Journal of Construction Engineering and Management

Different types of public–private partnerships (PPPs) have been practiced in worldwide infrastructure development with diverse results and a variety of problems have been encountered. A number of factors combine to determine the success or failure of an infrastructure project in terms of its objectives. There is an urgent need for a workable and efficient procurement protocol for improved practices in future PPP projects. As an important step toward the development of such a protocol, this study identifies, analyzes, and categorizes various critical success factors (CSFs) for PPPs in general based on a public–private win–win principle and a systematic research approach that includes case studies, literature review, and interviews/correspondence with international experts. A CSF package is developed that contains five main CSFs, each including a number of success subfactors (SSFs). Relative significances of these CSFs and SSFs are examined based on the results of a questionnaire survey of international expert opinions. Agreement analysis shows that there is a good agreement in the ranking of these CSFs and SSFs between respondents from the industrial sector and those from the academic sector.

Production home building possesses characteristics similar to manufacturing processes, such as the construction of more or less similar houses repeatedly and a growing demand for mass customization of homes. As a result of these similarities, larger homebuilders often attempt to view their production system as an assembly line process. However, the management tools generally utilized by these home builders are those used in other sectors of the construction industry, such as critical path method scheduling, cost estimating, and earned value analysis. These management tools do not provide an explanation or control/prediction tools for many undesirable situations that arise during home building, such as increasing cycle time which slows delivery of product to consumers and increases project capital costs, and increasing amounts of work in process that increases capital investment and thereby decreases company financial performance. In order to bring better management tools to the residential construction industry, this study examines relationships between cycle time, work in process, system throughput, new construction starts, and the capacity of the production system using building permit data for new single family homes in Chandler, Ariz. The applicability of Little’s law, a basic equation used in factory production management models, to a residential production system is examined. This study shows a definite, predictable relationship between cycle time, work in process, and production system throughput. It provides a pathway for further study of production system characteristics that have historically not been included in construction management models, with the expectation of developing new construction management tools that will account for more of the characteristics of construction production systems that affect project performance and company financial performance.

Increasing complexity of many constructed facilities and escalating demands for project performance are driving significant changes in design and construction. Increased project integration and technical support of construction operations provide a promising response to these demands. This paper identifies and describes nine critical activities to increase technical support for construction: integrate early planning; plan for regulatory compliance; consider construction methods and sequences in design; tailor and time technical information to users’ needs; provide materials to support effective construction; identify and provide construction-applied resources; create an environment for safe, productive, and high quality work; technically support efficient construction operations and completion; and transfer experience between projects. The paper’s relevance to industry practitioners includes multiple benefits of completing these activities for firms, projects, and professionals, along with the necessary steps to develop this capability and gain these benefits. Educators and researchers can use the activities to structure course topics related to technical fundamentals of construction and integration with design, along with future investigations of construction process knowledge.

Continual development in construction techniques results in emergence of specialized formwork systems. A new system will have to compete with in-use systems for adoption in a target operation. Thus, it is essential that decision makers anticipate the acceptability of new systems before making decisions to acquire them. Estimating acceptability basically assesses how features of a new system are comparable to that of in-use systems. Therefore, analogy is a focal factor for the acceptability estimating process. Neural networks (NNs) are more suitable to model construction problems requiring analogy-based solutions. A NN-based approach was employed to anticipate the acceptability of new formwork systems. The study collected data from a group of 40 users in Egypt. A set of six performance characteristics that mostly pertain to acceptability estimating were identified. The study used the analytical hierarchy process to produce pairs of a performance characteristics’ vector and the corresponding acceptability value, and utilized the developed pairs to train NNs. Finally, tests on trained NNs using unseen data indicated satisfactory performance.

This paper presents a fuzzy logic model that integrates daily site reporting of activity progress and delays, with a schedule updating and forecasting system for construction project monitoring and control. The model developed assists in the analysis of the effects of delays on a project’s completion date and consists of several components: An as-built database integrated with project scheduling; a list of potential causes for delays; a procedure to categorize delays; a method of estimating delay durations utilizing fuzzy logic; a procedure that updates the schedule; and, a procedure that evaluates the effects and likely consequences of delays on activity progress. This model is of relevance to researchers since it makes a contribution in project scheduling by developing a complete approach for handling the uncertainty inherent in schedule updating and activity delay analysis. It also advances the application of fuzzy logic in construction. It is of relevance to construction industry practitioners since it provides them with a useful technique for incorporating as-built data into the schedule, assessing the impact of delays on the schedule, and updating the schedule to reflect the consequences of delays and corrective actions taken. The use of fuzzy logic in the model allows linguistic and subjective assessments to be made, and thereby suits the actual practices commonly used in industry.

Quantifying the waste present in an operation is an important part of a number of performance improvement initiatives in the architecture engineering construction industry. Contemporary management approaches focus on waste minimization to reduce operating costs and to increase operating responsiveness and flexibility. In construction, studies have been conducted over the past $30\text{years}$ as part of productivity-improvement efforts that have documented levels of wasted time in construction activities. This paper draws on the methodology of meta-analysis to provide a synthesis of the findings across all of these studies. The analysis reveals that an average of 49.6% of time in construction is devoted to wasteful activity, although this amount is widely varied. Among other things, these results demonstrate considerable potential for improvement in construction through initiatives that reduce levels of wasteful activity.

Contractor selection is the process of selecting the most appropriate contractor to deliver the project as specified so that the achievement of the best value for money is ensured. Construction clients are becoming more aware of the fact that selection of a contractor based on tender price alone is quite risky and may lead to the failure of the project in terms of time delay and poor quality standards. Evaluation of contractors based on multiple criteria is, therefore, becoming more popular. Contractor selection in a multicriteria environment is, in essence, largely dependent on the uncertainty inherent in the nature of construction projects and subjective judgment of decision makers (DMs). This paper presents a systematic procedure based on fuzzy set theory to evaluate the capability of a contractor to deliver the project as per the owner’s requirements. The notion of Shapley value is used to determine the global value or relative importance of each criterion in accomplishing the overall objective of the decision-making process. The research reported upon forms part of a larger study that aims to develop a fuzzy decision model for construction contractor selection involving investigating multiple criteria selection tendencies of construction clients, relationship among decision criteria, and construction clients’ preferences of criteria in the contractor selection process. An illustration with a bid evaluation exercise is presented to demonstrate the data requirements and the application of the method in selecting the most appropriate contractor for the project under uncertainty. The proposed model is not intended to supplant the work of decision-making teams in the contractor selection process, but rather to help them make quality evaluations of the available candidate contractors. One major advantage of the proposed method is that it makes the selection process more systematic and realistic as the use of fuzzy set theory allows the DMs to express their assessment of contractors’ performance on decision criteria in linguistic terms rather than as crisp values.

Infrastructure privatization has multidimensional impacts with long-term uncertainties and wide risk portfolios. A wide range of barriers to public–private partnerships (PPPs) in infrastructure development have been identified through a questionnaire survey, which are broadly classified into six aspects: (1) social, political, and legal risk; (2) unfavorable economic and commercial conditions; (3) inefficient public procurement framework; (4) lack of mature financial engineering techniques; (5) problems related to the public sector; and (6) problems related to the private sector. To explore measures for removing these barriers, a systematic research approach (literature review, case studies and interviews/correspondences with experts and experienced practitioners) has been taken to draw experience, learn lessons, and benchmark the best practices in international PPPs. An improved PPP protocol for infrastructure projects in general has been developed, addressing key issues in nine areas: (1) appropriate roles of governmental authorities; (2) best value for money approach; (3) effective management of adviser services; (4) formulation of appropriate PPP schemes; (5) use of relational contracts; (6) improvement of the procurement framework; (7) payment structure; (8) contract monitoring, termination, and step-in rights; and (9) transfer management. Effective measures for successful PPPs are identified in each of the nine areas.

Time–cost optimization (TCO) is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Although the TCO problem has been extensively examined, many research studies only focused on minimizing the total cost for an early completion. This does not necessarily convey any reward to the contractor. However, with the increasing popularity of alternative project delivery systems, clients and contractors are more concerned about the combined benefits and opportunities of early completion as well as cost savings. In this paper, a genetic algorithms $\left(\mathrm{GAs}\right)$ -driven multiobjective model for TCO is proposed. The model integrates the adaptive weight to balance the priority of each objective according to the performance of the previous “generation.” In addition, the model incorporates Pareto ranking as a selection criterion and the niche formation techniques to improve popularity diversity. Based on the proposed framework, a prototype system has been developed in Microsoft Project for testing with a medium-sized project. The results indicate that greater robustness can be attained by the introduction of adaptive weight approach, Pareto ranking, and niche formation to the $\mathrm{GA}$ -based multiobjective TCO model.

Although the construction pollution index has been put forward and proved to be an efficient approach to reducing or mitigating pollution level during the construction planning stage, the problem of how to select the best construction plan based on distinguishing the degree of its potential adverse environmental impacts is still a research task. This paper first reviews environmental issues and their characteristics in construction, which are critical factors in evaluating potential adverse impacts of a construction plan. These environmental characteristics are then used to structure two decision models for environmental-conscious construction planning by using an analytic network process (ANP), including a complicated model and a simplified model. The two ANP models are combined and called the EnvironalPlanning system, which is applied to evaluate potential adverse environmental impacts of alternative construction plans.

Construction mismanagement results in multiple problems that can cascade throughout the work force chain, affecting the schedule and leading to damages to multiple parties. Although the problem may start with a single subcontractor, it can result in all contractors feeling some impact to their work. In this paper, a case study is presented of a project with seven different mismanagement scenarios. A description of each scenario is provided as well as a quantification of the damages that result from the problem. A construction claims section is also included that addresses many of the issues that could result from a claim for each of the seven scenarios. A discussion is presented outlining possible preventative steps to minimize the damages from the problems presented.

Most consultant selection models stress the importance of past performance. However, there are so far very few studies on evaluating consultant’s performance. It hampers the whole process of the selection model. This paper tries to establish a systematic approach in developing a consultant’s performance evaluation model for the evaluation of the performance of cost estimators in the construction industry of Hong Kong. Nominal group technique is adopted in identifying the decision criteria for the evaluation, and a reliability interval method (RIM) is developed to assess the importance weighting of each criterion. The RIM allows statistical analysis and fuzzy assessment of the weight. The results report the weights of each decision criterion and its subcriterion in evaluating cost estimator’s performance. Interestingly, the results show that traditional functions of cost estimator are the least treasured from the clients. Proactive and professional advice is considered to be much more important. The study is highly relevant to industry practitioners in assessing performance of costs estimators, as well as to researchers in further developing the consultant selection model.

The cost of site clearance and verification operations in the Gulf of Mexico is examined based on nearly 300 jobs performed by B&J Martin, Inc. from 1997 to 2001. A description of the activities and regulatory requirements involved in site clearance verification establishes the manner in which service cost is determined. Descriptive statistics are provided and relations are derived that estimate the time and cost of clearance and verification based on various descriptor variables. The expected size and potential value of the site clearance verification market in the Gulf of Mexico is also estimated. A major conclusion of the analysis is that the cost of site clearance verification is a time-variant site-dependent function which cannot be predicted prior to performing the service. The analysis represents the first empirical study to construct clearance and verification cost functions for the Gulf of Mexico region.

An expressway project is often divided into subprojects with different tendering packages, and carried out by several general contractors that apply different scheduling practices. Each schedule may contain hundreds of activities, each of which is associated with multiple pay items that determine its earned monetary value. With such huge amount of information, the reviewer can only check a sample piece of information, and the quality of review highly depends on the reviewer’s experience and devotion. Automated schedule review provides a solution to reduce such problems encountered in the industry. This paper presents a module-based schedule generation and review model, which includes a predefined set of network modules, network builder assistant computer system that helps schedulers manage and reuse the modules to build a new schedule, and another computer system network review assistant (NRA) that helps reviewers review schedules. The NRA uses generalized rule forms to represent the schedule critique knowledge collected from the industry. When potential errors are found, the NRA adopts case-based reasoning to suggest possible correction based on similar cases. The evaluation conducted by the practitioners using real projects indicates that NRA reduces review time, and provides more accurate review on finding activities and related pay items not conforming to standards, and reminding users of important but often omitted activities.

Mechanisms that inject cutting materials into a water jet and abrasively wear away steel/concrete are called abrasive cutters. The purpose of this paper is to model the cost of abrasive cutting operations associated with decommissioning offshore structures in the Gulf of Mexico. The elements of a standard abrasive cutting contract are presented and the total cost of a job is derived based on the parameters of the contract. The total cost to perform a severance operation is aggregated according to job type and normalized according to the number, size, and length of cut performed. Descriptive statistics are provided based on data collected over a three-year period from 2000–2002, and relations are derived that estimate the time and cost of a cutting operation based on various descriptor variables. A major conclusion of the analysis is that abrasive cutting is a structure-independent operation, or in other words, the total cost of performing the service does not depend on the characteristics of the structure and can only be predicted after the job is finished and the on-site time of the cutting crew is known. This is in sharp contrast to explosive cutting, where structural characteristics are very good indicators of job cost.