Journal of Construction Engineering and Management

This case study paper presents an innovative fast-track approach applied to a heavily trafficked urban freeway reconstruction project in Southern California. Badly deteriorated truck lanes in both directions along a $4.5\text{-}\mathrm{km}$ stretch of I-15 were rebuilt from the gravel base up. The operations, estimated to take $10\text{months}$ using traditional nighttime closures, were completed in two $9\text{-}\text{day}$ continuous closures with round-the-clock (about $210\mathrm{h}$ for each direction) operations. This “Rapid Rehab” project adopted state-of-practice technologies to accelerate construction, mitigate traffic disruptions, and propagate project information. As a result, traffic demand through the construction work zone was reduced by 20% and the maximum peak-hour delay was reduced by 50%. The estimated benefits of accelerated reconstruction on this project included a 28% reduction in agency cost and 29% time value savings to road users, compared to the traditional approach of using repeated nighttime closures. Web surveys showed dramatic changes in public perception of the Rapid Rehab approach from initial reluctance and objection to positive support.

With the increased popularity of concession projects over the last three decades, there is a need for a decision support system (DSS) capable of evaluating and comparing several concession project investment (CPI) options in an effective and efficient manner. Hence, a novel DSS has been developed that takes into consideration both financial and nonfinancial aspects of the investment option, as well as the uncertainties commonly encountered during the feasibility stage of a project. The DSS is fully implemented as a standalone computer software package, ECCO (evaluate and compare concession options), in order to be of practical use. This paper outlines and validates ECCO’s design and structure through the demonstration of its capabilities in the evaluation and comparison of three real-life CPI case studies.

Quantifying and minimizing the risks associated with delays in the construction industry are the main challenges for all parties involved. Float loss impact in noncritical activities is one of the complicated delays to assess on a project’s duration and cost. This is due to the fact that the deterministic critical path method cannot cope with such delays unless they exceed the total float values. Further, stochastic analysis, which is used in this research to assess the impact of such delays, is perceived by many planners to be complicated and time consuming. This paper presents a method to control the risks associated with float loss in construction projects. The method uses a recently developed multiple simulation analysis technique that combines the results of cost range estimates and stochastic scheduling, using Monte Carlo simulation. The proposed method quantifies the float loss impact on project duration and cost. Least-squares nonlinear regression is used to convert the stochastic results into a polynomial function that quantifies the float loss impact by relating directly the float loss value to project duration and cost at a specified confidence level.

The construction industry has employed various schedule analysis techniques to support delay claims. Paradoxically, resource-related issues are frequently ignored even though they can affect project completion time, too. The research presented here shows that delay analysis without resource allocation practice substantially affects results of schedule analysis. Some delay can cause unrealistic resource allocation in downstream work, which in turn may further delay the project. The effect of resource allocation can either add to or reduce the severity of some delaying event. Apportionment of delay responsibility may be inaccurate unless resource allocation practice is considered in the analysis. Practical and necessary steps are proposed to enhance the existing window analysis technique. A case study is presented to compare the enhanced window analysis with the existing window analysis. This research enables practitioners to make delay analyses and claims more practical and reliable. Further studies are needed to improve the usability, credibility, and acceptability of schedule analysis considering resource allocation.

Time and costs are considered to be substantial success factors of building construction projects. In Germany, early cost estimates are provided by multiplying the cost indicator with the gross floor area. When preparing these estimates, the question arises as to which specific cost indicator has to be selected? The relevant cost drivers provide guidance for this selection. Drivers show which parameters are the determinants for the selection of the project-specific cost indicators. However, currently these drivers are not known for building construction projects in the German-speaking region. The relevant cost drivers for residential properties in Germany are identified by using regression analysis. These drivers are the median floor height, the share of the ancillary area for services, the construction duration, and the compactness of the building. Of the four cost drivers, the median floor height proved to have the greatest explanatory significance. The method proves to be suitable for answering the research question. However, some theoretically relevant drivers were not available for the properties being examined. Therefore, these drivers have to be followed up and examined during future studies. Detailed information should be included especially about materials, the planning and construction process, and specific data about various dimensions of the building.

Engineering education is challenged to usher in new approaches to preparing its students for their professional careers. Many blue-ribbon committees call for systematic modifications in research universities to clear the path for cross-disciplinary learning communities. In this context, the paper investigates the effect of student ratings as a measure of teaching effectiveness. One survey found that engineering sophomores perceive active student-centered teaching methods as greatly ineffective, while a second survey highlighted that lecture-based teaching underpins student rating forms used at U.S. research universities. With the goal of aligning teaching objectives, learning outcomes, and the criteria for evaluating teaching, a student rating form is presented. The scales of the multidimensional construct are based on the most up-to-date understanding of effective pedagogy, the new American Accreditation Board for Engineering and Technology criteria, and a view of the future of our profession. The importance of this paper lies in its science-based proposal underlying a call for the establishment of a coalition to validate a constructive approach to further teaching performance in the field of construction engineering and management.

Interorganizational teamwork has attracted considerable attention over the years and is one of the characteristics of the construction industry. However, most of the research has just focused on the factors necessary for team success, rather than investigating human perceptions of interorganizational teamwork and what factors affect the individual’s perception that they are working in a team. Building on a modified model, the effects of cultural and context factors (individualism and power distance) and employee attitudes (task interdependence and trust) on team orientation (the individual’s perception of working in a team) were investigated in this research. Data were collected via questionnaire surveys from a sample of construction practitioners working in interorganizational project teams in Hong Kong. Using correlation and multiple regression analyses, the findings indicated that, as hypothesized, there were positive relationships between team orientation and contractual trust, competence trust and task interdependence, but there was a negative relationship between team orientation and opportunism. The results further suggested that the influence of team orientation was moderated to a certain extent by individualism and power distance in some employees’ attitudes.

Large multifaceted capital projects, such as those in the mineral resource industry, are often associated with diverse sources of both internal and external risks and uncertainties. Risks can cause delays to the planned schedule of a project, add a significant cost, and greatly influence its profitability. Uncertainties can be associated with project risks, as well as with opportunities that can develop throughout the project’s lifecycle. Having the ability to plan for these uncertainties, by incorporating flexible alternatives into the system design, is increasingly recognized as critical to long-term corporate success. This paper advances the knowledge needed to incorporate flexibility in systems engineering and management for both practitioners and researchers. Flexibility is defined in this paper as the ability of a system to sustain performance, preserve a particular cost structure, adapt to internal or external changes in operating conditions, or take advantage of new opportunities that develop during a mine’s life cycle by modifying operational parameters. By engaging in planning for flexible production systems, the effects of risk on a particular project value can be examined, project volatility can be calculated, and potential flexible mining alternatives can be evaluated. Once identified, a real options valuation provides a strategic decision-making tool for mine planners to determine the value of incorporating flexible alternatives into the mine plan. This paper demonstrates that flexibility can become an equal partner among the parameters controlling the decision-making process for underground engineering construction systems, followed by industry practitioners. It presents a methodology in mine production system design by introducing flexibility into design through the application of real options valuation techniques. Real world case studies related to flexible planning and design of construction and production systems in underground hard rock mines are presented.

Existing linear programming (LP) models of earthwork allocations in roadway construction assume that unit cost coefficients of earthwork activities and borrow pits/disposal sites capacities are certain and deterministic numbers. However in real-world problems there are naturally some uncertainties inherited in these values, which make it difficult to represent a single value as the candidate of entire possible values. This paper presents a fuzzy linear programming (FLP) model of earthwork allocations based on the fact of assuming unit cost coefficients and borrow pits/disposal sites capacities as fuzzy numbers while minimizing total earth-moving cost as an objective function. A method based on $\alpha$ cuts of a fuzzy set is used to take the uncertainty in borrow pits/disposal sites capacities into account. The uncertainty in fuzzy cost coefficients of the objective function and its effects on decision variables of the earthwork allocations model are also considered using the method presented by Chanas and Kuchta in 1994. Subsequently, a more general model is suggested which considers both uncertainties in borrow pits/disposal sites capacities and cost coefficients simultaneously. It is demonstrated that the presented FLP, compared to a deterministic LP, introduces a more robust solution; as the result of giving fuzziness to the uncertain parameters. Such a solution could be beneficial in real world decision making where uncertainties on resources and activities cost exist.

Delay in microtunneling projects is a complex multivariate problem. Delay in microtunneling is defined as the nonworking time of a microtunneling project due to any reason other than scheduled stops. There are many reasons for delay such as mechanical failure of system components, leakage of hydraulic hoses, blockage of slurry pipes, and waiting time for excavated materials hauling equipment. Delay time increases the project duration and consequently the project cost. Delay data were collected from 35 microtunneling projects. Collected delay data were delay duration, delay reason, time, and location from the start to the stopping point. Five categories of delay causes were used in the analysis. Prediction of delay time will enhance the estimation accuracy of microtunneling project duration. A predictive model using a probabilistic approach was selected to represent the delay time. Based on data characteristics, a Weibull distribution was determined to best represent the overall delay duration in microtunneling projects. Using “regression with life data,” expected overall delay in a microtunneling project could be predicted as a function of driven length. The model will help contractors to estimate total project time with reasonable accuracy. Knowing the anticipated delay time will allow contractors to have a point of comparison for actual performance.