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A hybrid ensemble and AHP approach for resilient supplier selection

Author

Listed:
  • Seyedmohsen Hosseini

    (University of Oklahoma)

  • Abdullah Al Khaled

    (Influence Health)

Abstract

Suppliers play a crucial role in achieving the supply chain goals. In the context of risk management, suppliers are the most common source of external risks in modern supply chains. The recognition that continuity of supply chain flow under disruptive event is a critical issue has brought the attention of companies to the selection of resilient suppliers. In contrast to the extensive number of researches on traditional and green criteria of supplier selection, the criteria associated with resilient supplier selection are not well explored yet. This paper first seeks to explore the resilience criteria for supplier selection based on the notion of resilience capacities which can be divided into three categories: absorptive capacity, adaptive capacity, and restorative capacity. Absorptive capacity refers to the capability of system to withstand against disruptive event in prior or called as preparedness of supplier, while adaptive and restoration capacities imply the capability of supplier to adopt itself and restore from disruption or recoverability of supplier. We identified eight effective elements for resilience capacities which contribute to the resilience of suppliers. Advanced data mining approaches like predictive analytics models are used to predict the resilience value of each supplier. We applied ensemble methods by combining binomial logistics regression, classification and regression trees, and neural network to obtain better predictive performance than individual algorithm from the historical data to predict individual supplier’s resiliency. This resilience value, obtained from ensemble methods, is coupled with additional four variables to assess the suppliers’ overall performance and rank them using different supplier selection models. Finally, a case study has been performed on international plastic raw material suppliers for a U.S. based manufacturer.

Suggested Citation

  • Seyedmohsen Hosseini & Abdullah Al Khaled, 2019. "A hybrid ensemble and AHP approach for resilient supplier selection," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 207-228, January.
  • Handle: RePEc:spr:joinma:v:30:y:2019:i:1:d:10.1007_s10845-016-1241-y
    DOI: 10.1007/s10845-016-1241-y
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    References listed on IDEAS

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    7. Ahmed Mohammed & Morteza Yazdani & Amar Oukil & Ernesto D. R. Santibanez Gonzalez, 2021. "A Hybrid MCDM Approach towards Resilient Sourcing," Sustainability, MDPI, vol. 13(5), pages 1-30, March.
    8. Ghanei, Shima & Contreras, Ivan & Cordeau, Jean-François, 2023. "A two-stage stochastic collaborative intertwined supply network design problem under multiple disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    9. Agus Ristono & Tri Wahyuningsih & Eko Junianto, 2020. "Proposed Method for Supplier Selection," Technium Social Sciences Journal, Technium Science, vol. 13(1), pages 376-394, November.
    10. Fangzhong Qi & Leilei Zhang & Kexiang Zhuo & Xiuyan Ma, 2022. "Early Warning for Manufacturing Supply Chain Resilience Based on Improved Grey Prediction Model," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    11. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    12. Xinlong Li & Yan Ran & Genbao Zhang & Yan He, 2020. "A failure mode and risk assessment method based on cloud model," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1339-1352, August.
    13. Nitsche, Anna-Maria & Kusturica, Wibke & Neumann, Denis & Schumann, Christian-Andreas & Laroque, Christoph, 2021. "Supply chain management in the course of time - A systematisation of past, present and future objectives," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Adapting to the Future: Maritime and City Logistics in the Context of Digitalization and Sustainability. Proceedings of the Hamburg International Conf, volume 32, pages 519-544, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    14. Batel Ziv & Yisrael Parmet, 2022. "Improving nonconformity responsibility decisions: a semi-automated model based on CRISP-DM," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 657-667, April.
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    16. Roya Ghamari & Mohammad Mahdavi-Mazdeh & Seyed Farid Ghannadpour, 2022. "Resilient and sustainable supplier selection via a new framework: a case study from the steel industry," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(8), pages 10403-10441, August.
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    19. Kaur, Harpreet & Prakash Singh, Surya, 2021. "Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies," International Journal of Production Economics, Elsevier, vol. 231(C).

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