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Selection of Suppliers for Speech Recognition Products in IT Projects by Combining Techniques with an Integrated Fuzzy MCDM

Author

Listed:
  • Atour Taghipour

    (Faculty of International Business, Normandy University, 76600 Le Havre, France)

  • Babak Daneshvar Rouyendegh

    (Department of Industrial Engineering, Ankara Yıldırım Beyazıt University, Ankara 06010, Turkey)

  • Aylin Ünal

    (Department of Industrial Engineering, Ankara Yıldırım Beyazıt University, Ankara 06010, Turkey)

  • Sujan Piya

    (Department of Mechanical and Industrial Engineering, College of engineering, Sultan Qaboos University, Muscat 123, Oman)

Abstract

In today’s environment, as the complexity of actual events develops, products become increasingly complicated. As a result, companies should collaborate to integrate disparate technologies while developing a product or service. Additionally, collaborating with the right supplier helps a company increase the flexibility, competitiveness, and profitability of its goods or services. The goal of this study is to look into the factors that influence supplier selection for speech recognition. Twelve sub-criteria for quality, affordability, maintenance, and adaptability are used to evaluate prospective providers. Two separate hybrid methodologies for finding the best supplier of an information technology product are presented. intuitionistic Fuzzy Due to the uncertainty of the data, VIKOR operates as the decision-making matrix and solves the issue by determining the ideal alternative for group utility using VIKOR. The second technique, Q-ROF TOPSIS, selects suppliers by utilizing q-rung orthopair fuzzy sets, which provides decision makers with greater expression flexibility than the majority of uncertainty-related strategies. To demonstrate the effectiveness of the recommended measures, a case study is conducted. The outcomes of various strategies are compared, as well as the associated advantages.

Suggested Citation

  • Atour Taghipour & Babak Daneshvar Rouyendegh & Aylin Ünal & Sujan Piya, 2022. "Selection of Suppliers for Speech Recognition Products in IT Projects by Combining Techniques with an Integrated Fuzzy MCDM," Sustainability, MDPI, vol. 14(3), pages 1-21, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1777-:d:741910
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    References listed on IDEAS

    as
    1. Babak Daneshvar Rouyendegh & Kazim Topuz & Ali Dag & Asil Oztekin, 2019. "An AHP-IFT Integrated Model for Performance Evaluation of E-Commerce Web Sites," Information Systems Frontiers, Springer, vol. 21(6), pages 1345-1355, December.
    2. Mohammadali Vosooghidizaji & Atour Taghipour & Béatrice Canel-Depitre, 2020. "Supply chain coordination under information asymmetry: a review," International Journal of Production Research, Taylor & Francis Journals, vol. 58(6), pages 1805-1834, March.
    3. Awasthi, Anjali & Govindan, Kannan & Gold, Stefan, 2018. "Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach," International Journal of Production Economics, Elsevier, vol. 195(C), pages 106-117.
    4. Atour Taghipour, 2014. "Improving the Plan of a Manufacturing Network with Non-Integrated Business Units," International Journal of Applied Logistics (IJAL), IGI Global Scientific Publishing, vol. 5(2), pages 1-11, April.
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    Cited by:

    1. Atour Taghipour & Mohammad Ramezani & Moein Khazaei & Vahid Roohparvar & Erfan Hassannayebi, 2023. "Smart Transportation Behavior through the COVID-19 Pandemic: A Ride-Hailing System in Iran," Sustainability, MDPI, vol. 15(5), pages 1-23, February.
    2. Babek Erdebilli & Ebru Gecer & İbrahim Yılmaz & Tamer Aksoy & Umit Hacıoglu & Hasan Dinçer & Serhat Yüksel, 2023. "Q-ROF Fuzzy TOPSIS and VIKOR Methods for the Selection of Sustainable Private Health Insurance Policies," Sustainability, MDPI, vol. 15(12), pages 1-22, June.

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