Journal of Construction Engineering and Management

Assessment of budget sufficiency and resource utilization for a resource-constrained project schedule is crucial to ensure practical feasibility of the schedule and successful delivery of a construction project. This paper proposes a quantitative assessment approach for characterizing budget sufficiency and resource utilization for a resource-constrained project schedule in an objective fashion. The budgeted unit, deployed unit, and scheduled unit in connection with a resource-constrained project schedule are first defined. Next, two budget sufficiency metrics, named the budget sufficiency index and budget sufficiency variance, are defined for measuring the sufficiency of control budget in terms of deploying resources to execute the project schedule with resource constraints. In addition, two resource utilization metrics, termed the resource utilization index and resource utilization variance, are defined for indicating utilization efficiency of deployed resources based on the schedule. The proposed metrics are applied to objectively assess multiple alternative resource-constrained project schedules derived from various approaches, including a practical scheduling approach (Primavera P6) and resource scheduling optimization techniques recently developed from in-house research. A textbook example and a refinery plant turnaround project are used to demonstrate the effective application of proposed metrics on alternative resource-constrained schedules. It is concluded that (1) resource scheduling optimization techniques outperform Primavera P6 in terms of budget sufficiency and resource utilization thanks to streamlining resource supply limits and shortening project duration by optimization; and (2) a significant portion of the idled resource time in the Primavera P6 schedule turns into extra contingency in the optimized schedule that can be reserved against any work unforeseen or unknown during the planning stage.

The characteristics of construction projects—e.g., one-off, high complexity, information asymmetry, and asset specificity—have led to a very common phenomenon of opportunism. In this paper, a questionnaire based on a sample of contractors was employed to explore the effect of contract completeness on contractors’ opportunistic behavior, as well as the moderating role of interdependence. The results show that term specificity, contingency adaptability, and contractual obligatoriness all have negative effects on contractors’ opportunistic behavior (both weak and strong forms), while issue inclusiveness positively influences contractors’ opportunistic behavior. In addition, except for the positive moderating role of interdependence magnitude on the relationship between contingency adaptability and contractors’ opportunistic behavior (weak form), the other three significant moderating effects (magnitude on issue inclusiveness and strong form, magnitude on contractual obligatoriness and strong form, asymmetry on term specificity and strong form) are all found to be negative. These findings can give insight into the many ways that contracts affect opportunism, and thus help both sides strategically react to opportunistic disturbances and minimize transaction costs.

When designing contracts in practice, project owners often allocate excessive risks to contractors. Although previous studies have suggested that such improper risk allocation may harm the relationship between the owner and the contractor and thus lower project performance, few have explicitly investigated the effects of risk allocation on the contractor’s cooperative behavior. This paper fills this gap by empirically exploring whether, how, and when risk allocation influences the contractor’s cooperative behavior. To do this, data were collected from 284 Chinese project professionals and hierarchical regression analysis was performed. The results show that pro-owner contractual terms with regard to risk allocation negatively affect the contractor’s cooperative behavior, and the contractor’s fairness perception partially mediates such an effect. Moreover, risk premium weakens the effect of environmental risks allocation on the contractor’s fairness perception, and term specificity strengthens the effect of the contractor’s fairness perception on the contractor’s cooperative behavior. Theoretically, these insights extend risk allocation studies by identifying the underlying mechanism behind the relationship of risk allocation and interfirm cooperation and thus contribute to sound contractual governance. Practically, this study’s findings can help project owners design better contracts, particularly by bearing in mind that risk premium should not always be used to restore the contractor’s fairness perception to elicit the contractor’s cooperative behavior because it does little to help when owner risks are allocated to contractors.

Employee turnover has long been, and will continue to be, a significant concern in the construction industry. Organizations that can retain skilled employees have a stronger competitive advantage. In two independent studies in China and the Philippines, the authors investigated the role of psychological contract breach in predicting employee turnover in the construction industry. The results reveal that psychological contract breach results in emotional exhaustion, which in turn predicts employees’ turnover intentions (Study 1) and actual turnover (Study 2). The results further suggest that younger as opposed to older construction workers who experience psychological contract breach are more likely to experience greater levels of emotional exhaustion and exit their organizations. Accordingly, to retain skilled workers, construction organizations should understand and continuously manage employees’ psychological contract expectations and provide more support to younger workers. This paper offers significant theoretical contributions because it is one of the few in the construction literature that examine both employee turnover intentions and actual turnover from a psychological contract perspective.

Severe weather can adversely affect the scheduling of construction projects. It is very important to be able to estimate the delay that would result from such severe weather because construction contracts generally differentiate between weather delays that can be anticipated and those that cannot. Only delays caused by abnormal and unforeseeable severe weather are granted a time extension. Normal and foreseeable weather delays in construction contracts are usually estimated as a monthly average of the severe weather days as determined from historical weather data, which are measured at the ground level. In high-rise building construction, however, this approach may be inappropriate because weather conditions generally vary with an increase in altitude and the height of high-rise buildings has become so great that those conditions can actually affect the construction of the upper floors. Therefore, weather delays estimated using this approach could be subject to this error. For such reasons, a simulation model capable of analyzing weather delays with consideration for altitudinal variations in the weather conditions is proposed for high-rise building construction projects. To achieve this goal, the literature addressing the types of weather variables, the threshold criteria causing weather delays, and the duration of weather delays was first reviewed. Then, a weather-generation model using a k-nearest neighbor time-series method and vertical weather profiles was developed to estimate the weather conditions at high altitudes. A simulation model was finally developed by integrating the weather generation model and a construction schedule simulation model by using a discrete event simulation method, and a case study was conducted to validate the results of weather delay estimation and to analyze the degree to which vertical weather variations affect the schedule of building construction projects. The contribution of this study is the proposal of a method based on a vertical weather profile that is capable of reasonably estimating weather delays in high-rise building constructions, and analyzing the pattern of weather delays in building construction projects.

A leading engineering and construction industry magazine has been collecting revenue data from construction firms and publishes the list of the 100 largest design-build (DB) firms every year. According to this magazine and many technical articles, DB has grown drastically over the last decade; however, information about growth trends for different firm sizes is lacking. Also missing is a forecast of future market trends over the next five years. Using revenue data from the top 100 DB firms, the authors have divided the firms into subsets, using $k$-means clustering, and analyzed the growth rates of each subset compared with the average of the top 100 DB firms as a whole. Whereas the results show increasing market share only for the largest firms, the authors have found that: (1) a large portion of this growth is occurring in international markets; and (2) all subsets of the top 100 DB firms have increased revenues over the past decade. Regression and time-series analyses allowed for the forecasting of the top 100 DB firms’ revenue growth, which the authors anticipate to increase by approximately 50% to nearly US$150 billion in 2020. This paper contributes to the construction engineering and management body of knowledge by (1) analyzing the DB market data using statistical clustering techniques to uncover differences in behavior for firms of different sizes, for the first time; and (2) forecasting DB market trends on the basis of these new findings. These contributions can help public agencies see how DB firms of all sizes are growing, while also understanding how international markets are driving the faster growth rate of larger DB firms. Additionally, the contributions of this paper can help DB practitioners anticipate market changes, on the basis of their firm’s size, and strategically plan their firms’ growth accordingly.

Earned value analysis (EVA) has been widely used in the construction industry for cost prediction at completion. The EVA’s accuracy of early cost projections is low since the method assumes static cost performance during construction. A project’s cost performance is evidenced as a stochastic process. In an effort to improve the EVA’s accuracy of early cost predictions, this work reports a modified method of Markovian simulation cost projection (MSCP). Based on Markov chain simulation, MSCP simulates the probability distribution of the cost performance indicators for each period of a project, and predicts the final cost using the summation of each simulated period cost. The MSCP method is demonstrated and validated through a case study of a real-world power plant project. Data analysis indicates that MSCP improves the prediction accuracy four times higher than EVA. Findings also suggest that MSCP is able to capture erratic changes of cost performance throughout a project’s lifecycle and thus provides better EAC (estimate at completion) predictions and early warnings.

Rework is a chronic problem in construction and engineering projects. A wide variety of studies examining the nature of rework have been undertaken since the seminal research of Burati in the early 1990s, which examined quality deviations. Initial studies focused on identifying the causal factors and costs of rework to quantify the severity of the problem. From these studies, it was recognized that rework causes were interdependent; so techniques such as cognitive mapping (CM) and system dynamics (SD) were subsequently introduced to model the complexity and dynamic of this phenomena. Although such results provided the essential building blocks to better understand and provide the much-needed stimulus for theory development, rework remains a pervasive issue. A number of factors have contributed to the causal ambiguity that presently prevails, which includes the epistemological underpinning used to construct the nature of causes and the subsequent use of tools and techniques that are used for analysis. Evidence of this is presented in recent studies that have failed to acknowledge the interdependency of rework causes as research regressed to identifying those causes of a singular nature. Consequently, such research continues to stymie progress toward reducing and containing rework, and a moratorium on such approaches is suggested. With this in mind, insights into the extant rework literature and causation philosophy are examined and recommendations to improve the understanding necessary to establish a theory for rework causality are proposed.

The construction industry continues to be among the leading industries for workplace fatalities in the United States. After experiencing 824 fatal injuries in 2013, the construction industry ranks as one of the most dangerous work environments when compared with other private industrial sectors in the United States. Conditions of construction sites often produce hazardous proximity situations by requiring pedestrian workers and heavy equipment to operate at close proximity. Injury and fatality statistics indicate that current safety practices of construction workers have proven inadequate. The research aims to design hazard zone around pieces of heavy construction equipment in which site personnel should not enter during construction operations. The scope is limited to construction sites and equipment at a horizontal grade and hazards between heavy construction excavation equipment and workers-on-foot. A framework for creating the hazard zone around a piece of construction equipment is presented including detailed methodology discussions for each step. A user interface is also presented that automatically creates a hazard zone around select pieces of construction equipment based on user-defined parameters. The hazard zone for a dump truck, excavator, and backhoe are shown using the created framework. Results indicate that hazard zones for pedestrian workers can be created around construction equipment to increase hazard awareness for workers. Contributions for this research include a user-friendly hazard zone creation tool and database for safety managers and scientific evaluation data of the created hazard zone framework. Safety standards can be formulated based on the design and implement hazard zones on equipment.

Contracting in overseas construction markets involves not only the typical risks at home, but also the complex and diverse risks peculiar to international transactions. In addition, international construction project risks are highly interdependent. The objectives of this study are to (1) explore the risk paths in the international construction projects performed by Chinese contractors, and (2) examine the risk effects on the objectives of these projects. To achieve the research objectives, a total of 60 risks were identified from literature review and a questionnaire survey was conducted with 104 professionals from Chinese international contractors. Adopting the structural equation modeling technique, this study proposed a networking of 20 significant risk paths. Specifically, host government–related risk, contractor’s lack of experience, and contractors’ lack of managerial skills had significant effect on project cost, quality, and schedule objectives, respectively. Moreover, host government–related risk affected project cost performance indirectly through resource price fluctuation, and contractors’ lack of managerial skills affects project schedule objective indirectly through decrease in productivity. This study contributes to the literature because it is different from most of the previous studies, which depended on separate risk categories and generic checklists but failed to explore the potential interrelationships among risks in international construction projects. Additionally, the identification of risk path scenarios enables practitioners to gain a better understanding of the sources and impact areas of risks, and to better deal with the risks, thereby contributing to the practice.