Journal of Construction Engineering and Management

Formal and analytical risk models prescribe how risk should be incorporated into construction bids. However, the actual process of how contractors and their clients negotiate and agree to price is complex and not clearly articulated in the literature. With participant observation, the entire tender process was shadowed in two leading U.K. construction firms. This was compared with propositions in analytical models, and significant differences were found. A total of 670 h of work observed in both firms revealed three stages of the bidding process. Bidding activities were categorized and their extent estimated as deskwork (32%), calculations (19%), meetings (14%), documents (13%), off-days (11%), conversations (7%), correspondence (3%), and travel (1%). Risk allowances of 1–2% were priced in some bids, and three tiers of risk apportionment in bids were identified. However, priced risks may be excluded from the final bid to enhance competitiveness. Although risk apportionment affects a contractor’s pricing strategy, other complex microeconomic factors also affect price. Instead of including pricing contingencies, risk was priced primarily through contractual rather than price mechanisms to reflect commercial imperatives. These findings explain why some assumptions underpinning analytical models may not be sustainable in practice and why what actually happens in practice is important for those who seek to model the pricing of construction bids.

Project managers implement the concept of time contingency to consider uncertainty in duration estimates and prevent project completion delays. Some project managers also build a distribution of the project time contingency into the project activities to create a more manageable schedule. Generally, both the estimation and distribution of the project time contingency are conducted by using subjective approaches. Because the project schedule feasibility mainly depends on the variable behavior of the project activities, the estimate of project time contingency and its allocation at the activity level should be obtained by considering the performance variability of each activity rather than basing on human judgment. In this paper, the stochastic allocation of project allowances method, which is based on Monte Carlo simulation, is proposed to estimate the project time contingency and allocate it among the project activities. The application of this method to a three-span bridge project results in a fair allocation of the project time contingency and provides practical means to control time contingencies at the activity level.

Construction requirements represent the key preconditions for construction. These include topological precedence, key resources, space requirements, etc. Consequently, identifying them is necessary for feasible construction planning to be achieved. Despite this, little attention has been given to the impact of construction requirements on a project schedule, possibly because of the lack of a good tool for representing these requirements. This paper distinguishes construction requirements into static and dynamic types, according to changes in the need of the requirement during its life cycle. A modeling framework, PDM++, is then proposed. The framework deals with schedule constraints arising from both static and dynamic construction requirements, provides greater semantic expression to capture schedule constraints unambiguously, and facilitates the representation of interdependent conditional relationships. The concept of meta-intervals is also devised to represent complex requirements involving several activities and schedule constraints, and it facilitates modeling at higher levels of plan abstractions. Finally, an illustrative case study is presented to show the applicability of PDM++ in representing schedule constraints and alternative scheduling from a construction requirements perspective.

Competitive bidding is the major mechanism of competition. Bidding is risky because the actual cost of the job is unknown. Thus, the bid should be high enough to make a profit but low enough to win the bidding. The result of competition depends on the competitor’s risk-taking behaviors, which are affected by the organization’s risk attitudes. A contractor’s risk-taking is an essential element of the construction business. The current study explores the domain of competition at the aggregate market level. An evolutionary simulation model was developed to investigate the effects of risk attitude on a contractor’s success and on the market structure. The analysis accounts for different risk-taking behaviors in competition, different performances by contractors, corresponding organizational changes, and aggregate patterns in the form of the market structure. The study finds that risk attitude is a competitive characteristic of contractors. The results provide new insight on competition in the market place, and explanations are given for a contractor’s competitive success.

Subcontractor selection strategies used by contractors can significantly affect short-term project and long-term organizational success. Existing research on subcontractor selection strategy implicitly assumes that the evaluation of subcontractors depends on current conditions. We extend this perspective by integrating an agent-based simulation model with game theory to examine whether precontract partner selection strategies that do not consider subcontractor selection as a repeated game may lead to a version of the holdup problem. The holdup problem we investigate focuses on relationship-specific investments in learning after the introduction of an innovation or organizational change across a project network. A minimum total cost strategy may decelerate the rate of adaptation to an innovation or organizational change, thereby proving that the holdup problem can exist in project networks. The findings contribute to subcontractor selection strategy literature by simulating the impact of the holdup problem in project networks, distinguishing task interdependence as a moderating variable, and identifying that the minimum total cost strategy can be a suboptimal strategy for project networks adapting to systemic changes.

Fault trees are deductive techniques constructed by taking a system failure event and deconstructing it into its root causes (basic events, gate events). Fault trees can be solved qualitatively, by determining minimal cut sets, and quantitatively, by calculating the probability of occurrence of the risk event. In conventional fault-tree analysis (FTA), the probability of occurrence for all basic events must be assessed in order to allow for quantitative fault-tree analysis. However, conducting quantitative fault-tree analysis, especially in construction projects, entails several difficulties owing to the lack of sufficient data, leading to an approximation of the probability of occurrence for some basic events. Assuming probabilities for any basic event will add further uncertainty to the analysis, resulting in a potentially questionable end result. To overcome the challenge of assessing probabilities, this paper presents a comprehensive framework in which experts can use linguistic terms rather than numerals to assess the probability of occurrence of basic events. Fuzzy arithmetic operations are used to perform quantitative fault-tree analysis. Fuzzy Reliability Analyzer (FRA) was developed to automate both qualitative and quantitative FTA. The method presented is demonstrated via a case study to quantify the probability of failure of horizontal directional drilling (HDD) in meeting project objectives. Fourteen minimal cut sets were identified and the fuzzy probability (FPro) of the top event (TE) was calculated. The proposed approach offers the advantage of allowing experts to express themselves linguistically to assess the probability of occurrence of basic events, which is more appropriate for the construction domain. In addition, the proposed method offers the risk analyst the advantage of ranking basic events according to their level of contribution to the probability of the risk event, which can help in establishing more effective risk response strategies.

The case-study research method is popular across various disciplines; however, critics of the method argue that results from this form of research are applicable only to the case studied and cannot be generalized further. In the field of construction engineering and management (CEM), the number of papers employing case-study research methods over the past decade has increased substantially. As the method proliferates, the question arises: are CEM case studies being performed with sufficient validity and reliability to meet the burden of proof to generalize from the case-study findings? Meeting the burden of proof is particularly critical in CEM because of the unique, site-based nature of the projects and industry. This paper presents a review of 156 papers employing case studies published in the Journal of Construction Engineering and Management, of which the writers identified 33 theory-building case-study-method papers. This subset of theory-building papers was examined to induce a set of requirements and guidelines derived from these case-study research efforts to aid researchers in meeting the burden of proof. The writers anticipate that more methodologically consistent and comprehensive case-study research will yield new lines of inquiry and rich theoretical models that enhance and expand CEM research.

Improvement of productivity in construction has been a major industry challenge, given its high impact on project results. It has received increased attention from construction researchers promoting different enhancement actions, since analyzing factors affecting labor productivity is an instrumental part in this process. This paper focuses on identifying and understanding the productivity factors affecting projects in a Chilean construction company on the basis of questionnaires administered to both direct workers and midlevel employees. Analysis of the questionnaire results helped to determine organizational and managerial weaknesses and facilitated comparison of the findings with previous productivity studies. The results proved to be useful in developing recommendations for productivity improvements. The main findings indicate that the critical areas affecting construction productivity were related to materials, tools, rework, equipment, truck availability, and the workers’ motivational dynamics. These results are similar to those obtained in previous studies in the United States and in Chile. Salary expectations were found to be the main reason for turnover in the studied company, which was an aspect not mentioned in previous studies. Finally, additional analyses seem to show that some factors affecting productivity are common to construction projects across boundaries, therefore validating data aggregation and the possibility of learning from experiences in different locations and even separated in time of occurrence.