IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v54y2016i7p2019-2034.html
   My bibliography  Save this article

A hybrid risks-informed approach for the selection of supplier portfolio

Author

Listed:
  • Chao Fang
  • Xiangxiang Liao
  • Min Xie

Abstract

In conventional supplier selection approaches, cost consideration is usually emphasised and it renders a vulnerable supply chain with various risks. This article aims to develop a quantitative approach for modelling both supply chain operational risks and disruption risks to support decision-making with regard to order allocation and risk mitigation. We introduce two types of risk evaluation models: value-at-risk (VaR) and conditional value-at-risk (CVaR). Specifically, VaR is used to measure operational risks caused by improper selection and operations of a supplier portfolio to the stochastic demand, which may frequently occur but result in relatively small losses to supply chains; CVaR is used to evaluate disruption risks that are less frequent and tend to cause significant damage. After incorporating risk factors into a probability-based multi-criteria optimisation model, different methods and parameters are compared and tested to determine the factors that may influence the supplier selection process. Computational examples by simulation are presented to illustrate the approach and how decision-makers make trade-offs between costs and hybrid risks.

Suggested Citation

  • Chao Fang & Xiangxiang Liao & Min Xie, 2016. "A hybrid risks-informed approach for the selection of supplier portfolio," International Journal of Production Research, Taylor & Francis Journals, vol. 54(7), pages 2019-2034, April.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:2019-2034
    DOI: 10.1080/00207543.2015.1076947
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2015.1076947
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2015.1076947?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liao, Zhiying & Rittscher, Jens, 2007. "A multi-objective supplier selection model under stochastic demand conditions," International Journal of Production Economics, Elsevier, vol. 105(1), pages 150-159, January.
    2. Weber, Charles A. & Current, John R. & Benton, W. C., 1991. "Vendor selection criteria and methods," European Journal of Operational Research, Elsevier, vol. 50(1), pages 2-18, January.
    3. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    4. Sawik, Tadeusz, 2014. "Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing," Omega, Elsevier, vol. 43(C), pages 83-95.
    5. Bilsel, R. Ufuk & Ravindran, A., 2011. "A multiobjective chance constrained programming model for supplier selection under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1284-1300, September.
    6. Ruiz-Torres, Alex J. & Mahmoodi, Farzad, 2007. "The optimal number of suppliers considering the costs of individual supplier failures," Omega, Elsevier, vol. 35(1), pages 104-115, February.
    7. Wu, Desheng Dash & Zhang, Yidong & Wu, Dexiang & Olson, David L., 2010. "Fuzzy multi-objective programming for supplier selection and risk modeling: A possibility approach," European Journal of Operational Research, Elsevier, vol. 200(3), pages 774-787, February.
    8. Silbermayr, Lena & Minner, Stefan, 2014. "A multiple sourcing inventory model under disruption risk," International Journal of Production Economics, Elsevier, vol. 149(C), pages 37-46.
    9. Ponlathep Lertworawanich, 2012. "Highway network restoration after the great flood in Thailand," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 64(1), pages 873-886, October.
    10. Sawik, Tadeusz, 2013. "Selection of resilient supply portfolio under disruption risks," Omega, Elsevier, vol. 41(2), pages 259-269.
    11. Wu, Desheng & Olson, David L., 2008. "Supply chain risk, simulation, and vendor selection," International Journal of Production Economics, Elsevier, vol. 114(2), pages 646-655, August.
    12. Amid, A. & Ghodsypour, S.H. & O'Brien, C., 2011. "A weighted max-min model for fuzzy multi-objective supplier selection in a supply chain," International Journal of Production Economics, Elsevier, vol. 131(1), pages 139-145, May.
    13. Lertworawanich, Ponlathep & Dechasakulsom, Montri & Aursudkij, Bhanitiz, 2012. "Highway network restoration after disasters," 53rd Annual Transportation Research Forum, Tampa, Florida, March 15-17, 2012 207120, Transportation Research Forum.
    14. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    15. Wang, Ge & Huang, Samuel H. & Dismukes, John P., 2004. "Product-driven supply chain selection using integrated multi-criteria decision-making methodology," International Journal of Production Economics, Elsevier, vol. 91(1), pages 1-15, September.
    16. Theißen, Sebastian & Spinler, Stefan, 2014. "Strategic analysis of manufacturer-supplier partnerships: An ANP model for collaborative CO2 reduction management," European Journal of Operational Research, Elsevier, vol. 233(2), pages 383-397.
    17. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    18. Hammami, Ramzi & Temponi, Cecilia & Frein, Yannick, 2014. "A scenario-based stochastic model for supplier selection in global context with multiple buyers, currency fluctuation uncertainties, and price discounts," European Journal of Operational Research, Elsevier, vol. 233(1), pages 159-170.
    19. Olivier Lavastre & A. Gunasekaran & Alain Spalanzani, 2012. "Supply chain risk management in french companies," Post-Print halshs-00740450, HAL.
    20. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marcus V. C. Fagundes & Bernd Hellingrath & Francisco G. M. Freires, 2021. "Supplier Selection Risk: A New Computer-Based Decision-Making System with Fuzzy Extended AHP," Logistics, MDPI, vol. 5(1), pages 1-17, March.
    2. Vijaya Dixit & Manoj Kumar Tiwari, 2020. "Project portfolio selection and scheduling optimization based on risk measure: a conditional value at risk approach," Annals of Operations Research, Springer, vol. 285(1), pages 9-33, February.
    3. Merve Er Kara & Seniye Ümit Oktay Fırat, 2018. "Supplier Risk Assessment Based on Best-Worst Method and K-Means Clustering: A Case Study," Sustainability, MDPI, vol. 10(4), pages 1-25, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Faiza Hamdi & Ahmed Ghorbel & Faouzi Masmoudi & Lionel Dupont, 2018. "Optimization of a supply portfolio in the context of supply chain risk management: literature review," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 763-788, April.
    2. Guertler, Benjamin & Spinler, Stefan, 2015. "When does operational risk cause supply chain enterprises to tip? A simulation of intra-organizational dynamics," Omega, Elsevier, vol. 57(PA), pages 54-69.
    3. Sawik, Tadeusz, 2015. "On the fair optimization of cost and customer service level in a supply chain under disruption risks," Omega, Elsevier, vol. 53(C), pages 58-66.
    4. Fattahi, Mohammad, 2021. "Resilient procurement planning for supply chains: A case study for sourcing a critical mineral material," Resources Policy, Elsevier, vol. 74(C).
    5. Ehsan Afshar Bakeshlou & Alireza Arshadi Khamseh & Mohammad Ali Goudarzian Asl & Javad Sadeghi & Mostafa Abbaszadeh, 2017. "Evaluating a green supplier selection problem using a hybrid MODM algorithm," Journal of Intelligent Manufacturing, Springer, vol. 28(4), pages 913-927, April.
    6. Hosseininasab, Amin & Ahmadi, Abbas, 2015. "Selecting a supplier portfolio with value, development, and risk consideration," European Journal of Operational Research, Elsevier, vol. 245(1), pages 146-156.
    7. Alikhani, Reza & Torabi, S. Ali & Altay, Nezih, 2019. "Strategic supplier selection under sustainability and risk criteria," International Journal of Production Economics, Elsevier, vol. 208(C), pages 69-82.
    8. Hammami, Ramzi & Temponi, Cecilia & Frein, Yannick, 2014. "A scenario-based stochastic model for supplier selection in global context with multiple buyers, currency fluctuation uncertainties, and price discounts," European Journal of Operational Research, Elsevier, vol. 233(1), pages 159-170.
    9. Pritee Ray & Mamata Jenamani, 2016. "Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach," Annals of Operations Research, Springer, vol. 237(1), pages 237-262, February.
    10. Pritee Ray & Mamata Jenamani, 2016. "Sourcing decision under disruption risk with supply and demand uncertainty: A newsvendor approach," Annals of Operations Research, Springer, vol. 237(1), pages 237-262, February.
    11. Salehi Sadghiani, N. & Torabi, S.A. & Sahebjamnia, N., 2015. "Retail supply chain network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 95-114.
    12. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    13. Lücker, Florian & Seifert, Ralf W., 2017. "Building up Resilience in a Pharmaceutical Supply Chain through Inventory, Dual Sourcing and Agility Capacity," Omega, Elsevier, vol. 73(C), pages 114-124.
    14. Merzifonluoglu, Yasemin, 2015. "Risk averse supply portfolio selection with supply, demand and spot market volatility," Omega, Elsevier, vol. 57(PA), pages 40-53.
    15. Scott, James & Ho, William & Dey, Prasanta K. & Talluri, Srinivas, 2015. "A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments," International Journal of Production Economics, Elsevier, vol. 166(C), pages 226-237.
    16. Preetam Basu & Soumita Ghosh & Milan Kumar, 2019. "Supplier ratings and dynamic sourcing strategies to mitigate supply disruption risks," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 46(1), pages 41-57, March.
    17. Lin, Rong-Ho, 2012. "An integrated model for supplier selection under a fuzzy situation," International Journal of Production Economics, Elsevier, vol. 138(1), pages 55-61.
    18. van der Rhee, Bo & Verma, Rohit & Plaschka, Gerhard, 2009. "Understanding trade-offs in the supplier selection process: The role of flexibility, delivery, and value-added services/support," International Journal of Production Economics, Elsevier, vol. 120(1), pages 30-41, July.
    19. Belleh Fontem & Megan Price, 2021. "Joint client selection and contract design for a risk-averse commodity broker in a two-echelon supply chain," Annals of Operations Research, Springer, vol. 307(1), pages 111-138, December.
    20. Aly Owida & P.J. Byrne & Cathal Heavey & Paul Blake & Khaled S. El-Kilany, 2016. "A simulation based continuous improvement approach for manufacturing based field repair service contracting," International Journal of Production Research, Taylor & Francis Journals, vol. 54(21), pages 6458-6477, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:2019-2034. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.