Automated two-stage continuous decision support model using exploratory factor analysis-MACBETH-SMART: an application of contractor selection in public sector construction

Abstract

Public sector client marks contractor selection decisions on technical and financial bid considerations where efficient use of public resources is never unheeded. A plethora of past studies has developed two-stage models; however, continuous assessment of contractors is disregarded, and the models compromise on the discontinuous progression that partially recognizes the prominence of the technical stage in the selection process. This research aims to develop a novel automated two-stage continuous decision model for contractors' assessment and selection where each contractor would be assessed on corresponding performance assessment grading levels. Exploratory Factor Analysis (EFA) assimilated with MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) employed to assess the model criteria, whereas, criteria assessment stage is developed using a novel hybrid combination of SMART (Simple Multi-Attribute Rating Technique), which in turn entails the EFA-MACBETH-SMART triplet-combination. The model encompasses extensive model criteria; thus, 76 model criteria were investigated and evaluated. Final selection of a contractor is proposed on technical bid/financial bid ratio mechanisms based on performance levels such as R-T/F: 80/20; 75/25; 70/30; 65/35; and 60/40. A hypothetical case is encompassed to portray the operational mechanism of the automated assessment system. Findings from the model unveil that continuous progression of technical assessment stage in final selection make justice with the highly qualified contractors, and the likelihood of project success increases. The developed model further conclude that technically highest bidders may be awarded the contract if additionally offers a feasible bid. The developed model preserves the concept of efficient use of public resources alongside supporting the technically highest bidders.