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A mixed-model multi-objective analysis of strategic supply chain decision support in the Thai silk industry

Author

Listed:
  • Natawat Jatuphatwarodom

    (Rajamangala University of Technology Thanyaburi)

  • Dylan F. Jones

    (University of Portsmouth)

  • Djamila Ouelhadj

    (University of Portsmouth)

Abstract

This paper presents a methodology for combined usage of data envelopment analysis (DEA), analytical hierarchy process (AHP) and extended goal programming (EGP) in order to provide managerial decision support. The methodology allows the three techniques to be used in a coordinated manner to give an enhanced level of holistic decision support. DEA is first used in a descriptive sense in order to provide information regarding the efficiency of a set of units. The AHP is then used in order to determine the importance of criteria arising from decision problem(s) related to the improvement of unit efficiency. Finally, EGP is used in a prescriptive sense in order to select a set of specific actions for improving unit efficiency. Two specific multi-objective situations arising from the Thai Silk industry are used as case studies for the proposed methodology. These involve supplier selection and inventory management system management in the presence of multiple conflicting goals and objectives. In the case studies, DEA is used to provide efficiency estimates of current suppliers and processes. AHP is then used in order to determine the relative importance of criteria for supply chain efficiency improvement. Adaptations are made to an automated inconsistency reduction algorithm in order to resolve high levels of inconsistency found. The relation between decision maker confidence and consistency is investigated. Finally, an EGP model is built in order to suggest improvement actions to the supply chain processes. Results are given for a set of eight Thai silk manufacturers and conclusions are drawn.

Suggested Citation

  • Natawat Jatuphatwarodom & Dylan F. Jones & Djamila Ouelhadj, 2018. "A mixed-model multi-objective analysis of strategic supply chain decision support in the Thai silk industry," Annals of Operations Research, Springer, vol. 267(1), pages 221-247, August.
  • Handle: RePEc:spr:annopr:v:267:y:2018:i:1:d:10.1007_s10479-018-2774-6
    DOI: 10.1007/s10479-018-2774-6
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    1. Fengyi Lin & Sheng-Wei Lin & Wen-Min Lu, 2018. "Sustainability Assessment of Taiwan’s Semiconductor Industry: A New Hybrid Model Using Combined Analytic Hierarchy Process and Two-Stage Additive Network Data Envelopment Analysis," Sustainability, MDPI, vol. 10(11), pages 1-16, November.
    2. 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.
    3. Houssem Felfel & Wafa Ben Yahia & Omar Ayadi & Faouzi Masmoudi, 2018. "Stochastic multi-site supply chain planning in textile and apparel industry under demand and price uncertainties with risk aversion," Annals of Operations Research, Springer, vol. 271(2), pages 551-574, December.
    4. Adel Hatami-Marbini & Siavash Hekmat & Per J. Agrell, 2022. "A strategy-based framework for supplier selection: a grey PCA-DEA approach," Operational Research, Springer, vol. 22(1), pages 263-297, March.

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