Journal of Construction Engineering and Management

A current trend in residential construction is the use of prefabricated wall panels. Panels are manufactured at a factory, then arranged into stacks for transporting to the construction site, where they are assembled. Current approaches to planning panelized construction are focused on stacking and transport efficiency, with little consideration given to assembly. This results in excessive panel material handling during construction, increased construction lead time, and increased risk of worker overload and/or injury. This paper proposes a lean approach to panel stacking, panel sequencing, and stack locating, where panels within each stack form a continuous structure and are erected via continuous flow. The objectives are to minimize the quantity of stacks, panel material handling distance, and the work required to position and brace panels—panel interference is ignored. Few researchers have addressed this problem: a single algorithm has been reported, and this only works for certain building shapes and may provide infeasible solutions. The proposed approach and algorithm result in improved performance, have no shape restrictions, and always provide feasible solutions. Additionally, computational experiments show that the algorithm outperforms methods being employed in the construction industry today.

The request for proposal (RFP) with the design-build (DB) procurement arrangement is a document in which an owner develops his requirements and conveys the project scope to DB contractors. Owners should provide an appropriate level of design in DB RFPs to adequately describe their requirements without compromising the prospects for innovation. This paper examines and compares the different levels of owner-provided design in DB RFPs by the content analysis of 84 requests for RFPs for public DB projects advertised between 2000 and 2010 with an aggregate contract value of over $5.4 billion. A statistical analysis was also conducted to explore the relationship between the proportion of owner-provided design and other project information, including project type, advertisement time, project size, contractor selection method, procurement process, and contract type. The results show that the majority (64.8%) of the RFPs provides less than 10% of the owner-provided design. The owner-provided design proportion has a significant association with project type, project size, contractor selection method, and contract type. In addition, owners are generally providing less design in recent years than previously. The research findings also provide owners with perspectives to determine the appropriate level of owner-provided design in DB RFPs.

The major challenges of project risk assessment may be attributed to the knowledge requirements for determining the level of uncertainty and the development of complex models to predict project outcomes. The duration–cost influence network is an adequate model that can be used for activity-based risk modeling. In this study, a scenario analysis feature is added to this model and a Web-based tool is developed that can be used to calculate risk-adjusted duration and cost, considering the risks affecting cost and duration of individual activities. Monte Carlo simulation is used to create scenarios, and the output of these scenarios is calculated by using the cost–duration influence system that simulates the vulnerability of the project to the identified risk factors. The Web-based tool can be used by decision makers during the preplanning stage of construction projects to estimate the cost and duration implications of various risk occurrence scenarios, determine contingencies, and prepare risk-management plans.

Improving productivity and reducing work-in-process are two activities that can improve project performance, but are often difficult to accomplish. The construction process is complex and consists of a large number of interdependent and sequential tasks. Construction activities are simulated as serial production lines, using state- and resource-based simulation of construction processes simulation models, to investigate the effects that different production control strategies (push/pull and balanced/unbalanced) have on productivity and work-in-process. The sensitivity to task duration variance is also examined for different working strategies. Simulation results are used to compare the models based on their performance. In the presence of duration variance, push strategies result in higher productivity, whereas pull strategies result in lower amounts of work-in-process. Pull strategies are more sensitive to the presence of duration variance. Work-in-process is also a function of the coefficient of variance. Simulation results are used to compare the tradeoffs between strategies. The findings will help construction managers better understand the effects of working strategies and conditions to decide which production control strategy is best suited for their needs.

Construction workers continue to experience high rates of injury and illness compared with many other industries. Growing evidence suggests that safety culture has a direct effect on safety performance. This study investigated measures of safety culture and risk perception among a residential-home-building cohort within the HomeSafe Pilot Program in the Denver metro area of Colorado. Investigators compared group-level responses of management to frontline construction workers. Results indicate that managers appraised the overall safety culture at higher levels compared with the workers. Managers also perceived a higher level of management commitment to safety and health than that reported by workers.

The focus of knowledge management (KM) in the construction industry is moving towards capability building for value creation. The study reported by this paper is motivated by recent assertions about the genesis and evolution of knowledge management capability (KMC) in the strategic management field. It attempts to shed light on the governance of learning mechanisms that develop KMC within the context of construction firms. A questionnaire survey was administered to a sample of construction contractors operating in the very dynamic Hong Kong market to elicit opinions on the learning mechanisms and business outcomes of targeted firms. On the basis of a total of 149 usable responses, structural equation modeling (SEM) analysis identified relationships among knowledge-governance mechanisms, knowledge processes, and business performance, thereby supporting the existence of strategic learning loops. The study findings provide evidence from the construction context for capability assertions that knowledge-governance mechanisms and processes form learning mechanisms that carry out strategic learning to create value, effect performance outcomes, and ultimately drive the evolution of KMC. The findings imply that it is feasible for managing construction firms to govern learning mechanisms through managing the capability-based holistic KM system, thereby reconfiguring KMC to match needs in the dynamic market environment over time.

One of the most challenging tasks of a construction project planner is to simultaneously minimize the total project cost and total project duration while considering issues related to optimal resource allocation and resource leveling. Therefore, project planners face complicated multivariate, time-cost-resource optimization (TCRO) problems that require time-cost-resource tradeoff analysis. The hybrid GA–PSO approach is presented to solve complex, TCRO problems in construction project planning. The proposed approach uses the fuzzy set theory to characterize uncertainty about the input data (i.e., time, cost, and resources required to perform an activity) in this hybrid approach. The proposed fuzzy-enabled hybrid GA–PSO approach is applied to solve two optimization problems that are found in the construction project planning literature. It is shown that the proposed fuzzy enabled hybrid GA–PSO approach is superior to existing optimization algorithms at finding better project schedule solutions with less total project cost, less total project duration, and less total variation in resource allocation. The results also show that the proposed approach is faster than existing methods in processing time for solving complex TCRO problems in construction project planning.

The total construction cost and time of projects are often overrun. It is known that when positive correlations between costs are disregarded, the range of possible total construction costs is underestimated. A model is needed to estimate the effect of correlations on the probability distributions of total cost and total time. Four cost–cost and one cost–time correlations in the construction of rail lines were identified, two of which were investigated in detail using a model applicable to the construction of any networked system. This paper presents the theoretical background of the model, the correlations occurring in rail line construction, and the analysis of the impact of such correlations in two case studies including several scenarios and one sensitivity analysis. The results clearly show that the standard deviation of the total cost increases with the magnitude of the correlation and, most importantly, it dramatically increases with the number of costs that are correlated; it also depends on the type of correlation matrix. Correlation between costs must be modeled to capture the wide range of the possible total cost; otherwise, the total construction cost of projects will continue being significantly underestimated.

Compaction quality is critical to the stability and durability of earth-rock dams. The traditional quality inspection method relies primarily on testing randomly sampled spots of a job site, which may cause unreliable representation of the compaction quality of the entire work and lead to delays not only in performing the construction work but also in identifying and rectifying quality issues. In this paper, a quality-inspection process is developed that monitors compaction operations of earth-rock dam construction in real time and establishes a multiple regression model to predict compaction quality by using independent variable data obtained from the real-time quality-monitoring system. These independent variables include compaction operation parameters (i.e., compaction passes, roller velocity, vibration status, and pavement thickness) and earth-rock aggregate’s moisture content and gradation. Furthermore, by using the kriging interpolation procedure, the compactness at any point of a work area can be estimated, and the overall passing rate and spatial uniformity of compaction quality of the work area can be analyzed. The case study of the NZD Dam project in southwest China demonstrates the effectiveness and feasibility of the proposed method. This method enables the evaluation of compaction quality covering 100% of the work area, thus reducing the uncertainty of quality inspection associated with random spot tests, and facilitates timely feedback for quality control and improvement of earth-rock dam construction.

The LEED (Leadership in Energy and Environmental Design) environmental certification system has developed as a standard for sustainable project planning, though research into its economic impacts have been limited. The main objective of this study is to investigate the economic impacts that two LEED public transportation access (PTA) components, a bus and a light rail system, have on appraised values of land parcels. This study developed a predictive model to quantify the impacts that the two LEED PTA components would have on the appraised unit values of unimproved land parcels. First, a LEED PTA indication map using geographical information system (GIS) was created to randomly select unimproved parcels. Second, the PTA-qualified parcels were selected from the unimproved parcels to use for this study. Lastly, a multiple linear regression method with a one-way ANOVA analysis was performed to predict the unit value of selected parcels by analyzing how the appraised unit value ($\${\mathrm{ft}}^2$) of parcels was affected by the PTA credits. The results indicate that the two PTA LEED components have a significant impact on the appraised land values, which suggests an economic benefit for adopting the LEED PTA components.

To counteract cost escalation and delays in infrastructure construction, an estimation model has been developed that simulates project uncertainty with probability distributions, correlations, and disruptive events. When applied to a new rail line project, three model inputs were not available from the designers: time distributions, cost correlations, and probability of occurrence and cost/time impacts of disruptive events. Experts in the field of tunnel-, viaduct-, and earthwork construction were asked to estimate the unavailable information. This paper presents a brief overview of biases that occur when experts estimate probabilities, the calibration steps taken to prevent the experts from being affected by such biases, and example questions from the questionnaire, followed by an in-depth discussion of findings. Unexpectedly, the experts followed radically different estimation techniques: the tunnel expert recalled values from past projects, the viaduct expert calculated the required values, while the earthwork expert estimated the mode value, and from it, the extreme values. Depending on estimation technique, a bias influences or cannot influence an expert. It was also observed that experts not familiar with probability theory encountered major difficulties in correlation estimation, despite concept explanation and visualization. Thus, for a successful correlation estimation it is paramount that experts be acquainted with probability theory in addition to being knowledgeable in their fields.

Although many researchers have attempted to examine the value-added advantages of adopting Leadership in Energy and Environmental Design (LEED) standards for sustainable design projects, quantitative research into its impact on the appraised unit value of land has been fairly limited. The objective of this study is to develop a quantifying model that predicts the unit value of unimproved lands by analyzing the interdependency between the adoption of three LEED sustainable site credits (LEED SSCs) and the appraised unit value of unimproved lands. By using a geographic information system mapping technique, a set of LEED SSC data was created and transformed for normality. A multiple linear regression analysis was then performed to develop the predictive model with a time and location adjustment factor to analyze how the appraised value of land was affected by the presence of three LEED SSCs. The analysis indicates that adapting projects to meet acceptance standards for LEED SSCs has a significant positive impact on the appraised unit value of improved lands. The findings of this study will help decision makers frame sustainable real estate development projects that consider LEED SSCs.