• Korean System Dynamics Review
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• v.8 no.2
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• pp.5-23
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• 2007

According to the system dynamics model of this study, if there is a significant network effect on vehicle operating costs, it is difficult to achieve the shift to AFV even in the long term without a policy intervention because the car market is locked in to the current structure. Network effect can be caused by an increasing return to scale in fuel supply sector as well as in maintenance service sector. It is also related to the fact that the reliability and awareness of consumers on new products increases with the growth of the market share of the new products. There are several possible policy options to break the 'locked in' structure of car market, such as subsidy on vehicle price (capital cost), subsidy on fuel (operating cost) and niche management policy. Combined policy options would be more effective than relying on a single policy option to increase the market share of AFV.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.64
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• pp.213-237
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• 2014

The medical-device market of Myanmar in the recent Asian region is where the influences of Thailand, China, India and Singapore are being shown considerably with the lift-up of economic sanctions by America and the West. However, although the global capital and liberalization have widened the openness and the international concerns, the relative Myanmar's medical environment demands an active assistance and improvement. The study, recognizing the importance of Medical-Devices and their market conditions emerging as key business for knowledge-based industry, aims to obtain consequential meaningful suggestions, pursuant to relative export-concentration and sustainable market growth of Medical Devices, by analyzing inter-nation trade intensity for key Medical Device items. To do so, this study selected 8 nations in total by reviewing three points: core Medicine-advanced countries, geographically adjacent countries to Myanmar, and relative export-concentration.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.43-47
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• 2013

We investigate the effect of bank's market power on financing constraints of non-financial firms in 11 Asian countries between 1995 and 2009. Using firm-level data we analyze financial constraints with the Euler equation derived from the dynamic investment model. We find that with a highly concentrated banking sector firms which have high market power are less financially constrained. These results are consistent with an information-based hypothesis that more market power increases bank's advantage to produce information on potential borrowers.

• The Journal of Fisheries Business Administration
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• v.44 no.1
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• pp.25-37
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• 2013

The permit system is the most typical regulation system in Korean fishery. Even now, it has caused resource management failure, it has also invited economic inefficiency and inequity. Accordingly, the Korean government has recently introduced the fishing boats market, it would be improve entry barrier for new capital and labor in fishing industry. This study aims to survey and to analyze the status of coastal fishing boat market using the executive documents on permit system in Gyongnam province. And also, this study put focus on improve fishing permit trade take advantage of the fishing boat trading. The survey results indicated that the number of fishing boats trading is estimated about 5,000 per year, however, fishing boat market is very narrow. An analysis on fishing permit trading showed that policy support is essential to reduce transaction cost. Therefore, it is necessary to explore corresponding policy tasks, this will be reduce transaction costs and sunk cost.

• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.11-23
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• 2021

House price prediction is a significant financial decision for individuals working in the housing market as well as for potential buyers. From investment to buying a house for residence, a person investing in the housing market is interested in the potential gain. This paper presents machine learning algorithms to develop intelligent regressions models for House price prediction. The proposed research methodology consists of four stages, namely Data Collection, Pre Processing the data collected and transforming it to the best format, developing intelligent models using machine learning algorithms, training, testing, and validating the model on house prices of the housing market in the Capital, Islamabad. The data used for model validation and testing is the asking price from online property stores, which provide a reasonable estimate of the city housing market. The prediction model can significantly assist in the prediction of future housing prices in Pakistan. The regression results are encouraging and give promising directions for future prediction work on the collected dataset.

• The Journal of Information Technology
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• v.8 no.1
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• pp.63-81
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• 2005

The purpose of this study is primarily to analyse empirically the productivity effects of worker participation in capital by Korean employee stock ownership plan that had taken newly effect on and after January 1,2002, and secondarily to examine the impact of unionization on productivity. The analysis data are those of 150 firms that listed or registered on the stock market, and introduced ESOP. The result of this study can be summarized as follows. First, the worker participation in capitia have significantly a positive effect on productivity, but the magnitude of those effects vary according to estimation models and sectors. The elasticity of stock share owned by employees on productivity is from 0.03 to 0.24. Second, there is no unitary relationship between unionization and productivity. The coefficients of union dummy variable are positive or negative according to models and sectors as well as insignificant.

• Journal of Information Technology Applications and Management
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• v.11 no.1
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• pp.161-174
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• 2004

This study is intended to suggest1 the optimized data mining model for the efficient customer credit evaluation in the capital finance industry. To accomplish the research objective, various data mining models for the customer credit evaluation are compared and analyzed. Furthermore, existing models such as Multi-Layered Perceptrons, Multivariate Discrimination Analysis, Radial Basis Function, Decision Tree, and Logistic Regression are employed for analyzing the customer information in the capital finance market and the detailed data of capital financing transactions. Finally, the data from the integrated model utilizing a genetic algorithm is compared with those of each individual model mentioned above. The results reveals that the integrated model is superior to other existing models.

• The Korean Journal of Financial Management
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• v.25 no.4
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• pp.25-51
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• 2008

In this paper, we analyse empirically the fixed asset investment smoothing of working capital of firms listed on Korea Securities Market. The main results of this study can be summarized as follows. Firms will seek to lower long-term cost by smoothing fixed asset investment and maintaining stationary investment with working capital. Working capital is not only an important use of fund, but also a source of liquidity that should be used to smooth fixed asset investment relative to cash flow shocks if firms face financial constraints. Working capital investment is more sensitive than fixed asset investment to cash flow fluctuations. If firms face financial constraints, working capital investment will compete with fixed asset investment for the limited pool of available cash flows. So, fixed asset investment will have negative relationship with working capital investment. However, criticism that the positive correlation between cash flows and fixed asset investment could arise simply because cash flows is proxy variable for investment demand. Finally, controlling for the fixed asset investment smoothing effects of working capital results in a much larger estimate of the long run impact of financial constraints. Financial constraints is measured by dividend payout ratio and market access level. Fazzari et al. (1988), Fazzari and Petersen (1993), and Faulkender et al. (2008) emphasize that low dividend firms or market unaccessible firms are more likely to face financial constraints, and rarely make use of new equity issuing. The results from empirical analysis show that financial constraints can be better explained using 'adjustment cost' concept. Specifically, the results show that financial constraints exist and that in order to measure financial constraint effects more succinctly, fixed asset investment smoothing effects with working capital should be considered.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.4
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• pp.258-261
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• 2012

In this paper, I propose a new asset allocation framework to cope with the dynamic nature of the financial market. The investment performance can be much improved by protecting the capital from the market crashes, and such crashes can be pre-identified with high probabilities by regime detection analysis via a specialized unsupervised machine learning technique.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.45-53
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• 2002

A company's market value-added, which equals the excess of a company's market capitalization over it s book value, is used as one of the measures for intangible assets valuation in accounting literature. One problem with the approach is that the valuation results are affected by severe fluctuations in capital markets. In this paper, we propose an approach using the Kalman filter for intangible assets valuation. We apply this method to data of Korean electronic companies.