Journal of Construction Engineering and Management

This paper presents an initial step in seeking to understand just how the adoption of advanced machine guidance technology, especially global positioning systems, leads to improvements in performance by the earthwork contractor. Two grading scenarios and one dozing scenario are examined based upon site observations and interviews with field personnel. Analysis demonstrated that productivity and unit cost improvements result from a reduction in surveying support, grade checking, an increase in operational efficiency, and a decrease in the number of passes. These results are in agreement with published results of benefits of 3D guidance over 2D guidance.

This paper discusses empirical research aimed at examining the relationship between the safety climate and safe work behavior in construction site environments. A literature review has identified a number of independent constructs with the potential to affect the safety climate. A research model was developed based on the hypothesis that safe work behaviors are consequences of the existing safety climate, which, in turn, is determined by the identified independent constructs. A questionnaire survey was used in order to facilitate the collection of information from construction sites. The model was tested using structural equation modeling. The paper presents the results of testing the research model. The results corroborate the importance of the role of management commitment, communication, workers’ involvement, attitudes, competence, as well as supportive and supervisory environments, in achieving a positive safety climate.

Conceptual frameworks dominate organizational learning literature with limited empirical assessments. This raises several questions about the validity and applicability of the various conceptual frameworks for how managers can build organizational learning capabilities. As such, lessons from the conceptual frameworks of organizational learning for addressing performance improvement that might have been used by construction contractors have been limited. This paper presents a quantitative analysis of organizational learning by construction contractors. The principles that underlie organizational learning and the factors that promote double-loop learning as a strategy for improving construction contractors’ business processes are presented. The paper has also established the learning orientations and focus of the surveyed construction contractors to determine their organizational learning dimensions as well as the factors that induced their double-loop learning, as rich lessons for organizations in the construction industry.

One of the most important and difficult problems faced by the steel fabrication industry is the planning and scheduling of shop activities. Competitive pressures force fabricators to disrupt schedules in progress to accommodate frequent requests from key customers for changes in design and/or delivery schedules. Capacity management is a complex problem and is key to proper management of manufacturing/fabrication activities. This paper presents a decision support system for planning and scheduling of steel fabrication projects. Although the immediate application of this approach is steel fabrication, its fundamental heuristic approach can be applied to any construction job shop scheduling exercise. Its main advantage over techniques such as CPM is that it is resource driven; its advantages over simulation techniques are its simplicity and overall schedule development time.

Work in construction always requires moving within, and interacting with, a complex environment while handling heavy materials and building elements to be joined, inserted, or aligned. Modern design software is able to digitally model all of those elements in their spatially correct configuration, and without interference. When it comes to the actual construction, however, the spatial models do not find any use. Twenty years after the manufacturing industry began using electronic design data to control their machinery, construction is also getting ready to move away from its longstanding tradition of working with paper-based blueprints. The newest steps on the path toward the use of three-dimensional digital design data in support of site operation are stimulated by the global positioning system and the many uses of lasers. Surveying has always performed critical functions on construction sites, such as marking building layouts, anchor bolts, concrete formwork, or bridge bearings. The objective of spatial integration in construction is to digitally merge spatial design data with the digital model of equipment working on implementing the design. This paper will briefly review historical advancements in “perfecting” the surveying technology before presenting three examples of a quantum leap in the way we design, plan, and control construction projects in the future.

With the surge of increasingly complex and fast-track construction projects, disputes are inevitable. Skills in dispute resolution should be part of the tool kit of any practitioner in a managerial position. The perceived shortcomings of litigation and arbitration, with their concomitant rise in costs, delays, and adversarial relationships, have encouraged the rapid growth of alternative dispute-resolution processes, namely, conciliation, mediation, adjudication, and other hybrid processes that have been widely used and well received by the Hong Kong construction industry. For example, mediation is now an integral part of most conditions of contracts published by the government of the Hong Kong Special Administration Region. However, the last decade evidenced the incorporation of increasingly complex dispute-resolution clauses in construction contracts, typically involving several alternative dispute resolution (ADR) techniques and arbitration arranged in sequential tiers. These dispute-resolution procedures render the supposedly more economic and speedy ADR process ineffective. In this study, a hierarchical model is developed to organize attributes of ADR processes. This presentation fits with the use of analytical hierarchy process methodology by a panel of experts to prioritize ADR process attributes. The top-ranked attributes identified as critical include, among others, preservation of relationships, enforceability, neutrality, and consensus. The experts also suggested means to establish these attributes. By focusing on these critical attributes, the dispute-resolution process can be kept simple and effective.

Construction site layout is concerned with the existence, positioning, and timing of the temporary facilities that are used to carry out a construction project. Typically these problems are very complicated to formulate and difficult to solve. They are, however, very important to virtually any construction project, since the site layout can significantly affect the cost of the project. This paper describes the general site layout problem from both a theoretical and a practical point of view. It proposes genetic algorithms as a possible solution technique and includes a theoretical example of positioning temporary facilities. This is extended to a practical problem in which the cost of movement is modeled realistically using an augmented genetic algorithm. Some preliminary conclusions are drawn for the application of genetic algorithms to construction site layout problems.

Notwithstanding the use of earthmoving equipment, cranes, and other machinery, physically strenuous and demanding tasks remain endemic to the construction industry. This research was motivated by the need to investigate the physical demands of construction work and to evaluate whether these physical demands are excessive. Physiological measures of energy expenditure, including oxygen consumption and heart rate data, were collected for 100 construction workers performing typical construction work. The average oxygen uptake for the measured construction activities was 0.82 L⋅min⁻¹ (±0.22 L⋅min⁻¹), and the average heart rate for the measured construction activities was 108 beats ⋅min⁻¹ (±17 beats ⋅min⁻¹). The measured data were evaluated against published guidelines for acceptable levels of physical performance in industrial settings indicating that a significant number of craft workers (20 to 40%) routinely exceed these physiological thresholds. The results clearly point to the need to promote and apply concepts of work physiology at the workplace to better the occupational health and safety of the construction workforce. This paper developed the foundation for further applied research regarding the physical demands of construction work.

Although a stochastic simulation study can eliminate the merge event bias in the project evaluation and review technique (PERT), the errors due to calculating the statistical descriptors of beta distributions with the three-point time estimates of PERT may still make the simulation results suspect. In order to enhance PERT simulation in terms of input modeling, this paper presents an artificial neural network (ANN)-based approach to estimate the true properties of the beta distributions from statistical sampling of actual data combined with subjective information. The minimum and maximum values along with the lower and upper quartiles are four time estimates used to uniquely define a beta distribution. The effects of shape parameters of beta distributions are closely examined, and the working range of shape parameters is defined. To construct an ANN model, data are prepared using random sampling techniques and Excel functions. Through exploring the training data provided, the ANN model has found the patterns between the inputs and the outputs, namely, the interactions and nonlinear relationships among the lower and upper quartiles and the shape parameters of the beta distributions. The ANN model was tested, validated, and compared with other packages for fitting beta distributions such as BetaFit, VIBES, and BestFit. The developed ANN-based input modeling method attempts to embed artificial intelligence into simulation and finds a new way to fit statistical distributions for activity duration in construction simulation, as demonstrated in a sample application.

Certain attributes of an architect or engineer (AE) may be used to predict his performance. These attributes may be categorized as “hard” or “soft” attributes. Hard attributes include an AE’s cognitive ability, job knowledge, task proficiency, and job experience. Soft attributes include an AE’s conscientiousness, initiative, social skills, controllability, and commitment. The purpose of this study is to identify those attributes that affect an AE’s performance, and to construct a model to predict his performance in design build (DB) projects. Twenty five attributes were generated using the hierarchy tree. The importance of these attributes was tested with designer/ builders who select and hire AEs, using a standard questionnaire. A statistical test showed that 24 of these attributes are significantly important. Thirty AEs were evaluated by experienced designer/builders (experts) who have worked with them in completed DB projects. Besides giving a global performance score of the AE (dependent variable), each expert also evaluated the AE on the degree to which they exhibited the important attributes (independent variables). Based on these ratings, an optimum multiple regression performance prediction model was obtained. To validate the model, another group of experts used the optimum model to evaluate 18 other AEs. The resulting performance score as calculated by the model was compared to the global performance scores awarded by the designer/builders. This validation process showed the model to be robust. The results of the study reveal that an AE’s performance can be predicted by using just three attributes: AE’s problem solving ability and project approach, AE’s speed in producing design drawings, and the AE’s level of enthusiasm in tackling a difficult assignment.

The statistical variance of total project cost is usually estimated by means of Monte Carlo simulation on the assumption that exact analytic approaches are too difficult. This paper tests that assumption and shows that, contrary to expectations, the analytic solution is relatively straightforward. It is also shown that the coefficient of variation is unaffected by the size (floor area) of the project when using standardized component costs. A case study is provided in which actual component costs are analyzed to obtain the required total cost variance. The results confirm previous work in showing that the approximation of the second moment (variance) under the assumption of independence considerably underestimates the exact value. The analysis then continues to examine the effects of professional judgment, and, with the simulated data used, the approximation is shown to be reasonably accurate—the professional judgment absorbing most of the intercorrelations involved. An example is also given in which the component unit quantities are priced by their average unit costs and which again shows the approximation to be close to the true value. Finally, this is extended to show how the exact total project cost variances may be obtained for each project.