Journal of Construction Engineering and Management

The estimation of markup is a difficult process for contractors in a changeable and uncertain construction environment. In this study, a fuzzy logic-based artificial neural network (ANN) model, called the fuzzy neural network (FNN) model, is constructed to assist contractors in making markup decisions. With the fuzzy logic inference system integrated inside, the FNN model provides users with a clear explanation to justify the rationality of the estimated markup output. Meanwhile, with the self-learning ability of ANN, the accuracy of the estimation results is improved. From a survey and interview with local contractors, the factors that affect markup estimation and the rules applied in the markup decision are identified. Based on the finding, both ANN and FNN models were constructed and trained in different project scenarios. The comparison of the two models shows that FNN will assist contractors with markup estimation with more accurate results and convincing user-defined linguistic rules inside.

Contractor’s ability to procure cash to carry out construction operations represents a crucial factor to run profitable business. Bank overdrafts have always been the major source to finance construction projects. However, it is not uncommon that bankers set a limit on the credit allocated to an established overdraft. Bankers’ interest rates and consequently contractors’ financing costs are basically determined based on the allocated credit limits. Furthermore, project indirect costs are directly proportional to the project duration which is affected by the allocated credit limit. Thus, the credit limit affects project financing costs and indirect costs which in turn affect project profit. However, finance-based scheduling produces financially executable schedules at specified credit limits while maintaining the demand of time minimization. Thus, finance-based scheduling provides a tool to control the credit requirements. This control enables contractors to negotiate lower interest rates which reduce financing costs. Thus, finance-based scheduling enables contractors to reduce project indirect costs and financing costs. This paper utilizes genetic algorithm’s technique to devise finance-based schedules that maximize project profit through minimizing financing costs and indirect costs.

The purpose of this study is to empirically evaluate the transformational and transactional leadership styles among building professionals in the construction industry. This is part of a large-scale research project undertaken by the writers. Bass’s transformational leadership theory reported in 1985 was employed and tested in a sample of 510 professional employees from a cross section of qualified building professionals selected from four countries. The main objectives of the study are (1) to examine the extent of leaders who are perceived to use transformational and transactional leadership styles; (2) to identify which of the two leadership styles is best able to predict outcomes of “leader effectiveness,” “extra effort by employees,” and “employees” satisfaction with the leaders; and (3) to offer insight into the management theory for building professionals in business organizations. Results of the study suggest that all five of the transformational factors and three of the transactional factors are significantly correlated with leadership outcomes of leader effectiveness, extra effort by employees, and employees satisfaction. The results further supported that transformational leadership could augment transactional leadership in producing greater amounts of performance and satisfaction.

The strength of housing construction has a profound effect on the national economy and the society. As a consequence, achieving high productivity, quality, and safety are considered of high priority for this industry segment. This paper proposes to replace the traditional management approach for site operation with a management philosophy that has as its sole and unifying objective the elimination of process waste. It will be demonstrated that a waste-based management philosophy creates a culture of continuous improvements and innovative progress driven by the goal to reduce wastes from injuries to unproductive work activities. Wall framing and masonry construction are used to demonstrate how the waste-based management approach functions. The results of the test case application provide evidence that paying attention to minimizing resource wastes at all levels, from laborer to site manager, will produce drastic effects on productivity, safety, and quality of residential construction.

When investing in information technology (IT) applications, construction managers implicitly account for the value of adding future applications to the original investment as the business and technical environment changes. A real option model links uncertainty to the value of an underlying traded asset, providing an objective measure of this managerial flexibility. A case study that investigated the value of options to extend a general contractor’s software platform showed that it is possible to construct a real option model which measures the value of this flexibility, since the major risk (the architect’s adoption rate) is external to the investing organization. In another case study, a contractor evaluated the value of the pilot project in view of the information it is expected to generate. Since the risks are internal, a decision analysis model is used instead of a binary option model. The results show that it is possible to quantify the value of managerial flexibility for IT investments in the architecture, engineering, and construction industry, but that the proper method to use is contingent on the nature of the investment project.

Four factors make it challenging to manage semiconductor fabrication facility (“fabs”) projects: technical complexity of the product design, need to compress the project duration, need to reduce upfront costs, and unexpected project changes. The strategies employed by practitioners to cope with these challenges form an intricate puzzle. We empirically develop a framework that provides a structure for helping to solve this puzzle, which comprises two principles: investing upfront in a flexible product design and structuring a flexible process. Empirical findings reveal that project teams make commitments early on by overdesigning but also postpone critical decisions by differentiating the scope of their work. Project teams employ other strategies such as increasing communication, using modular architectures, engaging in four-dimensional computer-based modeling, and fabricating components and subsystems off-site. Our analysis yields understanding on the purposes and performance tradeoffs of these strategies, and on how they embody the two principles. Project managers may find the framework useful when deciding which strategies best suit other equally challenging projects.

Most state highways in the United States were built during the 1960s and 1970s with an infrastructure investment of more than $1 trillion. They now exceed their $20\text{year}$ design lives and are seriously deteriorated. The consequences are high maintenance and road user costs because of degraded road surfaces and construction work zone delays. Efficient planning of highway rehabilitation closures is critical. This paper presents a simulation model, Construction Analysis for Pavement Rehabilitation Strategies (CA4PRS), which estimates the maximum amount of highway rehabilitation/reconstruction during various closure timeframes. The model balances project constraints such as scheduling interfaces, pavement materials and design, contractor logistics and resources, and traffic operations. It has been successfully used on several urban freeway rehabilitation projects with high traffic volume, including projects on I-10 and I-710. The CA4PRS helps agencies and contractors plan highway rehabilitation strategies by taking into account long-life pavement performance, construction productivity, traffic delay, and total cost.

Owing to the complexity of a construction project, the analytic network process (ANP) is helpful to deal with interdependent relationships within a multicriteria decision-making model. This paper demonstrates an example to illustrate how to empirically prioritize a set of projects by using a five-level project selection model. A questionnaire was filled by a group of construction professionals of a medium-sized local developer and scores were computed for prioritizing the potential projects. The paper is relevant to both industry practitioners and researchers. Industry practitioners may adopt the weighted criteria for direct project selection or apply the ANP method to prioritize their own set of selection criteria. Researchers may rely on this paper as a point of departure for exploring other uses of ANP.

The utilization of nighttime work in highway construction and rehabilitation projects has been increasing in recent years throughout the United States. In this type of projects, construction planners are required to develop and submit a lighting plan that provides: (1) adequate illuminance levels for all planned nighttime construction tasks; (2) reasonable uniformity of light distribution in the work area, and (3) acceptable glare levels to both road users and construction workers. In order to support construction planners in this vital and challenging task, this paper presents a lighting design model, named CONLIGHT, which is capable of considering the specific requirements of nighttime highway construction operations. The model is developed to enable construction planners to evaluate the performance of various lighting plans and select a practical design that complies with all lighting requirements for the nighttime work being planned. An application example is analyzed to illustrate the use of the model and demonstrate its accuracy and capabilities in generating practical lighting plans for nighttime construction and rehabilitation projects.

Many departments of transportation have recently started to utilize innovative contracting methods that provide new incentives for improving construction quality. These emerging contracts place an increasing pressure on decision makers in the construction industry to search for an optimal resource utilization plan that minimizes construction cost and time while maximizing its quality. This paper presents a multiobjective optimization model that supports decision makers in performing this challenging task. The model is designed to transform the traditional two-dimensional time-cost tradeoff analysis to an advanced three-dimensional time-cost-quality trade-off analysis. The model is developed as a multiobjective genetic algorithm to provide the capability of quantifying and considering quality in construction optimization. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in generating and visualizing optimal tradeoffs among construction time, cost, and quality.

The growing need for better monitoring and control of road construction projects, together with rapid technological progress, have led to a number of interesting developments, which are reviewed below. The present paper describes the development of a real-time monitoring model capable of measuring productivity and progress automatically. The model, which uses global positioning system for on-site automated data collection, was tested and validated on site. The results of the field experiments have indicated that the expected accuracy level of the model can be assessed as $\pm 4–5\%$ for unstructured activities and even higher for more structured ones, such as asphalt spreading. The paper concludes that it is possible to automatically measure the performance of earthmoving operations. Based on the results, it also highlights the needs for further research.

Work in trenches can be very dangerous if workers are not provided with adequate protection against trench cave-ins. One method of providing for worker protection in trenches is with the use of trench boxes, widely used, engineered structures that permit workers to work safely in trenches. A study of the experiences of utility contractors with the use of trench boxes provided several notable findings that can help in implementing safe work practices in trenches. Most safety problems with the use of trench boxes are attributed to human error or judgment. For example, several respondents commented that workers were observed exiting from the trench boxes by walking up the backfill, a practice that exposes workers to the dangers of trench cave-ins. The importance of training was also evident in the results. Firms with better safety performance records conducted specialized training courses for their employees, and they provided more frequent training courses.