Journal of Construction Engineering and Management

A significant number of studies have found that the emissions, production, and expenses of earthmoving operations are dependent on numerous variables. However, there has been less evidence that has explored the implications of alternative loading practices on emissions and production performance to date. This study investigates the impact of adopting alternative loading practices on emissions and production in excavator-truck operations to close the knowledge gap. In this paper, Monte Carlo simulation was applied to compare the performance of double-sided, fractional, and multiplier loading strategies with regular single-sided loading. The emissions, production, and optimality of the fleet size in terms of emissions per production were demonstrated using case-study data from a cut-and-fill method on a residence construction project. The results implied that different loading practices lead to different effects on production and fuel use, affecting the emissions per production. The findings of this study also revealed that service time had been shown to significantly influence the emissions per production for the changed loading practices. Hence, there is a promising opportunity to improve productivity by keeping a minimum service time in earthmoving operations. The results revealed from this paper would benefit those who are working on reducing or managing construction emissions. The significance and novelty of this research are that it presents an environmentally friendly technique of designing and controlling earthmoving operations by employing alternate loading practices in excavator-truck operations.

Building material inventory is routine work of the material delivery process at most construction sites. Manual counting is the conventional manner of taking inventory; however, it is subjective, time consuming, and error prone, especially for densely stacked material. This study proposes a new and accurate counting model based on YOLOv3 to automatically and efficiently count dense steel pipes by images. To promote counting models’ development and verification, a large-scale steel pipe image data set including various on-site conditions was constructed and publicly available. The proposed model was observed to be superior to the original YOLOv3 detector in terms of average precision, mean absolute error, and root-mean-square error based on the steel pipe data set. Furthermore, several improvement measures, split into bag of specials and bag of freebies, were introduced to enhance counting performance further and verified by an ablation study. Comparisons with other popular detectors demonstrate the effectiveness and superiority of the proposed model for counting densely stacked steel pipes. The counting model can be easily extended for other dense material counting and integrated into mobile devices for practical application at construction sites.

The Last Planner System (LPS) establishes short cycles of planning and control, comprising LP, the make-ready process, short-term planning commitments, identifying reasons for noncompletion, and implementing corrective actions. Most LPS research has covered longitudinal case studies, but quantitative transversal research is needed to determine the impact of key LPS processes in performance. The researchers aimed to determine the relationships between LPS components and project performance. Twenty three metrics were established to evaluate six components and 253 possible correlations between them. The authors assessed information from 255 projects and found 131 projects, in five categories, with sufficient information to construct the metrics. Two categories had sufficient sample sizes, which produced a sample of 71 high-rise building (HR) and 28 industrial construction (IC) projects. Each sample was assessed separately to test the correlations, and the project categories were compared to determine statistically significant differences. Then, the projects were classified according to their schedule performance outcome, using a clustering algorithm to find differences between high- and low-performance projects. Statistically significant correlations between the six components were found in both samples, six metrics presented statistically significant differences between high and low performance in HR projects and one in IC projects.

Integrated Project Delivery (IPD) is an innovative procurement approach through which the client, designer, and contractor work together under one contract as a team. While an integrated team is expected to be able to create extra value for the project, this practice may bring new risks if not all team members are committed. The slow uptake of IPD may possibly be due to the insufficient understanding of the risks involved, especially those hidden risks associated with inappropriate integration practice. This study identifies critical risks in IPD projects, and investigates if risk criticality can be alleviated by having previous or future partnership between IPD partners. By collecting the views of construction professionals on the level of criticality of general risks and IPD-specific risks, it is found that (1) most highly critical IPD project risks are borne from multidisciplinary teams of poor integration quality, inaccurate target costs, or unreasonable cost estimates; and (2) having future cooperation intent can significantly alleviate the criticality of certain IPD risks, whereas no effect of previous partnership was found on risk criticality. This study contributes to a growing body of knowledge on IPD by providing insight into the effect of new and general risks on IPD project outcomes in particular and clarifying the role of previous/future partnership in risk management. This study suggests active involvement of client and contractors in the design of IPD and signals future cooperation intent to IPD partners during the project process.

External management consultants have been increasingly employed by owners of complex construction projects (CCPs) to foster management innovation and improve their organizational capability. However, the dynamics of the owner-consultant collaboration process in such projects are still unknown. To bridge this gap, this paper explores the roles of external consultant involvement in fostering management innovation and developing an organizational capability in CCPs. Based on survey data collected from 102 such projects across different types in China, the partial least square-structural equation modeling analysis results uncover the positive effect of external consultant involvement in creating management innovation and building organizational capability. In particular, the mediating role of management innovation is identified in the exploration and transformation learning processes with external consultants involved. The findings of this study provide a novel explanation for the creation of management innovation in CCPs through external consultant involvement and useful guidance to project owners to better identify and utilize external consultants in the future.

The building sector has a major economic, environmental, and social impact on society; hence, it is crucial to promote sustainable construction practice. The facade is one of the largest main components of a building, which could strongly contribute to the sustainability performance for the whole building. Previous studies started defining tools to assess facade sustainability, although relevant indicators were dismissed or, if considered, they were rather subjectively quantified. Likewise, most existing tools omit stakeholder satisfaction in the assessment process for optimal facade systems. In this regard, this paper presents a new systematic approach based on the Integrated Value Model for Sustainable Assessment (MIVES) for holistic sustainability assessment of building facade systems by integrating stakeholders’ satisfaction in the decision-making process. To this end, for the first time to the authors’ best knowledge, the most representative and discriminative indicators for quantifying facade sustainability were identified to define a new approach to minimize subjectivity in the decision-making process and, consequently, to ease the task of decision makers when choosing and designing facade alternatives for new buildings and rehabilitation. This approach is validated and initially applied to assess the six most common residential facade systems in Barcelona, Spain. Results indicate that these building elements have low to medium sustainability performance.

The road maintenance workload for transportation agencies increases every year. To maintain roads effectively, one contracting method state Departments of Transportation (DOTs) use to outsource is performance-based contracting (PBC). However, state DOTs are having problems identifying the execution issues with PBCs. This study prepares a framework for execution of the PBC method for chip seals (one of the highest expenditure activities for most states), to help guide state engineers to effectively execute the contracts. This framework was developed by conducting a Delphi study with state engineers. The study found five reasons for selecting PBC chip seal; five performance measures; a range of incentives/disincentives to be provided; and the method of PBC team training. For the procurement phase, this study identified the five personnel to be included in the procurement team, as well as the contract duration and best contractor selection method. Similarly, for the contract implementation phase, the five key personnel to be included in the project implementation team, the best way to manage traffic, the timeliness to fix defects, responsibility, the frequency to complete quality assurance work, and the mobilization payment method were identified. As the primary contribution, this paper identified the critical factors of PBC contract life-cycle phases and developed a framework that will provide an easy-to-follow guide to execute PBC contracts to state DOTs. This study has a limitation with its sample size in the Delphi study due to a lack of experience of state DOTs in using the PBC method. The authors recommend conducting similar studies for other activities (cleaning, culvert cleaning, etc.) with larger sample sizes.

Modularization is a well-known approach that can potentially mitigate many of the current construction industry’s challenges including, for example, poor productivity, shortages in skilled labors, and poor safety performance. Recent studies have shown that contractual risks and disputes are still considered one of the top factors affecting the performance of modular processes. Many research efforts have analyzed disputes and their causes in the construction industry, but none of them addressed the unique and complex sources of disputes that could be associated with the use of modularization. The goal of this paper is to investigate dispute causation in modular construction projects. To this end, this study adopted an integrated multistep analytical research methodology. First, the authors collected and analyzed a total of 39 publicly available law cases of modular construction disputes in the US. Second, social network analysis was performed to identify the most common causes leading to disputes in modular construction projects. Third, spectral clustering was conducted to group the dispute causes based on the strength of their interconnectivities. Fourth, association rule analysis and Apriori algorithms were used to identify key associations of causes that would most likely trigger modular construction disputes. The results indicated that payment holds and delays, delay in project completion, poor communication among the project stakeholder, and lack of collaboration between various trades are common causes of disputes in modular construction projects. Also, as the authors were able to cluster the 40 identified causes of disputes into four clusters, the most significant associations of dispute causes were determined and quantified within each identified cluster. Further, the findings reflected that modular construction disputes are mostly triggered by the occurrence of multiple causes rather than by just a single cause. This paper adds to the body of knowledge by helping practitioners manage and control sources of disputes in modular construction projects. This should help to minimize dispute occurrence during modular processes, and thus maximize capitalization on modularization benefits. Ultimately, the outcomes of this paper should direct researchers and industry practitioners toward the contractual aspects of modularization that require appropriate adjustments and revision so as to better account for the uniqueness of modular processes within today’s complex construction industry.

Off-site manufacturing (OSM) offers a wide range of benefits to the construction industry by saving time, reducing waste, being an environmentally friendly solution, and providing a much safer onsite environment. However, safety management of OSM has become a concern due to the worker-related safety issues, which increase the safety incidents in off-site factories. However, research on the safety of OSM activities within a factory environment are still very limited. Therefore, this study aims to examine the interrelationships among worker-related safety factors and their influence on OSM safety performance. A probabilistic model based on Bayesian networks (BNs) to assess the influence of worker-related safety climate factors on OSM safety performance is utilized in this research study. A comprehensive review and evaluation of causal safety factors with the support of a questionnaire survey with OSM industry practitioners are the basis for this BN model. The proposed BN model is then verified by conducting a sensitivity analysis such as tornado diagrams and derivatives of sensitivity. The established model presents probabilities associated with different states of safety factors and identifies the interrelationships among worker-related safety climate factors and OSM safety performance. The research findings show that improvements in management safety response, coworkers’ safety values and practices, and quality of training exert a greatest effect on the safety performance. Analysis further indicates that a balance between safety and production significantly affects workers’ safety knowledge. This study contributes to the OSM safety domain by offering an effective tool to predict safety performance.

With digital technologies providing sustainable avenues for addressing construction problems, electronic procurement systems (EPS) offer viable solutions for transforming construction procurement processes in projects. However, the uptake of EPS has not been as apparent as it should have been due to the complexities of barriers and strategies. Unlike previous studies that focused narrowly on either barriers to or strategies for EPS use, this study aims at examining EPS barriers and strategies from various countries to provide a more comprehensive global perspective regarding EPS implementation. Through an expert survey, 94 procurement experts from different countries evaluated the influences of these barriers and strategies. Subsequently, factor analysis was used to objectively cluster the results from the survey. In effect, six groups of barriers and three groups of strategies were identified. The barrier groups were related to technological usability and evolution, security and unsupportive environment, culture, infrastructure, unethical practices, and financial and skill. For strategies, the groups were related to organizational dynamics, industry technology ecosystem, and innovation adaptation mechanism. Regarding the developed and developing economies categorization, the rank agreement analysis results showed several degrees of disparities and consensus on the influences of barriers and strategies to EPS implementation across the two contexts. In effect, the contextual variabilities in the influences of these barriers and strategies across the two economic contexts are provided for researchers and practitioners to improve their efforts in promoting EPS. This study contributes to EPS knowledge by providing insights on the contextual dynamics of critical barriers and strategies from the developed and developing economies contexts.

Choosing between different compensation strategies is one of the major concerns of owners in construction contracts. This paper is aimed at examining the choice between behavior-based and outcome-based payment types through the views of practitioners from construction projects with variables defined by agency theory. The study adopts the analysis of data through the Delphi technique supported by factor analysis and multinomial logistic regressions to test the paper hypotheses. The paper shows that in projects with a high level of contractor risk aversion, outcome uncertainty, task programmability, and information systems, cost-plus-fee payment is more attractive than lump-sum payment. Conversely, the paper shows that in projects with a high level of goal conflict and outcome measurability, lump-sum payment is more attractive than cost-plus-fee payment. The results demonstrate the practical usefulness of agency theory in the arena of construction management. The contribution of this paper lies in providing insights into choosing an appropriate contract payment type based on agency theory parameters.

Probabilistic and nonlinear models have been used to accurately model various phenomena in asset management systems (AMS). With a commonly adopted framework using Monte Carlo simulation and heuristic algorithms, AMS proposed in the literature aim to maintain the functionality of assets in their life-cycle by optimally allocating limited resources to different intervention actions. However, due to their high computational costs, upscaling complex project-level AMS to a multitude of assets currently is far from practical. To address this gap between the literature and the practice of project-level AMS, this paper presents a new machine learning–based methodology to estimate (near-)optimal intervention timings which usually are derived by optimization algorithms. To illustrate, an ensemble of random forests models was trained on optimal maintenance timings of more than 1.6 million semisynthesized bridges. The trained model yielded optimized maintenance, rehabilitation, and reconstruction (MRR) plans with greater than 95% accuracy on the test set and greater than 89% accuracy on more than 4,600 highway bridges in Indiana, and did so 6 orders of magnitude faster than the conventional framework of complex MRR optimization. Practitioners can adopt the proposed methodology to enhance their decision-making systems, obtain optimal maintenance plans without sacrificing complex and accurate models, and take another step toward sustainability objectives.

Construction businesses expanding internationally often need to devise corporate social responsibility (CSR) as an indispensable component of their competitive strategies. Companies will customize their CSR programs to be in line with host countries’ institutional environments. Meanwhile, this customization will be unavoidably influenced by the institutions in their home countries. This research aims to explore whether the institutional distance between home and host countries matters to CSR, in particular, its related environmental and social practices. Data regarding the CSR practices in host countries are extracted from CSR/sustainability reports by using content analysis and text mining. Logistic regression models are then applied to test the roles of institutional distance and host country contexts on the two types of CSR practices. It is found that the institutional distance has no impact on environmental practices in host countries, but the embedded contexts of host countries positively affect the practices. It is also found that the institutional distance is positively correlated with social practices; however, the positive relationship is less pronounced when the host country’s development level is higher. The novelty of this research lies in considering both host countries’ contexts and the institutional distance. The findings offer companies new insights on how to engage in environmental and social practices and develop CSR strategies in international construction markets.

Critical decisions about whether and how to integrate sustainability measures into the life cycle activities of green buildings are made in the early architectural design phase. To this end, researchers have advocated the use of various green building simulation technologies (GBSTs) to perform sustainability analyses to support integrated architectural design processes, cross-disciplinary communications, and evidence-based decision making. However, the adoption of GBSTs in architectural design practices remains limited. Building on the technology acceptance model, this paper investigates the determinants and mechanisms that influence the adoption of GBSTs in practice. Empirical data collected from architectural designers in Taiwan through qualitative interviews and a quantitative survey show that perceived usefulness is a strong predictor of designers’ intentions to adopt GBSTs. Job relevance, result demonstrability, compatibility, and competitive advantage are also important determinants of GBST adoption. Practical recommendations are offered to encourage greater adoption of GBSTs in architectural design practices. Theoretically, this research extends the technology adoption literature in the architecture, engineering, and construction (AEC) industry by broadening and deepening the understanding of context-specific determinants of GBST adoption.

There is growing interest in the use of offsite manufacturing (OSM) in the construction industry despite criticism that some offsite approaches used by housebuilders do not offer real improvement compared with their onsite counterparts. Quantitative performance measures from previous studies are based on conventional onsite methods, with little attention paid to the performance and process improvements derived from various OSM methods. In response, a case study was conducted based on two OSM methods using standardized and nonstandardized processes for the production stage of a factory-manufactured wall panel. Value system analysis and root cause analysis using the 5Whys method was adopted to evaluate possible improvements in terms of process waste. The study reveals that OSM production methods that replicate site arrangements and activities involving significant manual tasks do not necessarily provide a marked improvement over the conventional onsite method. Thus, there is a need to reevaluate the processes involved to eliminate such embedded process wastes as non-value-added time and cost, and to consider automating critical activities. The analysis adopted in this case study provides measurable evidence of the performance gained from having a structured workflow over a nonstructured workflow. It also reveals how process wastes are generated in the production process of wall panels offsite.

The architecture, engineering, and construction (AEC) industry globally has a long history of prudently adopting novel technologies to improve products and services. Yet the rapid development of digital technology currently taking place is threatening to produce a more disruptive inflection, or substantial jolt. This paper explores the state of readiness of the AEC industry for such anticipated transformation. We illustrate our conceptual arguments with evidence from an explorative study across a sample of AEC organizations in Australia. At the core of this paper, we offer six provocations that highlight what we consider major challenges for the AEC industry—across multiple levels of analysis—related to the increasing role of digital technology. We then turn to lessons learned from other industries in order to propose a framework consisting of four leadership thinking schemas to enable digital transformation readiness: future thinking, strategic thinking, capability thinking, and experimental thinking. For these four schemas, we present practices and initiatives that may help AEC firms to better adapt—or to proactively create and shape a sustainable future.

The need for manual semantic annotation to domain-specific building information modeling (BIM) models limits the application of BIM technology in various architecture, engineering, and construction fields. BIM semantic enrichment refers to a procedure that can identify missing information and improve interoperability across different applications. The need for semantic enrichment of BIM models is often emphasized in the literature; however, few studies have shown the potential of semantic enrichment approaches in dealing with problems in real-world cases. To provide an empirical demonstration in the practice, an example of BIM semantic enrichment for supporting underground garage compliance checking is selected as a case study. Geometric reasoning is one of the effective approaches to enhance semantic information in BIM models to support real-world applications. In this study, a computational geometric approach is developed to demonstrate how geometric information can be extracted and used to infer missing semantics in underground garage BIM models. A prototype system is developed, and real underground garage BIM models are used to validate the effectiveness of the proposed approach. The contribution of this study is that it provides the detailed implementation of performing geometric reasoning to enhance BIM semantics in real-world cases. Additionally, the findings of this case study show that the proposed computational geometric approach has the potential to enhance the semantics of BIM models to support decision making in real-world engineering problems, and the developed algorithms can be used to automate the compliance checking process of the underground garage.