Journal of Construction Engineering and Management

Firm performance is a crucial concept in business domains. However, an implicit understanding of firm performance may undermine the knowledge derived from quantitative organizational studies because the construct of firm performance is usually operationalized with low reliability and validity. Furthermore, managing professionals, such as senior managers and executives, may also face difficulties in appropriately measuring firm performance in order to accurately examine the status of their companies. The purpose of this paper is to explore the nature of firm performance in construction and find relevant hard evidence for eliminating potential pitfalls. Three distinct types of firm performance are proposed and examined: multidimensionality, dynamism, and comparability. Factor analysis and data envelopment analysis (DEA) are used to address these three issues by using 10-year (2002–2011) financial data of 265 of the U.K.’s largest construction companies. Several critical findings and implications are reached: (1) the result of factor analysis confirms the multidimensionality of firm performance, and these dimensions are interrelated and implicit; (2) the low reliability of selected measures (i.e., most Cronbach’s $\alpha$ values are below 0.7) demonstrates that simply measuring and aggregating firm performance would lead to inconsistency and significant measurement errors in quantitative studies; (3) DEA is superior to simple aggregation of performance measures, and it is also useful for evaluating the longitudinal performance of individual companies (i.e., dynamism) in order to compare with competitor performance (i.e., cross-sectional comparability); and (4) although profitability measures have higher internal consistency reliability than employee and growth measures in representing the overall performance of construction companies, a broader selection of performance measures can help more comprehensive evaluation and then better assist managerial activities. This paper primarily contributes to explicitly and empirically examining the multidimensional, dynamic, and comparable nature of firm performance in construction. It also demonstrates an alternative approach to measuring firm performance in both empirical research and practice.

The project development process aims to deliver the most appropriate roadway project given its context. Past work has shown that significant gains are realized when construction expertise is integrated early and throughout the project-delivery process. The Kentucky Transportation Cabinet has initiated a process that reviews design documents prior to construction to address issues that may result in time delays and cost increases. However, these efforts are not utilizing a systematic review process that would allow detailed documentation of the issues identified and provide a lessons-learned database for future use. The study undertaken classifies the constructability issues that typically impact highway construction projects. This paper first identifies the common constructability categories through a national review and then quantifies the frequency and severity of constructability issues by comment type and category, review year, reviewer, and comment severity. The paper’s primary contribution to the body of knowledge is the determination that constructability issues are dynamic and change over time, there is a need for consistency among reviewers, and that team reviews are more appropriate than a single-reviewer approach.

Nearly every safety management activity is designed around the fundamental and implicit assumption that the workforce is capable of identifying hazards before exposure. Unfortunately, research shows preliminary evidence that construction crews perform relatively poorly with respect to hazard recognition. This may be attributable, in part, to the diverse and dynamic nature of construction work. Consequently, many hazards remain unidentified, uncontrolled, and unmanaged until they are encountered by workers. To advance theory and practice in the area of construction hazard recognition and communication, a large-scale, multiphase research project was conducted with the following objectives: (1) devise a new hazard recognition method based upon the principles of cognitive mnemonics and that promotes hazard recognition skill; (2) build a maturity model to improve hazard recognition performance and encourage hazard communication; and (3) experimentally measure improvement in hazard recognition and communication resulting from the new program. The first two objectives were achieved by using the nominal group technique driven by input from an expert panel of 14 industry professionals from organizations with world-class safety records and an average of 26 years of safety management experience. A new method for measuring the quality of prejob safety meetings was devised in a series of eight face-to-face meetings and teleconferences among the experts over a 1-year period. The null hypothesis that the strategy does not improve the proportion of hazards identified and communicated before the start of construction was experimentally tested with six crews using the multiple baseline testing approach. This is a series of concurrent longitudinal A-B designs that are time-lagged among independent treatment groups. The obtained observations were analyzed using interrupted time series regression models. The results showed that workers were able to identify and communicate an average of 38% of hazards before the intervention was applied and that the new strategy caused a weighted overall level-change improvement in hazard recognition skill of 31% ($p<0.01$). This is the first known quasi-experimental test of a hazard recognition strategy in any industry and one of the first large-scale studies to employ multiple baseline testing with appropriate controls that optimize validity and statistical rigor.

An effective and well-known technique for earlier completion of construction projects is to overlap the project activities that normally would be performed in sequence. Overlapping, often called fast-tracking, is inherently risky because it increases uncertainties and can result in more changes and rework. In order to gain maximum advantages from early project completion, a trade-off between benefits and losses of activity overlapping is required. In this paper, a new model has been developed to (1) explain in detail the mechanism and characteristics of design activity overlapping and (2) formulate and discuss design activity overlapping time-cost trade-off. A qualitative research methodology including interviews and focus groups with experts was used to generate and refine the model. This model contributes to the body of knowledge of construction management by demonstrating (1) how to analyze multipath networks through introducing the multi-predecessor effect and (2) how to analyze concurrent overlapping through introducing the cascade effect. The results of this paper can generate insights for further research to solve the overlapping time-cost trade-off and determine the optimum overlapping degree.

Following an extensive literature review, it was established that professional subjective judgment and regression analysis were the two main techniques utilized for predicting the seismic retrofit construction cost. The study presented in this paper aims at predicting this cost by employing a more advanced modeling technique known as the artificial neural network (ANN) methodology. Using this methodology, a series of nonparametric ANN models was developed based on significant predictors of the retrofit net construction cost (RNCC). Data on these predictors, together with the RNCC, were collected from 158 earthquake-prone public school buildings, each having a framed structure. A novel systematic framework was proposed with the aim to increase the generalization ability of ANN models. Using this framework, the values of critical components involved in the design of ANN models were defined. These components included the number of hidden layers and neurons, and learning parameters in terms of learning rate and momentum. The sensitivity of the developed ANN models to these components was examined, and it was found that the predictive performance of these models was more influenced by the number of hidden neurons than by the value of learning parameters. Also, the results of this examination revealed that the overlearning problem became more serious with an increase in the number of predictors. In addition to the framework proposed for the successful development of ANN models, the primary contribution of this study to the construction industry is the introduction of building total area as the key predictor of the RNCC. This predictor enables a reliable estimation of the RNCC to be made at the early development stage of a seismic retrofit project when little information is known about the project.

Current sustainable construction research has been focused mainly on the design and operation stages of projects. But the execution or production stages have not received much attention. Also, current sustainable and construction management approaches often deal with environmental and production issues separately. In this paper, a lean production tool called value stream mapping (VSM) is used to simultaneously assess environmental and production waste over the execution stage of construction projects. VSM considers the elaboration of maps that assist project managers in diagnosing the current state of production to propose improvements in a future state. While traditional tools deal with symptoms, VSM tackles root problems. This paper reports a case study of the VSM application as a green-lean approach in the construction of a hospital in order to improve its environmental and production performance during the structural concrete work stage. The main contribution of this study is to provide a fully detailed experience of the VSM application in construction, confirming its ability to detect the sources of environmental and production waste, quantify them, and suggest reduction strategies. It also presents the development of a well-established implementation process of the VSM. The case study reinforces the effectiveness of the proposed green-lean approach for improving the sustainable performance of construction projects because it can help to optimize the use of resources and reduce costs, improve quality standards, and minimize the environmental impacts generated by the construction of projects.

Construction industry safety performance is of grave concern to practitioners and lawmakers. Despite a determined effort to improve, the results are still disappointing. Improving the industry’s track record requires an in-depth understanding of the factors that drive risks to individual safety and of how behavior and attitudes can be improved. Construction managers lack knowledge of the safety leadership characteristics, which specifically reduce risk-taking behavior of subordinates on construction sites. This information is presented in this research. A leadership-based safety model consisting of subordinates’ self-reported accident and near miss records were investigated along with leadership considerations and initiating constructs, the construction manager’s safety behavior and attitude profile, and the safety climate characteristics to determine whether any of these factors contributed significantly to a safer construction site. A stepwise regression model was developed to determine key drivers toward the risk-taking behavior of construction workers. Construction managers were also classified by their effective management of safety. Contrary to the postmodern perspective on safety leadership, construction managers who focused on safety standards on-site, ruled with an iron rod, and needled people working with them for greater efforts were more effective at reducing accidents on-site than those construction managers who did otherwise.

The quality of a project depends on the performance of the design team; design faults can be prevented by effective team management. In this context, effective leadership is needed to enable effective team management. The preference for more than one style of leadership is inevitable in complex business life because different styles are contingent on different situated contexts. This paper focuses on determining which of the two leadership styles architects predominantly prefer in Turkey, and whether there are any differences in the preferences of leadership styles between the design and production phases in a construction context. Data were collected through a questionnaire on leadership styles, which was distributed to 40 architects from different design offices in Turkey. The leadership styles are gathered into two primary groups: transactional and transformational leadership styles. Two styles fall under transactional leadership—coercive and authoritative—and four styles fall under transformational leadership—affiliative, democratic, coaching, and pacesetting. The results show that Turkish architects prefer affiliative, authoritative, and pacesetting leadership styles, but when two styles need to be combined, their choices are the affiliative–democratic and affiliative–coaching leadership styles. Within the frame of this research, the leadership preferences of leading Turkish architects are discussed in light of Hofstede’s parameters on Turkish national culture. Within this context, compatibility with the national culture of the leaders’ preferences for these behaviors may affect the overall performance of architectural design teams.

Latino workers in residential construction currently suffer disproportionately high rates of injuries and fatalities compared to Latino workers in commercial and heavy civil construction. The aim of this study is to investigate possible differences in safety culture and risk perception among Latino construction workers across residential, commercial, and heavy civil construction sectors. Analysis was conducted using 218 survey responses from Latino construction workers collected in the Denver metro and northern Colorado areas. Results suggest that Latino workers in commercial and heavy civil construction share more similar perceptions of safety culture and risk than those in residential construction. Specifically, Latino workers in residential construction were more likely to agree with the statements that (1) work productivity and quality have a higher priority than safety and (2) safety rules and safety procedures are difficult to understand and that dangers present on construction sites cannot cause death. This study enhances the knowledge about the safety culture and risk perceptions of Latino construction workers in all three sectors. Study findings support the hypothesis that differences in safety culture perceptions among Latinos may contribute to differences in injury rates across the three sectors. Specifically, perceptions of a less-supportive safety culture may correlate to higher rates of miscommunication and incorrect assumptions that influence decision making, resulting in disproportionately higher rates of injuries and fatalities in residential construction compared to commercial and heavy civil construction. Such research findings are important because they provide a meaningful context and basis for effective construction worker safety interventions in the future.

The construction market around the world has witnessed the growing eminence of construction professional services (CPSs), such as urban planning, architecture, engineering, and consultancy, while the traditional contracting sector remains strong. Nowadays, it is not uncommon to see a design firm taking over the work of a traditional main contractor, or vice versa, of overseeing the delivery of a project. Although the two sectors of contracting and CPS share the same purpose of materializing the built environment, they are as different as they are interrelated. Much has been mentioned about the nexus between the two but little has been done to articulate it using empirical evidence. This study examined the nexus between contracting and CPS businesses by offering and testing lead-lag effects between the two sectors in the international market. A longitudinal panel data composed of 23 top international contractors and CPS firms was adopted. Surprisingly, results of the panel data analyses show that CPS business does not have a significant positive causal effect on contracting as a downstream business, and vice versa. CPS and contracting subsidiaries, although within the same company, do not necessarily form a consortium to undertake the same project; rather, they often collaborate with other CPS or contracting counterparts to undertake projects. This paper provides valuable insights into the sophisticated nexus between contracting and CPS in the international construction market. It will support business executives’ rational decision making for selecting proper contracting or CPS allies, or a proper mergers and acquisitions strategy in the international market. The paper also provides a fresh perspective through which researchers can better investigate the diversification strategies adopted by international contracting and CPS firms.

Interpersonal conflict on the job is identified as one of the top occupational job stressors, strongly linked to a reduction in worker psychological and physical health. In addition, interpersonal conflict has been identified as a determinant of work disability, occupational accidents, and other costs related to reduced quality, loss of skilled employees, restructuring inefficiencies, decreased motivation and productivity, absenteeism, and employee turnover. For the construction industry, studies suggest that construction owners and contractors ranked conflict among construction project participants as the highest factor affecting project cost. It is astonishing, in light of this fact, that no research studies exist which attempt to expose the unmistakable financial cost of day-to-day conflict in the construction industry among project participants at the supervisory and trades level. Therefore, the research question being explored is: What are the triggers and consequences of interpersonal conflict on a construction site and at what financial cost? Using the critical-incident technique, a qualitative research method, 74 construction industry personnel were individually interviewed using a protocol designed to elicit one or more conflict incidents recalled by the interviewee. All interviews were audio taped, transcribed, and analyzed using Nvivo 9 qualitative software. Forty-one of the 86 reported incidents underwent an additional analysis using the time reported and associated labor costs. Based on the key findings, it is recommended that educational opportunities and innovative changes to the construction process could reduce/prevent the incidence of interpersonal conflict on the construction jobsite.

Hot mix asphalt (HMA) is a major construction material used for building roads, airport runways, and parking lots. During HMA construction, a massive amount of volatile organic compounds (VOCs) is emitted from the hot asphalt mixtures, creating a potential health risk to on-site workers. Few studies have quantitatively investigated the constituents and potential health effects of the VOCs generated in HMA pavement construction. This paper presents the results of a study in which air samples were collected at multiple locations and time points of several projects during HMA pavement construction and were subsequently characterized for their chemical compositions and concentrations by using gas chromatography/mass selective detector (GC/MSD). The analysis results are compared with occupational exposure limits mandated or recommended by various agencies. Although the individual concentrations of the identified chemicals were found to be below various exposure limits, their collective effect on human health remains unknown and may not be ignored. This paper contributes to the knowledge of the types and concentrations of VOCs generated in asphalt pavement construction, their potential health risks to workers, and possible mitigation measures.

It may be possible to reduce uncertainty in construction projects by adopting the prefabrication method. In this method, components are produced in factories and transported to the construction site to satisfy installation demands. For successful and effective prefabrication, the project designer and precaster must develop an integrated plan to manage the available resources in a way that satisfies design flexibility, production constraints, and installation demands. Configuring individual building elements and forming building components or modular units will result in employing a higher degree of prefabrication for higher productivity and ease of construction. The production of such complex configurations requires complex molds. To achieve optimization of resources and costs for the precast production of complex configurations, two new ideas have been adopted: namely prefabrication configuration and component groups; these are incorporated into the mixed integer linear programming (MILP) model. Moreover, an integrated plan is developed to efficiently utilize complex molds in production platform by using a mold adaptability matrix. Based on these concepts, an MILP optimization model is developed to adopt appropriate molds and create an optimal production plan. The model is validated by using two examples with different scenarios. The results show that employing the idea of prefabrication configuration and component grouping in production planning for prefabricated structures can reduce total costs by up to 13% compared to the existing planning approach. The developed model should help prefabrication manufacturers better manage their resources and possibly expand their production capacity.

Operational performance in residential construction production systems is assessed based on measures such as average house-completion time, number of houses under construction, lead time, and customer service. These systems, however, are prone to nonuniformity and interruptions caused by a wide range of variables such as inclement weather conditions, accidents at worksites, fluctuations in demand for houses, and rework. The availability and capacity of resources therefore are not the sole measures for evaluating construction production systems capacity, especially when rework is involved. The writers’ aim is to investigate the effects of rework timeframe and frequency/length on tangible performance measures. Different call-back timeframes for rework and their impact on house-completion times are modeled and analyzed. Volume home-building was chosen as the industry sector studied in the research reported in this paper because it is a data-rich environment. The writers designed several experiments to model on time, late, and early call-back timeframes in the presence of rework with different length and frequency. Both mathematical modeling and discrete-event simulation were then used to compare and contrast outputs. The measurements showed that the average completion time is shorter in systems interrupted by frequent but short rework. In other words, a smaller downstream buffer between processes is required to avoid work starvation than those systems affected by infrequent but long interruptions. Early call-backs for rework can significantly increase the number of house completions over the long run. This indicates that there is an opportunity for the mass house-building sector to improve work practice and project delivery by effectively managing rework and its related variables. The research reported in this paper builds on the current body-of-knowledge by applying even-flow production theory to the analysis of rework in the residential construction sector, with the intention of ensuring minimal disruption to construction production process and improving productivity.

This paper presents an analytic network process (ANP) experiment for demolition plan evaluation. An experimental case study on the Warren Farm Bridge demolition project is used to demonstrate the effectiveness of an ANP model to support finding the most appropriate demolition plan. Alternative plans used in the experiment include plans that utilise deliberate collapse, progressive demolition, and deconstruction. The ANP model adopted the same assessment criteria, which were previously used in an analytic hierarchy process (AHP) model for the same evaluation purpose for the case project, in order to further make a comparison between AHP and ANP models with different evaluation results. Further to the conclusion that ANP is a viable and capable approach to demolition plan evaluation, the experiment provides a notably different result, which matches the demolition plan actually used, on the most appropriate solution for the case project in comparison with the AHP model. This study indicates that further practice oriented research is necessary through case studies and model improvement to further validate ANP’s capability to support reliable decision making with regard to its inherent advantage in measuring interrelationships and interactions among evaluation criteria in a multicriteria decision-making (MCDM) model.

The measured mile/baseline method has been widely accepted to quantify labor productivity loss, which is demonstrated by comparing the impacted and unimpacted/lightly impacted portions of the work. Although the distinctions between these portions of a project can at times be identified through a cause and effect analysis, on many projects this distinction is not readily observable. For those projects, researchers and professionals have developed various procedures to implement the measured mile/baseline calculations, but shortcomings in those procedures can result in the failure to objectively identify the baseline. In this paper, a method based on basic statistical techniques is proposed to determine a baseline that represents the contractor’s normal operating performance, thus overcoming many of weaknesses in the existing methods. This paper will provide construction professionals and engineers with an objective approach to determine the productivity baseline, thus aiding in the resolution of labor productivity loss claims. Further, this new method avoids the arbitrary baseline sample size and the possibility of multiple competing solutions in existing methods. A numerical example is included to compare the results using different methods and demonstrate the advantages of the proposed method.