Journal of Construction Engineering and Management

Schedule delays are an unfortunate prevalent occurrence in the construction industry. To clearly visualize, track, and mitigate them, graphical and analytical tools are needed. But traditional bar charts do not clearly show delays, and network charts all but hide them. Neither facilitates side-by-side comparisons of schedule updates. Networks can be converted into a modified slip chart from the aerospace industry, which is particularly adept at analyzing delays. Contributions to the body of knowledge include the ability to communicate schedule information more efficiently with less ink, yet in a time-scaled manner, including lead or lag constraints, performing side-by-side comparisons that immediately reveal float gain or loss versus criticality, rapidly identifying underperforming activities, and scrutinizing delay events and assigning responsibility to project participants. To validate the new approach, a delay example from the literature is reanalyzed to gain insights into schedule performance. Comparing the network conversion with a previously developed linear schedule one indicates that the entire approach provides a single framework to plan and control project schedules, which thus can be called the Unified Diagramming Method.

Relationship quality as a measure of working relationships in construction has been associated with four general attributes of trust, commitment, teamwork, and performance satisfaction. These attributes have been previously explored and identified within New Zealand construction sector. However, much ambiguity remains as to what are the values or preference of parties involved in construction project procurement and how the attributes are traded-off in real decision making processes. Basically how do the industry practitioners judge their relationship quality based on the four mentioned attributes. Data is collected from New Zealand industry practitioners through a conjoint full profile questionnaire technique. Via conjoint and cluster analysis a judgment model for relationship quality is extracted. The overall aggregate conjoint analysis suggests that performance satisfaction is the most important attribute in judging relationship quality in construction activities. The other three attributes also attained a relatively large importance index inferring that all are valuable attributes and contributing to relationship quality. However, by assessing the conjoint measurements and utilities generated at individual level and applying hierarchical cluster analysis different clusters of practitioners with distinct patterns of judgment are identified. The largest cluster had performance satisfaction as their main decisive attribute followed by commitment and teamwork. Conversely the second cluster had trust and teamwork as the decisive attribute with performance satisfaction as the least important and finally the smallest cluster regarded trust and performance to be more decisive. Hence, judgment criteria for relationship quality in construction procurement are not unanimous and diverse perceptions exist as to what is relationship quality; with different managerial implications.

Despite empirical evidence of the effects of the Last Planner System. (LPS), the mechanisms by which it works are less well understood. Its strengthening of the social networks within construction projects implies the possibility of enhancing collaboration using means other than or in addition to the LPS. Inspired by Rousseau’s Social Contract, a new management artefact called the Social Subcontract (SSub) was devised to test this hypothesis. The impacts of SSub and LPS interventions on the workflow in eight residential construction projects were studied using action research over periods from 7 to 16 months. The results provide anecdotal evidence that application of SSub together with LPS improves coordination and workflow more than application of LPS alone. SSub also appears to motivate the general contractor to perform the make-ready process, which otherwise is often not implemented. The research provides new understanding of how the LPS functions. It contributes to industry and academia by relating theory to practice, potentially strengthening the confidence with which practitioners can apply such interventions to improve production flows.

In recent years, noise-related disputes caused by construction equipment have increased, resulting in delays and cost overruns in the construction process. To deal with this challenging issue, passive noise control methods such as soundproof barriers and enclosures have been widely used. However, these methods have a limited effect when used to attenuate low-frequency noise. This research aims to suggest a noise management model and to demonstrate the applicability of active noise control (ANC) as a new approach to supplement the limitations of passive noise control. Simulations were conducted to demonstrate and identify the noise reduction effect by active noise control for construction equipment. The simulation results show that noise cancellation can be highly efficient in the low- and mid-frequency bands below 1,000 Hz and that the reduction effect degraded as the frequency increased. On the basis of the findings presented in this research, an environmental manager will be able to mitigate noise-related disputes and their negative effects by applying active noise control during the construction phase.

This paper reports on an ethnographic-action research study of four-dimensional (4D) based coordination in three utility reconstruction projects. This research shows that implementation of 4D models in planning meetings supports mindful behavior, making stakeholders: (1) sensitive to operational processes, (2) pre-occupied with errors and inaccuracies, (3) resistant to simplifying construction plans, and (4) resilient and aware of process alternatives. By being first in synthesizing 4D implementation and mindfulness literature, this study makes a step toward a more systematic and comprehensive analysis of the impact of 4D on coordination. This study provides a practical contribution by showing that stakeholders in utility projects can use 4D to better anticipate and contain unwanted situations. This helps them tackling coordination issues effectively, and may eventually reduce the overruns and rework in utility construction.

This paper presents practical guidance and resources for use during the construction phase developed by the Construction Industry Institute (CII) Research Team (RT) 304, Sustainability Practices and Metrics for the Construction Phase of Capital Projects. It introduces 54 construction phase sustainability actions (CPSAs) that project teams can use during project execution to prioritize and carry out sustainability solutions. Further, it discusses the results of the sustainability survey on current and future capital project implementation of CPSAs, with a focus on frequency of use and barriers to deployment. By following the guidance provided here for adopting these CPSAs, owners and contractors will be better prepared to implement sustainability actions during the construction phase of their capital projects. This paper’s primary contributions are the identification of construction-related decisions and actions to advance sustainability implementation, the provision of detailed practical guidance for effective application, and the validation of the 54 CPSAs in the catalog based on the frequency of current and likely future application.

Construction labor productivity (CLP) is affected by numerous context-sensitive influencing variables made up of subjective and objective factors, practices, and work sampling proportions (WSPs), which cause complex variability. Modeling CLP is challenging because for any given context, the complex impacts of multiple variables have to be considered simultaneously, without sacrificing accuracy or interpretability. Such challenges are addressed in this paper through the development of a methodology that explicitly represents context in CLP modeling and optimizes context-specific CLP models in order to improve accuracy. In addition, interpretable, fuzzy inference system (FIS)–based, and context-specific CLP models have been developed for the purpose of modeling concrete pouring activity. The performance of the context-specific CLP models is then compared with a generic CLP model, which is developed by combining the context-specific data sets. The results of the investigation showed that the key variables vary between the studied contexts and that the respective context-specific models have better prediction accuracy than the generic one. This study contributes to the body of knowledge in construction project management by demonstrating the essential role of context in the CLP model development process using context attributes, which provide a useful approach for characterizing existing CLP models and facilitate the use and adaptation of existing CLP models in new project contexts. In addition, this study presents a series of highly interpretable, context-specific CLP models to predict labor productivity in various building project contexts.

A major cause of fatal construction accidents is falls from height (FFH). In this study, the Human Factor Analysis and Classification System (HFACS) was adopted and modified to assist in classifying the root causes of fatal FFH accidents in Hong Kong. The characteristics and root causes of the accidents were analyzed using frequency analysis. The associations among the causes were examined using Fisher’s exact test and latent class analysis (LCA). The cases apparently share some common characteristics and certain HFACS factors are closely associated. According to LCA results, the factors in all the cases may be placed into four classes, named as ill planning, violation, hidden hazards created by others, and incapable staffing. Recommendations are made to reduce FFH construction accidents based on the characteristics and root causes. The paper contributes to the body of knowledge in construction management by developing a modified HFACS framework for extracting structured information from construction accident reports, finding the general characteristics and managerial causes behind the FFH accidents, and using LCA to identify the connections among the managerial causes.

Moving the construction industry towards a more-integrated approach to project delivery could improve its overall performance. The aim of this paper is to develop a unified framework for project integration by identifying the critical success attribute and different levels of attribute importance, and by determining if there are major differences among the perceptions of survey respondents depending on their industry role. The survey sample ($N=264$) was composed of industry practitioners in the United States. The framework was developed using the Thurstone Scaling Method of Successive Interval Procedure; In addition, this method was complemented and validated using correlation analysis, cluster analysis, and analysis of variance (ANOVA). According to the perceptions of respondents, 19 of the 45 attributes under study were identified as critical for successfully achieving project integration. Four other categories of importance were identified. There were minor differences found between the perceptions that different project participants had in regard to the importance of the different attributes for achieving project integration, leading to the conclusion that the perceptions of respondents in regard to this matter are very homogeneous within the context of the 45 Integration Attributes.

Construction industry labor productivity is an important metric that provides feedback about industry level trends and improvements. However, labor productivity for the construction industry has historically been elusive to define and determine both qualitatively and quantitatively. Existing research studies have provided different methods to calculate productivity at a variety of levels (activity, project, industry), but none proved universally satisfying. This paper presents a new metric for quantifying productivity that was developed using RSMeans Building Construction Cost Data, which is a source that is reliable, repeatable, and developed from consistent and accurate data sources. The metric was developed using labor and cost information from a sample of typical construction activities. The study results showed a slightly sporadic, but consistent productivity decline in both output per labor hour and per dollar cost from 1990 through 2008. Other metrics were selected from existing research studies and sources for a comparative analysis against the new metric, which revealed varying trends across metrics on the basis of varying input data and sources. The paper presents the new metric, which has value in that it allows construction professionals to analyze industry level productivity by means of a generally used and consistently published reference manual.

In the field of construction, indoor localization of mobile construction resources remains a universal challenge. Although discussions have focused on the tracking accuracy and affordability of indoor localization technologies, few efforts have focused on practical criteria such as ease of use, latency, and data visualization and remote sharing. To close this gap in knowledge, this study introduces a building information modeling (BIM) and cloud-enabled radio-frequency identification (RFID) localization system. The system consists of three main components: the passive RFID localization system, the BIM visualization system, and the cloud computing system. The proposed system is tested in a full-scale implementation on an actual construction site. The test was designed and conducted to evaluate the localization accuracy, data latency, and real-time data processing and visualization for remote monitoring. A comprehensive analysis is made of various practical issues based on the test results and panel discussion. The findings in this study indicate that the BIM and cloud-enable RFID indoor localization solution has a great potential in practical applications such as site security control, safety management, asset management, and productivity monitoring.

Highway work zones often cause traffic congestion, resulting in increased road-user delays and vehicle emissions. These negative impacts of highway work zones can be minimized by a number of mitigating measures such as reducing the length of work zone segments, using the shoulder temporarily for traffic, and working during low-traffic nighttime hours. These work zone layout measures, however, cause an increase in highway construction cost. Accordingly, these tradeoffs between reducing work zone delays and minimizing construction cost need to be analyzed to establish an optimal balance between these two critical and conflicting objectives. This paper presents the development of a novel multiobjective optimization model for highway work zone layouts that is capable of generating optimal tradeoffs between minimizing traffic delays and construction cost. The model was developed in three main phases: formulation, implementation, and performance evaluation. First, the model was formulated to (1) identify all relevant work zone decision variables that affect mobility and cost, (2) model the two objective functions of minimizing work zone delay and construction cost, and (3) represent all practical constraints. Second, the model was implemented using a genetic algorithm to perform the multiobjective optimization computations and enable generating optimal tradeoffs among the two objectives in a single run. Third, the performance of the model was evaluated using an application example of a highway work zone. The results of the performance evaluation phase illustrate the novel and unique capabilities of the model in optimizing work zone layout parameters and generating optimal tradeoffs between minimizing traffic delays and construction cost.