Journal of Construction Engineering and Management

This paper presents a unique treatment of competitive bidding theory as applied to pricing engineering services. Unlike low-bid procurement, the selection of engineers and design consultants is often based on several factors such as quality, availability, reputation, resume, and references, and these criteria may or may not include price. From preliminary interviews, the authors conclude that there is a need for a systematic method of evaluating potential job opportunities and determining fair market prices. This hybrid model, Value-Bidding, refocuses the competitive bidding model from a fee-based selection criteria to a value-based selection criteria. Value-Bidding utilizes an established marketing research methodology, conjoint analysis, to establish the probability of winning based on multiple factors. The resulting analytical model enables engineers to analyze market conditions, evaluate client priorities, systematically track competitors, and optimize proposals, while maximizing the probability of winning, maximizing profit, and optimizing price.

A critical issue in public–private partnerships (PPPs) in international infrastructure development is the selection of the right private-sector partner. This necessitates a best value source selection methodology in which the establishment of a set of appropriate selection criteria is a prerequisite. Various important selection criteria have been identified through a literature review of previous studies on critical success factors; experience drawing and lessons learning from international PPP practices; examination of selection criteria used in worldwide PPP projects; and interviews/correspondence with international PPP experts and practitioners. These identified criteria are classified into four evaluation packages for PPP projects in general: (1) financial, (2) technical, (3) safety, health, and environmental, and (4) managerial. The relative importance of these evaluation packages and the relative significance of the criteria within each package have been statistically analyzed based on a structured questionnaire survey of worldwide PPP expert opinions. These statistical analyses include validity and reliability analysis, Mann Whitney U tests, direct comparisons of mean criterion significance indexes and criterion rankings between respondents across public, private, and academic sectors, and a general rank agreement analysis across sectors for each evaluation package. These research outputs would facilitate the formulation of a multicriteria best value source selection methodology for PPP projects in general and the development of both objective and subjective evaluation criteria to select the right private-sector partner for a particular PPP project.

Stringent pressure on public finances has made China’s infrastructure development a “bottleneck” in its bid to sustain rapid economic growth. As a result, many modalities have been developed to utilize the resources and skills of the private sector to supply essential infrastructure products and services, as well as to improve the efficiency in government procurement of the same. The build–operate–transfer (BOT) approach is an important example of these innovative modalities. The BOT approach in China is still in its infancy; many pitfalls await the unwary and obstacles impede more extensive application of this modality. The pitfalls are attributable to the complexities in the BOT approach, particularly when attempted in China’s transition economy emerging from decades of central planning to become one that is more market driven and globally integrated. This paper proposes two systems concepts to help manage this complexity: (1) a process modeling approach that maps key functions, parameters and interfaces in the project delivery process, and (2) the use of interface management involving specific measures that have contributed towards project success in Chinese BOT projects. The process modeling approach has led to the development of China’s BOT generic process model (CBGPM). Expert opinion was elicited on the criticality of the interfaces identified in CBGPM as well as the effectiveness of selected interface management measures. Finally, an interface management framework consisting of five key steps is suggested for China’s BOT projects.

Numerous public infrastructure projects have been privatized worldwide, where responsibilities, risks, and rewards are substantially reallocated between pubic and private sectors. The financial evaluation of a privatized infrastructure project is complex and challenging because of the risks and uncertainties due to the large size, long contract duration, nonrecourse financing, multiple project participants with different motives and interest, and the complexity of the contractual arrangements. Improved financial engineering techniques are required to overcome the limitations of traditional financial analysis techniques in addressing risks and uncertainties. This paper develops a methodology for capital structure optimization and financial viability analysis that reflects the characteristics of project financing, incorporates simulation and financial engineering techniques, and aims for win–win results for both public and private sectors. This quantitative methodology defines the capital structure of a privatized project in four dimensions, examines different project participants’ perspectives of the capital structure, optimizes the capital structure, and evaluates the project’s financial viability when it is under construction risk, bankruptcy risk and various economic risks (that are dealt with as stochastic variables), and is subject to other constraints imposed by different project participants. This methodology also evaluates the impact of governmental guarantees and supports, and addresses the issue of the equity holders’ commitment to project success by initiating the concepts of equity at project risks, value of governmental loan guarantee, and project bankrupt probability during construction. A framework and a solution algorithm are provided for this proposed methodology. These research outputs will significantly facilitate both public and private sector in evaluating a privatized project’s financial viability and collectively determining an optimal capital structure that safeguards their respective interests.

Cash flow forecasting methods have evolved to allow detailed predictions for individual projects. These methods, principally the cost-schedule integration (CSI) technique, make extensive use of project estimate and schedule data. An implicit assumption of these methods has been that accuracy is largely a function of the quality of data available to the model. To the writers’ knowledge, there has been no assessment of the ability of project specific cash-flow models to accurately predict cash flows given accurate input data. This paper makes two contributions. First, two complementary methods are presented—pattern matching logic and factorial analysis—that provide an ability to assess the accuracy of cash flow models. Second, through demonstration of these methods using data from two projects, a critique is made of the ability of existing CSI models to accurately predict cash flows. The paper concludes by recommending extensions of CSI models to include more detailed payment conditions, including differential payment lags, components for materials and labor, and payment frequency. A further conclusion is the call for more research to better understand the balance between managers’ need for information and the ability of predictive models to provide that information.

Continuous flight auger (CFA) piles do not receive sufficient research attention although they are widely used in the United States, United Kingdom, and other countries in the world. Therefore, this paper focuses on describing the CFA pile installation features, exploring its construction methods, and determining the factors that affect the CFA pile productivity and cost. A productivity index (PI) is developed to quantify the effect of subjective factors on the CFA process productivity. Current research concludes a PI value of 0.78 out of 1.0 (efficiency). Several models are designated to assess the CFA pile’s cycle time, productivity, and cost using deterministic approach. Various charts are developed to show this assessment based upon these models. Results show that the cycle time for $12.19\mathrm{m}$ depth and $\left(0.36\mathrm{m}\right)$ $\left(14\mathrm{in}\right)$ diameter piles is $16\min$ ; however, its productivity is 24 piles (holes)/day. The developed tools play an essential role in the CFA decision making process. This paper is relevant to both researchers and practitioners. It provides charts for practitioners’ usage to schedule and price out the CFA pile construction projects. In addition, it provides the researchers with a methodology of applying the deterministic approach to the CFA pile construction process and its limitations.

This study focuses on the phenomenon of ground instability causing mobile cranes to overturn. Four outriggers usually support a mobile crane in order to restrict pitching during hoisting operations. Nevertheless, the crane may become quite unstable if the outriggers should happen to sink into the bearing ground. In this paper, various types of analysis, including experiments, were performed in order to investigate the influence of ground penetration by outriggers on the stability of mobile cranes. Through study of the results of experimentation and simulation, it has been clarified that mobile cranes become highly unstable as a result of rapid penetration. It was found that an index of relative instability had a linear relationship to the common logarithm of an index for brittle failure as derived from the load–settlement curve for ground penetration. Finally, a method of evaluating the risk of mobile-crane overturning is proposed by using the maximum value of both the supporting surface’s failure risk and the kinetic risk due to ground penetration.

Bored piles are vital elements for highway bridge foundation. A large number of factors oversees productivity and cost estimation processes for piles, which creates many problems for the time and cost estimators of such process. Therefore, current study is designed to diagnose these problems and assess productivity, cycle time, and cost for pile construction using the artificial neural network (ANN). Data were collected for this study through designated questionnaires, site interviews, and telephone calls to experts in different construction companies. Many variables have been considered to manage the piling construction process. Three-layer, feed forward, and fully connected ANNs were trained with an architecture of seven input neurons, five output neurons, and different hidden layer neurons. The ANN models were validated and proved their robustness in output assessments. Three sets of charts have been developed to assess productivity, cycle time, and cost. This research is relevant to both industry practitioners and researchers. It provides sets of charts for practitioners’ usage to schedule and price out pile construction projects. In addition, it provides researchers with a methodology of applying ANN to pile construction process, its limitation, and future suggestions.

Construction incidents are essentially random events because they have a probabilistic component that causes their occurrence to be indeterministic. Thus, as with most random events, one of the best ways to understand and analyze construction incidents is to apply statistical methods and tools. Consequently, this paper presents a statistical framework based on the modified loss causation model (MLCM). Even though the MLCM has been used for the framework, the approach can be readily adapted for other incident causation models. The MLCM is separated into two basic components: random and systematic. The random component is represented by a probability density function (PDF), which has parameters influenced by the systematic component of the MLCM, while the systematic component is represented by the situational variables and quality of the safety management system. In particular, this paper proposes that the PDF can be represented by the Poisson distribution. Besides being a convenient and simple distribution that can be easily used in applications, the Poisson distribution had been used in various industries to model random failures or incidents. The differences in contexts and the undesirable effects of adopting an unrepresentative distribution will require formal analysis to determine the suitability of the Poisson distribution in modeling the random component of construction incident occurrence. Incident records for 14 major projects were used in the analysis. Hypothesis testing using the chi-square goodness-of-fit and dispersion tests shows that the incident occurrences can be modeled as a Poisson process characterized by some mean arrival rate. The paper also presents some applications of the proposed Poisson model to improve construction safety management, focusing on two specific concepts: the Bayesian approach and the partitioned Poisson.

Prefabrication, preassembly, modularization, and off-site fabrication, collectively termed as prework have become more viable with recent advances in design and information technologies. These construction methods offer a substantial opportunity to improve project performance when circumstances merit. Successful implementation of these methods on a particular project requires systematic analysis and early decision making based on specific factors of the project. This paper identifies those factors influencing decisions on the use of prework, and current industry practices for evaluating the applicability of prework on industrial projects. It then presents a decision framework to assist industry practitioners with evaluating the applicability of prework on their project, and describes a computerized tool to aid project teams in the decision-making process. The developed framework and tool are useful and effective in the decision-making process, and easy to use, as validated by practitioners in the industry.

This paper presents an analysis of the impacts of extended duration overtime on construction labor productivity. The results show a decrease in productivity as the number of hours worked per week increase and/or as project duration increases. The research focuses on labor intensive trades such as the electrical and mechanical trades. Overtime in this research is defined as the hours worked beyond the typical 40 h scheduled per week. The paper begins by presenting the effects of overtime and the need for an updated overtime productivity model. Data for the quantitative analysis was collected from 88 projects located across the United States by means of a questionnaire. Various statistical analysis techniques were performed to develop quantitative relationship curves, including multiple regression, $P$ -value tests, and analysis of variance.

The proper functioning of the subsurface infrastructure is vital for the public, industry, and government. As is demonstrated almost daily, small disruptions or malfunctions of public utilities, such as power, gas, or phone, can result in catastrophic events on local, regional, or national levels. This paper addresses a known weak point in protecting buried utilities from damage, the lack of accurate as- builts. It is suggested to take advantage of enabling technologies to automatically create as-built drawings relying on electronic sensory data collected real-time from operating machinery. A significant portion of the paper discusses the development of a spatially integrated trencher, a prototype that was subsequently used to execute field experiments. The encouraging outcome of those tests, which are supported with actual data, demonstrated the soundness of the concept and the level of accuracy that can be expected. The relevance to the industry lies in that it addresses a real and complex problem, proposing and demonstrating a workable technology to close a large gap in the way we track our subsurface infrastructure. It is hoped that researchers will be encouraged to extend the concept to other relevant applications while applying a similar rigorous method of experimental field testing.