A Bidding Assessment Framework using CRITIC and MABAC Methods
Received: 21 February 2025 | Revised: 24 March 2025 | Accepted: 28 March 2025 | Online: 18 April 2025
Corresponding author: Ahmed Reyadh Radhi
Abstract
The bidding process is instrumental for contractors and ensures work continuity and company survival. Even if the decision made to proceed with work contracting is confirmed, bidding preparation is one of the main factors effecting profit percentage. A bidding system must be built with high flexibility in order to be widely applicable and able to deal with data diversity. This paper introduces a new application of MABAC and CRITIC methods to cope with this need. The assessment framework consists of multi-attributive border approximation area comparison and criteria importance through inter-criteria correlation. A comparison made between the results gained from the proposed framework and the conventional process reveals a major difference in preference results.
Keywords:
MABAC, CRITIC, MARCOS, bidding process, bidders, decision support techniquesDownloads
References
M. O. Ahmed and I. H. El-adaway, "Data-Driven Analysis of Construction Bidding Stage–Related Causes of Disputes," Journal of Management in Engineering, vol. 39, no. 5, Sep. 2023, Art. no. 04023026. DOI: https://doi.org/10.1061/JMENEA.MEENG-5426
P. M. Silva, N. Domingo, and N. A. N. A. Ali, "Causes of disputes in the construction industry – a systematic literature review," Journal of Financial Management of Property and Construction, vol. 29, no. 2, pp. 193–210, Sep. 2023. DOI: https://doi.org/10.1108/JFMPC-03-2023-0012
Z.-S. Chen, X. Zhang, W. Pedrycz, X.-J. Wang, and M. J. Skibniewski, "Bid evaluation in civil construction under uncertainty: A two-stage LSP-ELECTRE III-based approach," Engineering Applications of Artificial Intelligence, vol. 94, Sep. 2020, Art. no. 103835. DOI: https://doi.org/10.1016/j.engappai.2020.103835
N. A. Ramadhan and S. M. Rasheed, "Modeling a Computer Program for Evaluating the Construction Consulting Bids According to the Iraqi Standard Bidding Documents," E3S Web of Conferences, vol. 318, 2021, Art. no. 02006. DOI: https://doi.org/10.1051/e3sconf/202131802006
Republic of Iraq: Standard bidding documents for executing the medium works contracts. https://mop.gov.iq/wp-content/uploads/2024/01/%D8%A7%D9%84%D9%88%D8%AB%D8%A7%D8%A6%D9%82-%D8%A7%D9%84%D9%82%D9%8A%D8%A7%D8%B3%D9%8A%D8%A9-%D9%84%D8%AA%D9%86%D9%81%D9%8A%D8%B0-%D8%B9%D9%82%D9%88%D8%AF-%D8%A7%D9%84%D8%A7%D8%B4%D8%BA%D8%A7%D9%84-%D8%A7%D9%84%D9%85%D8%AA%D9%88%D8%B3%D8%B7%D8%A9-en.pdf.
I. Marjanović and Ž. Popović, "MCDM Approach for Assessment of Financial Performance of Serbian Banks," in Business Performance and Financial Institutions in Europe: Business Models and Value Creation Across European Industries, A. Horobet, P. Polychronidou, and A. Karasavvoglou, Eds.Springer International Publishing, 2020, pp. 71–90. DOI: https://doi.org/10.1007/978-3-030-57517-5_5
Z. Fang, "System-of-Systems Architecture Selection: A Survey of Issues, Methods, and Opportunities," IEEE Systems Journal, vol. 16, no. 3, pp. 4768–4779, Sep. 2022. DOI: https://doi.org/10.1109/JSYST.2021.3119294
X. Wang, F. A. F. Ferreira, and P. Yan, "A multi-objective competency-based decision support system for the assignment of internal auditors to multiple projects," Annals of Operations Research, vol. 338, no. 1, pp. 303–334, Jul. 2024. DOI: https://doi.org/10.1007/s10479-024-05855-3
S. Zeng, J. Zhou, C. Zhang, and J. M. Merigó, "Intuitionistic fuzzy social network hybrid MCDM model for an assessment of digital reforms of manufacturing industry in China," Technological Forecasting and Social Change, vol. 176, Mar. 2022, Art. no. 121435. DOI: https://doi.org/10.1016/j.techfore.2021.121435
M. Dotoli, N. Epicoco, and M. Falagario, "Multi-Criteria Decision Making techniques for the management of public procurement tenders: A case study," Applied Soft Computing, vol. 88, Mar. 2020, Art. no. 106064. DOI: https://doi.org/10.1016/j.asoc.2020.106064
N. Mohan and R. Agrawal, "Evaluation Indian Technical Institutions using VIKOR Method," in 2023 1st International Conference on Cognitive Computing and Engineering Education (ICCCEE), Pune, India, Apr. 2023. DOI: https://doi.org/10.1109/ICCCEE55951.2023.10424581
R. T. Mergawy, H. E. Hosny, and A. S. Abdelazeem, "Decision Support Model for Contractor Selection," The Open Civil Engineering Journal, vol. 17, Mar. 2023, Art. no. e187414952301270. DOI: https://doi.org/10.2174/18741495-v17-e230215-2022-51
V. K. Acheamfour, Adjei-Kumi ,T., and E. and Kissi, "Contractor selection: a review of qualification and pre-qualification systems," International Journal of Construction Management, vol. 23, no. 2, pp. 338–348, Jan. 2023. DOI: https://doi.org/10.1080/15623599.2020.1868092
P. O. Kukoyi, I. C. Osuizugbo, H. S. Yohanna, U. E. Edike, and I. E. Ohiseghame, "Pre-Qualification of Selecting Construction Project Contractors Using Health and Safety Criteria," Journal of Engineering, Project, and Production Management, vol. 11, no. 1, pp. 30–36, 2021.
T. Cai, M. Dong, K. Chen, and T. Gong, "Methods of participating power spot market bidding and settlement for renewable energy systems," Energy Reports, vol. 8, pp. 7764–7772, Nov. 2022. DOI: https://doi.org/10.1016/j.egyr.2022.05.291
D. I. Božanić, D. S. Pamučar, and S. M. Karović, "Application the MABAC method in support of decision-making on the use of force in a defensive operation," Tehnika, vol. 71, no. 1, pp. 129–136, 2016. DOI: https://doi.org/10.5937/tehnika1601129B
İ. Özaytürk and E. K. Özekenci, "Analysis of Trade Competitiveness of the World’s Leading Textiles Exporters by Hybrid MCDM Methods," İşletme Araştırmaları Dergisi, vol. 16, no. 1, pp. 166–186, Mar. 2024. DOI: https://doi.org/10.20491/isarder.2024.1784
Q. Li, "Green Supply Chain Optimization with Fuzzy MCDM for Economic Growth," International Journal of Simulation Modelling, vol. 22, no. 4, pp. 690–700, Dec. 2023. DOI: https://doi.org/10.2507/IJSIMM22-4-CO16
K. Chatterjee, E. K. Zavadskas, J. Tamošaitienė, K. Adhikary, and S. Kar, "A Hybrid MCDM Technique for Risk Management in Construction Projects," Symmetry, vol. 10, no. 2, Feb. 2018, Art. no. 46. DOI: https://doi.org/10.3390/sym10020046
F. Jahan, M. Soni, S. Wakeel, and S. Ahmad, "Selection of Automotive Brake Material Using Different MCDM Techniques and Their Comparisons," Journal of Engineering Science and Technology Review, vol. 15, no. 1, pp. 24–33, 2022. DOI: https://doi.org/10.25103/jestr.151.04
S. Singh Sivam Sundarlingam Paramasivam, D. Kumaran, H. Natarajan, G. Sai Krishnan, and S. E. Sairaghav, "Process parameter optimization of key machining parameters of mg alloy with cryogenic treated tools by MABAC approach," Materials Today: Proceedings, vol. 47, pp. 7149–7154, Jan. 2021. DOI: https://doi.org/10.1016/j.matpr.2021.06.316
J. Wang, G. Wei, C. Wei, and Y. Wei, "MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment," Defence Technology, vol. 16, no. 1, pp. 208–216, Feb. 2020. DOI: https://doi.org/10.1016/j.dt.2019.06.019
T. Adar, Y. Ok, and E. K. Delice, "Selection of on-Site Energy Generation Technology with a New MCDM Approach Using MABAC & AHP," in International Conference on Industrial Engineering and Technology Management, Dallas, TX, USA, Apr. 2017.
A. T. Nguyen, D. B. Vu, V. T. Nguyen, X. H. Le, and M. C. Nguyen, "Determination of Best Input Parameters for Internal Grinding SKD11 Tool Steel using MCDM," Engineering, Technology & Applied Science Research, vol. 15, no. 1, pp. 20190–20196, Feb. 2025. DOI: https://doi.org/10.48084/etasr.9505
S. Komsiyah, Ayuliana, and D. A. Balqis, "Analysis of decision support system for determining industrial sub-district using DEMATEL-MABAC methods," Procedia Computer Science, vol. 216, pp. 499–509, Jan. 2023. DOI: https://doi.org/10.1016/j.procs.2022.12.162
A. R. Krishnan, M. M. Kasim, R. Hamid, and M. F. Ghazali, "A Modified CRITIC Method to Estimate the Objective Weights of Decision Criteria," Symmetry, vol. 13, no. 6, Jun. 2021, Art. no. 973. DOI: https://doi.org/10.3390/sym13060973
Ž. Stević, D. Pamučar, A. Puška, and P. Chatterjee, "Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS)," Computers & Industrial Engineering, vol. 140, Feb. 2020, Art. no. 106231. DOI: https://doi.org/10.1016/j.cie.2019.106231
Downloads
How to Cite
License
Copyright (c) 2025 Ahmed Reyadh Radhi, Yasser Sahib Nassar, Hassan Kamal Alhilli

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.