A Multi-Criteria Decision-Making Framework Based on the PROMETHEE Method for Selecting Support Service Providers in Governmental Organizations (Case Study: Foundation of Martyrs and Veterans Affairs)

Authors

  • Khadijeh Ghaziani * Department of Basic Sciences, Ayandegan University, Tonekabon, Iran. https://orcid.org/0000-0001-7860-3010
  • Mohammad Koloukhi Department of Business Management, Ayandegan University, Tonekabon, Iran.

https://doi.org/10.22105/raise.v3i2.90

Abstract

In the digital era, information technology support services serve as the backbone of organizational processes and play a vital role in ensuring the continuity of operations within public institutions. The Foundation of Martyrs and Veterans Affairs, as an organization dedicated to serving the veteran community, has become increasingly dependent on stable and secure information systems. However, selecting an appropriate contractor for maintaining these systems represents a complex challenge due to the diversity of evaluation criteria, budgetary constraints, and governmental compliance requirements. Traditional tender evaluation methods are often one-dimensional and incapable of effectively resolving conflicts among cost, quality, risk, and legal compliance considerations. Multi-Criteria Decision-Making (MCDM) approaches provide an innovative solution to this issue; nevertheless, their application within the Iranian public sector, particularly in the domain of IT support services, remains limited. The present study aims to design a decision-making framework based on the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) method for selecting IT maintenance service contractors in public organizations. Initially, 42 sub-criteria were identified across six principal dimensions. Subsequently, through three rounds of the Delphi method involving 15 experts, these were reduced to 20 final criteria. A hybrid weighting approach combining expert judgment and Shannon entropy identified service quality, technology, and economic factors as the highest-priority dimensions. Five contractors were then ranked using the PROMETHEE II method. The robustness of the proposed model was confirmed through sensitivity analysis, Geometrical Analysis for Interactive Aid (GAIA) analysis, and complete correlation with the SAW method. The proposed framework addresses the lack of indigenous methodologies in the governmental sector and provides a practical tool for risk reduction and cost optimization. By integrating the Delphi method, hybrid weighting techniques, and multi-layer validation procedures, the model offers an operational instrument for governmental decision-makers to achieve transparent, sustainable, and optimal contractor selection. The findings facilitate targeted contractor selection and support sustainable policy-making.

Keywords:

Multi-criteria decision-making, Preference ranking organization method for enrichment evaluations method, Supplier selection, Support services, Delphi method

References

  1. [1] Chang, J., Li, W., Zhou, Y., Zhang, P., & Zhang, H. (2022). Impact of public service quality on the efficiency of the water industry: evidence from 147 cities in China. Sustainability, 14(22), 15160. https://doi.org/10.3390/su142215160
  2. [2] Kim, B. S., Suh, B., Kim, K. I., Seo, I. J., Lee, H. B., & Gong, J. S. (2022). An enhanced tree routing through multi-criteria decision making over wireless sensor networks. 2022 IEEE 19th international conference on mobile ad hoc and smart systems (MASS) (pp. 570-576). IEEE. https://doi.org/10.1109/MASS56207.2022.00085
  3. [3] Chen, Q. (2024). Essays on public procurement and firms in china [Thesis]. https://escholarship.org/content/qt46c4b0jq/qt46c4b0jq_noSplash_184a01cd7da6f4a1a3e0a98639f22b68.pdf
  4. [4] Kim, B.S., Shah, B., & Kim, K.I. (2023). Adaptive scheduling for multi-objective resource allocation through multi-criteria decision-making and deep Q-network in wireless body area networks. Journal of ambient intelligence and humanized computing, 14(12), 16255–16268. https://doi.org/10.1007/s12652-022-03846-5
  5. [5] Habetemeherit, A. B., Mengistu, D. G., Sorsa, F. T., & Tesfaye, B. Z. (2026). Causes and impacts of public construction projects’ contract terminations. Engineering, construction and architectural management, 33(6), 4330–4346. https://doi.org/10.1108/ECAM-09-2024-1217
  6. [6] Alshamsi, A. M., El-Kassabi, H., Serhani, M. A., & Bouhaddioui, C. (2023). A multi-criteria decision-making (MCDM) approach for data-driven distance learning recommendations. Education and information technologies, 28(8), 10421–10458. https://doi.org/10.1007/s10639-023-11589-9%0A%0A
  7. [7] Mehregan, F., Hatami, M. R., & Shohani, A. (2024). Explaining the components of a modern administrative system in order to establish a federal structure in Iran. Parliament and strategy, 31(117), 39–74. (In Persian). https://doi.org/10.22034/mr.2023.5376.5134
  8. [8] Tavakoli, G., Zaheri, M. M., & Hamidifar, Z. (2021). Modeling the behavioral challenges and obstacles of employees in establishing a desirable organizational culture in government organizations. Strategic studies of the basij, 24(90), 79–102. (In Persian). https://dor.isc.ac/dor/20.1001.1.1735501.1400.24.90.3.3
  9. [9] Sanayei, A., Mousavi, S. F., & Yazdankhah, A. (2010). Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert systems with applications, 37(1), 24–30. https://doi.org/10.1016/j.eswa.2009.04.063
  10. [10] Ding, Y., Tu, Y., Pu, J., & Qiu, L. (2021). Environmental factors in operations management: The impact of air quality on product demand. Production and operations management, 30(9), 2910–2924. https://doi.org/10.1111/poms.13410
  11. [11] Peterková, J., & Franek, J. (2018). Decision making support for managers in innovation management: A PROMETHEE approach. International journal of innovation, 6(3), 256–274. https://doi.org/10.5585/iji.v6i3.236
  12. [12] Taherdoost, H., & Madanchian, M. (2023). Using PROMETHEE method for multi-criteria decision making: applications and procedures. Iris journal of economics & business management, 1(1). https://ssrn.com/abstract=4464669
  13. [13] Kaplan, P. O., & Ranjithan, S. R. (2007). A new MCDM approach to solve public sector planning problems. 2007 IEEE symposium on computational intelligence in multi-criteria decision-making (pp. 153-159). IEEE. https://doi.org/10.1109/MCDM.2007.369430
  14. [14] Essien, E., Lodorfos, G., & Kostopoulos, I. (2019). Antecedents of supplier selection decisions in the public sector in Nigeria. Journal of public procurement, 19(1), 15–45. https://doi.org/10.1108/JOPP-03-2019-023
  15. [15] Yildiz, A., & Yayla, A. Y. (2015). Multi-criteria decision-making methods for supplier selection: A literature review. South African journal of industrial engineering, 26(2), 158–177. https://doi.org/10.7166/26-2-1010
  16. [16] Ried, L., Eckerd, S., Kaufmann, L., & Carter, C. (2021). Spillover effects of information leakages in buyer--supplier--supplier triads. Journal of operations management, 67(3), 280–306. https://doi.org/10.1002/joom.1116
  17. [17] Koufteros, X., Vickery, S. K., & Dröge, C. (2012). The effects of strategic supplier selection on buyer competitive performance in matched domains: Does supplier integration mediate the relationships? Journal of supply chain management, 48(2), 93–115. https://doi.org/10.1111/j.1745-493X.2012.03263.x
  18. [18] 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. https://doi.org/10.1016/j.ejor.2009.05.009
  19. [19] Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: A literature review. Journal of cleaner production, 98, 66–83. https://doi.org/10.1016/j.jclepro.2013.06.046
  20. [20] Dotoli, M., Epicoco, N., & Falagario, M. (2020). Multi-Criteria Decision Making techniques for the management of public procurement tenders: A case study. Applied soft computing, 88, 106064. https://doi.org/10.1016/j.asoc.2020.106064
  21. [21] Essien, E. E., Kostopoulos, I., Konstantopoulou, A., & Lodorfos, G. (2019). Do ethical work climates influence supplier selection decisions in public organizations? The moderating roles of party politics and personal values. International journal of public sector management, 32(6), 653–670. https://doi.org/10.1108/IJPSM-10-2018-0227
  22. [22] Anelli, D., Pierluigi, M., Tiziana, A., Tajani, F., & others. (2025). Structuring multi-criteria decision approaches for public procurement: Methods, standards and applications. Systems, 13(9). https://iris.uniroma1.it/bitstream/11573/1745001/1/Tajani_Structuring-Multi-Criteria-Decision_2025.pdf
  23. [23] Alastal, H., Sharaf, A., Mahmoud, S., Alsaidi, O., & Bahroun, Z. (2025). Integrating multiple criteria decision-making techniques in sustainable supplier selection: A comprehensive review. Decision making: applications in management and engineering, 8(1), 380–400. https://doi.org/10.31181/dmame8120251243
  24. [24] Sahoo, S. K., Goswami, S. S., & Halder, R. (2024). Supplier selection in the age of industry 4.0: A review on MCDM applications and trends. Decision making advances, 2(1), 32–47. https://doi.org/10.31181/dma21202420
  25. [25] Weber, C. A., Current, J. R., & Benton, W. C. (1991). Vendor selection criteria and methods. European journal of operational research, 50(1), 2–18. https://doi.org/10.1016/0377-2217(91)90033-R
  26. [26] Zhan, Y., Chung, L., Lim, M. K., Ye, F., Kumar, A., & Tan, K. H. (2021). The impact of sustainability on supplier selection: A behavioural study. International journal of production economics, 236, 108118. https://doi.org/10.1016/j.ijpe.2021.108118
  27. [27] Govindan, K., Khodaverdi, R., & Jafarian, A. (2013). A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. Journal of cleaner production, 47, 345–354. https://doi.org/10.1016/j.jclepro.2012.04.014
  28. [28] Razmak, J., & Aouni, B. (2015). Decision support system and multi-criteria decision aid: a state of the art and perspectives. Journal of multi-criteria decision analysis, 22(1–2), 101–117. https://doi.org/10.1002/mcda.1530
  29. [29] Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European journal of operational research, 200(1), 198–215. https://doi.org/10.1016/j.ejor.2009.01.021
  30. [30] Zeleny, M., & Cochrane, J. L. (1982). Multiple criteria decision making. McGraw-Hill New York. https://books.google.com/books/about/Multiple_Criteria_Decision_Making.html?id=vTayAAAAIAAJ
  31. [31] Abdullah, L., Chan, W., & Afshari, A. (2019). Application of PROMETHEE method for green supplier selection: A comparative result based on preference functions. Journal of industrial engineering international, 15(2), 271–285. https://doi.org/10.1007/s40092-018-0289-z%0A%0A
  32. [32] Belton, V., & Stewart, T. (2012). Multiple criteria decision analysis: An integrated approach. Springer Science & Business Media. https://books.google.com/books?hl=en&lr=&id=AYYHCAAAQBAJ&oi=fnd&pg=PP11&dq=
  33. [33] Vaidya, O. S., & Kumar, S. (2006). Analytic hierarchy process: An overview of applications. European journal of operational research, 169(1), 1–29. https://doi.org/10.1016/j.ejor.2004.04.028
  34. [34] Azadfallah, M. (2017). Evaluation and selection of suppliers in the supply chain using the extended group PROMETHEE I procedures. International journal of supply chain and operations resilience, 3(1), 56–76. https://doi.org/10.1504/IJSCOR.2017.087161
  35. [35] Hwang, C.L., & Lin, M.J. (2012). Group decision making under multiple criteria: Methods and applications. Springer Science & Business Media. https://books.google.com/books?hl=en&lr=&id=F6r7CAAAQBAJ&oi=fnd&pg=PA1&dq=%5B35%5D+%0
  36. [36] Wu, W., Xu, Z., & Kou, G. (2020). Evaluation of group decision making based on group preferences under a multi-criteria environment. Technological and economic development of economy, 26(6), 1187–1212. https://doi.org/10.3846/tede.2020.13378
  37. [37] Fujita, T. (2025). Hyperfuzzy and superhyperfuzzy promethee methods for multi-criteria decision-making in it service management. https://doi.org/10.36227/techrxiv.174970457.78480523/v1
  38. [38] Agrawal, N. (2022). Multi-criteria decision-making toward supplier selection: Exploration of PROMETHEE II method. Benchmarking: an international journal, 29(7), 2122–2146. https://doi.org/10.1108/BIJ-02-2021-0071
  39. [39] Akram, M., Shumaiza, & Al-Kenani, A. N. (2020). Multi-criteria group decision-making for selection of green suppliers under bipolar fuzzy PROMETHEE process. Symmetry, 12(1), 77. https://doi.org/10.3390/sym12010077
  40. [40] Liu, F., Ji, X., & Gao, J. (2020). Extended SQ-Coons surface and its application on fairing automobile surface design. Mathematical problems in engineering, 2020(1), 4912978. https://doi.org/10.1155/2020/4912978
  41. [41] Goodarzi, A., & Gholamian, M. (2024). Selecting green suppliers with the new Prometheus-Abri group decision-making method; Case study: a petroleum products manufacturing company. Journal of modern research in decision making, 9(2), 63–97. https://journal.saim.ir/article_715187_8c974c5152d912f8dcacdebd849f474d.pdf
  42. [42] Hosseinpour, A., & Mahmoudabadi, A. (2017). Providing a method for multi-criteria decision-making to select the best supplier in the supply chain based on the joint opinions of suppliers and employers (Case study: Selecting the best university website design company). The second international conference on knowledge-based research in computer engineering and information technology. (In Persian). https://civilica.com/doc/696174
  43. [43] Heydari Dehoui, B. (2016). Presenting a hybrid multi-criteria decision-making model for selecting a knowledge management outsourcing provider [Thesis]. (In Persian). https://elmnet.ir/doc/11171400-26386
  44. [44] Brans, J. P., & Vincke, P. (1985). Note—a preference ranking organisation method: (The PROMETHEE method for multiple criteria decision-making). Management science, 31(6), 647–656. https://doi.org/10.1287/mnsc.31.6.647
  45. [45] Fountzoula, C., & Aravossis, K. (2022). Decision-Making methods in the public sector during 2010--2020: A systematic review. Advances in operations research, 2022(1), 1750672. https://doi.org/10.1155/2022/1750672
  46. [46] Ishizaka, A., & Labib, A. (2011). Review of the main developments in the analytic hierarchy process. Expert systems with applications, 38(11), 14336–14345. https://doi.org/10.1016/j.eswa.2011.04.143
  47. [47] Velasquez, M., & Hester, P. T. MCDM methods analysis: Advantages, disadvantages & applications. International journal of operations research, 10(2), 56–66. https://studylib.net/doc/8889609/an-analysis-of-multi-criteria-decision-making-methods
  48. [48] Beheshti, F., & Nabayi, H. (2023). Presenting a model for evaluating and selecting sustainable third-party logistics service providers in the supply chain based on a combined approach of fuzzy analytic hierarchy process and the Cocosu technique (case study: Dairy industry). Quarterly journal of the iranian management sciences association, 17(68), 45–74. (In Persian). https://civilica.com/doc/1691083
  49. [49] Brans, J.P., & Mareschal, B. (1994). The PROMCALC & GAIA decision support system for multicriteria decision aid. Decision support systems, 12(4–5), 297–310. https://doi.org/10.1016/0167-9236(94)90048-5

Downloads

Published

2026-05-30

Issue

Vol. 3 No. 2 (2026): Research Annals of Industrial and Systems Engineering

Section

Articles

How to Cite

Ghaziani, K. ., & Koloukhi, M. . (2026). A Multi-Criteria Decision-Making Framework Based on the PROMETHEE Method for Selecting Support Service Providers in Governmental Organizations (Case Study: Foundation of Martyrs and Veterans Affairs). Research Annals of Industrial and Systems Engineering, 3(2), 98-124. https://doi.org/10.22105/raise.v3i2.90

Similar Articles

1-10 of 36

You may also start an advanced similarity search for this article.