Data Envelopment Analysis (DEA) Approach for Making the Bid/No Bid Decision: A Case Study in a Turkish Construction Contracting Company

Abstract

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.

Application of Multiple Criteria Decision Making Methods in Construction: A Systematic Literature Review

“…Another idea is developing a benchmark based on expert knowledge and historical information and subsequently providing a ranking of different projects to bid in reference to the benchmark for bid project selection. Fuzzy-TOPSIS (Al-Humaidi, 2016) and DEA methods (El-Mashaleh, 2013;Polat & Bingol, 2017) can be adopted under this circumstance. The last idea is estimating project award prices with the help of artificial intelligence (AI) models, such as artificial neural networks (ANN) and general regression neural network (GRNN) (Shi et al, 2016).…”

Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making

“…More studies can be cited with the use of AHP in the automobile industry for manufacturing performance and production flow [15]. In the best use of equipment, eliminate bottlenecks, and enable training of operators [34].…”

“…The AHP method allowed for the assessment of both qualitative and quantitative criteria [34,35,41]. This aspect is important in the agricultural industry, as some additional qualitative criteria considered relevant by management could be included in the analysis.…”

Classification model for bid/no‐bid decision in construction projects

“…However, sometimes the DM does not have access to all this data. El‐Mashaleh (2013) and Polat and Bingol (2017) propose approaches that use data envelopment analysis (DEA) to decide whether to participate, while Mehrabani et al. (2020) consider a model that ranks the projects and in bidding decisions, prioritizes the first in the rank.…”

“…However, sometimes the DM does not have access to all this data. El-Mashaleh (2013) and Polat and Bingol (2017) propose approaches that use data envelopment analysis (DEA) to decide whether to participate, while Mehrabani et al (2020) consider a model that ranks the projects and in bidding decisions, prioritizes the first in the rank. In these methods, both quantitative and qualitative criteria are considered, but they do not incorporate the imprecision of the DM's judgment for qualitative bidding criteria.…”