Joint-Venture Contractor Selection Using Competitive and Collaborative Criteria with Uncertainty

Liang, Ru; Zhang, Jinwen; Wu, Changzhi; Sheng, Zhaohan; Wang, Xiangyu

doi:10.1061/(asce)co.1943-7862.0001588

Cited by 29 publications

(28 citation statements)

References 49 publications

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“…Various new MCDM methods have been used in projects in different domains, especially management, engineering, and for different purposes, such as construction management and energy saving [19]. Fuzzy theory, BT, and utility theory have been widely used [8,9,11,12,18,[20][21][22][23] to select the most appropriate contractor for building projects, with each theory involving different methods for weight calculation, such as the analytical hierarchy process (AHP), WASPAS, and TOPSIS methods [1,20,[24][25][26]. Other MCDM methods, such as the AHP, ANP, MOORA, COPRAS, and SWARA-FUCOM, can also be applied to the problem [1,19,25,27].…”

Section: Methods Of Selecting Multi-criteria Decision Making For Contractor Selectionmentioning

confidence: 99%

“…Other MCDM methods, such as the AHP, ANP, MOORA, COPRAS, and SWARA-FUCOM, can also be applied to the problem [1,19,25,27]. The use of Grey theory, PROMETHEE, and interval-valued intuitionistic fuzzy sets (IVIFS) in MCDM methods also aids the ranking of contractors [21,23,[28][29][30][31]. MCDM methods have also been used in the selection of cultural heritage buildings [26,[32][33][34].…”

Section: Methods Of Selecting Multi-criteria Decision Making For Contractor Selectionmentioning

confidence: 99%

“…The BT-based MCDM method of recalculating the criteria weights was used in a study where the quality of a school's classes was assessed. MCDM methods such as SAW, TOPSIS, EDAS, and COPRAS were used for the evaluation [2], including the combination of Fuzzy Theory [7,10,[15][16][17][19][20][21].…”

Section: Methods Of Selecting Multi-criteria Decision Making For Contractor Selectionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-Criteria Decision Making of Contractor Selection in Mass Rapid Transit Station Development Using Bayesian Fuzzy Prospect Model

2020

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In Taiwan, the most advantageous tender in governmental procurement is the selection of a general contractor based on a score or ranking evaluated by a committee. Due to personal, subjective preferences, the contractor selection of committee members may be different, causing cognitive difference between the results of the members’ selection and the preliminary opinions provided by the working group. Integrated, multi-criteria decision making techniques, combined with preference relation, Bayesian, fuzzy utility, and prospect theories are used to assess factors weighing up the duration/cost/quality, probability of external information, and utility function system. The paper proposes a Bayesian fuzzy prospect model for group decision making, based on probability and utility multiplied relation, and taking the sustainable development factors into consideration. This study aims to provide committees with an objective model to select the best contractor for public construction projects. The results of this study can avoid the lowest bidder being selected; besides, the score gap of contractor selection can be increased, and the difference between the top three contractors’ scores can be decreased as well. In addition to proposing an innovative decision-making system of contractor selection and an index weight-assessing system for sustainable development, this model will be widely applied and sustainably updated for other cases.

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Section: Methods Of Selecting Multi-criteria Decision Making For Contractor Selectionmentioning

confidence: 99%

Section: Methods Of Selecting Multi-criteria Decision Making For Contractor Selectionmentioning

confidence: 99%

Section: Methods Of Selecting Multi-criteria Decision Making For Contractor Selectionmentioning

confidence: 99%

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Multi-Criteria Decision Making of Contractor Selection in Mass Rapid Transit Station Development Using Bayesian Fuzzy Prospect Model

2020

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“…It has been applied extensively to solve MCDGM problems (Selvachandran, Quek, Smarandache, & Broumi, ). Liang, Zhang, Wu, Sheng, and Wang () established an optimisation model that was based on the maximizing deviation principle to select contractors. Tian, Wang, Wang, and Zhang () constructed a method incorporating the maximizing deviation method to improve performance and provide high‐quality products and services for customers.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi‐criteria group decision‐making method based on TODIM with probabilistic interval‐valued hesitant fuzzy information

Zhang

Wang

2019

Expert Systems

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Probabilistic interval‐valued hesitant fuzzy sets (PIV‐HFSs) are suitable for aggregating information from different groups because the probabilistic information of all the groups can be included by using interval values. Moreover, decision makers (DMs) prefer to use interval values to provide evaluation information. Furthermore, the traditional multi‐criteria group decision‐making (MCGDM) approach has some limitations, such as obtaining the DMs' weights with inappropriate methods and neglecting the interactions amongst the criteria and the psychological characteristics of DMs. Motivated by these research background, the main contents of this study are as follows. First, PIV‐HFSs are proposed, and the convex combination operation is extended into PIV‐HFSs. Second, a hybrid MCGDM approach with PIV‐HFSs is suggested that is based on the maximizing deviation method, fuzzy analytic network process (FANP) and TODIM (an acronym in Portuguese for interactive and multi‐criteria decision‐making model). Third, an evaluation case of health management centres based on the service‐specific failure mode and effect analysis (FMEA) is considered. The results show that the most crucial secondary factor is frequency (0.35775) and that the most serious failure mode is the inaccurate check‐in. The results demonstrate that the proposed model can evaluate service quality effectively and that it performs better than other methods.

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“…In the majority of MCDM problems, providing deterministic measurements to express the preferences of experts is very difficult due to limited time, the complexity and dimensions of the decision problem. In decision-making environments, it is probable to face kind of conditions while lacking information (Liang, Zhang, Wu, Sheng, & Wang, 2018). According to uncertain theories, a system whose private information is wholly known is called a white system.…”

Section: Introductionmentioning

confidence: 99%

A Grey Combined Compromise Solution (Cocoso-G) Method for Supplier Selection in Construction Management

Yazdani

Wen

Liao

et al. 2019

Journal of Civil Engineering and Management

147

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This study investigates an extended version of the combined compromise solution method with grey numbers, named CoCoSo-G for short, to measure the performance of suppliers in a construction company in Madrid. Seven criteria from a relevant previous study are the basis for assessing the performance of suppliers, while ten suppliers are composing our decision matrix. To initiate the decision-making process, we invite experts to aid us in the qualitative evaluation of the suppliers using grey interval values. Two weighting methods, including the DEMATEL (Decision Making Trial and Evaluation Laboratory) and BWM (best worst method) are used to achieve the importance of supplier criteria in a combined manner. The DEMATEL method is used to realise the best and worst criteria, and the BWM is used to sort the criteria according to a linear programming formulation. The CoCoSo-G method used to release the score of each supplier and rank them. We compare the results obtained by the CoCoSo-G with those obtained by the Complex Proportional Assessment method. It is evident that offering grey values for supplier qualification, using the combined weighting tool and proposing the new CoCoSo-G approach facilitate the evaluation process while indicating trustable outcomes.

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Joint-Venture Contractor Selection Using Competitive and Collaborative Criteria with Uncertainty

Cited by 29 publications

References 49 publications

Multi-Criteria Decision Making of Contractor Selection in Mass Rapid Transit Station Development Using Bayesian Fuzzy Prospect Model

Multi-Criteria Decision Making of Contractor Selection in Mass Rapid Transit Station Development Using Bayesian Fuzzy Prospect Model

Multi‐criteria group decision‐making method based on TODIM with probabilistic interval‐valued hesitant fuzzy information

A Grey Combined Compromise Solution (Cocoso-G) Method for Supplier Selection in Construction Management

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