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Subcontractor selection using the integration of the ahp and promrthee methods

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Vilnius Gediminas Technical University

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On many construction projects, especially building projects, 80–90% of the tasks are performed by subcontractors. Since the success of the project highly depends on the performances of the subcontractors, selecting the right subcontractor for the right job is critical. Main contractors generally tend to select the subcontractors that offer the lowest bid price. However, working with unqualified and insufficiently financed subcontractors may result in inefficiencies and failures. Thus, a combination of several compromising and conflicting criteria underpinning financial capacity and competencies of the subcontractors should be considered during the subcontractor selection process. This paper proposes an integrated decision approach, which employs analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluations (PROMETHEE) together, for the subcontractor selection problem. In the proposed approach, AHP is used to analyze the structure of the subcontractor selection problem and to determine the weights of the criteria, and PROMETHEE is employed to obtain complete ranking and perform sensitivity analysis by changing the weights of criteria. The proposed approach is applied to a problem of selecting the most appropriate subcontractor to be worked with in an international construction project. Company management found the proposed decision approach satisfactory and implementable in future subcontractor selection problems.

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JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT

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1392-3730

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OPEN

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subcontractor selection, Artificial intelligence, multi-criteria-decision-making, AHP, Economics, GAIA, Social Sciences, Business, Management and Accounting, Group Decision Making, Promethee, Multi-Criteria Decision Making, Management Science and Operations Research, Operations research, Preference, Decision Sciences, Information Systems Outsourcing and Offshoring, Management Information Systems, Supplier Selection, Selection (genetic algorithm), Engineering, sensitivity analysis, Complexity in Projects, Microeconomics, Risk analysis (engineering), Business, Civil engineering, Building construction, Analytic hierarchy process, Success Factors in Project Management, Electronic engineering, Ranking (information retrieval), Underpinning, Analytic Hierarchy Process, Computer science, Multiple-criteria decision analysis, Sensitivity (control systems), Process (computing), Operating system, TH1-9745, FOS: Civil engineering

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