Journal of Construction Engineering and Management

Construction management at risk, design/build and design/bid/build are three principal project delivery systems used in the United States today. This paper empirically compares cost, schedule, and quality performance of these three project delivery systems, using project-specific data collected from 351 U.S. building projects. The study included collecting, checking, and validating industry data, significance testing of univariate comparisons and the statistical development of multivariate linear regression models for predicting average project performance. A nonresponse study verified statistically that collected data were appropriate for analysis and representative of the industry from which they were drawn. Significance testing and multivariate comparisons used nearly 100 explanatory and interacting variables to explain project cost, schedule, and quality performance. Specific comparisons between project delivery systems, performance metrics, and six facility classes are discussed. Results and the level of confidence that surrounds each finding are presented.

The uncertain physical and regulatory conditions prevalent in the field of environmental restoration often lead to considerable project cost growth. To date, the ability of project personnel to predict the magnitude of such growth has been limited. A formal approach to identifying, classifying, and incorporating uncertainty into standard cost estimating procedures is needed to quantify the risk of large-scale cost growth prior to project commencement. Because the elicitation of expert knowledge is critical to the risk analysis process, this paper evaluates the effectiveness of several approaches to eliciting and encoding probabilistic judgments. In essence we ask, “How should one frame questions concerning uncertain judgments in order to get the best answers?” In addition, this paper examines using both influence diagramming and Monte Carlo simulation to model the uncertainties associated with environmental restoration projects.

The construction industry on average has a higher rate of occupational injury than most other industries. However, steps can be taken to reduce worker risk through the effective management of controllable factors. These controllable factors can be managed through an aggressive safety program with emphasis on hazard awareness, safer work practices, and employee involvement. While the initial cost impact to a company to establish a sound safety program can be substantial, the long-term benefits can lead to overall cost savings that may outweigh the costs of implementation and management. This paper highlights some of the areas addressed by Mason Construction, Inc. in the establishment of its safety program. Mason is a merit shop contractor with approximately $15 million annual revenue in the civil sector of the petrochemical industry of southeast Texas. Through the use of quantifiable data and multiple examples from this case study, it is shown that the benefits attributable to a strong safety program outweigh the costs of the program itself.

The contextual factors of a company, particularly age and size, are commonly argued to have important implications on its survival chances. The research presented in this paper explores these implications in the context of the construction industry by analyzing the age distribution of failed construction companies and computing age-specific failure probabilities over a 10-year period (1985–1994). The research findings support the liability of adolescence rather than the liability of newness concept. Computed age-specific failure probabilities reveal a pattern of failure in the U.S. construction industry where the risk of failure increases initially with increasing age, reaches a peak point and decreases thereafter as companies grow older. Youngness of a construction company, which implies lack of organizational learning and lack of legitimacy, coupled with smallness, appears to be the main factor explaining this pattern. The paper finally addresses the strategic implications of increasing turbulence in the construction industry on the survival or failure of construction firms.

Guidelines are provided for inspection and selective placement of quarrystone armor units used for breakwaters, jetties, and revetments. General guidelines are suggested for procurement and inspection of stone at quarries, transportation and storage of stone, and the individual placement of stone in structure armor layers. Guidelines for placement include recommendations for the progression of construction, orientation of stones, elevations of stones in the structure's armor layer, gradation and keying of stones, and on-site inspection for stone weights and quality.

Public sector owners are rapidly identifying new construction procurement methods. Changing procurement laws and documented project success are encouraging owners to attempt the design-build method of project procurement. Design-build is a radical departure from the traditional design-bid-build method. This paper reports on the analysis of 122 case studies and the resulting automated tool for public sector design-build project selection. Prediction models are developed for five performance criteria that correlate specific project characteristics to success. Performance criteria and associated models include budget variance, schedule variance, conformance to expectations, administrative burden, and overall user satisfaction. Project characteristics are categorized as project, owner, market, and relationship variables. Statistically significant correlations with success include scope definition, schedule definition, budget definition, project complexity, agency experience, agency staffing, owner design input, design-build market, design-builder prequalification, and method of selection.

Construction industry craft divisions in the United States are currently based on narrowly defined skill groupings. The steady demand for improved productivity and the shortage of skilled craft workers call into question this traditionally accepted “single-skilled” strategy. While these craft patterns are prevalent throughout the union and nonunionized sectors of the industry, they are not necessarily responsive to construction sequence or the optimal use of worker skills. Alternative labor utilization strategies may provide increased project performance and may reduce craft shortages through better utilization of the existing workforce. An analysis model is developed in this study to measure the project impact of alternative labor utilization strategies. The model is used to assess four multiskilling strategies on the construction of a $70,000,000 project. Benefits of multiskilled labor utilization strategies were demonstrated including potentially a 5–20% labor cost savings, a 35% reduction in required workforce, a 47% increase in average employment duration, and an increase in earning potential for multiskilled construction workers.

The construction industry has a difficult time prospectively identifying, with accuracy, either the scope or magnitude of change-caused disruption at the activity level. This difficulty increases contractors' risks when negotiating change orders, makes owners more suspicious of contractors' negotiating positions, increases the chances that change orders will not be settled and will turn into claims or disputes, and makes it more difficult for contractors to foresee and mitigate the disruptive effects of change orders. This article proposes a methodology which will solve these problems by (1) qualitatively identifying the scope of possible disruption, thereby limiting the scope of application of any disruption estimating methodology; (2) within this scope of possible disruption, quantifying disruption using an improved factor-based estimating methodology; and (3) yielding activity-specific estimates of disruption. The proposed methodology recognizes the specific characteristics of the interacting activities, and more realistically models the process by which disruption occurs. Activity-specific estimates of disruption will allow contractors to mitigate disruption by taking advantage of available float to selectively postpone some combination of the disrupting and/or disrupted activities.

Construction labor productivity is affected by several factors. Modeling of construction labor productivity could be challenging when effects of multiple factors are considered simultaneously. In this paper a methodology based on the regression and neural network modeling techniques is presented for quantitative evaluation of the impact of multiple factors on productivity. The methodology is applied to develop productivity models for concrete pouring, formwork, and concrete finishing tasks, using data compiled from eight building projects. The predictive behaviors of the models are compared with the previous productivity studies. Model results, advantages of the methodology, and study limitations are discussed.