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Outsourcing modelling using a novel interval-valued fuzzy quantitative strategic planning matrix (QSPM) and multiple criteria decision-making (MCDMs)

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  • Barak, Sasan
  • Javanmard, Shima

Abstract

Outsourcing drives companies to focus on: their capabilities, advantages of external resources, and decreasing overall operational costs. Selecting appropriate alliances, which are aligned with the company's strategies, establishes a situation through which the firms can enhance their technical capabilities and achieve new technologies. However, two critical issues in outsourcing modeling should be addressed: how to find strategic indicators for building successful alliances, and how to select these partners. Besides, as the imprecise and vague information (due to a lack of data) existing in the outsourcing models cannot be neglected, the application of fuzzy interval sets could efficiently address the complexity of these problems.

Suggested Citation

  • Barak, Sasan & Javanmard, Shima, 2020. "Outsourcing modelling using a novel interval-valued fuzzy quantitative strategic planning matrix (QSPM) and multiple criteria decision-making (MCDMs)," International Journal of Production Economics, Elsevier, vol. 222(C).
    • Handle: RePEc:eee:proeco:v:222:y:2020:i:c:s0925527319303123
    DOI: 10.1016/j.ijpe.2019.09.015
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    2. Zeng, Shouzhen & Zhou, Jiamin & Zhang, Chonghui & Merigó, José M., 2022. "Intuitionistic fuzzy social network hybrid MCDM model for an assessment of digital reforms of manufacturing industry in China," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    3. Heidary Dahooie, Jalil & Raafat, Romina & Qorbani, Ali Reza & Daim, Tugrul, 2021. "An intuitionistic fuzzy data-driven product ranking model using sentiment analysis and multi-criteria decision-making," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    4. Heidary Dahooie, Jalil & Qorbani, Ali Reza & Daim, Tugrul, 2021. "Providing a framework for selecting the appropriate method of technology acquisition considering uncertainty in hierarchical group decision-making: Case Study: Interactive television technology," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    5. Asma Fahim & Qingmei Tan & Bushra Naz & Qurat ul Ain & Sibghat Ullah Bazai, 2021. "Sustainable Higher Education Reform Quality Assessment Using SWOT Analysis with Integration of AHP and Entropy Models: A Case Study of Morocco," Sustainability, MDPI, vol. 13(8), pages 1-19, April.
    6. Jung-Fa Tsai & Chin-Po Wang & Ming-Hua Lin & Shih-Wei Huang, 2021. "Analysis of Key Factors for Supplier Selection in Taiwan’s Thin-Film Transistor Liquid-Crystal Displays Industry," Mathematics, MDPI, vol. 9(4), pages 1-18, February.
    7. Flora Kulembayeva & Aruzhan Seitkaziyeva & Rakymzhan Yelshibayev, 2022. "Economic Efficiency of Outsourcing Business Models: A Comparative Assessment," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 23(1), pages 75-88, March.

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