Abstract. Materials constitute a large proportion of the total project cost and the absence of right materials in the right quantities and quality on site when needed is one of the most commonly experienced causes of delays in construction projects. Although supplier selection is a strategic issue, contractors generally select suppliers based on their past experiences, which may result in selecting wrong suppliers. Supplier selection decision is generally made by multiple decision makers and is affected by several criteria. Therefore, selecting the right supplier among many alternatives considering several compromising and conflicting criteria is a multi-criteria group decision-making (MCGDM) problem. This paper proposes an integrated fuzzy MCGDM approach, which employs fuzzy analytic hierarchy process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) together, for the supplier selection problem. In the proposed approach, fuzzy AHP is used to analyse the structure of the supplier selection problem and to determine the weights of the criteria, and the fuzzy TOPSIS method is employed to rank the alternative suppliers. The proposed approach is applied to a problem of selecting the most appropriate rail supplier and company management found the proposed decision approach satisfactory and implementable in future supplier selection problems.

Construction contracting companies face two critical decisions in competitive bidding environment, which include: the bid/no-bid decision and the markup selection decision. Making the right bid/no-bid decision is critical to the survival, sustainability, and success of the contractors in the industry. There are many factors that a ect this decision. This makes the bidding decisions complex and complicated. Therefore, it is not an easy task for managers to consider the combined impact of all these factors on the bid/no-bid decision within a limited time frame with limited capacity of information they have for every single bidding opportunity. This study proposes a Data Envelopment Analysis (DEA) approach for making the bid/no-bid decision. DEA is a robust non-parametric linear programming approach, which is mostly used for benchmarking, performance measurement, and decision making problems. The applicability of the proposed approach was demonstrated in a real case study conducted in a Turkish construction contracting company. In the case study, 49 bidding opportunities formerly faced by the studied company were evaluated via the developed DEA model. The accuracy rate of the proposed approach was 92%. Company management found the proposed approach satisfactory and implementable in future bid/nobid decision problems.

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