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Scrutinizing Competitiveness of Construction Companies Based on an Integrated Multi-Criteria Decision Making Model

handle: 10397/105258
The construction sector continues to experience significant challenges brought by new techniques and technologies. Hence, there is a dire need for construction companies to address critical issues concerning changing environmental conditions, construction innovations, market globalization and many other aspects, thereby enhancing their competitive edge. Thus, the primary goal for this research is to develop a multi-criteria decision making model that would consider and evaluate all essential factors in determining the competitiveness index of construction companies. In the developed model, three new pillars (3P) for competitiveness are introduced: (1) non-financial internal pillar; (2) non-financial external pillar; and (3) financial pillar. The 3P includes 6 categories and 26 factors that are defined and incorporated in the developed assessment model for the purpose of measuring the companies’ competitiveness. The weights for the identified factors are computed using fuzzy analytical network process (FANP) to diminish the uncertainty inherited within the judgment of the respondents. The weight of factors and their affiliated performance scores are used as an input for the preference ranking organization method for enrichment evaluation (PROMETHEE II) technique. In this regard, PROMETHEE II is undertaken as a ranking technique to prioritize any given construction company by determining its respective competitiveness index. The developed model is validated through five cases studies that reveal its potential of illustrating detailed analysis with respect to the competitive ability of construction companies. A sensitivity analysis is carried out to determine the most influential factors that affect the competitiveness of construction companies. It is anticipated that the developed evaluation model can be used in the decision-making process by all parties involved in construction projects. For instance, contractors can leverage the evaluation model in taking better decisions pertinent to the markup values. In addition, it can benefit employers in the evaluation process of contractors.
- Hong Kong Polytechnic University (香港理工大學) Hong Kong
- Hong Kong Polytechnic University China (People's Republic of)
- Hong Kong Polytechnic University (香港理工大學) China (People's Republic of)
- King Saud University Saudi Arabia
- Hong Kong Polytechnic University (香港理工大學) China (People's Republic of)
Fuzzy analytical network process, competitiveness, multi-criteria decision making, fuzzy analytical network process, PROMETHEE II, Engineering (General). Civil engineering (General), Competitiveness, Multi-criteria decision making, construction sector, sensitivity analysis, construction sector; competitiveness; multi-criteria decision making; fuzzy analytical network process; PROMETHEE II; sensitivity analysis, TA1-2040, Sensitivity analysis, Construction sector
Fuzzy analytical network process, competitiveness, multi-criteria decision making, fuzzy analytical network process, PROMETHEE II, Engineering (General). Civil engineering (General), Competitiveness, Multi-criteria decision making, construction sector, sensitivity analysis, construction sector; competitiveness; multi-criteria decision making; fuzzy analytical network process; PROMETHEE II; sensitivity analysis, TA1-2040, Sensitivity analysis, Construction sector
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