An Integrated Model for Selecting and Evaluating Logistics Outsourcing Decisions using AHP and PROMETHEE II
Article Sidebar
Main Article Content
Abstract
Given the increasing demand and a number of Logistics Service Providers (LSPs) available in the market, it becomes challenging for the company to select and evaluate the best LSP objectively. Current decision-making is merely based on judgements and historical experience. Therefore, a proper and objective selection tool is essential for decision makers or managers to assess potential LSPs. The present study aims at designing a holistic and user-friendly decision-making framework and tool using a hybrid AHP-PROMETHEE II to assess and select potential LSPs. The present study proposed decision-making tool deploying hybrid AHP and PROMETHEE II as part of multi-criteria decision making (MCDM). The proposed hybrid approach is necessary to improve the weaknesses of AHP by pairing with PROMETHEE II to overcome the problem of rank reversals and the breach of a so-called order preservation criterion (COP). Hence, a hybrid AHP-PROMETHEE II was developed. The model was designed using VBA solver in spreadsheet in XML format which can be used in any different multi-criteria decision-making problem. To demonstrate the applicability and efficacy of the hybrid approach, the hybrid approach was implemented in a hair care manufacturing company GHD UK in order to identify the most suitable LSP company. AHP was used to determine the criteria weight, then PROMETHEE II was used to define the final ranking of each alternative. To balance the numerous measurements in this framework, multiple criteria and multiple stakeholders were evaluated. A comprehensive literature review was conducted in determining the identification and assessment of criteria. AHP model was performed in determining the criteria weight, and expert’s opinions from the case company are taken into consideration. The output of the AHP workbook was the criteria weights. Once the criteria weights were calculated, the PROMETHEE method was performed to evaluate and rank all the alternatives. The findings indicate that the holistic developed framework was an effective and robust tool to solve a strategic logistics outsourcing decision making.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
BCG Global. (2020). How to select a Logistics Service Provider? [online] Available at https://bciglobal.com/en/how-to-select-a-logistics-service-provider-.
Dutta, P., Borah, G. (2021). Multicriteria decision making approach using an efficient novel similarity measure for generalised trapezoidal fuzzy numbers. Journal Ambient Intelligence and Humanized Computing, 14, 1507-1529.
Godsmark, J. and Richards, G. (2019). The Logistics Outsourcing Handbook. 1st ed. Kogan Page. Available at: https://www.perlego.com/book/1589905/the-logistics-outsourcing-handbook-pdf (Accessed: 25 September 2021).
Gürcan, OF., Yazıcı,I., Beyca, OF., Arslan, CY., Eldemir, F. (2016). Third Party Logistics (3PL) Provider Selection with AHP Application. Procedia - Social and Behavioral Sciences, 235, 226-234.
Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16-24.
Karrapan, C. (2017). Benchmarking criteria for evaluating third-party logistics providers in South Africa. Journal of Transport and Supply Chain Management, 11(1), 1-10.
Langley, C. J. (2022). Third-party logistics study the state of logistics outsourcing–Results and findings of the 26th annual study. Capgemini Consulting. [online] Available at: https://www.3plstudy.com/ntt3pl/nttds_3pl.home , Accessed at 3rd June 2022.
Liu, Y., Zhou, P., Li, L., and Zhu, F. (2020). An interactive decision-making method for third-party logistics provider selection under hybrid multi-criteria. Symmetry, 12(5), 729.
Majdi, I. (2013). Comparative evaluation of PROMETHEE and ELECTRE with application to sustainability assessment.
Polat, T., Matthijs, P., Jansen, P. (2017). How Do Development HR Practices Contribute to Employees’ Motivation to Continue Working Beyond Retirement Age?. Work, Aging and Retirement, 3, 366–378.
Saaty, T.L. (1994). How to make a decision: the Analytic Hierarchy Process. Interfaces, 24(6), 19–43.
Singh, K. R., Gunasekaran, A., & Kumar, P. (2017). Third party logistic (3PL) selection for cold chain management: A fuzzy AHP and fuzzy TOPSIS approach. Annals of Operations Research, 267(1-2), 531–553.
Statista. (2022). Number of private sector businesses in the United Kingdom from 2000 to 2021, [online] Available at: https://www.statista.com/statistics/1111387/number-of-businesses-in-the-uk/. Accessed on: 3 June 2022.
Sun, X., Sun, L. (2022) On attribute importance measure and its application to supplier selection. International Journal of Machine Learning and Cybernetics, 13, 1167–1178.
Suratos, R., Srinon R., (2021) Fuzzy AHP Signifies Criteria Influencing Third Party Logistics Selection in Outsourcing Decisions of Freight Forwarding Company. IEOM Society International, 1865-1875.
Tang, M., & Liao, H., (2021) From conventional group decision making to large-scale group decision making: What are the challenges and how to meet them in big data era? A state-of-the-art survey. Omega, 100.