• Journal of the Korean Regional Science Association
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• v.31 no.3
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• pp.39-54
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• 2015

To assess an economic value of Cheonggyecheon river restoration project, an in-depth exit survey data was collected to apply travel cost method in this study. Poisson model, Negative Binomial, Zero-truncated Poisson, and Zero-truncated Negative Binomial model were executed due to the nature of count data. Empirical results showed that regressors were statistically significant and corresponded to general consumer theory. Since our survey data showed over-dispersion, Zero-truncated Negative Binomial was selected as an optimal one to analyze travel demand of Cheonggyecheon by model goodness of fit test among those aforementioned empirical models. Estimating an economic value of Cheonggyecheon river restoration project, which is known as an ecological river restoration project, we used annual visit of individual traveler and an optimal model. Suffice to say that the annual economic value of Cheonggyecheon river restoration project was estimated as 193.4 billion won in 2013.

• Korean Journal of Construction Engineering and Management
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• v.8 no.2
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• pp.155-163
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• 2007

Multiple parties-owners, engineering and construction contractors, and suppliers involve the delivery process of capital facility projects in the construction industry, and each party obtains or provides their workforce, material, equipment, or service tied into specific contracts. Considering that construction projects are based on the contracted relationship between the parties and that contract types are one of the significant factors determining project success. it is critical for project stakeholder to select appropriate contract types for successful deliveries of projects. With these considerations, this paper assesses impacts of different contract types on project cost, schedule, safety, change, or rework. Analyzing data from real construction projects, the differences in project performance between two contract types, Cost Reimbursable and Lump Sum are measured and statistically tested to investigate if the differences are significant. For this analysis, performance metrics developed by Benchmarking and Metrics program, the Construction Industry Institute are used.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.837-842
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• 2022

The "Intelligent Railroad Alignment Design Program (ei-Rail) developed in 2013 has been adopted in the planning and the evaluation/validation of design results of oversea railroad construction projects. Target countries of Korean railroad industries requires the operating speed increase with alignment improvement and the double tracking of prevailing single track railroads as well as new railroad construction. This study is to develop an additional module for double tracking project of prevailing single track railroads in the ei-Rail. The developed method is based on the geometrics of prevailing railroad, and the definition of planned project determines the project cost based on the unit cost by work type, and provides the draft design of double track. The module was validated with a oversea case. It is then expected for oversea railroad double tracking project more efficiently in planning and the evaluation of design results.

• Journal of the Korea Institute of Building Construction
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• v.23 no.1
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• pp.103-111
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• 2023

Accurate cost estimation in the early stages of a construction project is critical to the successful execution of the project. In this study, an ANFIS model was presented to predict construction costs in the early stages of a construction project. To increase the usability of the model, open construction cost data was used, and a model using limited information in the early stage of the project was presented. We analyzed existing studies related to ANFIS to identify recent trends, and after reviewing the basic structure of ANFIS, presented an ANFIS model for predicting conceptual construction costs. The variation in prediction performance depending on the type and number of membership functions of the ANFIS model was analyzed, the model with the best performance was presented, and the prediction accuracy of representative machine learning models was compared and analyzed. Through comparing the ANFIS model with other machine learning models, it was found to show equal or better performance, and it is concluded that it can be applied to predicting construction costs in the early stage of a project.

• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.174-182
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• 2022

The existing cost calculation standard for the implementation project to manage total maximum daily loads calculates cost by considering the area scale and the population based on the basic cost. This method renders it difficult to calculate cost when the detailed characteristics of a business are considered. Therefore, in this study, we proposed a costing method that applied the standard fee calculation, reflecting the area scale, a number of human and livestock, wastewater discharge facilities, etc. And, through the review of related order cases, the suitability of factors affecting the implementation project is verified and the appropriateness of the cost calculation method is verified.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.18-24
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• 1988

We consider sensitivity analysis sequencing problems, in which sequence of a finite set of expansion projects is sought to meet a deterministic demand projection in minimum discounted cost. In particular, by characterizing the underlying network structure, we find analytically the sensitivity range for a project cost such that the optimal sequencing policy remains unchanged for any value in the range. A numerical example is presented.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.966-971
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• 2003

[ $\lceil\;Cost Effectiveness Analysis\;\rfloor$ ] has been widely used to evaluate effectiveness of R&D resources. But, almost of cost effectiveness evaluation systems have some problems, especially estimating method of effect on R&D project is very rough and imprecise. To solve this problem, we have designed new single effect evaluation system, which are able to apply the distribution of order statistics and to transform relative measure into absolute measure for getting single effect.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.377-377
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• 2000

Current software cost estimation models, such as the 1951 COCOMO, its 1987 Ada COCOMO update, is composed of nonlinear models, such as product attributes, computer attributes, personnel attributes, project attributes, effort-multiplier cost drivers, and have been experiencing increasing difficulties in estimating the costs of software developed to new lift cycle processes and capabilities. The COCOMO II is developed fur new forms against the current software cost estimation models. This paper provides a case-based analysis result of the cost driver in the software cost models, such as COCOMO and COCOMO 2.0 by fuzzy and neural network.

• Proceedings of the KSR Conference
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• 2001.05a
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• pp.44-51
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• 2001

To account for uncertainties involved in an economic analysis of project, sensitivity analysis are usually being done in Korea. Though useful for policy analysis, but it larks explicit consideration of probability of occurring certain events considered in the sensitivity analysis. Risk analysis otherwise can explicitly account for the probability of certain event which has dire impact on project viability, such as cost, discount rate, and size of benefit. This paper reports experience of applying risk analysis method for economic evaluation of railroad investment. Probability distribution of event has paramount impact on the risk analysis results, while not many prior researches dealt with these issues. Probability distribution of rolling stock cost and operating cost, in addition to those cost variables, are developed considering railway demand in this study. Case study results are reported. Issues in applying risk analysis are reported in addition to further research direction.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.132-133
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• 2015

Efficient scheduling and resource management are the key factor to reduce construction project budget (e.g., labor cost, equipment cost, material cost, etc.). Resource-based line of balance (LOB) technique has been used to complement the limitations of time-driven scheduling techniques (e.g., critical-path method). Optimizing construction alternatives contributes cost savings while honoring the project deadline. However, existing LOB scheduling is lack of identifying optimal resource combination. This study presents a method which identifies the optimal construction alternatives, hence achieving resource minimization in a repetitive construction by using genetic algorithm (GA). The method provides efficient planning tool that enhances the usability of the system.