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Applying Entropy Weighting and 2-Tuple Linguistic T-Spherical Fuzzy MCDM: A Case Study of Developing a Strategic Sustainability Plan for Istanbul Airport

Author

Listed:
  • Filiz Mizrak

    (Faculty of Business Administrative Sciences, Logistics Management, Beykoz University, 34805 İstanbul, Türkiye)

  • Levent Polat

    (Vocational School of Logistics, Beykoz University, 34805 İstanbul, Türkiye)

  • Sezin Acik Tasar

    (Faculty of Business Administrative Sciences, Business Administration, Beykoz University, 34805 İstanbul, Türkiye)

Abstract

This study presents a novel sustainability plan tailored for Istanbul Airport, leveraging advanced decision-making methodologies to address the urgent need for sustainable practices in aviation. By integrating the entropy weighting and 2-tuple linguistic T-spherical fuzzy multi-criteria decision-making (MCDM) models, the study offers a comprehensive approach to evaluating and prioritizing sustainability criteria based on expert input from 12 professionals. The novelty of this research lies in its unique combination of advanced MCDM techniques with cutting-edge technologies, including IoT-enabled monitoring systems, digital twin models, blockchain-based sustainability reporting, and carbon capture initiatives, tailored specifically for large-scale airport operations. The study develops a phased implementation roadmap comprising three stages: (1) a short-term focus on energy efficiency and renewable energy infrastructure, achieving significant cost reductions within a 3–7.5-year payback period; (2) medium-term initiatives integrating IoT and digital twins to enhance operational efficiency; and (3) long-term measures incorporating carbon capture and blockchain for transparency and compliance. Key implementation steps include upgrading energy systems, deploying IoT sensors, creating digital replicas of airport infrastructure, and establishing regulatory and stakeholder collaboration frameworks. This research contributes a replicable framework for airports worldwide, bridging theoretical models with actionable solutions.

Suggested Citation

  • Filiz Mizrak & Levent Polat & Sezin Acik Tasar, 2024. "Applying Entropy Weighting and 2-Tuple Linguistic T-Spherical Fuzzy MCDM: A Case Study of Developing a Strategic Sustainability Plan for Istanbul Airport," Sustainability, MDPI, vol. 16(24), pages 1-28, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:24:p:11104-:d:1546747
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    References listed on IDEAS

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    1. Changhong Chen & Huijie Zhang, 2023. "Evaluation of Green Development Level of Mianyang Agriculture, Based on the Entropy Weight Method," Sustainability, MDPI, vol. 15(9), pages 1-22, May.
    2. Shoufeng Cao & Henry Xu & Kim P. Bryceson, 2023. "Blockchain Traceability for Sustainability Communication in Food Supply Chains: An Architectural Framework, Design Pathway and Considerations," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    3. Ruth Oluyemi Bamidele & Ali Ozturen & Mine Haktanir & Oluwatobi A. Ogunmokun, 2023. "Realizing Green Airport Performance through Green Management Intransigence, Airport Reputation, Biospheric Value, and Eco-Design," Sustainability, MDPI, vol. 15(3), pages 1-26, January.
    4. Thomas, Antonio & Scandurra, Giuseppe, 2023. "The transition toward sustainability of airport operators. Evidence from Italy," Journal of Air Transport Management, Elsevier, vol. 112(C).
    5. Ricardo Jorge Raimundo & Maria Emilia Baltazar & Sandra P. Cruz, 2023. "Sustainability in the Airports Ecosystem: A Literature Review," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    6. Jia, Xibei & Buyle, Sven & Macário, Rosário, 2023. "Developing an airport sustainability evaluation index through composite indicator approach," Journal of Air Transport Management, Elsevier, vol. 113(C).
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