Journal of Construction Engineering and Management

Recent decades have seen extensive use of public-private partnerships (PPP) in international infrastructure development from governments, private construction firms, and humanitarian organizations. Given the high social importance of civil infrastructure, considerable research attention has sought factors that lead to successful PPP. In a contribution to this body of work, and to the theory of the social sustainability of infrastructure, this paper presents statistical evidence showing that the choice of how to engage private investment in infrastructure is not culturally neutral. This analysis is built on a World Bank database of 1,792 railroad, seaport, airport, and toll road projects with private investment from 27 low- and middle-income nations and Hofstede’s cultural dimensions. Multinomial logistic regression shows that there are statistically significant relationships between Hofstede’s cultural dimensions and the various methods used to enable private investment in infrastructure projects. For all transport project types aggregated together, high power distance index scores predict the use of private funds in projects involving the construction of new infrastructure, while high individualism-collectivism and uncertainty avoidance scores predict the use of private funds in brownfield projects. Toll roads, which change a cultural norm regarding how most roads are accessed and paid for, emerged as a divergent technology type. Railroads are the technology type most strongly influenced by cultural dimensions. Engineers and policymakers may use these results to understand what forms of private investment in transportation infrastructure are more likely to be culturally acceptable in a wide variety of local contexts.

Construction sites are susceptible to damage due to the occurrence of natural and technological hazard events such as fire and thermal flux. Therefore, project planners must adopt innovative approaches for evacuating construction sites seamlessly. This research aims to develop a model to find the least-risk paths for evacuating sites in order to diminish losses, injuries, and fatalities. The model consists of two main processes. The first is the generation of an optimal site layout that aims to minimize the total risk using a genetic algorithm. The second process is running Dijkstra’s algorithm to find the shortest safe path from any position on the construction site to the safe places. Spatial analysis tools are exploited in this research to generate the spatial risk maps and implement the least-cost path analysis. The model is implemented in a case study composed of numerous facilities. The results revealed that the proposed model is able to generate paths through least-risk zones, which will minimize the victims in cases of emergencies.

Work-related stress is an important issue in any industry, particularly in construction, in which stressful environments are frequently encountered. “What are the primary stressors in the construction workplace?” and “What are the relationships between the strain effect of psychological distress and the countermeasures and coping mechanisms used by construction workers?” are, therefore, critical questions. The first question was addressed by using Q-methodology survey with 18 participants. The results showed that time, personal finance and the nature of tasks are important stressors. For the second question, a questionnaire survey administered to 91 participants on two construction sites of a single contractor was used to collect data about the stressors, psychological strain effects, and coping strategies they used. Mediated regression analysis of the data showed that lack of personal and family time, increases in the cost of living, and fears about job security all act as powerful stressors. Coping strategies including acceptance, self-blame, and disengagement are associated with higher levels of psychological distress. Increased substance use, although associated with lower levels of anxiety, may only be a short-term coping mechanism. An anomaly was found with humor as a coping strategy, in which the relationship was found to be counterintuitive and contrary to the findings of previous research. Future research should examine this more closely. Employers should better inform workers about the negative effects of maladaptive coping strategies and offer opportunities for adopting more positive alternatives.

Multicriteria decision making methods, in particular the analytic hierarchy process (AHP), are widely used in many sectors, and increasingly in the field of construction. The AHP is easily adaptable to many decision problems, but it presents great difficulties when the number of criteria or alternatives is large. This issue affects the consistency of the judgment matrix, which is related to the acceptability of the results. To overcome such a drawback of basic importance in the construction field, this paper proposes a novel optimized-AHP (O-AHP) method that redefines the judgment assignments and the generation of the judgment matrix by using a mathematical programming formulation. The validation benchmark tests show that the O-AHP exhibits the same effectiveness of the standard AHP, and it can be applied successfully when the number of alternatives is more than nine. Furthermore, the presented technique is applied to the building performance assessment in the field of antiseismic behavior. The results show that the O-AHP is an approach to simplify the decision-maker operations by defining a numerical value of the building pathology criticality index, which is useful for large-scale applications.

Workers’ unsafe behaviors have a substantial impact on construction safety. To regulate workers’ unsafe behavior, construction practitioners have mainly used formal controls (e.g., penalties). However, the formal approaches may not be effective at eliciting desired behavioral changes in improving safety behavior. Therefore, recently, researchers have paid more attention to how unsafe behaviors are produced. In this regard, cognitive models of safety behavior and empirical evidence on social influence have been suggested. However, there is a noticeable paucity of research investigating the mechanism behind the link between cognitive process, social influence, site risk, and safety behavior. In this paper, an empirically based agent-based model that incorporates theoretical and empirical findings of the sociocognitive process of workers’ safety behaviors is developed. The model is used to conduct experiments examining how the sociocognitive process interacts with safety management interventions (i.e., strictness and frequency of management feedback, and project identification) and influences workers’ safety behaviors across different site risk conditions (i.e., low-, modest-, and high-risk conditions). The results demonstrated that all three interventions contribute to decreasing the incident rate. Also, the interaction effects of the interventions in different site risk conditions were found using the parameter sweeping. The results indicated that (1) promoting workers’ project identification would be an effective strategy in the modest-risk site condition; (2) other interventions should be combined after achieving the medium strictness of management feedback in the high-risk site condition; and (3) other interventions would not be effective without very strict management feedback in the low-risk site condition. This paper contributes to the body of knowledge on construction safety by extending the authors’ understanding of the role of sociocognitive process and its interaction with the environment in shaping workers’ safety behaviors. Additionally, the experiment results are expected to lay a strong foundation for developing effective safety management interventions in the construction projects.

Construction noise control (CNC) is the process of identifying potential noise emissions and establishing noise-abatement plans to mitigate pollution impacts, a process that requires interdisciplinary knowledge and project-specific information. This study introduces an ontological approach to structure all known information on noise control with regard to construction operations, aiming to improve access to knowledge relating to CNC planning. More importantly, information that can be used to analyze the potential influences of noise-abatement measures in terms of costs, schedules, and technical rules is also considered in order to facilitate integrated decision making by outlining various outcomes for each alternative. Literature and expert reviews were conducted to identify the critical concepts and interrelationships between the method statement and the noise-control plan. Consequently, an ontology-based semantic model for CNC planning is presented as a modeling framework, which could be further enriched with more operational knowledge considering the specific purpose of an individual CNC plan. The prototype is applied to excavation construction to illustrate how CNC knowledge can be stored and reused through ontological and semantic web techniques.

The performance of railway tracks can be assessed by separately applying different approaches, such as reliability, availability, maintainability, and safety (RAMS) and lifecycle costing (LCC). Results of these approaches are not comprehensive because RAMS management lacks an LCC perspective and balance, whereas LCC develops an economic analysis but does not address specific issues of railway performance. Based on these considerations, this study defines a key performance indicator (KPI) for railway tracks as merging the LCC and RAMS approaches at a given time. Innovative algorithms are set up for LCC, RAMS, and their relationship in the definition of KPI. Algorithms are applied to two different track alternatives (ballasted and ballastless), and the KPI trend over time is assessed. Case study results show that the KPI of ballasted tracks is higher in the short-term, whereas the slab track performs better in the long-term. The trend of KPI for the two solutions under investigation shows that the breakeven point depends on traffic and speed in the railway lines. The method setup as well the results obtained contribute to the body of knowledge of construction engineering because: (1) the equations set up allow deriving agency-based algorithms through calibration; (2) the model set up and implemented allows agencies to handle basic technical instances (e.g., RAMS) and lifecycle-related issues (in which sustainability is considered) in a synergistic and quantitative way; and (3) the previously mentioned KPI has the potential to quantitatively affect decision making across the entire cycle of life (design, maintenance, and renewal).

In response to problems of cumbersome regulations and understaffed public agencies, governments have worked to simplify procurement statutes and streamline processes. One of the most widely used simplified processes in the United States public sector is a subclass of agreements known as indefinite delivery–indefinite quantity (IDIQ) contracts. Some scholars and practitioners have criticized their use, suggesting public officials have taken advantage of simplified procedures at the expense of protecting the public interest. Specifically, IDIQ contracts have been seen as limiting competition, with adverse consequences for markets and price. However, no studies to date have empirically examined claims of limited competition from simplified procurement tools like IDIQ. This paper seeks to address that gap by evaluating the use of IDIQ contracts in the context of federal construction procurement. Using univariate and multivariate statistics, this study examined bid data from 935 U.S. Department of Defense (DoD) construction projects awarded between 2008 and 2015. The results show that IDIQ contracting does correspond with lower levels of competition as measured by the number of bids, even when controlling for factors like delivery method and market conditions. Using microeconomic theory and traditional assumptions of low-bid contracting, such limits on competition could have negative economic consequences. However, multiple-award IDIQ contracts also appear to be effective at maintaining a minimal level of competition needed to protect the public’s interest while potentially lowering the transaction costs of both proposers and government agencies. For design-build projects in particular, IDIQ contracts may serve as a streamlined alternative to two-step source selection. This study serves as the largest empirical analysis of IDIQ contracting to date and adds to the bodies of knowledge on public procurement and competition in the construction industry. The findings lay the groundwork for researchers to explore the production and transaction cost tradeoffs of IDIQ contracting. The study will also prove useful for public policymakers overseeing procurement regulations and for practitioners that develop or bid on IDIQ contracts.

Construction sites are often described as some of the most hazardous work environments due to the unscripted nature of tasks which puts workers and equipment in close proximity, potentially resulting in near-miss situations or life-threatening contact collisions. Previous research has investigated location-aware methods to improve construction safety but has mostly fallen short in exploring the extent to which prediction techniques can be used to model and formulate the role and attributes of individual workers in addition to the physical characteristics of the jobsite that may lead to safety incidents. This paper studies the feasibility of a preemptive proximity-based safety framework by investigating two trajectory prediction models, namely polynomial regression (PR) and hidden Markov model (HMM). The HMM prediction is further calibrated by factoring in a worker’s risk profile, which is a measure of his or her affinity for or aversion to risky behavior near hazards. The method is tested in a series of field experiments involving trajectories of different shapes and complexity. Results demonstrate that the developed methodology can reliably detect unsafe movements and impending collision events.

Mechanical contractors have been among the very early pioneers of construction prefabrication by moving a significant amount of work to sheet metal fabrication shops off-site to produce common fittings of mechanical building systems and architectural metal finishes. These sheet metal fabrication shops usually follow standard families of fittings and batch-based production process, in which different customized fittings are fabricated together following a single instruction sheet, called a cut sheet. Aggregate and manual tracking systems are used to record the total fabrication labor hours for every cut sheet, which does not provide a direct means to measure the performance of fabrication of the whole batch and individual fittings. As such, the goal of this paper is to assess the feasibility of developing performance measurement models for HVAC sheet metal fabrication operations that are based on batch production with limited tracking data. Six different fabrication time estimation models with different tracking scopes and detail levels were formulated and implemented using multilinear regression and artificial neural networks. The models were trained, validated, and tested using a large sample of sheet metal fabrication data. The contributions of this study include (1) analyzing the trade-off between the formulation complexity and the reliability of their implementations, (2) implementing these formulations using two common machine learning tools (artificial neural networks and multiple linear regression) and comparing between their fit quality and prediction accuracy, and (3) examining the feasibility of reliable performance measurement models of batch production operations with only a single dependent variable (total fabrication time) and an abundance of fabrication and design variables.

Industrialized homebuilding (IHB) has been suggested as the solution to the housing crisis around the world. However, there is no clear understanding of the potential impacts of industrialization on the competition structure and dynamics of the homebuilding industry. As such, this study assesses the regional competition dynamics in industrialized homebuilding environment, especially between local and nonlocal home manufacturers of a large regional housing market. The study adopted a bottom-up market competition analysis methodology that involved data collection, market entry/exit analysis, and manufacturer survival analysis. An extensive detailed data sample of home ownership was acquired for manufactured housing in Texas, which was processed to generate the manufacturer data and their time series. The study found that manufacturers from out of state have less market power, illustrated by their smaller concentration, higher exit rate, lower market share, smaller relative sizes, and shorter survival periods than those of nonlocal manufacturers. The main contribution of this study is assessing the competition imbalance of the industrialized IHB industry using representative competition metrics that were derived from a large, detailed sample of home manufacturers.

Inefficient communication among project stakeholders is one of the most critical issues in the architecture, engineering, and construction (AEC) industry. In reality, it is difficult to create a common understanding about a project among key stakeholders located remotely. The recent progress of virtual reality (VR) makes it a promising approach for interactive visualization of design, construction, and facility management. However, the lack of interactions in VR, such as data interaction, human-building interaction, and human-human interaction, has impeded the adoption of VR in the AEC industry. To fill the gaps, this paper introduces a cloud-based multiuser VR headset system called collaborative virtual reality (CoVR) that facilitates interpersonal project communication in an interactive VR environment. CoVR provides not only a shared immersive experience, but also allows interactions with the underlying simulated world and face-to-face conversations in the virtual world. A real case was used to test the usability of the CoVR system, followed by a building inspection experiment in which 71 subjects were recruited to test the comparative advantages of CoVR. Results indicate that CoVR improves interpersonal interactions in the immersive virtual environment and enhances communications in construction projects. Users of CoVR tended to perform better in a building inspection task than those who were using a single-person VR system. In practice, CoVR is expected to help project stakeholders create a shared vision before construction work commences.

Although adherence to project schedules and budgets is most highly valued by project owners, more than 53% of typical construction projects are behind schedule and more than 66% suffer from cost overruns, partly because of an inability to accurately capture construction progress. To address these challenges, this paper presents new geometry- and appearance-based reasoning methods for detecting construction progress, which has the potential to provide more frequent progress measures using visual data that are already being collected by general contractors. The initial step of geometry-based filtering detects the state of construction of building information modeling (BIM) elements (e.g., in-progress, completed). The next step of appearance-based reasoning captures operation-level activities by recognizing different material types. Two methods have been investigated for the latter step: a texture-based reasoning for image-based 3D point clouds and color-based reasoning for laser-scanned point clouds. This paper presents two case studies for each reasoning approach to validate the proposed methods. The results demonstrate the effectiveness and practical significances of the proposed methods.

The negative impacts of change orders on construction projects are well documented in the literature. Effective management of change orders requires a comprehensive approach to identify and analyze their causes. A change order in construction projects is usually an outcome of combining several interrelated causes, rather than a single cause. Most of the previous studies have considered the causes of change orders as independent causes. However, the causes of change orders have a complicated causal structure, which makes it difficult to independently analyze and prioritize them. Therefore, this study contributes to the body of knowledge in change order management by proposing a fuzzy cognitive map (FCM) approach, which has the capability to analyze the causes of change orders considering their entire causal interactions. The root causes of change orders, as well as the direct ones, can be identified and prioritized by the proposed approach. The manageability of the causes can also be analyzed by the FCM approach. The performance of the proposed approach is evaluated by implementing it in a real construction project. A modeling-validating approach is used to construct and validate the FCM model. It is believed that the proposed FCM approach presents a powerful tool for analyzing the causes of change orders. In addition, this research contributes to knowledge in the area of FCMs by proposing a new inference law.

The design-build (D-B) project delivery method has been used increasingly by state departments of transportation (DOTs) because of its documented benefits. Many studies have shown the superior performance of D-B projects when compared to traditional design-bid-build (D-B-B) projects. However, these studies often rely on experts’ judgments or small sample sizes based on data collected from surveys, interviews, or case studies. There are few, if any, empirical studies that have compared D-B-B and D-B highway project performance by work types. This research analyzed 139 pairs of D-B-B and D-B highway projects built by the Florida DOT. The 139 pairs of projects were classified into five categories of work types: (1) new construction; (2) reconstruction; (3) resurfacing, restoration, rehabilitation (3R) projects; (4) intelligent transportation systems (ITS)–related projects; and (5) miscellaneous construction such as sidewalks, bike lanes, or landscaping. The study employed both parametric and nonparametric statistical tests to compare cost growth, schedule growth, and construction intensity metrics across the five project work types. The results show that D-B projects statistically perform better than D-B-B in terms of cost growth and schedule growth for miscellaneous construction and 3R project work types, respectively. Design-build projects also statistically provide a higher construction intensity (more work put in place) than D-B-B for new construction and reconstruction work types. No statistically significant differences between D-B-B and D-B projects were found for other project work types. This study contributes to the construction engineering and management body of knowledge by providing empirical comparisons between D-B-B and D-B project performance on the basis of different types of work. The findings from this paper may provide guidance for state DOTs and practitioners to select D-B project delivery for specific work types and benchmarks D-B against D-B-B.

Workforce planning plays a pivotal role in smooth execution of construction projects. The growing challenges faced by the construction industry related to skill shortage, aging problem, and workforce attraction, retention, and buy-in have added to technical complexities of workforce planning. Nevertheless, the available workforce planning techniques are either qualitative or lack a strategic perspective that accounts for the above challenges in hiring workforce, leading to suboptimal decisions with regards to hiring and unplanned firing. This paper proposes a novel framework for optimization of hiring and firing decisions by accounting simultaneously for organizational human resource (HR) strategies, labor rights, and technical and managerial constraints of a construction project. The framework starts by setting the model parameters and the decision-making criteria using the information made available by building information modeling (BIM), project performance database, and contractual and legislative documents. It then identifies the optimal mode and duration of the employment for the workers with different skills, skill levels, and multiskilling capabilities using a dynamic programming algorithm. The application and advantages of the proposed framework are demonstrated using a case study.

Construction claim negotiation has become a common managerial process in the construction business. Research on negotiation has overlooked relationships between negotiators as an important contextual factor. This study aims to examine the role of relationships in construction claim negotiations as both explanatory and outcome variable. Based on a systematic literature review, a hypothesized research model was developed. A questionnaire survey was administered to collect data from construction professionals. By performing a set of statistical analyses, the model was validated empirically. The results showed that the relationship construct can be defined based on 16 relationship dimensions, which were then categorized into five categories, namely harmonic, dependable, intimate, openness, and faithful. The study empirically supports the hypothesis that the relationship between the negotiators affects the negotiation process, particularly the adoption of coercive actions and the degree of information sharing, which further influences the preservation of an ongoing relationship. If the initial relationship is cohesive, the negotiators tend to implement information-sharing strategies and are unlikely to take coercive actions. The adoption of coercive actions deteriorates negotiators’ ongoing relationship, while the implementation of information sharing is instrumental to preserving ongoing relationships. This study contributes to the negotiation research by explicating the role of relationships between negotiators in construction claim negotiation. It also adds to the relationship research by viewing negotiations as strains in ongoing relationships between the parties. The findings of this study provide clear directions on how to select suitable negotiators, what best practices to be adopted, and how to become more effective negotiators.

The potential benefits of applied radio-frequency identification (RFID)-aided systems have been studied by many construction research projects. After reviewing previous works, this paper presents a self-developed system with the focus of a specific case in Australia. The system enables efficient material tracking, aiming for productivity improvement in the case. Initial site observations confirmed the need for an object-oriented material tracking system based on the principles of lean thinking and logistics qualities. Subsequently, a system was designed to activate a proposed method for optimizing material management during the supplier phase of the mega construction project. The experiments in this paper finally present two main streams: (1) performance testing of the system; and (2) productivity measure. As a result of performance testing, the tracking system was successful in locating the distributed 23 tags within an average range of 3.40 m. Supported by this system, the field productivity measurements consisting of four trailer-loading works (two lead and two tail trailers) quantified the feasible benefit of its application. The RFID-aided system facilitated the improvement of work performance, resulting in 10.14 (lead) and 11.80% (tail) productivity improvement. This research project therefore validated the benefits of RFID application in a construction supply chain by measuring its true value via the productivity improvements.

Maintenance cost optimization and performance prediction of bridge structures have become important challenges in bridge management systems. The performance of bridge structures should be carefully monitored, especially in severe climatic conditions. The objective of this study is to develop a rational method that predicts the most cost-effective intervention schedule for bridges, where the structural safety is maintained with the minimum possible lifecycle cost. The framework functions through (1) a central database that contains the asset inventory along with the maintenance actions list, (2) a biquadratic system reliability–based deterioration model, (3) an intervention effect model that simulates the effect of undertaking various intervention scenarios on the bridge superstructure performance, (4) a financial model that computes the lifecycle costs throughout the planning horizon, and (5) an optimization model that utilizes a genetic algorithms engine to compare the different intervention scenarios and selects the most cost-effective one. This method is applied to a simply supported bridge superstructure case study, designed in accordance with Canadian highway bridge design standards. The results indicate that undertaking less costly minor repair actions may considerably reduce the lifecycle costs as a result of decreasing the number of costly major interventions. The optimum scenario resulted in an equivalent uniform annual cost of US$8,277 per year, which shows 4.5 times cost saving as compared with the conventional scenario where only major repairs are performed. This innovative combination of reliability analysis, nonlinear finite-element modeling, and genetic algorithms optimization supports asset managers in long-term planning and ensures undertaking rational and objective decisions.

In bidding for construction projects, a contractor often uses the simple method of adding a combined rate of overheads and markup on top of the estimated direct cost for arriving at a bid. If the rate is subjectively charged, a greater loss risk is involved. An improved approach to determining the lower limit of the rate for a project is proposed. A neural network model built from recent winning bids and project attributes maps the rate in the winning bid for a project and is used to estimate the probabilities of winning for various rate levels. Then, the minimum rate to be charged is determined based on minimization of the overall loss risk defined by a probabilistic model with the estimated probabilities of winning and project cost variability. The approach is illustrated by an example using a firm’s bidding cases in Taiwan; the results are consistent with the features of the approach. In setting the lower limit of the overheads-cum-markup rate, the approach can be used to prevent arbitrary overcuts in bids under intense competition, thereby filling a gap among existing works and advancing the field of bidding.

Industrialized building companies apply various product predefinition strategies, derived from market- or resource-based strategic perspectives. This strongly affects the buildup of such companies’ business models and their operational structure. Ten companies were included in a case study, presenting strategic orientations and business models. The aim of this study was to analyze the primary characteristics of different business models applied by industrialized building companies, further describe their strategic orientations, and picture different paths of business model development. The emergence of industrialized building companies implies that new offerings and new roles for the building market is explored to lead to competitive advantages. This study showed that a key driver is to use deep customer knowledge to develop competitive end-product offers aimed at certain customer segments, achieving high customer value. Further findings were that a good fit and balance between the business model corner stones—offering, operational platform and market position—are crucial for industrialized building companies’ success. Business models for industrialized building companies evolve over time and lead to a fine-tuned balance and, thereby, increase fit. Differences and similarities between the studied companies’ business models and strategic orientations were affected by the surrounding market conditions. This study contributes to the theoretical buildup of business models and strategic orientations of industrialized building companies, and contributes to practitioners’ understanding of industrialized building companies from a strategic, company perspective.

Quality failure costs have been reported to range from less than 1 to over 20% of a project’s original contract’s value (OCV). Inconsistencies in their definition and determination have rendered such costs often being cited inappropriately to support a case for addressing poor quality in construction. Quality failure costs, which are expressed in the form of nonconformances (NCRs) costs, are derived and analyzed for 218 projects delivered by a contractor between 2006 and 2015. A total of 7,082 NCRs are categorized and quantified in accordance to their cost, and the differences among project type, procurement, and contract size are statistically examined. The analysis revealed that (1) mean NCR costs were 0.18% of OCV; (2) structural steel and concrete subcontracted works had the highest levels of NCRs; and (3) differences were found in the cost of NCRs among different procurement methods and contract sizes. The research provides the international construction community with invaluable insight into the real costs of quality failure that have been borne by a contractor. Thus, the paper makes a call to reinvigorate the need to engage with performance benchmarking so as to engender process improvement throughout the international construction industry.

In recent years, the Florida Department of Transportation (FDOT) adopted a form of performance-based maintenance contracting (PBMC) that it calls the asset maintenance contracting (AMC) program. This case study presents an analysis of the AMC program in Florida using a survey, an interview, and content analysis. Although similar studies have been conducted in the past, the survey presented here is unique in that the opinions of contractors and lower-level state employees were solicited. The results indicated that contractors were more confident in the success of the AMC program than were the state employees in Florida and that the cost and performance data needed to be maintained for quantitative analysis. The results highlighted the need for partnering between state agencies and contractors, emphasized the need for a shared-risk model, and stressed the importance of a well-defined scope and of quantifiable performance measures. The unique work associated with this paper included the use of contractors and lower-level employees in the survey and the use of content analysis to examine the interview responses. This was the first study of its kind conducted in Florida.