Hybrid Evaluation Model Based on FA-DEA-AHP," Sustainability, MDPI, vol. 10(2), pages 1-17, February.
    9. Pankaj Dutta & Bharath Jaikumar & Manpreet Singh Arora, 2022. "Applications of data envelopment analysis in supplier selection between 2000 and 2020: a literature review," Annals of Operations Research, Springer, vol. 315(2), pages 1399-1454, August.

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