Journal of Construction Engineering and Management

The contractors’ pricing for contract risks in tenders determines how much the employers have to pay for the risk transfer. Therefore, understanding the factors influencing the contractors’ pricing for contract risks is crucial for employers to optimize the cost effectiveness of risk allocation in contracts. This study investigates the factors that contractors perceive to be important when they are pricing “time-related” contract risks. A questionnaire survey was designed for collecting data from building contractors currently operating in Hong Kong. Contractors were not only required to rate the importance of individual factors, but also to state the cost implications when compared with normal pricing in the absence of the concerned factor. The findings reveal that a single factor may have two-sided implications (both inflating and deflating the prices) for which they can be in unequal scales. These scales vary according to the contractor size and the reasons of the differences are investigated. The findings also assist employers in formulating a cost effective contract strategy by equipping them with the necessary knowledge.

In recent years, the state departments of transportation have implemented a number of highway rehabilitation projects across the country. These projects differ fundamentally from new highway projects in that they require an uninterrupted flow of traffic throughout both the duration and geometric length of the project. Synchronization of traffic closure with the construction activities is crucial in such projects to avoid the traffic conflicts and prevent idle time for equipment and labor. Although most highway rehabilitation projects involve predominantly linear activities, the techniques of linear scheduling are not readily applicable to highway rehabilitation projects due to the conflict between the workzone and traffic flow. This paper documents the development of a traffic closure integrated linear schedule (TCILS) that addresses both traffic closure and work progress issues. The TCILS generates a single schedule for both the construction activities and the associated traffic closures. Visual and graphical features are also applied in the system, which makes it particularly applicable for highway rehabilitation projects. An actual concrete pavement rehabilitation project using the TCILS is presented as a sample of application. The findings from the sample project, although they are limited, show that the TCILS can be applied to an actual project. With recommended future development, the system is believed to be beneficial for both construction practitioners and academics.

Alternative dispute resolution (ADR) techniques are adopted by architecture, engineering, and construction project participants to help achieve reasonable settlement of claims and change orders (CCOs) that arise during a project’s life cycle without having to resort to protracted litigation for final determination of merit. Since such ADR techniques require resources to prepare, review, and resolve CCOs, the managerial decisions regarding the investments for these resources need to be economically justified. The application of the net present value approach to determine the value of any ADR investment is limited because the future cash flows resulting from such an investment cannot be estimated a priori as they will vary with the nature of the CCOs, the amounts claimed, and the effectiveness of the ADR in addressing these CCOs. This paper presents a conceptual and mathematical model to evaluate ADR investments by drawing an analogy from theories of financial and real option pricing. The objective is to provide the owner with a decision framework that accounts for the uncertainty in estimating the ADR investment cash flows during the project planning phase, and provides realistic results regarding the value of this investment. The model presented in this paper is applied to a real case study involving a seismic retrofit of a bridge project to demonstrate the parameter estimation and the practical application of the model.

The S-curve is a graphical representation of a construction project’s cumulative progress from start to finish. While S-curves for project control during construction should be estimated analytically based on a schedule of activity times, empirical estimation methods using various mathematical S-curve formulas have been developed for initial planning at predesign stages, with the mean for past similar projects often used as the basis of prediction. In an attempt to make an improvement, a succinct cubic polynomial function for generalizing S-curves is proposed and a comparison with existing formulas shows its advantages of accuracy and simplicity. Based on an analysis of the attributes and actual progress of 101 projects, four factors, i.e., contract amount, duration, type of work, and location, are then used as the inputs of a model developed for estimating S-curves as represented by the polynomial parameters. For model development, it is proposed to use neural networks for their ability to perform complex nonlinear mapping. The neural network model is compared with statistical models with respect to modeling and testing accuracy. The results show that the presented methodology can achieve error reduction consistently, thereby being potentially useful for owners and contractors in early financial planning and checking schedule-based estimates.

Reliable forecasting is instrumental in successful project management. In order to ensure the successful completion of a project, the project manager constantly monitors actual performance and updates the current predictions of project duration and cost at completion. This study introduces a new probabilistic forecasting method for schedule performance control and risk management of on-going projects. The Bayesian betaS-curve method (BBM) is based on Bayesian inference and the beta distribution. The BBM provides confidence bounds on predictions, which can be used to determine the range of potential outcomes and the probability of success. Furthermore, it can be applied from the outset of a project by integrating prior performance information (i.e., the original estimate of project duration) with observations of new actual performance. A comparative study reveals that the BBM provides, early in the project, much more accurate forecasts than the earned value method or the earned schedule method and as accurate forecasts as the critical path method without analyzing activity-level technical data.

Rework continues to affect both cost and schedule performance throughout the construction industry. The direct costs alone often tally to 5% of the total construction costs. Using the data obtained from 359 construction projects in the Construction Industry Institute database, this paper assesses the impacts of rework on construction cost performance for projects in various categories. In addition, it identifies the sources of this rework, permitting further analyses and the development of rework reduction initiatives. The results of this study establish that the impacts of rework differ according to project characteristics and that the sources of rework having the greatest impact are not significantly different among project categories. By recognizing the impacts of rework and its sources, the construction industry can reduce rework and ultimately improve project cost performance.

In the quest to shorten project delivery time, construction professionals have the option of overlapping design and construction activities. Although time savings can be achieved by overlapping, conducting design and construction operations in a nonnatural sequence can carry significant risks. To mitigate these risks and make more appropriate overlapping decisions, concurrent engineering concepts can be used to classify upstream design activities in terms of design evolution and downstream construction activities in terms of sensitivity to upstream design changes. The focus of this work is to determine the factors that contribute to the sensitivity of construction activities. A series of semistructured interviews with experienced construction professionals show that the level of transformation, lead time, modularity, and the interaction of built components are some of the factors that determine the amount of sensitivity in construction activities to upstream design changes. These determinants provide for a quick assessment of an activity’s sensitivity, which can help practitioners limit risk when planning the overlapping of design and construction activities.

Recently, a significant number of major construction companies embarked on the implementation of integrated information technology solutions such as enterprise resource planning (ERP) systems to better integrate various business functions. However, these integrated systems in the construction sector present a set of unique challenges, different from those in the manufacturing or other service sectors. There have been many cases of failure in implementing ERP systems in the past, so it is critical to identify and understand the factors that largely determine the success or failure of ERP implementation in the construction industry. This paper presents the process of developing an ERP systems success model to guide a successful ERP implementation project and to identify success factors for ERP systems implementation. The paper identifies factors associated with the success and failure of ERP systems, and develops a success model to analyze the relationships between key factors and the success of such systems. The proposed ERP systems success model adapts the technology acceptance model and DeLone and McLean’s information systems success model and integrates those with key project management principles. The goal of the ERP systems success model is to better evaluate, plan, and implement ERP projects and help senior managers make better decisions when considering ERP systems in their organization.

In efforts to quantify craft workers’ perspective of construction productivity, a nationwide survey involving 1,996 craft workers was employed. The survey quantified the relative impact of 83 productivity factors, which had been identified through a series of focus group sessions involving craft workers conducted on construction jobsites located throughout the United States. The findings show that craft workers do have a good understanding of the factors affecting their daily productivity, and most of the adversarial factors affecting productivity can be addressed by site management teams. Factors involving tools and consumables, materials, engineering drawing management and construction equipment were identified as having the greatest impact on productivity from the craft workers’ perspective. A statistical comparative analysis was employed to distinguish the significant factors encountered by craft workers on projects with relatively low perceived productivity. The research further examined the differences in the perceived relative magnitude of productivity factors’ influence on construction productivity based on respondents’ union status and trade. These findings will be beneficial for engaging craft workers in productivity improvement and improving the efficiency of construction jobsites.

Construction fatalities continue to occur during steel erection. Using 166 case files resulting from Occupational Safety and Heath Administration (OSHA) investigations of steel erection fatalities during the years 2000–2005, the writers examined the data to determine the proximal causes and contributing physical factors. Of the 166 fatal events, results showed proximal cause “falls” represented 125 of the fatal events, “crushed/struck/hit by object” represented 40, and one was caused by electrocution. The rate of fatalities tended to reduce from 2000 to 2005. As a result, OSHA may be reaching one of its goals established following the introduction of the new steel standards in 2002, an annual reduction of 30 fatalities. The results of this study indicate that employer compliance with OSHA’s fall protection standards and instructing employees in recognition and avoidance of unsafe conditions could save lives.