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Skewed pricing is a typical tactic used by tenderers in unit price projects to gain additional advantages at the expense of the owner or other competing tenderers. This paper aims to describe the development of a model for detecting skewed pricing in competitive tendering for unit price contracts.

The model evaluates how much the offered unit rates for work items deviate from the reasonable rate identified from the item’s submitted unit rates. Item rate deviations are integrated into a total deviation score for each submitted tender based on the relative weight of the work item to the total project amount. The model allows for assigning higher weights to work items that are more prone to skewed pricing, such as those that are performed early and those that are expected to experience quantity fluctuations.

The paper presents a detection model that uses only the submitted prices of the competing tenderers to perform the needed calculations, which reduces subjectivity in identifying skewed tenders. Two examples are given to demonstrate how the model may be used to detect skewed tenders.

The model supports tendering officials in the challenging task of identifying skewed tenders, which is required by rules and regulations governing public procurement. The model’s ease of use is expected to make it more widely used as a decision-support tool during the tender evaluation stage of real-world projects.

Public construction authorities need to evaluate the level of competition in the submitted bids for a certain project before awarding the contract. A lack of adequate competition is a reason for rejecting all bids and reissuing an invitation to bid for the project. This paper aims to present an analysis of the adequacy of competition in public construction projects.

The paper uses five competition indicators to correlate the level of competition effect obtained with the number of contractors competing for the project. The analysis is based on the bid opening results for 917 public construction projects in Jordan that include 6,309 bids, with an average number of 6.88 bids per project.

The results illustrate that there is an improvement in the competition effect over the five analyzed competition indicators as the number of bidders increases. However, the rate of improvement decreases with the increase in bidders. The empirical analysis performed does not support the proposition that an optimum number of bidders exists in competitive bidding for construction projects or the proposition that a higher number of bidders may lead to higher bid prices. However, the indicators developed in this study found that at least 5 bidders are recommended and after 8 bidders, the rate of improvement continues at much slower rate.

The current research presented a multifaceted method for assessing the minimum number of bidders needed to ensure a competitive bidding process. Moreover, the research used actual data from 917 public projects.

The purpose of this paper is to analyze and evaluate bidding competitiveness and success rate of contractors bidding for public construction projects (PCPs). Additionally, this research determines the effect of work sector, contractor’s classification category (experience), project size and number of bidders on contractors’ bidding competitiveness, and the influence of work sector and classification category on their success rate.

The data were collected through 2,296 bidding attempts for 289 tender projects that were announced by the Government Tenders Department in Jordan between 2013 and 2016. The research uses bid competitiveness percentage (BCP) to evaluate contractors’ bidding competitiveness. Pearson correlation is used to investigate the correlation among variables. Hypothesis testing using ANOVA was conducted to evaluate the effect of the abovementioned factors on contractors’ bidding competitiveness, and their success rate.

The results of the analysis indicate that contractors’ average BCP and success rate in Jordanian PCPs are 83.8% and 13.3%, respectively. The analysis also reveals that work sector, contractor’s classification category, project size and number of bidders significantly affect contractors’ bidding competitiveness, whereas classification category and work sector do not affect bidding success rate. Therefore, experience of contractors affects their bidding competitiveness, but does not affect their success rate.

The present research uses contractors’ bidding success rate as a measure to evaluate their bidding competitiveness for PCPs. The novel model of this research can be applied in any country, after considering local regulations, to measure and evaluate contractors’ bidding competitiveness, and success rate when bidding for PCPs. Also, contractors cannot depend on their experience (i.e. classification category) or increasing bidding attempts to win bids and improve bidding success rate, rather than enhance their bidding strategy.