Journal of Construction Engineering and Management

International construction, where contractors perform works in foreign countries, poses cultural and contractual risks resulting from the dissimilarities in social and legal outlooks. One of the major risks that leads to disputes in such international projects is poor contract administration. Research has been focused toward the cultural risks and ex-post dispute resolution in international construction, missing the important ex-ante dispute avoidance aspect. This paper addresses this knowledge gap with a special focus on the Kingdom of Saudi Arabia (KSA), which is the largest economy in the Middle East and North Africa. The paper does so by providing in-depth—yet practical—contract administration guidelines for U.S. contractors working in public works projects in KSA. The focus was put on KSA because of its economic strength and because KSA’s associated contractual risks are uniquely relevant to those of other countries. To this end, the authors conducted comparative analysis between the Saudi Public Works Contract (PWC) and the U.S. Federal Acquisition Regulation (FAR) with respect to change orders, extension of time, liquidated damages, differing site conditions, and dispute resolution. Through exhibiting the important contractual and legal considerations that are unique to KSA, the outcomes of this research include: (1) a comparative checklist showing the similarities and differences between the two governmental approaches; and (2) a matrix of relative opportunities and risks of the PWC and FAR. Such an approach of analyzing the Saudi contracting environment from a U.S.-based context has not been undertaken before. As such, the study is beneficial to the U.S. contractor as it facilitates the understanding of the contractual premises in KSA and the associated risks and opportunities. This enhanced understanding will not only improve performance and minimize risks but also promote the contractor’s strategic presence in the global market.

Performance and productivity in construction management are essential for schedule and profit considerations, but are often diminished by conflict. Task conflict provides incentive for decisions and innovative solutions, whereas interpersonal conflict, also referred to as relationship conflict, is detrimental to performance and productivity because it affects schedules, cognition and collaboration efforts, and the morale of the team. This qualitative study investigates how relationship conflict affects performance and productivity among construction management professionals. Interviews were conducted in 18 construction firms with 25 construction management professionals, including project executives, senior project managers, project managers, and superintendents. The goal is to understand the antecedents and consequences of relationship conflict within construction management, and discover methods used to mitigate these effects. Key antecedents producing relationship conflict are lack of communication, old-school attitude, and lump-sum contracts. The key individuals generating relationship conflict are the owner or owner’s representative, subcontractors, and superintendents. Consequences of relationship conflict include schedule delays, lowered morale and motivation, and reduced profit, whereas mitigating factors are good communication and trust building.

One of the most critical decisions made by transportation project stakeholders is the choice of a project delivery method for their project. Delivery methods have been shown to significantly impact project cost and schedule. As the use of alternative project delivery methods increases, the perceptions of the advantages and disadvantages to using a particular method have matured. This paper reports on a national study of over 80 transportation owners and designers to measure their perceptions of the three most widely used delivery methods: design bid build (DBB), construction manager at risk (CMAR), and design build (DB). The study develops a list of factors that influence the selection of a delivery method, and then tests the most significant factors that lead to the selection of each individual method. Analyses using Fisher’s least significant difference intervals and multiple range tests allow for the identification of specific correlations between the delivery method and motivating factors or project goals. The analyses show that delivery method selection is motivated primarily by project urgency, cost, and risk allocation. For the three main delivery methods of DBB, CMAR, and DB, motivation for their selection is primarily based on cost, risk allocation, and project urgency, respectively. User perceptions align with findings from literature in terms of schedule performance, but do not align in terms of cost performance. This research contributes to the body of knowledge by reporting on the most current motivating factors for the selection and use of the most popular delivery methods.

Environmental issues are becoming a growing concern for the construction sector and cause a number of complaints. Construction noise is one of the most prevalent stressors to the public, especially for residents near worksites. Many academic and practical studies have been conducted to address such noise-related problems. However, conventional approaches typically focus on monitoring noise and experts’ judgment; they are limited at evaluating the degree of risk caused by noise. This paper proposes a model for determining the noise-induced risk, with the severity based on the predicted noise level from a Monte Carlo simulation and the occurrence probability of the noise exceeding a certain limit. Case studies were conducted to confirm the applicability of the model. The results indicate the crucial period that needs to be carefully managed, which is more applicable to determining the noise-induced risk compared to existing approaches. This paper contributes to the literature for noise management by presenting a method for evaluating the impact of noise-related risk and providing a pragmatic alternative to supplement existing approaches during the preconstruction phase.

Research and development (R&D) of smart construction systems has been constrained by the contentious relationship between system developers and potential industry users. System developers are critical of practitioners’ reluctance to embrace new technologies, while practitioners tend to view developers’ systems as disruptive. In explaining acceptance or non-acceptance of smart construction systems, the well-established technology-acceptance model (TAM) is a powerful instrument. However, the model fails to capture changes in user acceptance over time. In this study, an extended TAM that can reflect the changes in attitude is modeled from and substantiated by a two-year longitudinal action research study conducted in parallel with the codevelopment of a smart system for prefabrication housing construction. It is discovered that users’ attitudes toward a smart construction system are not invariable, nor toward the “perceived usefulness” and “perceived ease of use.” Developers should continuously enhance usefulness and user-friendliness of a system to facilitate its adoption. A particularly noteworthy finding is that external isomorphic pressures, including normative, coercive, mimetic, or a combination thereof, can affect users’ attitudes toward a smart construction system, and, in turn, influence the uptake of the system. Managers tactically can create such pressures to enhance technology acceptance within their organizations. These findings, in combination with the extended TAM, offer the foundations for development of a general theory on technology infusion in the construction industry.

Despite many advantages of precast concrete members, the conventional precast members lack in the treatment of construction waste, require concrete pour forms at joints, and their structural discontinuity leads to low redundancy in the load paths. This study aims to provide novel solutions to these problems by developing interlocking mechanical joints with fully restrained moments for the connections of both steel-concrete composite precast and reinforced concrete precast columns. In the proposed connections, a pair of steel plates was provided; each plate was installed at the bottom of the upper columns and on top of the lower columns, which were then connected monolithically via vertical column rebars passing through the metal plates, providing flexural capacity similar to that of conventional monolithic column connections. The column rebars were spliced by couplers that were manufactured to be fastened by the weight of the upper column, which was heavy enough to push the vertical rebars into the couplers in the area prepared at the lower part of the upper column, providing a monolithic joint for the connected precast columns. Throughout the erection test, it was found that conventional monolithic cast-in-place joints for assembling precast concrete frames can be replaced by the interlocking mechanical joints, offering rapid erection compared with traditional practices. The columns with proposed joints were also proved to demonstrate sufficient structural capacity. Stresses and strains were found within allowable limits on the basis of finite-element analysis considering concrete plasticity during the assembly of heavy precast frames. The erection test showed sufficient verticality ensuring rebars to be connected via couplers when the upper columns were released down to the lower columns. This novel frame did not require concrete cast at the joint, eliminating the use of concrete pour forms adopted in conventional construction methods over the last years. Effortless erection with structural efficiency was demonstrated by using the proposed assembly method, with a significant reduction in the time required to assemble precast frames, similar to that of steel frames. The novel frames proposed in this study are expected to replace the conventional concrete frames including cast-in-place frames and precast frames with traditional joints. These novel frames contribute to the concrete industry by providing rapid and dependable construction of both precast and cast-in place frames.

The improvement of construction productivity has always been a key concern for both researchers and project managers. Several studies have analyzed construction productivity from different perspectives; however, little research has been conducted to evaluate the impact of outdoor ambient environmental factors on construction productivity, especially at the project level. Therefore, to assess such impacts, a nonparametric regression model—the generalized additive model (GAM)—and a nonlinear machine learning model—random forest (RF)—are comparatively used to assess these contributors on the scaffolding construction performance factor (PF). The meteorological variables used in this study include temperature, humidity, ambient pressure, wind speed and wind direction, specific weather event (clear day, fog, rain, or thunderstorm), and the ultraviolet (UV) index. Results demonstrate that the joint meteorological factors play a key role in construction PF variation, with contribution ranging from 32.50% (GAM) to 59.41% (RF). The better performance of RF and GAM shows that the relationship between outdoor ambient environment and construction productivity is nonlinear and should be built by nonlinear models.

As the scale and complexity of capital projects continue to increase, so do collaboration requirements among owners, engineers, architects, contractors, and other stakeholders in the project lifecycle. These organizational network challenges can impede successful project delivery. Innovation is a key factor in executing complex projects that require expertise from each party in a collaboration network. Unlike in many other industries, collaborations in architecture, engineering, and construction (AEC) project networks are typically temporary and require periods of intense collaboration. In an effort to understand the characteristics and evolutionary paths of innovative collaboration networks in the AEC industry, the authors collected data on more than 200 projects over a 15-year period (2000–2014) that were awarded the State Science and Technology Advancement Prize (SSTAP) of China and examine each of these as innovation collaboration cases. Social network analysis (SNA) techniques are used to understand the network characteristics and to examine the evolutionary patterns over time. The results find the studied innovative collaboration networks to be large and interwoven. Universities, with significantly greater betweenness centralities, serve as key network nodes in spreading creativity and promoting practical–theoretical integrations. This study also reveals that fewer repeated collaborations lead to more innovativeness. In other words, repeated collaborations may have a negative impact on novel and challenging AEC projects. Understanding such characteristics could promote innovations in the AEC industry and aid in the selection of strategic partners to participate in the execution of large and complex AEC projects more efficiently and effectively.

Because of significant characteristics such as complexity and uncertainty, the construction schedules of large-scale projects are often postponed as a result of a shortage of important equipment. By sharing its own incentive reward with other contractors for acquiring extra equipment, a contractor with a lack of equipment resources can reduce time delays and even complete projects in advance. This paper focuses on analyzing onsite construction equipment sharing among contractors from different sections of the same project. First, two forms of time incentives are applied to encourage the contractors to decrease their construction duration by sharing equipment resources. Then, based on an analysis of the influence that equipment sharing has on construction duration, a Stackelberg model among the equipment-sharing contractors is developed to build the contractors’ gain functions and simulate the equipment-sharing process. Finally, a numerical analysis is conducted to analyze the effect that a time incentive and construction costs have on the contractors’ benefits. The results demonstrate that the incentive for a contractor needing more equipment is positively associated with the gains of both contractors, whereas the incentive for the contractor lending out equipment acts inversely. This paper contributes to the body of knowledge for understanding the process of onsite equipment sharing among contractors. By capturing the contractors’ aspect of equipment sharing, this study provides a practical model to aid the client in settling resource-leveling problems rather than using traditional approaches that have been conducted from the client’s perspective. This research should be beneficial for project managers to better understand how suitable incentive contracts can facilitate equipment sharing among contractors and consequently help ensure construction schedule.

Many inherently risky industries improve their safety management by learning from near-miss incidents. The construction industry is starting to manage near-miss incidents for improving safety, and several studies have been performed to introduce a system to manage near-miss incidents during construction. However, an analytic framework to technically investigate near-miss events remains missing. In this research, a structuralized analysis of safety events (including both near misses and accidents) in metro tunnel construction was presented. A number of incidents (57 accidents and 186 near-miss events) were collected, and these crude reports were compiled through qualitative analysis into a database of safety events. The database, with both categories and variable definitions incorporated, served as the basis for quantitative analysis. Groups of events were mined to figure out whether they were similar or identical through cluster analysis. The entries in the database were divided into clusters by the iterative self-organization data analysis (ISODATA) algorithm based on the variables defined. For each level of outcome severity, the risk potential of each cluster was compared with that of other clusters and the whole database; thus, the magnitude of the risk potential of the cluster under consideration was quantified. The analysis showed that the biggest risk factors in metro tunneling excavation were in (1) improper soil reinforcement and drainage at the launching or arrival portal and (2) soil instability of the tunneling face. The developed approach in this research can be used as a decision tool to provide insights for better interpreting characteristics and patterns of the identified clusters (within different levels of risk potential) mined from the historical near-miss and accident reports in tunnel construction.

Stability analysis and risk assessment are key issues in the design and construction of tunnels; however, these assessments are often hard to conduct accurately because of the complexity of tunnel engineering. In order to improve tunnel construction technology, this paper uses the safety factor as the assessment index. A quantitative analysis method for tunnels is presented by using the convergence–confinement principle and the numerical simulation analysis method. To meet these objectives, based on the actual construction technology, the tunneling method is studied using a detailed numerical model to investigate the effects of different patterns for advancing the tunnel face. A new method for solving the safety factor of the support structure is proposed using a three-dimensional numerical model; the detailed solution process is illustrated through the case of Luoyixi tunnel. The results show that the safety factor of a lagging tunnel is significantly less than that of the leading tunnel, and that in order to ensure the stability of a lagging tunnel, reinforcement measures should be included during the construction process. Moreover, there is also a danger signal for leading tunnels: the direction of the butterfly-shaped wings in the plastic zone began to deflect to the vault at the start of lagging tunnel construction. In order to prevent the possibility of the roof falling, an advanced rockbolt should be applied in time. For designers and builders, the developed quantitative method in the form of safety factors can be used for a comprehensive evaluation of the support design and the rock state. For these reasons, this method is a convenient option for optimization analysis in construction technology.

Workers’ unsafe behaviors are one of the main causes for construction accidents. Fully understanding the causes of unsafe behaviors on site will help to prevent them, thus reducing construction accidents. The accurate and timely identification of site workers’ unsafe behaviors can aid in the analysis of the causes of unsafe behaviors and prevention of construction accidents. However, the traditional methods (e.g., site observation) of behavior data collection on site is neither efficient nor comprehensive. This paper develops a skeleton-based real-time identification method by combining image-based technologies, construction safety knowledge, and ergonomic theory. The proposed method recognizes unsafe behaviors by simplifying dynamic motions into static postures, which can be described by a few parameters. Three basic modules are involved: an unsafe behavior database, real-time data collection module, and behavior judgement module. A laboratory test demonstrated the feasibility, efficiency, and accuracy of the method. The method has the potential to improve construction safety management by providing comprehensive data for the systematic identification of the causes to workers’ unsafe behaviors, such as inappropriate management methods, measures or decisions, personal characteristics, work space and time, as well as warning workers identified as behaving unsafely, if necessary. Thus, this paper contributes to practice and the body of knowledge of construction safety management, as well as research and practice in image-based behavior recognition.

Uncertainty and risks have been the inherent characteristics of large-scale projects. Although practitioners have applied different project risk management standards, numerous uncertainties, and risks in large-scale construction projects have led to significant failures in fulfilling a project’s goals. Therefore, in this study, a hybrid approach based on failure mode effects analysis (FMEA)/ISO 31000 has been proposed to identify, evaluate, and control the problem effectively. This hybrid approach is not a very accurate approach in providing an appropriate risk response; hence, a mixed-integer programming (MIP) model has been proposed to select the optimized risk response strategies for the project. In the present study, a model based on synergies among project risk responses was developed that is capable of considering the various criteria in the objective function and optimizing them based on the defined projects. Risk response selection for a large-scale project is a complex problem. Because of the nondeterministic polynomial time (NP)-hardness of the presented model, two metaheuristic algorithms, namely, the self-adaptive imperialist competitive algorithm and invasive weed optimization, were developed to solve the proposed MIP model. A large-scale high-rise residential building was evaluated as a case study to investigate the model proposed in this study empirically.

The assessment of pavement condition rating (PCR) for hot mix asphalt (HMA) surfaces and exposed portland cement concrete (PCC) in composite pavements is an important component of the decision-making process for treating reflective cracking. Visual inspections such as PCR or falling weight deflectometer (FWD) have been conducted as current practices for reflective cracking treatment. However, these evaluation methods are not able to identify the severity of cracking in the underlying PCC slab. Furthermore, additional evaluation methods, such as coring tests, and milling operations could involve various types of costs including time delay costs, traffic control costs, and labor costs. Because of such extensive cost requirements, field engineers often tend to rely solely on visual inspection of the HMA surface without performing actual milling operations. Therefore a systematic decision-making process is needed to select appropriate maintenance treatments for reflective cracking in composite pavements. In response to this need, this research proposes a framework for composite pavement maintenance decision making that consists of three modules: (1) field evaluations to assess the condition of the pavement at the joint, (2) development of a PCC pavement condition prediction model to determine the severity of PCC cracking at the joint in a composite pavement, and (3) a treatment selection table to help determine a possible mitigation strategy for the treatment of each reflective crack type. A case study is conducted to validate the proposed prediction model, with the results showing 0.77 accuracy. Therefore the proposed systematic decision-making process is able to provide field engineers with a more accurate treatment selection process for reflective cracking in composite pavements than is currently available. Furthermore, the proposed process can reduce maintenance costs by simplifying field test evaluation methods and alleviating the need for milling the HMA surfaces.

The project management triad consists of scope, time, and cost. In this study, the schedule variance and schedule performance index, in traditional two-variance earned value management (EVM), are proven not proper time performance indicators, and it is suggested to restore the original physical meanings of work performance as work variance (WV) and work performance index. It is found that work performance can equal time performance before the project’s planned duration in certain cases. However, the same is not true generally, especially once the project is overdue. An average work rate-based earned time method (ETM) is introduced in this study, which can serve as an alternative approach to estimate project time at completion. Finally, it is suggested that an independent performance measure, WV, be added to EVM, and that a three-variance approach be used to analyze the performance statuses in work, time, and cost integrally of a given project.

Construction development projects are often complicated and influence multiple stakeholders with different requirements and interests. Public engagement (PE) has emerged as a prerequisite for collecting stakeholders’ opinions and involving them in the planning and decision making of construction development projects. It is not easy to identify and manage stakeholders in PE because different stakeholders possess different types of power and interests that have the potential to dramatically affect stakeholder behaviors and final project outcomes. However, the effects of stakeholder attributes (i.e., power and interest) on stakeholder management in PE and final PE outcomes have been insufficiently studied. This study aimed to investigate the complicated relationships between stakeholders’ power, interests, and PE outcomes through a questionnaire survey. An integrated model for stakeholder power, interest, and PE outcomes was developed using a structural equation model. The results showed that different forms of power and interest influenced final PE outcomes either directly or indirectly. PE organizers are encouraged to directly involve project teams, experts, and reputable stakeholders in the PE process and allow the media and nongovernmental organizations to monitor the decision-making process. The findings of this study will contribute to stakeholder management for PE in construction projects by developing a structural model that can be adopted to identify stakeholder power and interests and engage appropriate stakeholders in the decision-making process. It is expected to improve PE outcomes and enhance stakeholder satisfaction for construction development projects.

Construction crew performance is a function of both motivation and the situation in which tasks are performed. However, previous research in construction has not comprehensively investigated situational/contextual factors and their impact on the relationship between motivation and performance. This paper defines a comprehensive set of crew performance metrics, analyzes the relationship between motivational factors and crew performance, and identifies key situational/contextual factors that affect the relationship between motivation and performance. Multiple-source interview surveys identify factors that motivate construction crews, situational/contextual factors, and crew performance metrics. Correlation analysis is performed on field data to determine the relationship between motivational factors and crew performance. Hierarchical regression analysis is used to identify key moderators of the relationship between motivation and performance. This paper makes three major contributions: it develops a comprehensive set of construction crew performance metrics that relate not only to task performance, but also to contextual performance and counterproductive behavior; it reveals how motivational factors affect crew performance; and it provides a comprehensive list of key moderators of the relationship between construction crew motivation and performance.

Recreational drug use in construction is an area of concern for safety managers, and the legalization of marijuana in several US states may result in increased use among workers. Experimental approaches and policy creation are not straightforward because of the problems around existing methods of drug testing for marijuana that stem from the fact that its longevity in the body outlasts actual intoxication and a lack of scientific agreement of quantifiable long-term effects on work performance. Here, a social constructionist methodology has been adopted to explore perspectives of marijuana legalization as revealed through conversations with 50 construction site workers. Findings show that although legalization has had no impact on use among construction workers, impairment while at work remains unacceptable. A conflict now exists around personal freedoms and drug testing, leading to both resignation and dissatisfaction among workers. This could negatively influence the development of a positive safety culture on sites and hinder worker engagement with safety overall. It is recommended that companies and unions recognize that blanket testing policies are problematic in practice and support the development of accurate testing for immediate impairment from marijuana use.

In Santiago, Chile, the market conditions are seemingly excellent for the household adoption of photovoltaic (PV) technology, yet the uptake is negligible. To explore this paradox, the authors conducted a Delphi study to solicit the knowledge of a panel of Chilean PV experts. These efforts yielded 26 factors—both motivations and barriers—impacting the diffusion of PV in Santiago. Of the 26, experts were in consensus on the relative importance of 21. The literature suggests that diffusion of PV technologies is influenced by complex technical, economic, and social factors. Similarly, the experts saw influence from financial, environmental, and energy supply (e.g., electrical reliability) factors. They saw emergent barriers to adoption as being financial, technical, institutional, and knowledge factors. They considered the most important factors influencing adoption to be financial motivations (e.g., subsidies) and financial barriers (e.g., high upfront costs); they considered the least important factors to be environmental motivations (e.g., environmental stewardship) and technical barriers (e.g., concerns with roof mounting). With this knowledge, the authors develop an adoption framework for household PV that describes the interaction among the identified motivations and barriers. This framework informs policy recommendations for Santiago, Chile, and contributes to the body of literature exploring the interconnected systems of factors that influence civil infrastructure in general and PV adoption in particular.

The proper management of water sanitation and hygiene (WASH) services is critical in serving displaced populations. In 2015, the Azraq refugee camp in Jordan serving the displaced Syrian populations became one of the first in the world to have an on-site advanced wastewater treatment plant (WWTP). Although there exist guidelines and best practices on the proper WWTP incident management, evidence suggests that they are largely ineffective in providing substantial benefits to active incident management. This study applied a mental model approach to investigate the Azraq WWTP project stakeholder decision practices during an active incident management phase and to initiate work to identify the factors that influence the WWTP project delivery during a disaster response. These findings showed that improving the practitioners’ ability to recognize and address the nontechnical internal concepts that impact their decision processes could positively influence the wastewater treatment plant construction and operation in new and challenging project conditions. The implementable recommendations include flat communication structures, training for locating knowledge within new disaster response project groups, and increasing the stakeholders’ ability to create improvised solutions on the basis of their existing professional knowledge.

Design errors are one of the major risk factors causing rework and delay. Therefore, accurate cost analysis of potential economic losses attributable to design errors is crucial from a practical point of view. This paper proposes a basis for establishing building information modeling (BIM) investment strategies by quantifying the various costs associated with design errors for error prevention. The design errors were classified into three basic types: simple design (Type 1); rework-related (Type 2) that may lead to demolition and rework; and delay-related (Type 3) likely to prolong the construction period. To evaluate the effects of BIM application quantitatively, the performance potential of BIM-assisted identification of individual design errors was examined. A comparison of the influences of classified design errors on the project revealed that the total cost of the design errors leading to schedule delay was 194.69% higher than that of the simple design errors and the direct design error costs due to errors leading to demolition and rework.

Prior studies explored and identified the interrelationships of various flash track practices and concepts. This research formalizes a reengineered workflow process for successful flash tracking, known as cPEpC (little c stands for committed and collaborative engagement of downstream stakeholders at the onset of the project, big P stands for procurement of strategic and long lead items, E stands for engineering, little p stands for procurement of balanced items, and big C stands for construction). The cPEpC model is centered around the notion of the importance of building a fully integrated team by engaging key specialty contractors and vendors early on during the conceptual and detailed scoping phases. cPEpC formalizes the committed involvement of both contractors and specialty contractors as well as facilities operators and managers early in the project. In essence, it enables a construction-driven and operation and maintenance (O&M)–driven design philosophy or method of directing the design development process by injecting into it, at the outset, substantial knowledge and experience about means and methods of construction and considerations for O&M. cPEpC requires a heightened degree of concurrency among procurement, design, and construction, while maintaining safety, quality, and the risk tolerance that is needed to manage the volatility inherent in flash track projects. This paper contributes to the body of knowledge by formalizing the cPEpC workflow process and by providing empirical evidence of its implementation in a first-to-market flash track project in the food and consumer products industry.