Journal of Construction Engineering and Management

From the relational contract approaches currently emphasized in construction, researchers have noted that there is enough evidence pointing toward social psychological theories of team formation. Building on a theoretical framework, this paper analyzes social, construction, and team formation literature through a comprehensive literature review. Findings reveal that construction teams form as small worlds out of clusters that emerge either through contractual, professional, task, or trade relationships, which strongly supports the proposed theoretical framework for social networks in construction. This paper contributes to the body of knowledge by bringing together three diverse theories of team formation, social network, and collaborative teams into construction engineering and management research while at the same time identifying gaps and areas for future research. In addition, this study reveals that fragmented construction teams are characterized by clusters, and resources are constrained from one cluster to the other. As such, construction teams lack bridging ties necessary to reduce social distance between members, an area that has received limited attention from researchers.

Supplier performance analysis can enlighten a construction company about improvement possibilities for better project outcomes. However, for systematic evaluation of a supplier across projects, changing the operating environment between projects should be addressed. Therefore, we first elaborate how supplier evaluation is challenged due to differences between projects in three characteristic groups: project product and location characteristics, project organization characteristics, and buyer–supplier transaction characteristics. We next discuss the possibility of applying data envelopment analysis (DEA) for supplier evaluation in construction, and argue how changing the operating environment can lead to nonhomogenous decision-making units in DEA. Building on these, we propose the process for supplier evaluation in the presence of a changing operating environment and different input–output profiles. Characteristics of 12 projects and supplier evaluations in 44 projects are used to illustrate evaluation challenges. The research extends current knowledge on supplier evaluation in construction by underlining how changing the operating environment across projects challenges systematic performance evaluation and by suggesting the process which further research could develop toward practical applications.

Contractors in bidding for a construction project often focus on the direct cost and determine a bid price by applying an overheads-cum-markup rate on top of the estimated direct cost. Such a simple method is prone to incorrectness if a rate is charged without a sound basis. As an improvement, a fuzzy logic model is proposed for determining the minimum rate for a project based on the bid position of a contractor. Using the estimates of chance of winning and loss risk as inputs, the model incorporates the bid position in a set of fuzzy rules that reflect the degree of need for work and risk attitude. A regression equation built from bid data for public sector projects connects the ratio of winning bid to owner’s budget with project attributes and is used in estimating the chances of winning for various rates. An illustrative example is provided, in which the rules representing the bid positions in nine scenarios were formulated and recent bids in Taiwan were collected for building the regression equation. The results of simulation of bidding for two bidding cases show that the model can differentiate the bid positions and suggest minimum overheads-cum-markup rates consistently. The model may prevent inadequate rates in bidding under intense price competition, thus advancing the field of bidding.

The commissioning and startup (CSU) stage of industrial capital projects is made up of a large number of discrete activities. These activities are executed across the construction, precommissioning, commissioning, and startup (CCSU) project phases by a host of organizations and disciplines. CCSU activities are often fraught and have adverse consequences which may broadly impact overall project success. This research sought to discover which activities are commonly problematic across industrial sectors, and how these activities are characterized. A better understanding of commonly problematic activities (so-called Hot Spots) will give insight into how best to address problems when or before they arise. Contributions made by this research include a list of 20 of the most common problematic CCSU activities, characterizations of 7 attributes for each of the 20 Hot Spots, an analysis of themes recurring among the characterizations, and a model for implementation of research findings on projects. These contributions will provide perspective on common CCSU shortcomings and guidance on how to remedy them.

Building information modeling (BIM) is an encouraging development in the architecture, engineering, construction, and operations (AECO) industry due to its data-rich digital representation of building components. Although BIM is technically mature, its legal and contractual systems are yet to be standardized. Motivated by this need, the current study has developed a framework for legal and contractual risks within BIM. In this study, 14 significant risks were identified from 10 published taxonomies, and five standard and three custom BIM contracts were reviewed to assess their coverage and check their redressal strategies. On the basis of the triangulation of information gathered from published contracts, expert opinion, and custom manuscripts, mitigation strategies for the legal risks were proposed and formalized into a contractual framework designed for a design-bid-build delivery system. This study contributes to the body of knowledge and practice by helping the AECO community understand the current level of legal and contractual maturity of BIM, and by stimulating the technological and legal fraternities to sufficiently deliberate the contractual uncertainties in order to facilitate the uptake of BIM in the AECO industry.

Multiskilling allows for dynamic reallocation of workers from one stage of production to another in response to bottleneck configurations and, therefore, has been advocated as a potential strategy to improve productivity in off-site construction. The aim of this research is to investigate the extent to which operational benefits associated with different resource management policies pertaining to bottleneck configurations can be achieved in off-site construction. To this end, the flow shop environment is recognized as an appropriate operational framework for modeling production dynamics. A quadratic resource allocation model was developed to expose different operational performances corresponding to different resource management strategies. Different resource management policies included no cross-training, hiring single-skilled crew, direct capacity balancing, chaining, and hiring multiskilled crew. Operational performance encompassed makespan and labor costs. Production data from a prefabrication factory based in Melbourne, Australia, were fed to the model, providing the basis for comparison of different resource management policies. Research findings contribute to resource planning and management in off-site construction.

In this paper, compressive strength, water absorption, diffusivity capacity, pore area, and the role of the enzyme on clay soil brick were verified. The higher compressive strength at enzyme:water ratios of $1:150$, $1:250$, and $1:350$ was greater than 7 MPa, and lower water absorption at the same state was less than 16%. These values satisfied ordinary clay brick standards, which are a minimum strength of 7 MPa and a maximum limit of 20% water absorption. The enzyme concentration affected the pore area of the brick samples. Based on ImageJ analysis, the pore area of enzyme clay brick decreased when the enzyme concentration increased. The cross-linking matrix bond and the early stage of ettringitelike structure formations are the effects of enzyme on clay soil as observed by a scan electron microscope (SEM) using Matlab image processing. These structures are important for the strength and immobilization properties of enzymes in clay soil. Enzyme brick could be applicable mainly in developing countries to provide affordable housing.

In 2015, 28 European countries cumulatively received over two million applications for asylum, almost three times more than in the previous year. This resulted in pre-existing accommodation facilities reaching capacity and requiring the provision of urban emergency accommodations in unconventional buildings. To meet this housing need, ad hoc task forces across multiple disciplines formed to mitigate the extreme uncertainty of providing infrastructure services in a short period of time. The involvement of water and wastewater utilities in this technical project was explored through employee perspectives from two German water and wastewater utilities using qualitative analysis techniques. Ethnographic interviews were iteratively coded for excerpts legitimizing the interviewee’s involvement in providing water or wastewater services for emergency accommodations. Results show three emergent themes from utility employees: the necessity of improvisation during the design process, confidence in the situational response by individuals and the utility, and the necessity for improved coordination with other actors in the synthetic organization. In addition, this work provides a theoretical framework for the technical application of organizational legitimacy theory in the circumstances of extreme contextual uncertainty. Practical implications of this work suggest utility monitoring of emergency accommodations for improved design and better protocols for coordinating with other actors.

Millions of migrant construction workers (MCWs) worldwide make significant economic contributions to their host countries or regions but often suffer poor housing conditions. It is therefore important to explore new ways to improve housing conditions for MCWs. Based on the concept of sustainable design, the authors propose a semicustomized design framework of container accommodation through improvements to the job process of a classical value engineering process in three aspects. First, a method of design scheme innovation based on Maslow’s hierarchy of needs is developed; second, two types of decision makers are integrated in different stages of the design process to satisfy the diversified housing needs of MCWs from social and psychological perspectives; and third, to better measure the housing satisfaction of MCWs, the authors developed an evaluation method of quantifying worker housing satisfaction with different design schemes using the analytic hierarchy process (AHP) method, including an evaluation indicator system with MCW psychological factors. This framework can be used to determine the supply of container accommodation and prices that best fit the needs of MCWs by optimizing the function and cost of design schemes. To demonstrate the feasibility of the framework, a case study is conducted. In addition, the limitations of the framework are discussed.

In project management, resources and time are two critical aspects influencing the success of a project. On the one hand, resource leveling, an effective resource optimization technique, is widely adopted to guarantee the efficient use of resources. On the other hand, to deliver a project as soon as possible, it can typically be accelerated by overlapping some activities. In a real-life project environment, uncertainty is inevitable and further complicates resource leveling and activity overlapping. However, existing research tends to study resource leveling and activity overlapping separately and little attention has been paid to level resource usage with uncertain activity overlapping. Therefore, the authors model activity overlaps as minimum time lags and study the resource leveling problem with stochastic minimum time lags (RLP-SMTL), where both the time lags and the activity durations are uncertain. This study aims to obtain a scheduling strategy such that the usage of renewable resources is as smooth as possible over time. The tuple represented by a random key vector, a strategy dynamically schedules activities at each decision point. A simulation-based solution framework for the RLP-SMTL is proposed. Built upon the proposed solution framework, two metaheuristics, an evolutionary algorithm (EA) and a bat algorithm (BA), are designed. Based on 1,080 randomly generated 100-activity instances, extensive computational experiments are performed to evaluate the effectiveness of the proposed algorithms. The results reveal that the EA outperforms the BA in terms of both the objective function’s value and the timely project completion probability. Although the strategies generated by the BA are slightly weaker than the EA, the BA is much faster than the EA. The results obtained by an additional comparison experiment further show that the proposed algorithms outperform the existing best-performing metaheuristic. Additionally, an example project is adopted to illustrate how the proposed approach can be applied to practical resource leveling in construction projects. In conclusion, this paper contributes to the body of knowledge in construction engineering and management by developing effective metaheuristics that equip the project manager with an automated tool to make effective resource leveling decisions under uncertainties.

Construction supply chain management (CSCM) requires the tracking of material logistics and construction activities, an integrated platform, and certain coordination mechanisms among CSCM participants. Researchers have suggested the use of building information modeling (BIM) technology to monitor construction activities and manage construction supply chains. However, because material warehousing and deliveries are mostly performed outside construction project sites, project information from a single BIM model is insufficient in meeting the needs of construction supply chain management. In this research, an integrated framework was developed based on four-dimensional (4D) BIM and a geographical information system (GIS) for coordination of construction supply chains between the construction project sites and other project related locations, such as supplier sites and material consolidation centers. The proposed integration was used to solve three common tasks in CSCM, namely (1) supplier selection, (2) determination of number of material deliveries, and (3) allocation of consolidation centers, using information from 4D BIM and GIS. The proposed 4D BIM-GIS framework was demonstrated via case studies. The results of the case studies indicated that determinations of supplier and number of deliveries need to take into account both the transportation distance and material unit price. Mathematical solutions were also generated to support decision making for the allocation of consolidation centers in congested regions with long transportation distances. The outcomes of this paper serve as a decision support base for a more efficient CSCM in the future.

The health and safety (H&S) of workers is a critical project management goal in construction. As globalization and migrant movement increases, construction projects are becoming more nationally diverse. Among multinational workforces, language barriers present an obvious but largely unresolved H&S communication challenge, with current strategies in use yet to be assessed. On a large construction project in the United Kingdom, H&S communication strategies were explored through an ethnographic approach. This paper contributes by revealing the impracticalities of using employees as interpreters in workgroups of six or more and the limitations of technologies in a dynamic construction site environment. It also highlights the unresolved challenge of translating safety videos in multiple languages. Challenges arose including translators refusing to translate because they were not receiving extra financial benefits or recognition in their workload. Translators were also given favorable treatment during disciplinary processes because they were crucial to the continued operation of the site team. This reveals the complexities involved in implementing effective H&S communication strategies on international and multinational projects, which have previously remained largely ignored.

Estimation of highway project construction time prior to design development has received comparatively little focus from researchers. State transportation agencies (STAs) and their management teams need a method or tool to estimate construction time during the project planning and development phases, where STAs typically manage hundreds of projects at the program level. These programs of projects are updated periodically, which requires an estimation methodology that is efficient, less time consuming, and reliable during the phases where limited project information is available. This paper presents an approach to developing a planning-phase construction time estimation model using linear regression modeling on actual construction time and cost data from 623 highway projects completed by the Dallas District Office, Texas Department of Transportation (TxDOT). The study developed a multiple linear regression model with three project parameters that were identified as key predictors to construction time. The accuracy and reliability of the developed model were higher than those of the well-known Bromilow’s time-cost (BTC) model. The model was also validated by the Mann-Whitney test of its applicability to a large group of projects. The proposed model requires less effort to develop, update, and revise with new data, which allows STAs to conduct planning-phase estimation of the construction time of a large portfolio of diverse projects effectively and efficiently. STAs would benefit from using this model in various project planning areas such as financial planning, staff planning, transportation impact mitigation, budget allocation, and project prioritization. This study also contributes to the body of knowledge with the proposed construction time estimation methodology during the planning and development phase that has been less focused.

This paper proposes a camera placement framework that incorporates characteristics of complex construction jobsites. The proposed framework consists of three main processes: (1) identification of visual monitoring determinants, influencing factors, and camera placement conditions; (2) problem definition and mathematical modeling; and (3) hybrid simulation-optimization of camera placement on construction jobsites. To evaluate the performance of the proposed framework, a case study for an actual construction jobsite was performed. The results of the case study show the potential of the proposed framework to find the optimal number, types, locations, and orientations of cameras for jobsite visual monitoring. This research makes three main contributions: (1) identification of critical elements to be considered when installing fixed cameras on complex construction jobsites; (2) development of a systematic framework for camera placement on jobsites; and (3) visualization and quantification of multiple camera network designs and their performance (i.e., total costs and visible coverages) before installing cameras at actual jobsites.

Highway construction costs are subject to significant variations from project to project and over time. Variations in construction cost disrupt transportation agencies in making right investment decisions and estimating accurate construction costs for projects. A wide range of variables has been proposed in different studies to explain variations in construction cost. There is value in conducting a research study that attempts to consider a comprehensive list of variables with potentials to explain the variations. The study needs to simultaneously take into account all possible explanatory variables to examine their relations with construction costs. The objective of this research is to assess the relations of several potential variables to explain variations in submitted unit price bids for major asphalt line items in highway projects. The primary contribution of this paper to the body of knowledge is the creation of a random parameters model to explain variations in submitted unit price bids for asphalt line items in highway projects. The identified variables used to build the random parameters model were classified into two major tiers. Tier 1 represents project-specific categories, including project characteristics, major supply sources for critical materials, and price adjustment clauses. Tier 2 represents global and external categories, consisting of the level of activities in local highway construction market, construction market conditions, macroeconomic conditions, and energy market conditions. It is expected that the findings of this paper will contribute to the current practice of cost estimation and investment decision making by helping transportation agencies develop more accurate budgets and contractors prepare more accurate bids for highway projects.

In an attempt to enhance the trustworthiness of contractors and reduce corruption, the Chinese government has launched a construction contractor credit scoring (CCCS) scheme in Beijing to evaluate the compliance and integrity of contractors registered in the construction market. The contribution of this paper to the body of knowledge is to analyze how the incorporation of CCCS may affect general contractors’ present and future competitiveness through a case study in China. This paper analyzes the procurement of 158 building projects tendered in Beijing involving 2,071 local general contractors active in the market. The results show that (1) the contractors’ CCCS scores are important for being awarded large and mega project contracts; (2) CCCS scores have a generally positive effect on future corporate financial income; and (3) contrary to expectations, the policy does not increase the CCCS of companies. Finally, the changing trend in contractors’ CCCS scores is observed to be highly correlated with their initial values (the scores of higher CCCS scoring companies increase faster on average than that of other companies). The final remarks address ways to better implement CCCS schemes in the future and avoid the potential risks involved in their use.

Public participation is a critical aspect of the success of public infrastructure megaprojects (PIMs), in which ineffectiveness is a constant problem. Although studies have focused on public participation, a method that can measure and improve its effectiveness is lacking. The present study addresses this knowledge gap using a game theory model and social utility equations to measure the effectiveness of public participation in PIMs. Results indicate that the institutional arrangements and social responsibility of PIMs (SR-PIMs) determine stakeholder behaviors, which influence the effectiveness of public participation. The Shanghai Maglev construction project was used as a case study to validate the proposed model and the assumptions of the current study. A conceptual model of governance framework was proposed to enhance the effectiveness of public participation in PIMs. This study contributes to the body of knowledge concerning public participation in PIMs by measuring the effectiveness of such participation and identifying a method to improve it. The policy implication of this study for the PIM global community is that the high effectiveness of public participation entails responsible behaviors among stakeholders. That is, stakeholders should perfect institutional arrangements and cultivate SR-PIMs to reduce game space and expand social effects.

Recycling concrete waste helps reduce the negative environmental impacts of construction activities. Worldwide, concrete recycling rates and available applications for recycled concrete vary widely. A deep understanding of the current status of concrete recycling in individual countries or regions would allow development of applicable and effective strategies for improvement. This empirical research on concrete recycling in the United States consists of two parts: a qualitative study of the legislation, regulation, and practice of solid waste management (SWM) and concrete recycling in 45 states and the District of Columbia, and a questionnaire survey of practitioners’ views of concrete recycling in Ohio and California. Based on the qualitative analysis, the studied states and district were grouped into three categories, representing advanced, average, and below-average SWM practices, with the majority of states having average to below-average practice and so being in need of improvement. The survey results showed that practitioners in the two selected states have positive, consistent perceptions of the practice and benefits of and recommended methods for concrete recycling and identified no major difficulties except for a lack of government awareness and support. This research not only provides an updated understanding of concrete recycling legislation and practice but also offers useful strategies for government and industry to work together to promote concrete recycling.