Two-stage continuous assessment decision support model for selection of contractors in Pakistan's public projects

Recent massive number of urban construction developments in Pakistan and around the globe have drawn attention to researchers in systematic way of undertaking the project. More importantly, the project=s team should consist of capable parties especially contractors. In relation to this, it is crucial to select the most competitive contractors and the most systemic approach to the selection which needed to be given serious attention. A plethora of research is carried in the last three decades to develop decision support models in selecting contractors. However, the complexity of contractor selection models is proliferating, and the user-friendly decision system is yet to be developed. In more specific geographical context such as Pakistan, there is very limited work has been done to assess the contractors‘ capability especially in the public sector. Therefore, this study aims to develop a decision support model for final contractor selection in public construction projects in Pakistan. To accomplish this, the study is underpinned by four objectives. Firstly, to compute the significance of attributes affecting selection of contractor, and the second objective is aim to assess the contractors selection practices in Pakistan‘s public sector departments and suggest suitable directions to improve the current process. The third objective aims to compute contractor selection attributes‘ weightages and performance assessment weightages for contractors‘ assessment. The fourth objective is to develop a decision support model for the final selection of contractors in Pakistan‘s public project. A novel triplet hybrid integrated approach of multi-criteria decision-making techniques is applied to analyse the data. A total of seventy-six (76) attributes were analysed, correlated, rotated, and weighted using Exploratory Factor Analysis. Later on, MACBETH is applied to compute the attributes weightages via M-MACBETH software package. Finally, with the help of SMART, the performance assessment grading levels were calculated to assess the contractors which turns into a triplet hybrid model of EFA-MACBETH-SMART. The research computes extensive attributes of contractor selection and classified these into four novel categories such as eligibility, critical, value-added, and desirable criteria. The study also assesses the current contractor selection practices which outlines several common practices including flaws in the system and later suitable directions are suggested. Furthermore, the attributes‘ weightages are computed using MACBETH, and performance assessment weightages are computed using SMART based on different performance levels. Finally, a two-stages continuous assessment decision support model is developed on technical and financial bid ratio mechanisms based on contractors‘ performance levels. Findings from the model unveil that continuous assessment from technical stage in final selection make justice with the highly qualified contractors, and the likelihood of project success increases. The developed two-stage model further conclude that technically highest bidders may be awarded the contract if additionally offers a feasible bid. The model improves the current assessment process in assisting clients for making right and justified decisions, keeping the bid price and other technical criteria into consideration. Furthermore, the model selects the most capable contractor with priorities to technical attributes, and besides, the model also preserves the lowest evaluated bid concept which is additional improvement in current assessment process