Joint-Venture Contractor Selection Using Competitive and Collaborative Criteria with Uncertainty
Publication: Journal of Construction Engineering and Management
Volume 145, Issue 2
Abstract
Selecting an appropriate joint venture contractor (JVC) is paramount to the success of large-scale infrastructure projects. The purpose of this paper is to develop a unified approach for JVC selection. The proposed approach integrates competitive information and collaborative information, focusing on the hesitant fuzzy variables of the bid evaluators. An optimization model is established based on the maximizing deviation (MD) principle to determine the criterion weights objectively. Then, the weights of the bid evaluators are obtained through calculating the relative closeness coefficients of each bid evaluator and the group from the JVCs to the fuzzy positive-ideal solution (FPIS). All the potential JVCs are ranked through minimizing the deviation model based on the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach. A case study of the JVC selection process for the Hong Kong–Zhuhai–Macau Bridge (a large-scale island and tunnel engineering project) was conducted to illustrate the proposed approach. The results showed that, compared with the existing methods, the proposed method can select the contractors with good collaborative performance. This is important for the practice, because collaborative criteria are reflected in the key criteria currently used in JVC evaluation and selection. The findings from this study can help the JVC manager to identify a JVC with good collaborative performance and control the project risk from the initial stage.
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Data Availability Statement
Data generated or analyzed during the study are available from the corresponding author by request. Information about the Journal’s data-sharing policy can be found here: http://ascelibrary.org/doi/10.1061/(ASCE)CO.1943-7862.0001263.
Acknowledgments
The authors would like to thank the anonymous referees for their valuable comments and suggestions. This work was partly supported by the Sino-Australia Collaborative Innovation Alliance for Megaproject Management in the Era of Internet+ and Big Data; the National Natural Science Foundation of Key Projects (No. 71390520); the National Natural Science Foundation of China (Nos. 91646123, 71471077, 71671088, 71571098, 71501102, 71271103, 61473326); the program for Outstanding Ph.D. candidate of Nanjing University (Nos. 201601A001, 201702B041); and the Discovery Project from the Australia Research Council (DP170104612).
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Journal of Construction Engineering and Management
Volume 145 • Issue 2 • February 2019
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©2018 American Society of Civil Engineers.
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Received: Feb 20, 2018
Accepted: Jul 12, 2018
Published online: Nov 23, 2018
Published in print: Feb 1, 2019
Discussion open until: Apr 23, 2019
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