Journal of Construction Engineering and Management

To improve the chance of success of a public-private partnership (PPP) scheme, it is essential to consider the feasibility of the scheme both from the economical and noneconomical perspectives according to the interests of all three key stakeholders, namely the government, the private investor, and end-users. Acknowledging the diverse and sometimes conflicting interests of the stakeholders, decision makers must identify a viable scheme that could satisfy public accountability, commercial interests, and social consideration of the government, investor, and community, respectively. However, because each decision item could have several possible values or states, it is difficult for decision makers to come up with different PPP schemes by adopting the conventional analytical methods. This paper proposes the use of Bayesian network (BN) techniques to imitate human reasoning and conduct multiobjective decision making. By establishing a decision network that connects the decision items, evaluating criteria, and the ultimate objectives (i.e., the satisfaction of the three main stakeholders), evaluation can be conducted through the BN and the noisy-OR gate concepts. A weighted score approach is applied to combine the objectives of the three stakeholders into a single value. This enables decision makers to evaluate and compare different PPP alternatives and identify a suitable strategy that could minimize the conflict, thereby ultimately increasing the chance of success of a PPP scheme.

Renegotiations are frequently perceived as the Achilles’ heel of concessions. After two decades of concessions development, empirical evidence suggests a recurrent need to renegotiate contracts. What drives renegotiation? Why does it occur? What are the results? The literature still lacks data on renegotiation patterns and on its main causes and results, thus not answering these questions. This paper intends to fulfill this gap by identifying some of the key determinants of renegotiations and presenting the main results. Using an econometric analysis on a real database of 87 Portuguese concessions, the research identified some variables that help explaining the high probability of renegotiation, such as the concession duration and investment, or the existence of a regulator when the contract was signed. The research also found empirical evidence of the high costs involved in renegotiations, as well as of poor control and poor management of concessions by the government.

Recent research efforts on project delivery have been heavily focused on using project-level indicators to predict cost and schedule outcomes. However, specialty contractors performing at the system level have an increasingly important role in the design and construction of healthcare and other high-performance facilities. From curtain wall assemblies to HVAC systems, specialty contractors possess the system knowledge and field expertise to support delivery of energy-efficient, cost-effective systems. Therefore, this research adapted the use of existing metrics from broader, project-level applications to a narrower building system, focused to contextualize the importance of system delivery. A comparative case study analysis was conducted to collect quantitative data on schedule and cost outcomes, construction safety, and building energy performance on two large healthcare facilities. By comparing a design-build and design-assist case, this paper demonstrates how increasing design involvement of mechanical contractors provides opportunities to reduce cost growth, schedule growth, and safety incidents, and improve the HVAC system performance in healthcare projects. Contextual lessons from the design-build case are discussed and suggested for application in other forms of project delivery.

Over the past decades, numerous research efforts have been undertaken concerning the allocation of construction risks. Although the research currently available provides many valuable insights into the issue, industry participants remain concerned over risk associated with construction contracting. Based on this problem, a research product was developed to aid contracting parties in identifying, assessing, and allocating each construction risk. After a three-phase survey methodology for data collection, three worksheets were developed to identify construction risks with high potential for conflict and to aid in assessing and allocating these risks to the appropriate parties. To complement the model worksheets, three tools were developed: flowcharts, to help determine which party should carry each particular risk; legal research; and risk allocation principles, to help select appropriate contract language to address the identified risks. This paper discusses (1) the risk assessment and allocation model, including its accompanying tools, followed by a legal research discussion that will help parties to better understand construction contracts; and (2) the legal terms that often cause misallocation of risk with severe consequences.

Line-of-balance (LOB) methodology produces a work schedule in which resource allocation is automatically performed to provide a continuous and uninterrupted use of resources, but the distribution of resources could be further improved by resource leveling even if multiple resources are involved. The objective of this study is to develop a genetic algorithm (GA)-based multiresource leveling model for schedules that are established by LOB. The proposed model postulates that the production rate and duration of an activity are governed by the resource that requires the longest duration in completing a unit. Once the LOB schedule is established, resource leveling is performed according to the principle of optimum crew size that makes use of a utility data curve, which shows that productivity will suffer if the crew size is different than the optimum crew size, and the principle of natural rhythm that allows shifting the start times of an activity forward or backward at different units of production by changing the number of crews employed. The duration of an activity in any one unit and the precedence relationships between activities do not change during the leveling procedure. When applied to the LOB schedule of a pipeline project that was used to illustrate the model, it was observed that the proposed multiresource leveling model provided a smoother resource utilization histogram while maintaining optimum productivity.

Real-life construction projects are large in size and are challenged by many constraints, including strict deadlines and resource limits. In this paper, constraint programming (CP) is used as an advanced mathematical technique that suits schedule optimization problems. A practical CP optimization model has been developed to resolve both deadline and resource constraints simultaneously in large-scale projects. The proposed CP model is much faster than metaheuristic techniques and provides a set of feasible project durations that do not violate resource limits. The paper compares the CP results with several case studies from the literature to prove the practicality and usefulness of the CP approach to both researchers and practitioners. The CP model of this paper could provide solutions within 6.5% deviation from optimum schedules for a large project of 2,000 activities within minutes of processing time. This paper thus contributes to introducing a superior optimization model that is suitable for large-size projects and helps to render schedule optimization a mainstream cost-saving function within commercial scheduling systems.

The construction industry employs approximately 6% of all U.S. workers but accounts for over 16% of all occupational fatalities. Recent statistics indicate that over 40% of all U.S. construction laborers cannot speak English proficiently. To ensure strong safety performance, it is vital to include every individual in a construction crew in safety-related communications, regardless of language proficiency. Considering that most safety communication is delivered in English, it is not surprising that Spanish-speaking construction workers are fatally injured at a disproportionate rate. To conduct the first exploration of the characteristics of strong, multilingual safety networks in the Denver Metropolitan region of the United States, a multilingual research team conducted interviews with the members of 14 construction crews. Demographic attribute data for each individual (e.g., language proficiency, years of experience, position in the company) and network data were collected to analyze the safety communication network for each crew. The units of analysis included the individual actors in the network and the networks as a whole. The exploratory results contribute to the body of knowledge by revealing that unilingual work crews have safety performance that is 51% better than multilingual work crews ($p=0.10$), bilingual workers play a more central role than unilingual workers when more than one language is spoken ($p<0.001$), workers less than 35 years of age have a higher degree of centrality than do workers who are older than 35 years old ($p=0.11$), and managers play an important role in the exchange and diffusion of safety knowledge regardless of language proficiency ($p<0.001$). Most importantly, social-network analysis metrics show that these language-boundary spanners often form the core of a network that connects disparate groups of individuals. By contrast, crews with relatively weak safety performance tend to have clear and disparate subnetworks distinguished by language and high turnover rates. Such characteristics are of concern because individual actors are not able to effectively warn one another of uncontrolled hazardous exposures or work in transition.

This paper presents a hands-on exercise on construction project management to augment traditional teaching methods and help students improve their construction experience and project management skills. The exercise involved 100 students participating in managing and constructing a 3.8-m (12.5-ft) model of Canada’s CN Tower within a 30-min deadline. Before construction, the groups prepared method statements, cost estimates, and schedules for constructing the model. During construction, the groups had to manage limited resources, procurement challenges, and forced interruptions to keep the project on track. To experience new project-tracking methods, students were introduced to a voice-based prototype for collecting progress information and automatically updating the schedule. The results indicate that students gained better understanding of the real construction environment and how to apply their acquired construction management skills to handle the involved complexities and interdependencies. The paper can be of interest mainly to researchers and educators. It presents the design, planning, and implementation of this educational exercise and discusses its practicality and ability to enhance the project management skills of students.

In construction projects, the management team needs to conceptualize the management of safety in order to foster a strong safety culture. The aim of this research is to investigate what constitutes project management personnel’s conceptual skill and how this skill can be developed and applied in the context of construction safety. To achieve this aim, a conceptual skill questionnaire was developed, validated, and used to collect data in which 273 sets of valid responses were received. Factor analysis of the collected data found two components of conceptual skill important to construction safety: visioning, and scoping and integration. Based on this, a theoretical model was derived and analyzed using a structural equation modeling (SEM) method to demonstrate the influence of conceptual skill on construction safety. The results showed that conceptual skill helps project management personnel implement safety management tasks, which in turn promotes an onsite safety climate. Thereafter, interviews were conducted with experienced personnel to confirm the SEM results and to recommend skill development approaches, which include lifelong learning, learning in practice, intrinsic motivation, and specific training programs. Theoretically, this research advances the existing body of knowledge on conceptual skill by providing empirical evidence of its contribution to improve construction safety. Practically, this research suggests that construction organizations recognize the importance of project management personnel’s conceptual skill for managing construction safety and provide relevant training opportunities for them to improve the skill.

The internationalization of construction companies has become of significant interest as the global construction market continues to be integrated into a more competitive and turbulent business environment. However, due to the complicated and multifaceted nature of international business and performance, there is as yet no consensus on how to evaluate the performance of international construction firms (ICFs). The purpose of this paper, therefore, is to develop a practical framework for measuring the performance of ICFs. Based on the balanced scorecard (BSC), a framework with detailed measures is developed, investigated, and tested using a three-step research design. In the first step, 27 measures under six dimensions (financial, market, customer, internal business processes, stakeholders, and learning and growth) are determined by literature review, interviews with academics, and seminar discussions. Subsequently, a questionnaire survey is conducted to investigate weights of these 27 performance measures. The questionnaire survey also supports the importance of measuring intangible aspects of international construction performance from the practitioner’s viewpoint. Additionally, a case study is described to test the framework’s robustness and usefulness. This is achieved by benchmarking the performance of a Chinese ICF with nine other counterparts worldwide. It is found that the framework provides an effective basis for benchmarking ICFs to effectively monitor their performance and support the development of strategies for improved competitiveness in the international arena. This paper is the first attempt to present a balanced and practically tested framework for evaluating the performance of ICFs. It contributes to the practice of performance measurement and related internationalization in the construction industry in general.

Existing studies tend to agree that there are links between owners’ capabilities and project performance. However, limited research has systematically addressed the relationships among the multiple facets of organizational capabilities and project performance. This paper quantitatively investigated the relationships among them by developing and testing a capability model. With support of data collected from the hydropower project industry in China, this study has revealed strong correlations between owners’ capabilities and project performances, confirming owners’ capabilities on obtaining scarce and valued resources, interorganizational linking, information management, and integrating and managing resources can have significant impacts on hydropower project performances. It is concluded that these owners’ capabilities are not only important to improve project performances on quality, time, cost, and safety by maximizing the effectiveness of each participant’s resources, but also critical to appropriately deal with hydropower projects’ externalities for achieving the objectives on project migration, and ecological and environmental impacts. Future studies should be conducted to understand how owners can correctly perceive the properties of external environments for obtaining resources, and to successfully integrate and manage reciprocally interdependent project delivery processes at both intra- and interorganizational levels to achieve superior project performance.

Construction firms have been seen as prime candidates for enterprise risk management (ERM) adoption. The ERM maturity assessment helps them to identify weak areas of their ERM implementation and to prioritize resources to improve these areas. The objectives of this paper are to identify the ERM best practices and important ERM maturity criteria in Chinese construction firms (CCFs) and to develop an ERM maturity model for CCFs. Through an in-depth literature review and a questionnaire survey conducted with 89 professionals, a total of 66 applicable ERM best practices and 16 important maturity criteria were identified and thus used in the proposed model. The results indicated that commitment of the board and senior management; risk identification, analysis, and response; and objective setting were the top three most important criteria. In addition, this model adopts the fuzzy set theory to quantify the implementation levels of the best practices. Moreover, this model was applied in a CCF based in Singapore and the output result was consistent with its current ERM practice. Although this paper focuses on CCFs, it helps other construction firms to prepare their customized model using the best practices and criteria identified in this paper, contributing to the global body of knowledge relating to ERM.

Changes in construction materials prices have a great impact on the cost of construction projects. Such changes in prices occur randomly at different rates over time. There is no clear relationship that can be used to provide accurate calculations of materials prices. One of the biggest problems that faces the construction contracts is unbalanced rights and obligations between owners and contractors (the two parties of construction contracts). It is necessary to have a system that is capable of estimating the size and amount of the change in materials prices at reasonable accuracy. There is also a need to predict the change in building materials prices (either increase or decrease) during the execution phase of the project as well as during the preparation of tenders. Thus, determination of the appropriate lead time to order needed building materials to execute various activities could be done. This research presents a system that utilizes fuzzy logic to identify construction materials that are most sensitive to the change in prices. The research proposes a methodology for identification of construction materials that are most sensitive to the change in prices to be used in modifying the contract price with an attempt to predict the amount of future change in materials prices using neural networks technique. To achieve this objective, the research classifies construction cost items into four different components (building materials, equipment, labor, and administrative expenses), which represent the basic cost elements of any cost item. The system is based on the study of the changes in materials prices that occurred in the Egyptian market from 2000 to 2010. It also provides the impact on the prices of cost items in the priced bill of quantities (BOQ), which is determined by the change in prices of cost items’ materials and their share percent on forming the cost item. Getting to identify materials’ share in the bill of quantities’ items has a great influence on the price of the cost item and the priority in ordering these materials according to their impact on the item’s price. The developed system aids construction contractors in studying bids during the tendering stage and procurement planning during the project’s execution. It can also be used by owners’ representatives to estimate the expected total cost of upcoming projects. The system data are obtained from the Central Agency for Public Mobilization and Statistics in Egypt through published periodicals. A numerical example is presented to demonstrate the use of the proposed system.

This study investigates the long-run equilibrium of the construction sector in an open macroeconomy in which the growth rate and money supply (M3) are exposed to exogenous shocks from foreign capital transfers (FCT). Specifically, the study examines the econometric relationship between M3, FCT, gross domestic product (GDP), and the construction value added (CVA), empirically determining the direction of causality among these variables for North Cyprus. Results reveal that M3 and real GDP are significant determinants of a long-run equilibrium relationship with CVA and FCT, reflecting openness of the capital market in North Cyprus. A positive significant relationship is found between M3 and real GDP in the long run. The results also confirm that CVA is indirectly affected by expansion in M3 and the overall GDP growth during 1977–2008. Most empirical studies and modeling of construction engineering and management are micro level. This study breaks new ground as it attempts to analyze the construction industry within a macro and open economy framework. The findings reported here will benefit especially professionals working on international joint ventures (IJV), interested in securing current strategic positions of IJVs within the competitive environment and formulating strategies to be placed in better performing clusters.

This study investigates how firm attributes affect construction contractors’ efficiency in Hong Kong and Mainland China, from the period 2004 to 2010. This study finds that the efficiency of Hong Kong contractors is associated with their managerial capability to control business costs and financial capability to manage both short-term and long-term capital liquidity. The efficiency of Mainland China contractors is also associated with their managerial capability to control business and administrative costs but not with their financial capability to maintain capital liquidity. Theoretically, this study shows that managerial and technological abilities are two common factors that transcend different institutions and systems. Hong Kong is the freest economy in the world, whereas the economy of Mainland China is more regulated. Methodologically, data envelopment analysis is adopted to establish the efficiency scores of contractors to be analyzed by panel data regression, which controls individual contractor’s return to scale. Few construction competitiveness studies have attempted this methodological process, which can be replicated for future research in other countries, at different stages of their economic development, to ensure equally useful measures for cross-country comparison and to promote the sustainable developments of their construction industries.

Loss is a form of financial distress that refers to total costs of a company exceeding its total revenues. The purpose of this study is to develop models to predict the occurrence of future loss for large construction companies. To ensure the models are useful to both internal and external stakeholders, the study employs a broad range of financial accounting and market variables calculated from publicly available data. The main part of the study develops two models: a full model consisting of 17 predictors, and a reduced model consisting of 11 selected predictors. Both models are developed using a training sample consisting of 959 loss firm-years and 2,313 nonloss firm-years and are validated using a test sample consisting of 368 loss firm-years and 1,035 nonloss firm-years during a sample period spanning the years 1976 to 2010. The models suggest that the level of sales revenue, average sales revenue generated by one unit of total asset, net worth per unit of fixed assets, operating expenses, leverage, presence of special items and foreign transactions, and type of stock exchange are useful factors for predicting loss status. The models also indicate that construction companies engaging in material manufacture and fabrication and those engaging in design and consulting are more likely to experience loss than other types of construction companies. Both models have fairly good out-of-sample prediction accuracy, that is, approximately 74% accuracy in predicting loss and 70% accuracy in predicting nonloss status. Users may find the reduced model more appealing because it involves fewer predictors but offers comparable prediction accuracy. In addition, the research develops a model for predicting future loss in 2 years and a model for predicting a high level of loss the next year. This paper contributes to the scarce literature on construction companies’ financial distress. The models developed in the paper are useful to give stakeholders an early warning about a construction company’s declining financial health, information that will help investors to make better investment decisions and provide notice to executives so they can take necessary steps to prevent more severe financial distress.

The construction cost index (CCI), which has been published monthly in the United States by Engineering News-Record (ENR), is subject to significant variations. These variations are problematic for cost estimation, bid preparation, and investment planning. The accurate prediction of CCI can be invaluable for cost estimation and budgeting of capital projects, and can result in accurate bids. The research objective of this paper is to create appropriate multivariate time series models for forecasting CCI based on a group of explanatory variables that are identified by using Granger causality tests. The results of cointegration tests recommend vector error correction (VEC) models as the proper type of multivariate time series models to forecast CCI. Several VEC models are created and compared with existing univariate time series models for forecasting CCI. It is shown that the CCI predicted by these VEC models is more accurate than that predicted by the previously proposed univariate models (i.e., seasonal autoregressive integrated mean-average and Holt-Winters exponential smoothing). The comparisons are based on two typical error measures: mean absolute prediction error and mean squared error. The primary contribution of this research to the body of knowledge is the creation of multivariate time series models that are more accurate than the current univariate time series models for forecasting CCI. It is expected that this work will contribute to the construction engineering and management community by helping cost engineers and capital planners prepare more accurate bids, cost estimates, and budgets for capital projects.

The effectiveness of a quality program implemented during the initial 18 months of the Qom monorail project in Iran is examined. A quality costing exercise was undertaken, and it was revealed that quality failures accounted for 0.05% of the project’s contract value. The contractor’s experiences in implementing and analyzing its quality costs offer a learning opportunity for companies seeking a competitive advantage by implementing quality improvement programs.

Recently, with the rapid development of information technology, old methods have been superseded by web-based building product information systems that speak the same language as the international building product manufacturers. The purpose of this paper is to emphasize the necessity of an environment that enables building product information sharing across today’s global world and that provides access to any kind of up-to-date and accurate building product information in the building production process. To achieve this purpose, two large-scale field surveys were conducted among the supply side and the demand side in the Turkish construction industry. According to the survey results, the demand side’s existing practices, desires, and expectations differ from the supply side’s existing methods and practices. The major differences are about the usage of web-based building product information systems and their desires and expectations from the characteristics of a web-based system. The field survey findings will help to determine the behaviors and perspectives of the supply side and the demand side on building product information to find out the problem areas in building product information acquisition, and to offer recommendations for a more rational process for building product selection. The survey findings will also be used to develop a web-based building product information system that will enable building product information sharing and introduce all the characteristics of the building products produced in Turkey to the international construction industry. This web-based system will not only enable global building information sharing, but also will provide an introductive tool for international companies planning to enter the Turkish construction industry. Furthermore, the findings of this study can be regarded as an alternative model for the other developing countries that need to develop a similar system to solve similar problems.

This paper addresses one of the costs of new bridges, i.e., the cost of doing the preliminary engineering (PE). This particular aspect of cost has largely been neglected because of the difficulty in obtaining appropriate data. Typically, PE costs are determined as a percentage of construction costs, disregarding other project-specific parameters. Bridge projects let by the North Carolina (NC) DOT between 2001 and 2009 were reviewed. From an analysis of these 461 projects, the writers developed statistical models linking variation in PE costs with distinctive project parameters. The primary contribution this paper makes to the body of knowledge is the finding that PE cost estimates for bridge projects are commonly and significantly underestimated. The writers found that bridge projects exhibited a mean PE cost ratio of 28%. This result is significantly greater than the percentage used in practice. An investigation of data sources related to bridge projects, a description of regression techniques applied to predict the PE cost of such projects, and an assessment of the predictive performance of models are addressed in this paper. New knowledge contributions include identification of key factors affecting the PE costs of bridges, illustration of how those key factors enabled us to predict PE costs of future projects, and discussion of the data collection problems that hindered model development. The writers’ PE cost analyses and predictive modeling effort relate to infrastructure funding issues. All of the parties involved in infrastructure construction, from legislators to contractors, must understand costs and have confidence in the cost estimates developed to ensure efficient and effective funding of infrastructure projects. This paper on bridge PE costs addresses one component of infrastructure funding.

Risk management is a critical part of construction project management. Most previous studies on construction project risk management (PRM) have focused on the project level rather than the enterprise level. The objective of this study is to explore the role that enterprise-level risk management (ERM) plays in PRM. A case study approach was adopted in which two Chinese international construction firms with different risk management practices and performance were investigated. Data were collected from face-to-face interviews and archival documents. The results indicate that ERM can improve the ability and performance of PRM through controlling project risk at the enterprise level, which is based on four key components: risk management department, risk management procedure, external service, and corporate culture. Both senior management and academics will find the study useful because it improves the understanding of how ERM can influence PRM, with a view to stimulating further research.