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Evaluating Supply Chain Network Models for Third Party Logistics Operated Supply-Processing-Distribution in Thai Hospitals: An AHP-Fuzzy TOPSIS Approach

Author

Listed:
  • Duangpun Kritchanchai

    (Department of Industrial Engineering, Faculty of Engineering, Mahidol University, Nakhon Pathom 73170, Thailand)

  • Daranee Senarak

    (Cluster of Logistics and Rail Engineering, Faculty of Engineering, Mahidol University, Nakhon Pathom 73170, Thailand
    Greenline Synergy Co., Ltd., Bangkok 10250, Thailand)

  • Tuangyot Supeekit

    (Department of Industrial Engineering, Faculty of Engineering, Mahidol University, Nakhon Pathom 73170, Thailand)

  • Wirachchaya Chanpuypetch

    (Multidisciplinary and Interdisciplinary School, Chiang Mai University, Chiang Mai 50200, Thailand
    Faculty of Agro-Industry, Chiang Mai University, Samut Sakhon 74000, Thailand
    Cluster of Innovation for Sustainable Seafood Industry and Value Chain Management, Faculty of Agro-Industry, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

Background : This study introduces a novel supply chain management (SCM) model tailored for the hospital industry in Thailand. The model emphasises the integration of third-party logistics (3PL) providers to streamline supply-processing-distribution (SPD) functions. By outsourcing non-core activities like SPD to 3PL providers, hospitals can enhance their operational efficiency, allowing healthcare professionals to focus on core tasks and ultimately improving service delivery. Methods : This research employed a dual methodology, combining an analytic hierarchy process (AHP) with a Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). These approaches evaluated various SCM models based on multiple hospital logistics performance attributes. Results : The AHP results highlighted on-time delivery, patient safety, utilisation rate, and emergency procurement as critical criteria for selecting the optimal model. Fuzzy TOPSIS analysis identified the SCIII: W-G-H model as the most suitable for implementation in Thai hospitals. This model incorporates a centralised warehouse for negotiation leverage, a Group Purchasing Organisation (GPO) for cost efficiency, and regional SPD hubs for effective inventory management and rapid responses to demand fluctuations or emergencies. Conclusions : Adopting this SCM model is expected to significantly enhance supply chain performance, reduce operational costs, and improve the quality and safety of patient care in Thai hospitals.

Suggested Citation

  • Duangpun Kritchanchai & Daranee Senarak & Tuangyot Supeekit & Wirachchaya Chanpuypetch, 2024. "Evaluating Supply Chain Network Models for Third Party Logistics Operated Supply-Processing-Distribution in Thai Hospitals: An AHP-Fuzzy TOPSIS Approach," Logistics, MDPI, vol. 8(4), pages 1-28, November.
  • Handle: RePEc:gam:jlogis:v:8:y:2024:i:4:p:116-:d:1517621
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    References listed on IDEAS

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    1. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    2. Rajak, Manindra & Shaw, Krishnendu, 2019. "Evaluation and selection of mobile health (mHealth) applications using AHP and fuzzy TOPSIS," Technology in Society, Elsevier, vol. 59(C).
    3. de Vries, Jan, 2011. "The shaping of inventory systems in health services: A stakeholder analysis," International Journal of Production Economics, Elsevier, vol. 133(1), pages 60-69, September.
    4. Pasura Aungkulanon & Walailak Atthirawong & Pongchanun Luangpaiboon & Wirachchaya Chanpuypetch, 2024. "Navigating Supply Chain Resilience: A Hybrid Approach to Agri-Food Supplier Selection," Mathematics, MDPI, vol. 12(10), pages 1-42, May.
    5. Huidan Lin & Qun Li & Xueguo Xu & Ying Zhang, 2021. "Research on dispatch of drugs and consumables in SPD warehouse of large scale hospital under uncertain environment: take respiratory consumables as an example," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 848-865, November.
    6. Rosales, Claudia R. & Magazine, Michael & Rao, Uday, 2015. "The 2Bin system for controlling medical supplies at point-of-use," European Journal of Operational Research, Elsevier, vol. 243(1), pages 271-280.
    7. Gengjun Gao & Yuxuan Che & Jian Shen, 2021. "Path optimization for joint distribution of medical consumables under hospital SPD supply chain mode," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 866-883, November.
    8. Constance E. Helfat & Margaret A. Peteraf, 2015. "Managerial cognitive capabilities and the microfoundations of dynamic capabilities," Strategic Management Journal, Wiley Blackwell, vol. 36(6), pages 831-850, June.
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