Journal of Construction Engineering and Management

Many existing studies about construction schedule management focus on the planning phase of a project, particularly on schedule estimation based on the labor resources involved in the project. However, equipment resources, which are another crucial factor in the productivity of a construction project, have not been considered in existing research. Therefore, this study aimed to develop a schedule estimation model considering both labor and equipment resources. For the purpose of this study, core wall construction was selected because it is a very important construction activity in terms of schedule estimation for high-rise building construction. To develop a schedule estimation model for core wall construction, an in-depth case study was conducted. On the basis of the results of the case study, a simulation model was developed using the CYCLONE method. Finally, by using the results of the simulation, a schedule estimation model for core wall construction was developed by conducting multiple-regression analysis. By using the developed model, a project manager can easily, quickly, and accurately perform schedule estimation when there are problems that may cause construction schedule delays during the construction phase.

Measuring the performance of joint ventures has been an important research topic for a few decades. No consensus on an appropriate definition and measurement of performance of international joint ventures (IJVs) has yet emerged, and the validity of the underlying measures is still questionable. In this study, the construct validity of measures that define IJV performance in construction is evaluated using data obtained through a questionnaire survey. A second-order performance construct is proposed, which is measured by means of project performance, partner performance, performance of IJV management, and perceived satisfaction with IJV. The validity of the performance measures is evaluated by means of tests that assess content validity, reliability, and convergent and discriminant validity. The findings reveal that all proposed indicators are valid measures of IJV performance and that they correspond to different dimensions of performance. This research is expected to trigger further work on developing a multidimensional performance measure for IJVs in construction. In addition, the findings can help practitioners reflect on how they operate and measure the success of their IJVs.

Construction contractor evaluation is a critical issue in successfully completing a project. It is important for project owners and other stakeholders to identify potentially failing contractors and to avoid awarding them contracts. Previous studies developed construction contractor default prediction models incorporating managerial or economic variables into traditional financial ratio models to enhance predicting power. However, managerial variables are subjective and qualitative, and both economic variables and financial ratios are only available periodically and may not provide the necessary information in time. This study predicts contractor default by employing three option-based credit models (BSM, CB, and BS) based on stock market information, and the empirical results show that all of the models have strong discriminatory power in ranking contractors from riskiest to safest. The misclassification rates of the three models are BSM: 10%, CB: 10%, and BS: 12.7%, all of which are smaller than that of the enhanced ratio model developed by Russell and Zhai (22%), and two of which are smaller than that of the model developed by Severson and colleagues (12.5%). The results show that option-based credit models are good alternatives for construction contractor default prediction.

Efficient planning of materials procurement and storage on construction sites can lead to significant improvements in construction productivity and project profitability. Existing research studies focus on material procurement and storage layout as two separate planning tasks without considering their critical and mutual interdependencies. This paper presents the development of a new optimization model for construction logistics planning that is capable of simultaneously integrating and optimizing the critical planning decisions of material procurement and material storage on construction sites. The model utilizes genetic algorithms to minimize construction logistics costs that cover material ordering, financing, stock-out, and layout costs. The model incorporates newly developed algorithms to estimate the impact of potential material shortages on-site because of late delivery on project delays and stock-out costs. An application example is analyzed to demonstrate the capabilities of the construction logistics planning model in simultaneously optimizing material procurement decisions and storage layout plans.

A fuzzy similarity consensus (FSC) model is presented for alignment of construction project owner and contractor project teams to their roles and responsibilities, identifying and reducing fundamental problems of conflicts, duplication, and gaps in roles and responsibilities as early as the project initiation stage. The model achieves its objective by incorporating consensus and quality of construction project teams in aggregating their opinions to decide on the party responsible for every standard task of a construction project. The roles and responsibilities of the owner and contractors are described to different extents using seven linguistic terms defined by triangular membership functions and constructed using a three-step Delphi approach, which allows experts to develop common understanding of the meaning of the terms by determining their overlap on a fuzzy linguistic scale. A modified similarity aggregation method (SAM) aggregates experts’ opinions in a linguistic framework using a consensus weight factor for each expert that is based on the similarity of his or her opinion relative to the other experts to ensure that the experts’ final decision is a result of common agreement. A fuzzy expert system (FES) determines an importance weight factor, representing expert quality for each expert; opinions are aggregated using this factor and the consensus weight factor. The FSC model contributes to the construction industry by solving a fundamental problem for project owners who want to identify and reduce potential conflicts between their project teams on the extent of their roles and responsibilities prior to the construction stage. Also, the FSC model provides an improvement over previous consensus-based approaches, which rely on a subjective assessment of experts’ important weights in aggregating their opinions, and it modifies the SAM to adapt it to a linguistic environment.

Infrastructure projects have major effects on implementing the principles of sustainable development. Infrastructure projects will continue to be developed in the coming years, particularly in developing countries such as China and India; therefore, it is important to find methods and solutions for improving the sustainability of them. Although existing studies have suggested various methods for practicing sustainable development principles in the process of implementing infrastructure projects, effective assessment indicators are unavailable, which presents a barrier to the effective assessment of infrastructure project sustainability. This study introduces key assessment indicators (KAIs) for assessing the sustainability performance of an infrastructure project. The research data used for analysis were collected from a questionnaire survey given to three groups of experts, including government officials, professionals, and clients in the Chinese construction industry. The fuzzy set theory was used to establish KAIs. A procedure for using the KAIs is demonstrated by a case study. These research findings provide an alternative solution to appraise the sustainability of infrastructure projects.

Despite the construction industry’s generally positive reaction to the use of information and communication technologies (ICTs) in many of its functions, some of the profession’s key players reside in a digital divide and do not benefit from advances in technology. Hispanic construction workers, an at-risk population with high rates of workplace accidents, are affected by that divide because they rarely take advantage of available ICTs at work. One application of ICTs that can help Hispanic/Latino workers is computer-based training (CBT) for occupational safety. However, the design of CBT materials for Spanish-speaking workers needs to go beyond basic localization of existing products in English. A radical localization approach that uses participatory design sessions with construction workers and their supervisors is proposed in this paper. This case study reports that Latino workers reacted positively and retained knowledge from CBT materials, including videos with elements of humor and without graphic representations of accidents, modeled after the genre of a television situation comedy.

Korea’s level of competitiveness in the global construction market has significantly improved over the years; from being an underdeveloped country in the 1960s, Korea is currently one of the top ten countries in terms of revenue in the global construction market. In general, an international construction business entails various risks and requires advanced financing and managerial and technical ability to become competitive. Therefore, it is challenging for developing countries to expand their share in the global construction market. In this regard, the case of the Korean international construction business (KICB) may serve as a benchmark for other countries aspiring to enter or reinforce their status in the global construction market. To this end, the strategies to achieve and maintain competitiveness need to be analyzed chronologically rather than focusing only on a particular period, especially the current status. This paper details the history of KICB, showing its evolution over the past 40 years, divided into four major phases that correspond with significant events. Moreover, the important aspects for securing competitive advantage in the market are clarified using four sets of strength, weakness, opportunity, and threat (SWOT) analyses. In addition, the strategic evolution over the four major phases is explored by introducing the adaptation, aggregation, and arbitrage (AAA) framework. The research findings indicate that the strategies adopted by KICB for achieving competitiveness included presenting a memorable performance in a primary country of a particular region (adaptation) during the initial phase, achieving economies of scale in a few regions during the development phase (aggregation), developing international specialization during the depression phase (arbitrage), and adapting to receive orders in a severely competitive market while coping with the local industry protection policy during the resurrection phase (adaptation).