Competency-Based Model for Predicting Construction Project Managers’ Performance

Using behavioral competencies to influence human resource management decisions is gaining popularity in business organizations. This study identifies the core competencies associated with the construction management role and, further, develops a predictive model to inform human resource selection and development decisions within large construction organizations. A range of construction managers took part in behavioral event interviews where staff were asked to recount critical management incidents, decisions, and actions from which their key competencies could be identified. By delineating the sample according to their levels of performance measured against a range of role-specific performance criteria, the competencies defining superior management performance could be determined. These were then used to construct a logistic regression model from which a project manager’s performance can be predicated. The validated results reveal that “self-control” and “team leadership” are the most predictive behaviors of effective project management performance within the framework of the model. The paper explores the potential role and application of the framework to underpin human resource management decision making with regards to recruitment, performance management, succession planning, and resource allocation.     

Development of Lean Model for House Construction Using Value Stream Mapping

Lean construction has recently attracted considerable attention in the home building industry. Lengthy delivery time and significant waste in the construction process have caused many home builders to seek a more effective production model that will increase process reliability, reduce total lead time, and improve quality. However, although housing construction provides the closest analogy to manufacturing, a high level of variability prevents the direct transplantation of lean paradigm and techniques. In collaboration with a local home builder, a systematic approach based on value stream mapping technique is developed in this research to analyze the current process and to formulate a lean production model. The model has four main features: synchronized first-in, first-out lane-based flow, production leveling at pacemaker, work restructuring, and improved operation reliability. A simulation template is built to verify the model and to assist in the development of interim implementation models. This paper presents data collection and value stream selection, current practice analysis, and specific changes proposed for the lean production model.     

Impact of Stress on the Performance of Construction Project Managers

The work of construction project managers (CPMs) is often highly stressful, due to time pressures, and due to the uncertainties and the dynamic social structure involved in construction projects. This study aims to investigate the impact of stress on the performance of CPMs. Correlation analysis and structural equation modeling are employed to uncover the relationships between different types of stress (i.e., objective stress, burnout, and physiological stress) and the work performances (i.e., task performance, interpersonal performance, and organizational performance) of CPMs. Data were collected from 108 CPMs who work in a variety of construction sectors, including prime contractors, subcontractors, developers, consultant firms, and the public sector. Results showed that (1) objective stress reduces the task performance of CPMs while burnout can have a positive effect on it; (2) interpersonal performance is maximized with a moderate level of objective stress (i.e., an inverted-U-shaped relationship between these two variables) and increases in line with the improvement of the task performance of individuals; and (3) organizational performance has U-shaped relationships with both burnout and physiological stresses and is worsened by objective stress. Last, it is suggested to stakeholders that regular reviews of job allocation, stress appraisals, stress management workshops, group or individual counseling, and psychological treatment or physiotherapy be carried out to optimize the stress and the performance of CPMs.     

CBR Revision Model for Improving Cost Prediction Accuracy in Multifamily Housing Projects

For any construction project to succeed, it is very important to accurately estimate the construction cost during the project’s initial stage. This is why there has been much interest lately in cost prediction models that use case-based reasoning (CBR). It has been pointed out, however, that existing CBR-based cost prediction models may yield inaccurate results even though they could survey optimal similar cases, if the number of cases in the case base is not enough. As opposed to the existing CBR-based construction cost prediction models, this study developed a CBR revision model that reflects the “revise” phase of the CBR cycle (retrieve, reuse, revise, and retain) based on nine multifamily housing projects executed recently by “A” Housing Corporation. To verify the developed model, a case study was performed using three case projects completed by “B” and “C” Housing Corporations. The result showed that the prediction error ratio after the Revise (I) phase decreased from 97.44 to 22.58%. This model can be effective when there are insufficient established cases in the case base.     

Neurofuzzy Genetic System for Selection of Construction Project Managers

Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions.     

Selection Model for Delivery Methods for Multifamily-Housing Construction Projects

Selecting an appropriate delivery method that will achieve a project’s objectives and characteristics is one of the most critical factors for the project’s success. A selection model for this study was developed by using actual construction case data in quantitative data analysis methods such as logistic regression, factor analysis, and correlation analysis. The model was developed on the basis of the design-build and design-bid-build methods from various project delivery methods. To validate the developed model, comparative tests were conducted on the selection of the delivery method for multifamily-housing construction projects, which showed that the model resulted in 95.0% accuracy. It is expected that the developed selection model will enable owners to select delivery methods that accurately meet their needs characteristics, project characteristics, and external environments.     

Risk Assessment Model of Tendering for Chinese Building Projects

This paper presents a risk assessment model for tendering of Chinese building projects on the basis of identification and evaluation of the major risk events in the Chinese construction market, investigations and interviews from which the factors inducing the risk events were determined, questionnaires on building projects within China’s borders, and the logistic regression method. The findings show that, to a certain extent, the risk of tendering for projects and the risk of a contracted project can be assessed through analysis of factors such as owner type, source of project financing, existence or lack of past cooperation between contractors and owners, the intensity of competition for tendering, the reasonableness of the bid price, and the degree of support from the contracting company to its projects. The model can serve as a supplementary tool for Chinese contractors in making decisions for project tendering within Chinese borders. At the same time, it is of reference significance for international contractors, enabling them to further understand the risks in the contract market for Chinese building projects.     

Predicting Profit Performance for Selecting Candidate International Construction Projects

International projects are inherently exposed to unpredictable and complicated risk scenarios. To minimize possible losses due to these risk exposures, construction firms have their own procedures or basic tools for selecting potential projects, but they are usually based on the experience and knowledge of the firm’s engineers and decision makers that are often very subjective and lack scientific basis. This paper presents a quantitative profit prediction model for the early stage of an international project as a systematic risk-screening tool that involves the processes of defining, analyzing, and evaluating various profit-influencing risk variables. Various successful and unsuccessful international project cases with respect to profit levels are collected. Then, a scale-based profit prediction model to select candidate overseas projects is developed through factor analysis and a multiple regression analysis. Finally, this paper provides implications for global project management and lessons learned from case studies to improve profitability for international projects.     

Lean Management Model for Construction of High-Rise Apartment Buildings

Execution of the finishing works in high-rise apartment buildings is made complex by the need to customize apartments to the varying requirements and designs of individual clients. The conventional construction planning practice of progressing upward from floor to floor breaks down in the face of the arbitrary sequence in which clients finalize their decisions. The results are long cycle times for delivery of completed apartments and corollary high levels of work in progress, budget and schedule overruns, and general dissatisfaction with the process on the part of the developer, contractor, subcontractors, and the clients. Application of lean construction principles to this problem has led to development of a management model that adopts pull scheduling, reduced batch sizes, and a degree of multiskilling. The main benefits expected are an enhanced ability to provide customized apartments, improved cash flow, and reduced apartment delivery cycle times. The model was first formulated in theory, then tested using a management simulation game and computer simulation, and subsequently, developed for practical application. This paper presents an analysis of conventional practice, the theoretical background to the lean approach, and the specific management changes proposed.     

Assessment with 360° Evaluations of Leadership Behavior in Construction Project Managers

Although the literature documents substantial research on enhancing the performance of construction project managers, one central component has been inadequately researched: leadership behaviors. This study of a major construction company had two objectives: (1) to analyze the differences in leadership behaviors between a top performing group and a control group of construction project managers; and (2) to identify the causal influences for those leadership behavior differences. This paper addresses the first objective. Of 335 construction project managers, 40 were identified as top performers and 40 were selected randomly from the remaining 295 to serve as controls. The final two groups (35 top performers and 33 controls who completed the evaluation) were not significantly different in terms of age, gender, type/amount of formal education, or type of project experience. A 360° leadership evaluation found that the top performers had quantifiably better leadership behaviors than the controls. These findings may indicate a need in the construction industry for a comprehensive leadership culture, including leadership training and development programs.     

Causes of Delay in Building Construction Projects in Egypt

Delay in construction projects is considered one of the most common problems causing a multitude of negative effects on the project and its participating parties. This paper aims to identify the main causes of delay in construction projects in Egypt from the point of view of contractors, consultants, and owners. A literature review was conducted to compile a list of delay causes that was purged based on appropriateness to Egypt in seven semistructured interviews. The resulting list of delay causes was subjected to a questionnaire survey for quantitative confirmation and identification of the most important causes of delay. The overall results indicated that the most important causes are: financing by contractor during construction, delays in contractor’s payment by owner, design changes by owner or his agent during construction, partial payments during construction, and nonutilization of professional construction/contractual management. The contractor and owner were found to have opposing views, mostly blaming one another for delays, while the consultant was seen as having a more intermediate view. Results’ analyses suggest that in order to significantly reduce delay a joint effort based on teamwork is required. Furthermore, causes of project delay were discussed based on the type and size of the project.     

Procurement Routes in Public Building and Construction Projects

This paper deals with procurement routes in public building and construction projects in Norway. Seen from a practical point of view, as well as from a theoretical one, it is important to improve methods for selection of procurement procedure, contract model, and compensation formats. The paper objective is to find out if public owners select a procurement route according to recommended practice. The sources are literature, support material for two software tools for selection of the procurement route, and documentation from 22 public building and construction projects in Norway. According to the literature and the support material for the two software tools, the answer to what is the proper procurement route will depend on the characteristics of each project. The documentation study implies that public owners continue to select the same procurement route as they are in the habit of. They do not consider what procurement route suits each single project, and therefore they do not select the route according to recommended practice. The paper calls for innovation and better supported selection of the procurement route in public building and construction projects.     

Statistical Analysis on the Cost and Duration of Public Building Projects

A probabilistic model is proposed to predict the risk effects on time and cost of public building projects. The research goal is to utilize a real history data in estimating project cost and duration. The model results can be used to adjust floats and budgets of the planning schedule before project commencement. Statistical regression models and sample tests are developed using real data of 113 public projects. The model outputs can be used by project managers in the planning phase to validate the schedule critical path time and project budget. The comparison of means analysis for project cost and time performance indicated that the sample projects tend to finish over budget and almost on schedule. Regression models were developed to model project cost and time. The regression analysis showed that the project budgeted cost and planned project duration provide a good basis for estimating the cost and duration. The regression model results were validated by estimating the prediction error in percent and through conducting out-of-sample tests. In conclusion, the models were validated at a probability of 95%, at which the proposed models predict the project cost and duration at an error margin of ±0.035% of the actual cost and time.     

Integrating Neurofuzzy System with Conceptual Cost Estimation to Discover Cost-Related Knowledge from Residential Construction Projects

Cost estimation during early stage of a building construction project plays an important role for feasibility analysis in the planning and design phase. Traditional knowledge-based approaches suffer an essential difficulty due to resource price fluctuation in the market. This paper presents a hybrid method that integrates the principal items ratio estimation method with the adaptive neurofuzzy inference system for mining of cost estimation data. The proposed method provides exceptional capability for mining estimation knowledge that is difficult to be discovered by traditional knowledge-based approaches. A case study of residential building projects in China is conducted to demonstrate the proposed method. The testing results show that the proposed method does not only achieve high estimation accuracy, but also provide desirable features for estimators, such as explicit fuzzy decision rules and graphical presentations.     

Management of Daily Progress in a Construction Project of Multiple Apartment Buildings

This paper presents the methods used and a case study of a project management system (PMS) to manage daily progress in the construction of multiple apartment buildings in South Korea. A dilemma encountered in previous research in the field of progress management is that efforts to enhance data accuracy cause the data handling workload to soar. A main feature of the method presented by the writers for calculating the budgeted cost work schedule is to allocate the project budget into control attributes, activities, and tasks that are defined in a work-packaging model, according to daily weight value. The method offers enhanced practicability by reducing data-handling workloads while not sacrificing the rationale of progress management. The work-packaging model is designed to enable project managers to acquire and process data for progress management at various levels of detail. The budgeted cost of work performed is measured daily at the tasks level using the earning percentage rate from daily work reports. The implementation of PMS focuses on functions to distribute the budget according to daily weight values and acquire the earning percentage from the daily work report. The PMS was applied to a construction project of 54 apartment buildings in South Korea. The case study of its use shows that company headquarters and managers in the field can acquire data for progress management without additional data-handling workloads, and can analyze the progress daily at various levels of detail.     

Identifying and Assessing Influence Factors on Improving Waste Management Performance for Building Construction Projects

Environmental sustainability has become one of the key drivers for continuous growth in the construction industry. Many project practitioners face challenging circumstances in finding an effective way to prevent pollution and minimize wastes by making the best use of the increasingly scarce natural resources. However, most of these efforts are focused on planning and/or design strategies; therefore, they fail to thoroughly cover the environmental issues based on the construction execution level. Further, there is a lack of quantitative measurement system and management-level guidance. To overcome these limitations, this paper proposes a new methodology that assists project managers to assess the performance level of a project in terms of waste management practice. This study is based on a two-pronged approach. One is the identification of the waste management influence factors that play an important role in decreasing waste and increasing recycled materials on construction sites. The other is the development of an assessment tool to measure the level of waste management performance for a particular project. As a result of this work, 59 factors were identified and an assessment tool was developed based on quantification of these factors. The tool has been proved to effectively measure waste management performance throughout four real-case validity tests. From the industry perspective, this paper contributes to establishing the environmentally sustainable production systems by providing the project stakeholders with an established set of influence factors and with a diagnosis tool for measuring their current performance. Additionally, project owners can use the output of the tool, especially the total index score, as a measure to benchmark the level of waste management for continuous improvement.     

Drivers for Cost Estimating in Early Design: Case Study of Residential Construction

This paper proposes the use of a series of independent variables for an early estimation of the building construction cost of residential buildings. Based on 70 German residential properties, these variables serve as the cost drivers of a project, and the regression model, tested against the 70 properties, has a mean absolute percentage error of 9.6%. When applied to predict the cost of five more properties that were excluded from the 70 in the regression model, the percentage error ranges between–12 and 13%. The identified cost drivers are: compactness of the building, number of elevators, size of the project, expected duration of construction, proportion of openings in external walls, and region.     

Implications of Even Flow Production Methodology for U.S. Housing Industry

Production building in the residential sector is often described as the portion of the construction industry that is most like the manufacturing sector. In modern tract construction in the United States, a small number of models are generally repeated several times in a relatively confined area, using specialized trade contractors to complete each phase of each home. Management of the handoffs between predecessor and successor trade contractors is therefore a critical component in the successful completion of a residential project. In order to bring more reliable planning to this process, a workflow-leveling strategy known as even flow production has come into use in the industry in recent years. Even flow production is a strategy intended to reduce the variability in the workflow for trade contractors in the process, thereby gaining production efficiencies. In practice, different operational definitions are in use. This paper describes a series of simulation experiments to identify the management implications of two common strategies (activity-based versus start-based). A special-purpose simulation template was built for the Simphony environment for this purpose. The pace chosen for the flow of activities was found to significantly affect the speed at which the subdivision was completed. The even flow strategy was found to affect the subdivision completion time only slightly, but to have a significant impact on workflow variability and management effort. Control of the pace of starts of only the first activity exhibited nearly the same degree of variability as if the pace of starts were matched to a sales pace.     

Review of Life-Cycle Assessment Applications in Building Construction

Life-cycle assessment (LCA) has been used to assess product development processes “from cradle to grave” for many years. With the current push toward sustainable construction, LCA has gained importance as an objective method to evaluate the environmental impact of construction practices. A substantial amount of construction-related LCA work has been published recently; however, most of this work has been fragmented and a systematic compilation of this literature has not been undertaken. This article presents a structured review of building construction-related LCA literature, classified under four categories: LCA applications for construction products selection; LCA applications for construction systems/process evaluation; LCA tools and databases related to the construction industry; and LCA methodological developments related to the construction industry. Current challenges for using LCA in construction are discussed and potential areas for future research are highlighted. This review and similar efforts may provide the construction industry and associated researchers the necessary background to make better-informed construction decisions and assist the development of an agenda for further research.