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An Integrated Decision Support Model Based on BWM and Fuzzy-VIKOR Techniques for Contractor Selection in Construction Projects

Author

Listed:
  • Aziz Naghizadeh Vardin

    (Department of Civil Engineering, Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin 3414896818, Iran)

  • Ramin Ansari

    (Department of Civil Engineering, Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin 3414896818, Iran)

  • Mohammad Khalilzadeh

    (CENTRUM Católica Graduate Business School, Pontificia Universidad Católica del Perú, Lima 15023, Peru)

  • Jurgita Antucheviciene

    (Department of Construction Management and Real Estate, Institute of Sustainable Construction, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania)

  • Romualdas Bausys

    (Department of Graphical Systems, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania)

Abstract

Sustainable development of any country to some extent depends on successful accomplishment of construction projects, particularly infrastructures. Contractors have a key role in the success of these projects. Hence, the selection of a competent contractor as a complicated and hard decision process has a vital importance in the destiny of any construction project. Contractor selection is in essence a multicriteria decision-making that ought to encompass so many aspects of the project and the client’s requirements on one hand and the capabilities and past records of the contractors on the other hand. Failure in selecting a competent contractor may cause time and cost overruns; quality shortcomings; increasing in claims, disputes and change orders; and even failure of the project. In spite of deficiencies of selecting a contractor by the rule of “the lowest bid price”, it still prevails in many countries including Iran. In this paper, a new contractor selection model based on the best-worst method (BWM) and well-known Fuzzy-VIKOR techniques is proposed as a solution to overcome the deficiencies of the traditional “lowest bid price” rule. An illustrative example of a water channel construction project verified the applicability of the proposed model in practice.

Suggested Citation

  • Aziz Naghizadeh Vardin & Ramin Ansari & Mohammad Khalilzadeh & Jurgita Antucheviciene & Romualdas Bausys, 2021. "An Integrated Decision Support Model Based on BWM and Fuzzy-VIKOR Techniques for Contractor Selection in Construction Projects," Sustainability, MDPI, vol. 13(12), pages 1-28, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6933-:d:578407
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    References listed on IDEAS

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    1. Zydrune Morkunaite & Romualdas Bausys & Edmundas Kazimieras Zavadskas, 2019. "Contractor Selection for Sgraffito Decoration of Cultural Heritage Buildings Using the WASPAS-SVNS Method," Sustainability, MDPI, vol. 11(22), pages 1-25, November.
    2. Hassan Hashemi & Seyed Meysam Mousavi & Edmundas Kazimieras Zavadskas & Alireza Chalekaee & Zenonas Turskis, 2018. "A New Group Decision Model Based on Grey-Intuitionistic Fuzzy-ELECTRE and VIKOR for Contractor Assessment Problem," Sustainability, MDPI, vol. 10(5), pages 1-19, May.
    3. Edmundas Kazimieras Zavadskas & Zenonas Turskis & Jolanta Tamošaitiene, 2008. "Contractor selection of construction in a competitive environment," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 9(3), pages 181-187, August.
    4. Min-Yuan Cheng & Shu-Hua Yeh & Woei-Chyi Chang, 2020. "Multi-Criteria Decision Making of Contractor Selection in Mass Rapid Transit Station Development Using Bayesian Fuzzy Prospect Model," Sustainability, MDPI, vol. 12(11), pages 1-32, June.
    5. Liang, Fuqi & Brunelli, Matteo & Rezaei, Jafar, 2020. "Consistency issues in the best worst method: Measurements and thresholds," Omega, Elsevier, vol. 96(C).
    6. Willem Karel M. Brauers & Edmundas Kazimieras Zavadskas & Zenonas Turskis & Tatjana Vilutiene, 2008. "Multi‐objective contractor's ranking by applying the Moora method," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 9(4), pages 245-255, July.
    7. 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.
    8. Zedan Hatush & Martin Skitmore, 1997. "Criteria for contractor selection," Construction Management and Economics, Taylor & Francis Journals, vol. 15(1), pages 19-38.
    9. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    10. Patrick Sik-Wah Fong & Sonia Kit-Yung Choi, 2000. "Final contractor selection using the analytical hierarchy process," Construction Management and Economics, Taylor & Francis Journals, vol. 18(5), pages 547-557.
    11. Eddie W. L. Cheng & Heng Li, 2004. "Contractor selection using the analytic network process," Construction Management and Economics, Taylor & Francis Journals, vol. 22(10), pages 1021-1032, December.
    12. Sameh Monir El-Sayegh, 2009. "Multi-criteria decision support model for selecting the appropriate construction management at risk firm," Construction Management and Economics, Taylor & Francis Journals, vol. 27(4), pages 385-398.
    13. K. C. Lam & Tiesong Hu & S. Thomas Ng & Martin Skitmore & S. O. Cheung, 2001. "A fuzzy neural network approach for contractor prequalification," Construction Management and Economics, Taylor & Francis Journals, vol. 19(2), pages 175-188.
    14. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    15. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    16. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    17. Zedan Hatush & Martin Skitmore, 1997. "Assessment and evaluation of contractor data against client goals using PERT approach," Construction Management and Economics, Taylor & Francis Journals, vol. 15(4), pages 327-340.
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    1. Ramin Ansari & Mohammad Khalilzadeh & Roohollah Taherkhani & Jurgita Antucheviciene & Darius Migilinskas & Shohreh Moradi, 2022. "Performance Prediction of Construction Projects Based on the Causes of Claims: A System Dynamics Approach," Sustainability, MDPI, vol. 14(7), pages 1-19, March.

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