IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v68y2019ics0038012117300307.html
   My bibliography  Save this article

Decision making framework for tender evaluation and contractor selection in public organizations with risk considerations

Author

Listed:
  • Cheaitou, Ali
  • Larbi, Rim
  • Al Housani, Bashayer

Abstract

Selecting the best construction contractor plays a critical role in the success of any construction project. Moreover, in the public sector, the traditional lowest bid method is still broadly used and contracts are often awarded based on the lowest price. However, this method has been criticized by many researchers because even if it might guarantee the lowest cost for a project, it does not guarantee the maximum value in terms of time and quality. More particularly, the risk exposure during the tendering process is usually very high and the success of the construction project is strongly related to managing this risk in an appropriate way. Therefore, the selection of the most appropriate contractor should be based on a set of criteria such as technical capability, financial stability, risk, safety, etc., in addition to cost in order to avoid problems that may happen after the contract is awarded. This study aims therefore to develop a decision making framework (DMF) to assist the public organizations in selecting the most appropriate construction contractor(s). The proposed DMF uses a combination of multi-criteria decision making (MCDM) tools and fuzzy logic theory and consists of three stages. In the first stage, data envelopment analysis (DEA) is used to reduce the number of contractors, based on multiple criteria, such that only efficient contractors are considered. In the second stage, the risk factors that are related to each efficient contractor are identified and assessed using a fuzzy logic based approach. Finally, in the third stage, a bi-objective mixed integer linear programming (MILP) model is developed to select the best contractor(s) based on cost and risk and to determine the optimal quantity of work to be assigned to each selected contractor. Indeed, the proposed approach considers the multiple award contract case in which more than one contractor can be selected to share the amount of work to be performed. We assume that prior to using the proposed DMF, a pre-qualification study is conducted using multiple criteria chosen by the public organization, and only pre-qualified contractors are included in the first stage of the proposed DMF. Moreover, a case study inspired from the contractor selection process in a public organization in the United Arab Emirates (UAE) is used to show the effectiveness of the proposed approach.

Suggested Citation

  • Cheaitou, Ali & Larbi, Rim & Al Housani, Bashayer, 2019. "Decision making framework for tender evaluation and contractor selection in public organizations with risk considerations," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:soceps:v:68:y:2019:i:c:s0038012117300307
    DOI: 10.1016/j.seps.2018.02.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012117300307
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2018.02.007?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. Pablo Ballesteros-P�rez & Martin Skitmore & Eugenio Pellicer & M. Carmen Gonz�lez-Cruz, 2015. "Scoring rules and abnormally low bids criteria in construction tenders: a taxonomic review," Construction Management and Economics, Taylor & Francis Journals, vol. 33(4), pages 259-278, April.
    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. Falagario, Marco & Sciancalepore, Fabio & Costantino, Nicola & Pietroforte, Roberto, 2012. "Using a DEA-cross efficiency approach in public procurement tenders," European Journal of Operational Research, Elsevier, vol. 218(2), pages 523-529.
    4. Yang, Wei & Shi, Jinfeng & Qiao, Han & Shao, Yanmin & Wang, Shouyang, 2017. "Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 14-24.
    5. Anton, James J. & Brusco, Sandro & Lopomo, Giuseppe, 2010. "Split-award procurement auctions with uncertain scale economies: Theory and data," Games and Economic Behavior, Elsevier, vol. 69(1), pages 24-41, May.
    6. Cheaitou, Ali & van Delft, Christian & Jemai, Zied & Dallery, Yves, 2014. "Optimal policy structure characterization for a two-period dual-sourcing inventory control model with forecast updating," International Journal of Production Economics, Elsevier, vol. 157(C), pages 238-249.
    7. Gabriel, Steven A. & Kumar, Satheesh & Ordonez, Javier & Nasserian, Amirali, 2006. "A multiobjective optimization model for project selection with probabilistic considerations," Socio-Economic Planning Sciences, Elsevier, vol. 40(4), pages 297-313, December.
    8. Zedan Hatush & Martin Skitmore, 1997. "Criteria for contractor selection," Construction Management and Economics, Taylor & Francis Journals, vol. 15(1), pages 19-38.
    9. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2014. "The bi-objective Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 232(3), pages 464-478.
    10. Andersson, Christian & Månsson, Jonas & Sund, Krister, 2014. "Technical efficiency of Swedish employment offices," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 57-64.
    11. William P. Rogerson, 1994. "Economic Incentives and the Defense Procurement Process," Journal of Economic Perspectives, American Economic Association, vol. 8(4), pages 65-90, Fall.
    12. Chee Wong & Gary Holt & Patricia Cooper, 2000. "Lowest price or value? Investigation of UK construction clients' tender selection process," Construction Management and Economics, Taylor & Francis Journals, vol. 18(7), pages 767-774.
    13. Ashraf, Junaid & Uddin, Shahzad, 2016. "New public management, cost savings and regressive effects: A case from a less developed country," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 41(C), pages 18-33.
    14. Zedan Hatush & Martin Skitmore, 1997. "Evaluating contractor prequalification data: selection criteria and project success factors," Construction Management and Economics, Taylor & Francis Journals, vol. 15(2), pages 129-147.
    15. Cheaitou, Ali & van Delft, Christian, 2013. "Finite horizon stochastic inventory problem with dual sourcing: Near myopic and heuristics bounds," International Journal of Production Economics, Elsevier, vol. 143(2), pages 371-378.
    16. Christian van Delft & Ali Cheaitou & Zied Jemai & Yves Dallery, 2010. "Two-stage flexible supply contract with payback and information update," Post-Print hal-00537098, HAL.
    17. Jasper Mbachu, 2008. "Conceptual framework for the assessment of subcontractors' eligibility and performance in the construction industry," Construction Management and Economics, Taylor & Francis Journals, vol. 26(5), pages 471-484.
    18. Zied Jemai & Ali Cheaitou & Christian van Delft & Yves Dallery, 2014. "Optimal policy structure characterization for a two-period dual-sourcing inventory control model with forecast updating," Post-Print hal-01672389, HAL.
    19. Ali Cheaitou & Zied Jemai & Yves Dallery & Christian Van Delft, 2010. "Two-stage flexible supply contract with payback and information update," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 4(4), pages 471-492.
    20. Ali Cheaitou & Christian van Delft, 2013. "Finite horizon stochastic inventory problem with dual sourcing: Near myopic and heuristics bounds," Post-Print hal-00989433, HAL.
    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. Khaled Alkhaledi & Allison Arnold & Kenneth Means & In-Ju Kim & Salaheddine Bendak, 2020. "A Novel Multicriteria Decision Making Model for Sustainable Stormwater Management," Sustainability, MDPI, vol. 12(22), pages 1-19, November.
    2. Vendrell-Herrero, Ferran & Darko, Christian & Vaillant, Yancy, 2022. "Firm productivity and government contracts: The moderating role of corruption," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    3. Mehmedali Egemen, 2022. "Building Construction Clients’ Design Consultant and Contractor Selection Criteria Versus Post-Occupancy Satisfaction Levels," SAGE Open, , vol. 12(2), pages 21582440221, April.
    4. Nadeera Abdul Razak & Obuks Ejohwomu & Peter Fenn & Kamil Okedara & Babatunde Dosumu & Firdaus Muhammad-Sukki, 2021. "Identification of Health and Safety Prequalification Criteria for Contractor Selection in Construction Projects: A Systematic Review," Energies, MDPI, vol. 14(21), pages 1-17, November.
    5. Katerina Fotova Čiković & Ivana Martinčević & Joško Lozić, 2022. "Application of Data Envelopment Analysis (DEA) in the Selection of Sustainable Suppliers: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(11), pages 1-30, May.
    6. Khoso, Ali Raza & Yusof, Aminah Md & Chen, Zhen-Song & Skibniewski, Mirosław J. & Chin, Kwai-Sang & Khahro, Shabir Hussain & Sohu, Samiullah, 2022. "Comprehensive analysis of state-of-the-art contractor selection models in construction environment-A critical review and future call," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    7. Amir Karbassi Yazdi & Yong Tan & Cristi Spulbar & Ramona Birau & Jorge Alfaro, 2022. "An Approach for Supply Chain Management Contract Selection in the Oil and Gas Industry: Combination of Uncertainty and Multi-Criteria Decision-Making Methods," Mathematics, MDPI, vol. 10(18), pages 1-20, September.
    8. Georgiou, Giorgos S. & Rouvas, Constantinos & Nathanael, Demetris, 2022. "Enhancing expansion of rooftop PV systems through Mixed Integer Linear Programming and Public Tender Procedures," Renewable Energy, Elsevier, vol. 187(C), pages 347-361.
    9. Mansour Selseleh Jonban & Luis Romeral & Elyas Rakhshani & Mousa Marzband, 2023. "Flexible Smart Energy-Management Systems Using an Online Tendering Process Framework for Microgrids," Energies, MDPI, vol. 16(13), pages 1-19, June.
    10. Omid Valizadeh & Mojtaba Ghiyasi, 2023. "Assessing telecommunication contractor firms using a hybrid DEA-BWM method," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(4), pages 189-200.

    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. Cheaitou, Ali & Cheaytou, Rima, 2019. "A two-stage capacity reservation supply contract with risky supplier and forecast updating," International Journal of Production Economics, Elsevier, vol. 209(C), pages 42-60.
    2. Svoboda, Josef & Minner, Stefan & Yao, Man, 2021. "Typology and literature review on multiple supplier inventory control models," European Journal of Operational Research, Elsevier, vol. 293(1), pages 1-23.
    3. Bingsheng Liu & Tengfei Huo & Pinchao Liao & Jie Gong & Bin Xue, 2015. "A Group Decision-Making Aggregation Model for Contractor Selection in Large Scale Construction Projects Based on Two-Stage Partial Least Squares (PLS) Path Modeling," Group Decision and Negotiation, Springer, vol. 24(5), pages 855-883, September.
    4. Roni, Mohammad S. & Jin, Mingzhou & Eksioglu, Sandra D., 2015. "A hybrid inventory management system responding to regular demand and surge demand," Omega, Elsevier, vol. 52(C), pages 190-200.
    5. Han, Guanghua & Dong, Ming & Liu, Shaoxuan, 2014. "Yield and allocation management in a continuous make-to-stock system with demand upgrade substitution," International Journal of Production Economics, Elsevier, vol. 156(C), pages 124-131.
    6. Zheng, Meimei & Dong, Shuangshuang & Zhou, Yaoming & Choi, Tsan-Ming, 2023. "Sourcing decisions with uncertain time-dependent supply from an unreliable supplier," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1365-1379.
    7. Martínez, Ricardo & Sánchez-Soriano, Joaquín & Llorca, Natividad, 2022. "Assessments in public procurement procedures," Omega, Elsevier, vol. 111(C).
    8. Amirhosein Jafari, 2013. "A contractor pre-qualification model based on the quality function deployment method," Construction Management and Economics, Taylor & Francis Journals, vol. 31(7), pages 746-760, July.
    9. Ekici, Ali, 2013. "An improved model for supplier selection under capacity constraint and multiple criteria," International Journal of Production Economics, Elsevier, vol. 141(2), pages 574-581.
    10. Wang, Qingwei & Zheng, Meimei & Lee, Ka-Man & Shi, Xiaoqian & Shen, Yichi & Pan, Ershun, 2024. "Optimal product and after-sales service decisions considering risk attitudes under price-dependent uncertain demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    11. Rota, Cosimo & Zanasi, Cesare, 2011. "Sustainable Relations in International Development Cooperation Projects: The Role of Organizational Climate," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 2(1), pages 1-15, September.
    12. Boulaksil, Youssef & Hamdouch, Younes & Ghoudi, Kilani & Fransoo, Jan C., 2021. "Comparing policies for the stochastic multi-period dual sourcing problem from a supply chain perspective," Other publications TiSEM 242598b9-99de-4a3c-a1a9-4, Tilburg University, School of Economics and Management.
    13. Boulaksil, Youssef & Hamdouch, Younes & Ghoudi, Kilani & Fransoo, Jan C., 2021. "Comparing policies for the stochastic multi-period dual sourcing problem from a supply chain perspective," International Journal of Production Economics, Elsevier, vol. 232(C).
    14. Akinkunmi Olutayo Gabriel & Aghimien Douglas Omoregie & Awodele Oluwaseyi Alabi, 2018. "Appraising the use of labour-only procurement system for building construction in Nigeria," Organization, Technology and Management in Construction, Sciendo, vol. 10(1), pages 1719-1726, May.
    15. Andove Wilson Mwangu & Mike Amuhaya Iravo, 2015. "How Monitoring and Evaluation Affects the Outcome of Constituency Development Fund Projects in Kenya: A Case Study of Projects in Gatanga Constituency," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 5(3), pages 13-31, March.
    16. Roni, Mohammad S. & Eksioglu, Sandra D. & Jin, Mingzhou & Mamun, Saleh, 2016. "A hybrid inventory policy with split delivery under regular and surge demand," International Journal of Production Economics, Elsevier, vol. 172(C), pages 126-136.
    17. Patra, T. Devi Prasad & Jha, J.K., 2021. "A two-period newsvendor model for prepositioning with a post-disaster replenishment using Bayesian demand update," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    18. Zhang, Bin & Duan, Dongxia & Ma, Yurui, 2018. "Multi-product expedited ordering with demand forecast updates," International Journal of Production Economics, Elsevier, vol. 206(C), pages 196-208.
    19. Nassimbeni, Guido, 1996. "Factors underlying operational JIT purchasing practices: Results of an empirical research," International Journal of Production Economics, Elsevier, vol. 42(3), pages 275-288, April.
    20. Pishchulov, Grigory & Trautrims, Alexander & Chesney, Thomas & Gold, Stefan & Schwab, Leila, 2019. "The Voting Analytic Hierarchy Process revisited: A revised method with application to sustainable supplier selection," International Journal of Production Economics, Elsevier, vol. 211(C), pages 166-179.

    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:eee:soceps:v:68:y:2019:i:c:s0038012117300307. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    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.