Journal of Construction Engineering and Management

Risk allocation in privately financed public infrastructure projects, which are mainly referred to as public-private partnership (PPP) projects, is a challenging job due to the nature of incomplete contracting. An investigation into the mechanism that guides the formation of efficient risk allocation strategies is thus desirable. Drawing on the transaction cost economics and resource-based view of organizational capability, this paper has identified five main features of the transactions associated with risk allocation in PPP projects. They include partners’ risk management routine, partners’ risk management mechanism, partners’ cooperation history, risk management environmental uncertainty, and partners’ risk management commitment. For achieving cost efficiency, different risk allocation strategies may suit different conditions of the features. Accordingly, a theoretical framework and five hypotheses were proposed for testing. Data collected in an industrywide survey were analyzed using multiple linear regression technique. It was found that generally, the identified features are determinants in the decision-making process of efficient risk allocation. Therefore, the proposed theoretical framework provides both government and private agencies with not only a logical and holistic understanding of but also a support tool for decision making on risk allocation strategy in PPP projects. Study limitations and future research directions are also set out.

Project risk management emphasizes the need to rank and prioritize risks in a project to focus the risk management efforts. This risk prioritization is of special significance in public-private partnership (PPP) projects, since project success depends upon the efficient allocation of risks to the party who can best manage it. Previous studies on risk identification and assessment of PPP project risks have only produced an unstructured list of such risks and prioritizing them on the basis of probability and impact. This paper suggests the use of interpretative structural modeling (ISM) to prepare a hierarchical structure as well as the interrelationships of these risks that would enable decision makers to take appropriate steps. MICMAC (matrice d'impacts croises-multiplication appliqué a un classemen) analysis is also done to determine the dependency and driving power of the risks. ISM, along with MICMAC analysis, provides a useful hierarchy of risks whose individual relationships are unambiguous but whose group relationships are too complex to organize intuitively and can help practitioners better understand risk dependencies and prioritize risk-mitigation efforts. This study identified 17 risks encountered during the development phase of PPP projects in Indian road sector and found that fourteen risks were weak drivers and weak dependents. Delay in financial closure, cost overrun risk, and time overrun risk have been found to have the highest dependence on other risks. The analysis can be extended by practitioners for risk analysis in other infrastructures such as railways, seaports, airports etc.

An issue has arisen with regard to which of the schedule generation schemes will perform better for an arbitrary instance of the resource-constrained project scheduling problem (RCPSP), which is one of the most challenging areas in construction engineering and management. No general answer has been given to this issue due to the different mechanisms between the serial scheme and the parallel scheme. In an effort to address this issue, this paper compares the two schemes using a permutation-based Elitist genetic algorithm for the RCPSP. Computational experiments are presented with multiple standard problems. From the results of a paired difference experiment, the algorithm using the serial scheme provides better solutions than the one using the parallel scheme. The results also show that the algorithm with the parallel scheme takes longer to solve each problem than the one using the serial scheme.

Risk assessment, consisting of hazard identification and risk analysis, is an important process that can prevent costly incidents. However, due to operational pressures and lack of construction experience, risk assessments are frequently poorly conducted. In order to improve the quality of risk assessments in the construction industry, it is important to explore the use of artificial intelligence methods to ensure that the process is efficient and at the same time thorough. This paper describes the adaptation process of a case-based reasoning (CBR) approach for construction safety hazard identification. The CBR approach aims to utilize past knowledge in the form of past hazard identification and incident cases to improve the efficiency and quality of new hazard identification. The overall approach and retrieval mechanism are described in earlier papers. This paper is focused on the adaptation process for hazard identification. Using the proposed CBR approach, for a new work scenario (the input case), a most relevant hazard identification tree and a set of incident cases will be retrieved to facilitate hazard identification. However, not all information contained in these cases are relevant. Thus, less relevant information has to be pruned off and all the retrieved information has to be integrated into a hazard identification tree. The proposed adaptation is conducted in three steps: (1) pruning of the retrieved hazard identification tree; (2) pruning of the incident cases; and (3) insertion of incident cases into the hazard identification tree. The adaptation process is based on the calculation of similarity scores of indexes. A case study based on actual hazard identifications and incident cases is used to validate the feasibility of the proposed adaptation techniques.

Analyzing and designing a crane supporting system can be time-consuming process. In particular, the dynamic nature of mobile crane operations entails a variety of reaction values for truck and crawler cranes. The platform of a mobile crane can either be set on outriggers—denoted as a truck crane, or on a crawler tracks—denoted as a crawler crane. Designing of a mobile crane supporting system depends on the lifting configuration, type of crane and the type of materials to be used under the crane outriggers or crawler tracks. This paper presents an automated system which is designed to assist practitioners in calculating the mobile crane’s support reactions and in designing the supporting system. This system is developed such that it can generate a 2D reaction influence chart which shows the reactions for each outrigger at varying horizontal swing angles and vertical boom angles to the ground. Most of the geometric configurations needed to perform the support design are not ordinarily given in crane manufacturer’s manual and to address this deficiency, this newly developed system has been integrated with a previously developed crane database which contains information on widely used mobile cranes for construction along with a crane selection system. A case example is described in order to demonstrate the use and effectiveness of the presented system in automating crane lift analysis.

The intense complexity of interfaces in a construction project makes information technology (IT) applications a must for effective interface management (IM). This largely requires a unified, accurate, and efficient way of modeling interface information. Conventionally, interfaces are simply modeled as dependencies/relationships between project entities; various interface information is loosely presented in different ways, which reduces the accuracy and completeness of interface information as well as the efficiency in information exchange and application. This paper introduces an object view of interfaces and its inherent interface object modeling technique, and then presents an interface object model (IOM) framework. The IOM is the first in the literature that aims to systematically define the data structure and dependencies of interface information for modeling. It is at the core of a conceptually proposed systematic model-based IM strategy. When fully developed, the IOM can be used to accurately model multiple types of interfaces. This will greatly enhance the quality and interoperability of interface information, promote IT applications for IM, and ultimately improve interface-related project performance.

In recent years, general contractors in the construction industry have gradually begun to implement a system called enterprise resource planning (ERP). During the ERP implementation process, contractors performed required analyses on daily operation functions demanded by the enterprise. The analyses focused on function mapping to ensure that ERP satisfies all the requirements, including the functions of existing information systems, and meets future requirements. The process of function mapping in the construction industry typically involves a series of lengthy and time-consuming meetings, and face-to-face discussions; systematic analysis procedure was lacking. This research will propose a novel function mapping approach, the Architecture of Integrated Information Systems (ARIS)-house-based (AHB) method, to enhance the effectiveness of meetings and improve the efficiency of discussions. In addition, AHB method will use the structure of ARIS-house diagram to guide the function mapping process, streamline existing information systems, meet future requirements, and successfully implement ERP. Finally, this research will use a case study to verify the effectiveness of the AHB method for contractor to implement ERP.

Manually inspecting concrete surface defects (e.g., cracks and air pockets) is not always reliable. Also, it is labor-intensive. In order to overcome these limitations, automated inspection using image processing techniques was proposed. However, the current work can only detect defects in an image without the ability of evaluating them. This paper presents a novel approach for automatically assessing the impact of two common surface defects (i.e., air pockets and discoloration). These two defects are first located using the developed detection methods. Their attributes, such as the number of air pockets and the area of discoloration regions, are then retrieved to calculate defects’ visual impact ratios (VIRs). The appropriate threshold values for these VIRs are selected through a manual rating survey. This way, for a given concrete surface image, its quality in terms of air pockets and discoloration can be automatically measured by judging whether their VIRs are below the threshold values or not. The method presented in this paper was implemented in C++ and a database of concrete surface images was tested to validate its performance.

As construction industry service providers have expanded their service offerings to meet the demands of construction owners, new management techniques have evolved. One of these management techniques, program management, has emerged as a service offering that covers all aspects of the construction life cycle. This paper reviews specific topics related to the hiring of an external program management service provider, including fees, types of firms, factors considered, and organizational models. Each of these topics was addressed in a recent survey of nonresidential construction industry owners. The survey results are first presented for all respondents and are then segregated by sector (public and private sector respondents). It is apparent that the use of program management firms is still lacking in comparison to the use of other firms and service providers and that construction owners typically use an organizational model that allows them to retain control of their construction program, which true external program management does not. Also, the survey results showed differences between the public and private sectors in the factors considered when hiring a program manager. Because program management is the ultimate form of outsourcing, it is both a particularly timely topic and a topic that is very relevant to construction professionals.

Interpersonal trust is an important factor affecting the performance of the design team in a construction project. To improve the team’s performance, factors affecting interpersonal trust need to be identified thereby increasing trust between team members. A questionnaire survey of architects in project design teams is conducted in Beijing, Shanghai, and Qingdao, People’s Republic of China. Based on the personal construct theory, the survey collects personal construct-based factors which may affect interpersonal trust. Then the factors are tested using structural equation modeling method. Two significant factors i.e., “social interaction” and “attitude on work” are identified. The results suggest that team managers should enhance the social interactions between team members and provide guidance to team members about the correct attitude on work such that the level of interpersonal trust can be improved.

The complexity of construction industry requires the identification of work tasks and the coordination of interactions among them. As a result, construction planning is considered to be one of the most critical steps toward success and is the main focus of past research. Consequently, little research has been performed regarding the preconstruction planning, which is the planning completed by the contractor in the period between project award and project execution. This paper focuses on sheet metal preconstruction planning, primarily that of mechanical and heating ventilations and air conditioning contractors. The research was completed in three phases: phase one gathered data on the current state of preconstruction planning, phase two developed a model sheet metal preconstruction planning process to be used by sheet metal contractors, and phase three validated the model preconstruction planning process. Based on project data collected for this research, projects that used a planning process similar to the model process performed more successfully—they achieved an average profit margin of 23% while projects that were poorly planned experienced an average profit margin of −3%.

The present research describes the fundamental working mechanism of photogrammetry and characterizes the errors of the photogrammetry-derived geometric measurements on building products in a systematic, practical, and statistically significant way. A site engineer simply takes snapshots of a building product with a digital camera from different angles. Back in office, the engineer derives as-built measurements through postprocessing those photos by use of photogrammetry software. The twelve objects sampled in our experiments were building products and building facilities found on the campus of Hong Kong Polytechnic University, yielding 79 paired geometric measurements (length, width, and height) by photogrammetry and by measurement tape, respectively. The biases and limitations of analyzing the agreement between two sets of measurements by regression and correlation coefficient techniques were first revealed. Then, the “95% limits of agreement” method was applied on the sample data and the confidence intervals were established for the limits of agreement derived, so as to ensure validity and statistical significance of the results. In short, the main contribution of this research lies in formalizing a statistically significant, quantitatively reliable technique to assess the accuracy of applying photogrammetry in particular applications of construction engineering. Through weighing the accuracy level achievable by photogrammetry against the accuracy level desirable in a particular application, the engineer makes the final decision on the applicability of the photogrammetry-based approach.

This paper presents three mixed-integer linear programming models to assist project managers in making decisions to compress project completion time under realistic activity time-cost relationship assumptions. The models assume nonlinear activity time-cost functions that are rational functions that can be convex or concave. A user of the models needs to estimate an activity time between normal and crash times where the rate of increase in the cost of performing an activity changes significantly. An efficient piecewise linearization method is presented through which nonlinear cost functions can be approximated in a mixed-integer linear programming model. Each of the models focuses on a different objective a project manager may pursue, such as minimizing project completion subject to a crash budget constraint, or minimizing total project cost, or minimizing total cost under late completion penalties or minimizing total cost with early completion bonuses of a project contract. The paper also uses a simple example which has activities that have all the different types of cost functions discussed in the paper to demonstrate how each model can be used for a project manager’s different objectives.

Framing contractors have the highest rate of nonfatal incidents among specialty contractors. This case study analyzes 654 safety incidents that occurred over a period of $5\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$2$}\right.\text{years}$ in a large residential framing company. Accident analysis and interviews with safety and production experts identify the high-risk tasks, the errors that lead to incidents, and the task factors that increase the likelihood of incidents. The analysis resulted in a framework of five task factors that increase the task demands: (1) working platform constraints; (2) ergonomic postures constraints; (3) material/load handling requirements; (4) tool use/accuracy requirements; and (5) difficulties due to external forces. The combined effect of these factors determines the task difficulty and the likelihood of incidents. The paper discusses safety measures to reduce the task demands of the high-risk tasks, as opposed to measures that reduce exposure or mitigate the consequences. Reducing task demands can reduce the likelihood of accidents while at the same time increasing productivity. For practitioners, the study points to the need to understand the high-risk tasks and reduce task demands in their operations. The framework of the five task demand factors provides the “building blocks” of task difficulty for framing tasks and provides directions for further research in understanding and mitigating the combined effect of the task demand factors.