Mark-up Size Estimation in Railway Projects using the Integration of AHP and Regression Analysis Techniques

The construction industry is commonly characterized by high level of competition. Since the large majority of the contractors win jobs through the bidding process and the owners predominantly select the contractors, who offer the lowest bid price, estimating the bid price accurately is critical for winning the contract and achieving business continuity. The bid price mainly consists of two components, which are: the base estimate and the bid mark-up. In general, the bid mark-up is estimated as the percentage of the base estimate based on the estimators' intuitions and past experiences. While the base estimate is found to be more or less same by competitor contractors, the offered bid prices greatly differ due to the variations in the bid mark-up size estimations. The bid mark-up size is affected by several factors. Therefore, determining the appropriate bid mark-up size is a complex decision problem. The main objective of this study is to propose an integrated approach, which may assist contractors in estimating the bid mark-up size more accurately and systematically. The main steps in the proposed approach include: 1) identifying the factors that may affect the bid mark-up size and categorization of these factors and developing a decision hierarchy of the mark-up size estimation problem (i.e.; identifying the main criteria and sub-criteria), 2) determining the weights of the main criteria and sub-criteria in the mark-up size estimation problem using the Analytic Hierarchy Process (AHP) approach by top managers considering the long-term strategies of the company, 3) identifying the importance levels of the main criteria and sub-criteria for the projects for which the company management is willing to offer bids, 4) determining the overall risk score of the projects in question by incorporating the weights and importance levels of the main criteria and sub-criteria, 5) estimating the bid mark-up size using the regression analysis, and 6) measuring the performance of the developed regression model. The proposed approach was applied in a contracting company, which is specialized in railway projects. Actual data of 10 railway projects completed in foreign countries within the last five years were collected from the top managers and estimators of the studied company. It was found that the bid mark-up size can be accurately estimated by the proposed approach.