• Information Systems Review
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• v.8 no.1
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• pp.265-285
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• 2006

The purpose of this research is to identify the major evaluation criteria of IT investment projects and establish the importance weights of criteria through AHP analysis. Seven evaluation criteria which have been drawn from prior studies and industry practices are direct costs, indirect costs, financial benefits, strategic value, risk, technical necessity, and political considerations. Data have been collected from 95 IT projects in 40 public organizations and private firms in Korea. After having applied the data reliability test, 79 projects have been selected. The results of AHP analysis show the importance weights and priorities of seven evaluation criteria as follows: financial benefits 25.2%, strategic value 22.36%, direct costs 14.34%, risk 12.10%, technical necessity 11.55%, political considerations 8.3%, and indirect costs 6.48%. And the weights of seven criteria shows considerable differences among three different IT project types such as transactional, informational, and infrastructural.

• Korean Management Science Review
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• v.34 no.1
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• pp.15-25
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• 2017

We evaluated industry growth and employment effects of every possible pairs of 22 manufacturing sectors and 16 regions (i.e, 352 region-sectors). We used annual data of manufacturing sectors from 2008 to 2014 for the evaluation. The evaluation comprises of two steps; We first find several region-sectors that outperform others with respect to the effects of industry growth and employment, which are measured by location quotient analysis, shift share method, employment to GDP ratio and employment elasticity. In addition, cross-efficiency analysis follows to classify region-sector pairs into two sub-categories : efficient region-sectors that deserve to hold the current level of investments and inefficient region-sectors where we should consider efficiency improvements. To examine the efficiency, R&D investment, employment size, and capital investment were used as input factors and production volume, added value, changes in employment size, changes in annual salary per capita were used as output factors. For region-sector pairs that have outstanding growth and employment effects but are inefficient, we employed a CCR DEA model and analyzed how much to adjust the values of input and output factors to improve the efficiency scores. The analysis results showed that inefficiency is mainly due to several factors such as R&D investment, changes in employment size and changes in annual salary per capita.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.31-41
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• 2022

As the environmental impacts of fossil fuel energy sources increase, the South Korean government has tried to change non-environmental-friendly enery sources to environmental-friendly energy sources in order to mitigate environmental effects, which lead to global warming and air pollution. With both a limited budget and limited time, it is essential to accurately evaluate the economic and environmental effects of renewable energy projects for the efficient and effective operation of renewable energy plants. Although the traditional economic evaluation methods are not ideal for evaluating the economic impacts of renewable energy projects, they can still be used for this purpose. Renewable energy projects involve many risks due to various uncertainties. For this reason, this study utilizes a real option method, the Geske compound model, to evaluate the renewable energy projects on Jeju Island in terms of economic and environmental values. This study has developed an economic evaluation model based on the Geske compound model to investigate the influences of flexibility and uncertainty factors on the evaluation process. This study further conducts a sensitivity analysis to examine how two uncertainty factors (namely, investment cost and wind energy production) influence the economic and environmental value of renewable energy projects.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.107-116
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• 2009

Even though there are growing numbers of IT utilization in many organizations, they are required to use only constrained amount of resources due to the decrease in IT Investment, following economic recession. Besides, the CEOs in those organizations are required to assess how IT Investment, which has been gradually increased during the industrial growth, affects their organizational performances. Thus, they began to enforce IT governance so as to measure IT efficiency and minimize business risks. As a result, they improved the decision making process of IT Investment, enforced IT value assessment, and established the IT Investment-performance evaluation process as well. In this article, I aimed to make it clear how IT Investment affects the IT Performance by analyzing the effects of the factors constituting the IT Investment managing system and the Process Maturity on the User Satisfaction. This analysis can suggest a practical IT Investment-performance model, which can increase organizational performances.

• Journal of Korean Society of Transportation
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• v.5 no.1
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• pp.25-31
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• 1987

This article shows that, in the logit models, the(conditional) expected utility of the decision makers choosing an alternative is invariant across all alternatives. This property of the logit model implies that the logit model can not explain the distributional wealfare effects of a transportation policy (or transportation investment) among different alternatives, and thus the logit model is not proper for evaluating transportation policy in equity aspects.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1559-1565
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• 2004

Railway system is consisted of various resources such as rail-line, signal, and railcar. It is necessary to efficiently utilize these limited and expensive resources as much as possible up to given line capacity. So far, we treat the line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that changes dynamically according to operational conditions, so there is a need of new line capacity estimation system. In this paper, we present an improved systematic line capacity model. The proposed model has three main components ; TPS(tain performance simulator), PES (parameter evaluation simulator), LCS(line capacity simulator). The concept of each sub-component is described, including the evaluation method of capacity parameters. And capacity parameter evaluation and estimation results using sample line section data are presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.4
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• pp.177-187
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• 2008

It is very important to select optimal investment alternative. The common method of economic evaluation is to compare of NPV, FW, AE by MARR, or the rate of return for the cash flow of alternatives. This method is undergoing by assumption that cash flow can be always evaluated by MARR, but the cash flow is not always increased or discounted like MARR. So this paper suggests a model on an economic analysis and evaluation regarding to various cash pattern, that is helpful for the person in the field to use easily.

• International Commerce and Information Review
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• v.10 no.4
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• pp.417-437
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• 2008

Korean firms have had a short history of foreign direct investment and export in China market entry. This present study empirically analyzed determinants of the choice of foreign market entry modes, Particularly forcusing on the China market entry on Korean manufacture firms. This study developed a research model to determinant factor in the China market entry and collected 77 survey responses from the Korean manufacture firms. This study model construct in the third factor, China market character, company character and product character. In China market character, the variance are China trade barrier, culture different, competition power. The variance in company character are internationalization experience, enterprise rage and entry motivation. Also the variance in product character are product different, customer service and cost advantage. It is researcher's main interest that which type of China market entry format brought most positive evaluation form the Korean manufacture firms. therefor, these research results turned out to be different a little both export and direct investment in China market of Korean manufacture firms.

• KDI Journal of Economic Policy
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• v.40 no.4
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• pp.47-63
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• 2018

Government R&D grants for SMEs have risen to three trillion Korean won a year, placing Korea second among OECD nations. Indeed, analysis results have revealed that government support has not only expanded corporate R&D investment and the registration of intellectual property rights but has also increased investment in tangible and human assets and marketing. However, value added, sales and operating profit have lacked improvement owing to an ineffective recipient selection system that relies solely on qualitative assessments by technology experts. Nevertheless, if a predictive model is properly applied to the system, the causal effect on value added could increase by more than two fold. Accordingly, it is important to focus on economic performance rather than technical achievements to develop such a model.