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Sustainable Cloud Service Provider Development by a Z-Number-Based DNMA Method with Gini-Coefficient-Based Weight Determination

Author

Listed:
  • Han Lai

    (Chongqing Engineering Laboratory for Detection, Control and Integrated System, Chongqing Technology and Business University, Chongqing 400067, China
    Business School, Sichuan University, Chengdu 610064, China)

  • Huchang Liao

    (Business School, Sichuan University, Chengdu 610064, China
    Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Jonas Šaparauskas

    (Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius LT-10223, Lithuania)

  • Audrius Banaitis

    (Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius LT-10223, Lithuania)

  • Fernando A. F. Ferreira

    (ISCTE Business School, BRU-IUL, University Institute of Lisbon, Avenida das Forças Armadas, 1649-026 Lisbon, Portugal
    Fogelman College of Business and Economics, University of Memphis, Memphis, TN 38152-3120, USA)

  • Abdullah Al-Barakati

    (Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

The sustainable development of cloud service providers (CSPs) is a significant multiple criteria decision making (MCDM) problem, involving the intrinsic relations among multiple alternatives, (quantitative and qualitative) decision criteria and decision-experts for the selection of trustworthy CSPs. Most existing MCDM methods for CSP selection incorporated only one normalization technique in benefit and cost criteria, which would mislead the decision results and limit the applications of these methods. In addition, these methods did not consider the reliability of information given by decision-makers. Given these research gaps, this study introduces a Z-number-based double normalization-based multiple aggregation (DNMA) method to tackle quantitative and qualitative criteria in forms of benefit, cost, and target types for sustainable CSP development. We extend the original DNMA method to the Z-number environment to handle the uncertain and unreliability information of decision-makers. To make trade-offs between normalized criteria values, we develop a Gini-coefficient based weighting method to replace the mean-square-based weighting method used in the original DNMA method to enhance the applicability and isotonicity of the DNMA method. A case study is conducted to demonstrate the effectiveness of the proposed method. Furthermore, comparative analysis and sensitivity analysis are implemented to test the stability and applicability of the proposed method.

Suggested Citation

  • Han Lai & Huchang Liao & Jonas Šaparauskas & Audrius Banaitis & Fernando A. F. Ferreira & Abdullah Al-Barakati, 2020. "Sustainable Cloud Service Provider Development by a Z-Number-Based DNMA Method with Gini-Coefficient-Based Weight Determination," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3410-:d:349060
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    References listed on IDEAS

    as
    1. Liao, Huchang & Wu, Xingli, 2020. "DNMA: A double normalization-based multiple aggregation method for multi-expert multi-criteria decision making," Omega, Elsevier, vol. 94(C).
    2. Seok-Keun Yoo & Bo-Young Kim, 2018. "A Decision-Making Model for Adopting a Cloud Computing System," Sustainability, MDPI, vol. 10(8), pages 1-15, August.
    3. Zhiying Zhang & Huchang Liao & Jiaying Chang & Abdullah Al-barakati, 2019. "Green-Building-Material Supplier Selection with a Rough-Set-Enhanced Quality Function Deployment," Sustainability, MDPI, vol. 11(24), pages 1-21, December.
    4. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
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    Cited by:

    1. Abhijit Saha & Arunodaya Raj Mishra & Pratibha Rani & Ibrahim M. Hezam & Fausto Cavallaro, 2022. "A q -Rung Orthopair Fuzzy FUCOM Double Normalization-Based Multi-Aggregation Method for Healthcare Waste Treatment Method Selection," Sustainability, MDPI, vol. 14(7), pages 1-28, March.
    2. Manuel Sousa & Maria Fatima Almeida & Rodrigo Calili, 2021. "Multiple Criteria Decision Making for the Achievement of the UN Sustainable Development Goals: A Systematic Literature Review and a Research Agenda," Sustainability, MDPI, vol. 13(8), pages 1-37, April.

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