Journal of Construction Engineering and Management

The level of customization currently being built by U.S. industrialized homebuilders, including modular and manufactured homes producers, is characterized and the impacts of customization on plant operational performance, and employee and customer satisfaction are examined. To assess the current state of the industry, including the level of customization offered and operational performance, a large-scale survey of industrialized housing producers was conducted. Results revealed that in general, the operational performance of the surveyed homebuilders deteriorates with an increase in home customization. Producers that offer more customization tend to be less efficient in their use of manufacturing space and less efficient with their labor. Results also show that a higher level of customization leads to higher employee satisfaction (lower labor turnover) and leads to lower customer satisfaction. However, those producers that had active quality programs (e.g., continuous improvement) had higher customer satisfaction ratings. Therefore, industrialized housing manufacturers have not reached the ideal of mass customization (i.e., effectively managing the production complexities of customization) and are paying a price for offering more choices to their customers. Lessons learned from this study and mass customization enabling factors are discussed.

This study establishes the chemical properties of blended cement pastes to understand the effect of marble and brick powders on cement chemical properties. Thus, this paper extends knowledge of construction material handling and practices. Marble and brick powder and CEM I 42.5N cement clinker have been used as materials in this work. Blended cements have been prepared with the addition of CEM I 42.5N cement clinker for marble or brick powder at the ratios of 6, 20, 21, and 35%. CEM I 42.5N cement has been used as reference cement. A total of 24 cement paste samples were mixed with blended cements and reference cements according to the Turkish standard EN 196-1, and they waited in water for 7, 28, and 90 days. The chemical properties of blended and reference cement pastes were determined through the Turkish standard EN 196-2, known as wet analysis, at the 7th, 28th, and 90th days of the curing period after they were dried and ground in the laboratory. The results show that the chemical properties of cement pastes could be enhanced with the industrial wastes that have been stored on agricultural land instead.

Due to the mounting complexity of sustainable, high-performance building projects, there is a consequent increase in the requirements for optimized solutions and multidisciplinary teams. Research suggests that project delivery attributes have an important influence on project outcomes of such buildings, especially on cost growth and the level of sustainability achieved. However, the extent of the influence of project delivery attributes and critical patterns of project delivery features that affect project outcomes has yet to be determined through rigorous research. Recognizing this need, this study adopts the defined evaluation metrics from recently completed research to descriptively show the extent to which the relationships and influence of project delivery attributes, such as owner commitment, team integration, and contractual relationships, affect project sustainability goals. The study collected data from 12 green office buildings in the United States. To maintain the quality, validity, and reliability of data, two to three participants (including the owner, constructor, and designer) were interviewed from each project. The findings suggest that the strong owner commitment toward sustainability, the integration in the delivery process by an early involvement of the constructor, and the early inclusion of green strategies are attributes crucial for the delivery process and can have altering effects on project outcomes, especially on sustainability goals.

Recent research on unbalanced bidding models has identified both the benefits and the risks generated from different prices applied to the component items of a construction project. It has also been proposed that modern portfolio theory (MPT) be used as the technique by which to trade-off the conflicting objectives of maximizing the expected profit and, at the same time, minimizing the risk. The MPT methodology has previously been found to provide contractors with a technique by which they can identify and sift out all of the efficient item-price combinations, such that they need not suffer the consequences of deciding upon any substandard inefficient pricing combination. The use of MPT still leaves contractors with a wide range of choices. This paper introduces and applies microeconomic techniques [namely cumulative prospect theory (CPT)] to narrow these choices down to only one optimal choice. CPT serves to equate different return-risk alternatives to find the one set of item prices that will provide the optimal outcome in light of the contractor’s risk profile. The paper concludes by applying and evaluating this technique, on a small hypothetical project. Results show that a contractor with such a profile is able to identify prices that will generate an expected mean profit of 150%, more than they could accomplish by way of balanced pricing.

Little systematic knowledge is available on the dynamics of rework in complex hydrocarbon (oil and gas) projects, despite the fact that they frequently exceed budget and schedule projections by more than 10%. To better understand pertinent issues associated with rework, twenty three in-depth interviews were undertaken with personnel from a major international oil and gas operator. The interviews sought to elicit deep individualistic knowledge about the dynamics of design changes, errors, and omissions that contributed to rework in four off-shore projects that they were involved with. Akin to previous research, the factors of poorly defined scope, unrealistic schedules, design changes, and coordination problems were identified as contributors to rework. A significant difference from previous studies, however, was that rework was expected and considered a norm. The issue at hand therefore related to ‘when and where’ rework would materialize, because it was considered that the implementation of front end loading, audits, and reviews would capture any design flaws that may have materialized. The potential revenue that could be generated from earlier extraction and production of oil and gas outweighed any rework costs that were likely to be incurred. A systemic model representing the underlying conditions that contributed to rework was developed from the findings to provide managers with the necessary insights about the interdependencies and behavior between key variables. The developed model can be used to identify future areas in which rework prevention and mitigation strategies should focus on in future projects.

A negotiation is doomed if a negotiator loses the desire to continue with the discussion, and it is described as withdrawal (WA). Construction project disputes are content-specific, with resolution options governed by the contract, thus fitting neatly with the rationality framework. Nevertheless, failure in construction project dispute negotiation (CPDN) is not uncommon. The prospect of having a successful negotiation is hampered when behavioral factors creep in. This study aims to uncover the underlying factors affecting WA in CPDN from a behavioral perspective. The behavioral tradition of negotiation study identifies three behavioral primers: motivation (task versus relation), cognition (emotion versus rationality), and personality (competition versus cooperation). With these, a relationship framework between WA and the three behavioral primers is proposed. With data collected from construction professionals in Hong Kong, the relationship framework is subjected to a confirmatory analysis by structural equation modelling (SEM). Emotion under the cognitive domain is found to be the most critical contributor to WA in CPDN. This finding reinforces the fact that negotiators should be good at the technical aspects of the dispute subject matter and be emotionally stable.

Construction scheduling techniques often generate schedules that cause undesirable resource fluctuations that are inefficient and costly to implement on site. This paper presents the development of a novel multiobjective optimization model that is capable of measuring and minimizing these undesirable resource fluctuations to maximize resource utilization efficiency and minimize project duration while complying with all precedence relationships and resource availability constraints. The model incorporates three main modules: (1) a startup module that calculates lower and upper bounds for the model decision variables; (2) a scheduling module that generates practical schedules and evaluates their performance; and (3) a multiobjective genetic algorithm module that searches for and identifies optimal schedules. The model is integrated in a commercially available software system to facilitate its use and adoption by construction planners. An application example is analyzed to illustrate the use of the model and demonstrate its new and unique capabilities in generating optimal trade-offs between maximizing resource utilization efficiency and minimizing the duration of construction projects.

Radio frequency identification (RFID) technology is an effective automated data collection technology that has been adopted by a number of industries. Researchers and practitioners in the construction industry have explored and implemented RFID technology extensively in the past decade. To provide a holistic examination of this implementation, this paper first presents the state of the art of RFID technology and then demonstrates 39 academic research projects and construction industry use cases. On this basis, the paper analyzes the interaction between academia and industry, which reveals that this interaction is not fully utilized and that research is not the major driving force of the industry adoption. Suggestions on how to strengthen this interaction are provided. The paper also argues that successful adoption of RFID technology in the construction industry is not realized yet, and accordingly calls on more integrated RFID technology implementation from a building life-cycle perspective. The paper presents the potential benefits of such integrated implementation, including data consistency, decreased investment, and better standards and interoperability, and then identifies research questions to advance the implementation of RFID technology for building life-cycle management.

The significant advancement in digital imaging and widespread popularity of digital cameras for capturing a comprehensive visual record of construction performance in the architecture, engineering, construction, and facility management (AEC/FM) industries have triggered an extensive growth in the rate of site photography, allowing hundreds of images to be stored for a project on a daily basis. Meanwhile, collaborative AEC technologies centering around building information models (BIMs) are becoming widely applied to support various architectural, structural, and preconstruction decision-making tasks. These models, if integrated with the as-built perspective of a construction, have great potential to extensively add value during the construction phase of a project. This paper reports recent developments from research efforts in (1) automated acquisition of as-built point-cloud models from unordered daily site photo collections and geo-registration of site images, (2) automated generation of four-dimensional (4D) as-built point-cloud models, and (3) semiautomated superimposition of the integrated as-built model over 4D (three dimensions plus time) BIMs to generate integrated 4D as-built and as-planned visualizations. The limitations and benefits of each modeling approach, the motivations for development of 4D augmented-reality (${\mathrm{D}}^4\mathrm{AR}$) environments for integrated visualization of as-built and as-planned models, the perceived and observed applications, and the benefits in seven case studies are discussed. Not only does a ${\mathrm{D}}^4\mathrm{AR}$ model visualize construction processes and performance deviations, it can also be used as a tool for automated and remote monitoring of progress and safety, quality control, and site layout management, and enables enhanced coordination and communication.

In the construction industry, on-site labor is one of the most variable and costly factors that affect project profits. Because of the variable nature of construction labor and its correlation with profits, construction managers require a comprehensive understanding of the activities of workers on-site. For project success, it is obviously important that workers are spending the majority of their time installing materials that advance the project. This material installation time is known in the construction industry as “direct-work” or “tool time.” Continuously improving the direct-work rate through the life of the project is critical to project success, and yet no workface assessment method exists in the literature to provide (1) a detailed description of worker activities; or (2) a continuous productivity improvement process to help management identify productivity inhibitors affecting site labor, develop a plan to reduce or eliminate these issues, and measure improvements as a result of these changes. In response to this need, this research focused on the development of a workface assessment method called activity analysis. Activity analysis is a continuous productivity performance improvement process, which efficiently measures the time expenditure of workers on-site and identifies productivity inhibitors that management must reduce or eliminate to provide workers with more time for direct-work activities. Six case studies were conducted to verify the feasibility of the activity analysis process. Further, cyclical data from two major construction firms, including 26 project data points, were collected and analyzed to statistically validate the hypothesis, which in the past was supported by limited numbers of case studies, that activity analysis can improve direct-work rates. The research concluded that activity analysis, as a continuous performance improvement process, is feasible and when continually applied to a construction site, can significantly improve direct-work rates through the life of a project.

Mini-excavators ($m$-excs) are commonly used in construction and allied industries to maximize productivity and reduce costs, but they present considerable health and safety hazards, the greatest of which is arguably their tendency to overturn. Assessment of $m$-exc stability is not prescribed in recognized standards and is primarily achieved using a “tilt-test.” The tilt-test has considerable limitations and its application in practice varies, indicating that procurers have incomplete information on selecting the most stable (i.e., safest) machine. The purpose of this study was to compare three types of $m$-exc stability tests (i.e., tilt, operational, slewing) and contrast these to determine the most reliable testing regime. From these results, an innovative mini-excavator procurement model is proffered that incorporates the assessment of machine stability and practical selection criteria. The effect of the study to date (and for the future) on encouraging original equipment manufacturers to engender innovative $m$-exc design and production is presented; and a call for the development of a new stability testing standard is made.

Despite the significant amount of work in recent years to better understand the implementation of technologies in project-team settings, the research community still lacks an in-depth understanding of the social dynamics around the implementation of a new technology to support decision-making tasks at the operational project-team level. To increase this understanding, this paper presents a longitudinal case study about the implementation of a four-dimensional (4D) decision support system by a project team. This paper provides a grounded analysis of the observations from this study. The analysis shows that the implementation of the 4D system was characterized by a constant negotiation about the goals of the implementation and the process of how to best implement the 4D system. During these negotiations actors applied their technical and project task related knowledge to analyze, understand, and influence the goals and the process of the implementation. This knowledge, however, changed throughout the implementation and hence, the goals and processes of the implementation also changed frequently. On the basis of these findings, this paper suggests that construction management theory and practice should account for the possibility of shifting goals and processes during technology implementations.

The emergence of the effective management of knowledge resources as a key factor in gaining and sustaining competitive advantage presents new challenges to construction firms. Evaluating knowledge management practices is considered one of the most important challenges facing firms in today’s business environment. This paper proposes a model for evaluating the knowledge management practices of construction firms. The proposed model incorporates knowledge management concepts and multilayer perceptron (MLP) neural networks to construct an importance–comparative performance analysis (ICPA) map, a simple visual tool that can provide powerful diagnostic information to executives of construction firms. The model evaluates a firm’s knowledge management practices, identifies its competitive advantages and disadvantages in each knowledge management practice, and sets priorities for managerial actions to improve knowledge management practices. A real-world case study was conducted by administering a survey to 105 construction firms operating in Turkey and is presented to illustrate the implementation and utility of the proposed model. The case study findings provided preliminary support for the validity of the proposed model.

In recent years, greater environmental awareness had induced the managers of building projects to “go green,” and several studies have been conducted on the project delivery of green building. However, there is no comprehensive study that explores the important project management factors from the perspective of architectural, engineering, and construction (AEC) firms, whose decisions can significantly affect the environmental performance of building projects. In Singapore, Green Mark, a certification for green building, has become a compulsory requirement for all new buildings. AEC firms are now facing challenges on how best to attain Green Mark certification with minimum cost and resources. The purpose of this research is to identify the controllable critical project management factors for delivering Green Mark certified projects to achieve higher Green Mark ratings. Nineteen controllable project management factors were first identified from related literature, and then a survey was carried out to collect data needed to perform the principal component factor analysis. The factor analysis revealed that the controllable project management factors could be grouped into five major components, namely, (1) human resource–oriented factors, (2) technical and innovation-oriented factors, (3) support from designers and senior management, (4) project manager’s competence, and (5) coordination of designers and contractors. Finally, multiple regression analysis was applied. It was found that the coordination of designers and contractors and technical and innovation-oriented factors are the most critical success factors, and possible reasons are discussed. With the help of the research findings, project organizations in Singapore will manage their Green Mark certified projects to achieve higher rating levels in a more efficient and effective way.

The major aim of this research is to demonstrate that causal relationships exist among various risk factors that necessitate identification of risk paths, rather than individual risk factors, during risk assessment of construction projects. International construction projects have more complex risk-emergence patterns because they are affected by global and foreign country conditions and project-related factors. Identification of a network of interactive risk paths, each of which initiated from diverse vulnerabilities of the project system, is considered to be a better reflection of the real conditions of construction projects than the use of generic risk checklists. In this study, using the data from 166 projects carried out by Turkish contractors in international markets and utilizing structural equation modeling (SEM) techniques, 36 interrelated risk paths were identified and the total effects of each vulnerability factor and risk path on cost overrun were assessed. SEM findings demonstrate that every risk path is initiated from a specific vulnerability factor related to project environment, and that contractor-specific vulnerabilities have the most effect on project cost overrun. Risk identification using SEM helps decision makers in answering what-if questions in the early stages of a project, tracing the effects of interdependent risks throughout the life cycle of the project and evaluating the influence of alternative mitigation strategies, not only on specific risks but also on the whole network of interrelated risk factors.

Many academic researchers have conducted studies on the selection of a design-build (DB) delivery method; however, there are few studies on the selection of DB operational variations, which pose challenges to many clients. The selection of a DB operational variation is a multicriteria decision-making process that requires clients to objectively evaluate the performance of each DB operational variation with reference to the selection criteria. This evaluation process is often characterized by subjectivity and uncertainty. To resolve this deficiency, the current investigation aimed to establish a fuzzy multicriteria decision-making (FMCDM) model for selecting the most suitable DB operational variation. A three-round Delphi questionnaire survey was conducted to identify the selection criteria and their relative importance. A fuzzy set theory approach, namely, the modified horizontal approach with the bisector error method, was applied to establish the fuzzy membership functions, which enables clients to perform quantitative calculations on the performance of each DB operational variation. The FMCDM was developed using the weighted-mean method to aggregate the overall performance of DB operational variations with regard to the selection criteria. The proposed FMCDM model enables clients to perform quantitative calculations in a fuzzy decision-making environment and provides a useful tool to cope with different project attributes.

Risk assessment and risk management for deep foundation pit engineering are essential for quality and safety in civil engineering owing to the needs of urban construction projects. However, uncertainty and fuzziness continue to challenge studies of the probability and consequences of risks in this area. Therefore, a fuzzy comprehensive evaluation method based on Bayesian networks (BNs) is proposed to assess the risks of deep foundation pit construction. This methodology has five main parts: modeling of BNs, determination of occurrence probabilities of risk events, assessment of consequences, calculations of risk value and membership degree of risk rating, and definitions of risk acceptance criteria. In a case study, primary data analysis of a simple accident database from a deep foundation pit construction project in Shanghai is used to provide the probabilities of basic events and approximate distributions of risk consequences. The probability of every risk event is calculated by using deductive BN techniques. Then the consequence of each event is calculated by using fuzzy analysis (i.e., statistical consequence distributions and weight coefficients of risk events are determined through the database). A fuzzy comprehensive evaluation model with a membership function is also presented, and each risk event in the deep foundation pit construction his rated. In addition, risk precautions and control measures are suggested on the basis of the risk assessment results and are applied to risk management in deep foundation pit construction.

The general consensus of most archaeologists is that approximately 25,000 workers labored for 23 years to build the Great Pyramid in Egypt at Giza. However, by examining the “mysterious tools” and other clues left behind , it is found that the Egyptians were masters of energy management and that the 25,000-worker build time could be reduced to only 138.6 days (using very conservative calculations). More realistically, and matching evidence found at the pyramid site, approximately 4,000 workers were probably used, and they took 4–6 calendar years at a fairly leisurely pace. This is on the basis of archaeological evidence, standard engineering principles, and ingenuity. Management of energy of assembly is a critical issue in the efficient construction of large structures. The principles used in ancient times are still applicable today. It is assumed that the Egyptians were smart people and that they were capable of employing the technology that they are known to have possessed in a creative and resourceful manner.

Public Private Partnerships (PPPs) have been used globally as a method to procure infrastructure projects, such as expressways, bridges, water plants, and power plants. The risks involved in such PPP projects are unique because of the large amount of investment and long contractual concession period. This paper proposed a fuzzy analytical hierarchy process (AHP) as risk assessment technique to simulate the vagueness of human judgement and to improve the assessment accuracy. Furthermore, a comparison was made between the proposed fuzzy AHP and straight-AHP in this paper. The fuzzy AHP process was illustrated by using an actual PPP expressway project from China. The results showed that planning deficiency, low project residual value (after 30 years of operation), lack of qualified bidders, design deficiency, and long project approval time were assessed as the top five risks for the project, and the feedback from the experts showed that these results reflected the actual project risk situation.