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Abotaleb, I S and El-adaway, I H (2017) Construction Bidding Markup Estimation Using a Multistage Decision Theory Approach. Journal of Construction Engineering and Management, 143(01).

  • Type: Journal Article
  • Keywords: Contracting; Construction bidding; Markup estimation; Decision theory; Bayesian statistics;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001204
  • Abstract:
    Determining an optimum bid value maximizes the probability of winning a construction project while realizing proper profit. Thus, this issue has been one of the important research topics in construction-related research. Various models have provided different methodological approaches for bid pricing using statistical analysis of competitors’ prior bids. However, the accuracy of these models is compromised in cases where the data set of competitors’ historic bids is not complete and/or where such competitors utilize a dynamic behavior (i.e., having bidding schemes that change significantly with time). Through a multistage decision theory approach, this paper presents a more advanced model for construction bidding markup estimation that uses a Bayesian analytic framework. To this effect, a three-stage research methodology was utilized. First, the authors established a systematic procedure to fit competitors’ historical data into appropriate Bayesian prior density functions while taking the stochastic variability of cost estimates into consideration. Second, the authors developed stochastic likelihood functions through the most recent observation(s). Third, the authors created the posterior distributions from which the joint probability of winning and the expected profit can be calculated. To this end, the use of the Bayesian statistics in the model enables it to draw sound statistical inferences even in cases of data incompleteness and dynamic behaviors of competitors, thus tackling two important weak spots in the previous models. The proposed model was applied to two case studies from the literature with different scenarios to demonstrate its use and to illustrate the effect of different parameters on the resulting optimum markup. It was shown that the more recent bidding strategies of competitors play a significant role in predicting the future ones. Also, as the contractor becomes more certain about its competitor’s behavior, both its probability of winning and optimum bidding markup increase. This research should be beneficial for the construction stakeholders to better understand the bidding decision-making processes and consequently help create a healthy contracting environment.

Chang, C and Ko, J (2017) New Approach to Estimating the Standard Deviations of Lognormal Cost Variables in the Monte Carlo Analysis of Construction Risks. Journal of Construction Engineering and Management, 143(01).

Francis, A (2017) Simulating Uncertainties in Construction Projects with Chronographical Scheduling Logic. Journal of Construction Engineering and Management, 143(01).

Franz, B, Leicht, R, Molenaar, K and Messner, J (2017) Impact of Team Integration and Group Cohesion on Project Delivery Performance. Journal of Construction Engineering and Management, 143(01).

Gambatese, J A, Pestana, C and Lee, H W (2017) Alignment between Lean Principles and Practices and Worker Safety Behavior. Journal of Construction Engineering and Management, 143(01).

Huang, C and Wong, C K (2017) Discretized Cell Modeling for Optimal Facility Layout Plans of Unequal and Irregular Facilities. Journal of Construction Engineering and Management, 143(01).

Li, D and Lu, M (2017) Automated Generation of Work Breakdown Structure and Project Network Model for Earthworks Project Planning: A Flow Network-Based Optimization Approach. Journal of Construction Engineering and Management, 143(01).

Moussavi Nadoushani, Z S, Hammad, A W A and Akbarnezhad, A (2017) Location Optimization of Tower Crane and Allocation of Material Supply Points in a Construction Site Considering Operating and Rental Costs. Journal of Construction Engineering and Management, 143(01).

Patel, D A and Jha, K N (2017) Developing a Process to Evaluate Construction Project Safety Hazard Index Using the Possibility Approach in India. Journal of Construction Engineering and Management, 143(01).

RazaviAlavi, S and AbouRizk, S (2017) Genetic Algorithm–Simulation Framework for Decision Making in Construction Site Layout Planning. Journal of Construction Engineering and Management, 143(01).

Swei, O, Gregory, J and Kirchain, R (2017) Probabilistic Approach for Long-Run Price Projections: Case Study of Concrete and Asphalt. Journal of Construction Engineering and Management, 143(01).

Umer, W, Li, H, Szeto, G P Y and Wong, A Y L (2017) Identification of Biomechanical Risk Factors for the Development of Lower-Back Disorders during Manual Rebar Tying. Journal of Construction Engineering and Management, 143(01).

Zhang, S, Bogus, S M, Lippitt, C D and Migliaccio, G C (2017) Estimating Location-Adjustment Factors for Conceptual Cost Estimating Based on Nighttime Light Satellite Imagery. Journal of Construction Engineering and Management, 143(01).