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AbstractThe impact of contractor selection on construction project success has led to numerous studies on contractor selection. However, an up-to-date systematic review of contractor selection trend is still lacking. This study aims to fill the gap by reviewing published literature from 1990 to 2019. A desktop search was conducted under the ‘T/A/K (title/abstract/keyword)’ in Scopus search engine where 252 papers were identified. Based on a two-phase filtering approach, which included journal relevance assessment and article relevance assessment, 137 published papers within 22 journals were used for the study. The major finding was that the questions were raised on the suitability of selection criteria for appraising contractors and it was acknowledged that, choosing appropriate contractor selection criteria are affected by other factors hence can be regarded as a Multiple Criteria Decision Making problem suitable for machine learning tools. A major limitation of was that, even with the 137 reviewed papers, not all contractor selection-related papers were reviewed. The outcome of the study suggests a greater involvement of practitioners in model development and stimulates future studies that delve into the development of models to aid in selecting optimal contractor selection criteria for a particular project.

Over the past decade, value engineering (VE) has developed to become a recognized methodology with ordinarily comprehended tools and procedures. Its adoption in public projects in developed countries is credited with meeting stakeholders' expectations. Although this may be so for construction industries in developed countries, the situation is bleak for developing countries. This paper considers the challenges facing the successful implementation of VE in public projects among developing countries. Using an empirical questionnaire survey, respondents were invited to rate their perception of 22 challenges identified from literature. This paper is based on a survey of construction and consulting firms based in Ghana. The data set was subjected to factor analysis. Correlations between the 22 variables show that five key components underlie the challenges facing VE in developing countries. Findings and recommendations of this study may be useful to construction professionals who are seeking innovative ways to enhance value for money.