CONTRACTOR SELECTION MODEL IN COMPETITIVE BIDDING SYSTEM

The lowest bid has often been favoured for award of contracts in competitive bidding. Despitethe fact that the essence is to achieve value for money for the client, studies show that the lowestbid doesn't often guarantee cost efficacy of construction projects. Different models have beendeveloped to improve on the lowest bid award system. Some of the research results producedregression models that will identify not just any lowest bid but the lowest responsive responsiblebid among bidders. However, the independent variables in such equations raise some questionsthat demand answers from research consideration. The major questions were the rational onthe choice of variables and the reasons for using only two independent variables in theequations. This research is set to consider those questions in developing a more reliableregression model that will identify the lowest responsive responsible bid in competitive bidding.Water engineering projects competed in the north eastern part of Nigeria between 2015 and2017 were used. Thirty six (36) completed projects of diverse magnitudes involving 220 bidswith diverse level of competition were used. Three new regression models were developed, twoof which has 3 independent variables and one has 4 intendant variables. Both were comparedwith earlier similar equations developed with 2 independent variables. It was found thatdifferent matrixes of independent variables presented different predictive power of the lowestresponsive responsible bid. Comparison shows that the equation with 4 independent variablesis the most robust predictor of the lowest responsive responsible bid. However, for the sake ofconvenience and early identification, the optimum equation with 2 variables containing thenumber of bids and the consultant's estimate was recommended. This is in line and justifiesearlier research recommendations. It is expected that the result will enable quick identificationof bon-a'-fide contractor at the early stage of the bidding process through which thecumbersome task of bid analyses will be reduced, as such cost and time of bidding also reduced.