Chang-Taek Hyun

Effect of project characteristics on project performance in construction projects based on structural equation model

Most past studies that analyze project performance and the characteristics that affect such performance consist of a simple form, in which they present the brief relationship between project performance and a few characteristics that affect it. Furthermore, due to the limitations of the research methodologies used in these studies, important characteristics were often not considered in developing the relationship between project performance and project characteristics. This study aims to analyze the overall relationship between project performance and a projects characteristics. This study deduced (i) the overall causal relationship and (ii) the degree of influence between 17 project characteristics and five project performance indices. In order to achieve this goal, this study employed the factor analysis method and a structural equation model (SEM). In addition, this study established a SEM based on quantitative data from actual case studies as opposed to previous SEM studies that mainly use qualitative data. The SEM developed in this study can identify the project characteristics that affect the level of project performance required by owner in the planning stage, and is thus expected to help facilitate the decision-making process in the early planning stage of a project.

A CBR-based hybrid model for predicting a construction duration and cost based on project characteristics in multi-family housing projects

Decision-making in the early stage of a project has a significant impact on the project. However, limited and uncertain information on the project and a complex correlation among various factors that affect the project’s construction duration and cost, make it difficult to predict and manage the project. Therefore, this study developed a case-based reasoning (CBR)-based hybrid model with which to predict the construction duration and cost of a project in its early stage. One hundred and one cases among multi-family housing projects that were completed between 2000 and 2005 were used. The CBR-based hybrid model developed in this study is the result of integrating the advantages of (i) prediction methodologies, such as case-based reasoning, multiple regression analysis, and artificial neural networks, (ii) the optimization process using a genetic algorithm, and (iii) the probability distribution and the analysis process of outlier using Monte-Carlo simulation. The results of this study are expected to suppo...

The development of a construction cost prediction model with improved prediction capacity using the advanced CBR approach

Decision-making in the early stages of a construction project will have a significant impact on the project. Limited and uncertain information, however, makes it difficult to accurately predict constriction costs. To solve this problem, this study developed the advanced case-based reasoning (CBR) model with 101 cases of multi-family housing projects. The advanced CBR model was developed to integrate the advantages of prediction methodologies such as CBR, multiple regression analysis (MRA), and artificial neural networks (ANN), and the optimization process using a genetic algorithm. This study defined four optimization parameters, as follows: (i) the minimum criterion for scoring the attribute similarity, (ii) the range of attribute weight, (iii) the range of case selection and (iv) the tolerance range of cross range between MRA and ANN. Since the system was developed using the Microsoft-Excel-based Visual Basic Application (VBA) for ease of use, it is expected that the model supports the stakeholders in charge of predicting and managing a construction cost in the early stages of a construction project to get more accurate result from historical cases as a reference.

MRA-based revised CBR model for cost prediction in the early stage of construction projects

Accurate prediction of construction cost in the initial phase of a construction project is critical to the success of the project. Accordingly, many researchers have proposed various methodologies for predicting the cost in the initial phase with the use of limited information. This study was aimed at improving the prediction performance of a cost prediction model based on the Case-Based Reasoning (CBR) technique, which has recently become widely used. Toward this end, an improved CBR model that uses the Multiple Regression Analysis (MRA) technique in the revision phase of the CBR technique was developed. To verify the prediction performance of the proposed model, a case study was performed on 41 business facilities and 99 multi-family housing projects. The results showed that the prediction performance of the revised CBR model for business facilities and multi-family housings improved by 17.23% and 4.39%, respectively, compared to that of the existing CBR model. The proposed MRA-based revised CBR model is expected to be useful in estimating the construction cost in the initial phase of a project.

Simulation-Based Schedule Estimation Model for ACS-Based Core Wall Construction of High-Rise Building

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.

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 ...

Integrated Schedule and Cost Model for Repetitive Construction Process

Several efforts have been made by many researchers to develop a model for schedule and cost integration in construction projects, but it is difficult to integrate and manage schedule and cost in an actual construction site using such a model. The integrated schedule and cost model developed in this study (1) enables the planning and control of repetitive construction processes and (2) can be used by a project manager in an actual construction site. Furthermore, an integrated schedule and cost model for the core wall construction, which is an important repetitive process in the recently booming high-rise building construction in terms of scheduling, was developed using the integration model developed in this study. It is expected that the integrated schedule and cost model developed can allow project managers to integrate the schedule and cost of repetitive construction processes more effectively and support the project managers’ decision-making.

CBR-based cost prediction model-II of the design phase for multi-family housing projects

Predicting adequate construction cost is an important factor in effective investment because owners must set the most appropriate budget for their projects. Unlike the existing cost prediction models, the variables that have an interrelation with construction cost were selected as attributes using correlation analysis based on 786 cases. In selecting the attribute weight, the cost prediction model-II for construction projects was developed using the genetic algorithm. The developed cost prediction model-II was verified with four project cases. The result of the verification showed error ratios of -2.57%, -4.25%, 5.25%, and 4.59%, respectively. The developed cost prediction model-II can predict construction cost that corresponds with the project characteristics. It can also be expected that the developed model is effective in design management and cost management since the construction cost can be predicted before the completion of a projects design stage.

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.

Scheduling model for repetitive construction processes for high-rise buildings

In a high-rise building project that involves many repetitive construction processes, the effective control of such repetitive construction processes is a key factor in the success of the project. Unlike the existing scheduling methods for repetitive construction processes, a scheduling model that considers (i) the flexible job logic of the multiple work tasks that comprise a construction process and (ii) the productivity of the construction equipment and labor was developed in this paper. Various theories and algorithms such as the linking dummy, the linear scheduling method, and the production rate, were implemented in the development of the model. A scheduling model was then proposed based on such theories and algorithms and on a mathematical formula. The proposed model was verified by applying it to core wall construction, a key repetitive process in a high-rise building project. Verification showed that the developed model exhibited over 90% reliability. It is expected that the proposed model will al...