• Journal of Family Resource Management and Policy Review
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• v.15 no.2
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• pp.147-171
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• 2011

The purpose of this study was to examine low-income households' financial problems and the demand for financial counseling. For these purposes, a survey of 500 low-income households was conducted by an on-line survey company. The results were as follows. First, four types of low-income households classified by income and job criteria were: the not-working poorest (16.2%), the working poor (27.0%), the not-working low-income (13.8%), and the working low-income (43.4%). Also, seven areas of financial problems were found through factor analysis. They included difficulty of survival, insufficient funds for special expenditures, defaults on financial obligation, decrease of income, increase of debts, emotional anguish, and difficulty in meeting living expenditures. 61.6% of respondents requested financial counseling, and 44.5% of them preferred internet counseling to counseling by phone or in-person, while 49.5% desired access to public counseling organizations. The five types of financial counseling content for low-income households that were found through factor analysis were financial planning, credit management, asset management/investment, public support, and use of credit cards. The low-income householders demanded financial planning counseling and pubic support counseling more than the other types of financial counseling. Logistic regression analysis revealed that the demand for financial counseling participation was significantly influenced by age and income. The demand for financial counseling content was age, income, and types of financial problems. Therefore, general financial counseling programs for low-income households should be expanded. Furthermore, those counseling programs can be useful if they not only include credit management but also financial planning, economic support information and savings.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.45-59
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• 2014

Real estate has been the most preferable investment asset since 1980's has begun. Especially the ups and downs of housing price influence significantly on the household and national economy for a digital economy. In this analysis, monthly movement of apartment price of Seoul and its correlation with KOSPI, construction concerned shares, securities concerned shares, interest rate and exchange rate for 320 months(from January, 1987 to August, 2013) are shown. From the analysis, correlation coefficient of the price of apartment in Seoul and KOSPI is 0.8566 which is highly positive while the price of apartment in Seoul and interest rate are shown strong negative correlation which is -0.7846. The rise of stock market does affect the rise of the price of apartments in Seoul, on the contrary, the price goes down when the interest rate goes up.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.592-609
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• 2019

This study attempts to expand the leverage cycle theory using the subprime real estate investors. The leverage cycle theory has demonstrated asset price fluctuations irrelevant to changes in fundamentals through the restructuring of transaction composition centered on optimistic buyers. However, it needs to understand how this theory works in the depressed housing market with low-income residential regions to explain the geographic origins of the financial crisis. In the depressed housing market, the subprime real estate investors focused on low-income residential regions. Through this spatial focus, the low-income residential regions solely have real estate investor-oriented composition of new purchase transactions in the depressed housing market. The discovery of the subprime real estate investors as new actors lays the foundation for applying the leverage cycle theory to the depressed housing market which has been a underserved area for capital investment. This attempt illustrates how the geographical reinterpretation of an economic theory reestablishes spatio-temporal context of economic phenomena.

• Fashion & Textile Research Journal
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• v.15 no.2
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• pp.219-230
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• 2013

To generate future profits, luxury brands need to recognize and understand customers as individually important and analyze the impact factors that improve specific customer equity. With the growing recognition that customer equity is a key strategic asset, this study empirically investigates the effect of customer equity drivers on customer loyalty based on the study of Vogel et al.(2008) which expanded the Rust et al.(2000)'s study on customer equity. We empirically examine if the customer equity drivers have a different impact on customer loyalty. This study hypothesizes that the relative effect of customer equity drivers would be different depending on the purchasing behavior of consumers and examines the effects of them on the relationship of the drivers of customer equity and customer loyalty. We use stepwise multiple regression analysis to empirically test the relationship of value equity, brand equity, and relationship equity and customer loyalty. Relationship equity influences customer loyalty more strongly than value equity and brand equity. Customers seem to build loyalty based on the careful assessment of all costumer equity drivers (value equity, brand equity, and relationship equity). In addition, their relative impact is different depending on the purchasing behavior of consumers. A company cannot maintain all customer equity drivers at a high level with limited marketing resources; therefore, marketing investment for all customer equity drivers need to be allocated differentially depending on the purchasing behavior of consumers.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.2
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• pp.233-250
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• 2008

This paper aims to analyze the characteristics of BTL, and to propose the effective models connecting BTL and project finance, through the analysis of current state and case study of BTL. The main results of this study are as follows. Firstly, BTL business have been increasing fast, and most of projects are middle size projects below 100 billion Won. Nextly, key suggestions for improving BTL business model are analyzed, which are, first, risk allocation between public and private interests, second, improvement of method for selecting private investment consortium, and third, alleviation of long-term burden of local finance. Finally, effective models for connecting BTL and project finance, which are, first, model for using asset backed securities, second, model for dividing project corporations into construction corporation and operation corporation, and third, model for risk allocation between public and private interests.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.197-212
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• 2019

The purpose of this study is to identify the maturity stages of venture firms through classification analysis, which is widely used as a big data technique. Venture companies should develop a competitive advantage in the market. And the maturity stage of a company can be classified into five stages. I will analyze a difference in the growth stage of venture firms between the survey response and the statistical classification methods. The firm growth level distinguished five stages and was divided into the period of start-up and declines. A classification method of big data uses popularly k-mean cluster analysis, hierarchical cluster analysis, artificial neural network, and decision tree analysis. I used variables that asset increase, capital increase, sales increase, operating profit increase, R&D investment increase, operation period and retirement number. The research results, each big data analysis technique showed a large difference of samples sized in the group. In particular, the decision tree and neural networks' methods were classified as three groups rather than five groups. The groups size of all classification analysis was all different by the big data analysis methods. Furthermore, according to the variables' selection and the sample size may be dissimilar results. Also, each classed group showed a number of competitive differences. The research implication is that an analysts need to interpret statistics through management theory in order to interpret classification of big data results correctly. In addition, the choice of classification analysis should be determined by considering not only management theory but also practical experience. Finally, the growth of venture firms needs to be examined by time-series analysis and closely monitored by individual firms. And, future research will need to include significant variables of the company's maturity stages.

• Journal of the Korean Institute of Educational Facilities
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• v.27 no.6
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• pp.3-12
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• 2020

Like most OECD countries, Korea is experiencing a decline in population and demographic changes, deterioration of public facilities, and limited investment in public facilities maintenance due to low economic growth and increased welfare budgets. In this case, not only the inconvenience of using the public facilities can lead to the occurrence of an accident due to the damage of the facilities. However, as the importance of the management of public facilities has not been recognized yet, new policies are being promoted. Korea is expected to reduce the total population since the late 2020s, and there will be a large difference in population reduction between the cities, towns, and towns within the same administrative districts. Therefore, it is necessary to change the management policy regarding the change in demand of public facilities due to population change such as population decrease and aging. Accordingly, this study analyzes the management policies and actual conditions of public facilities in Korea, and suggests the implications for public facilities management by analyzing Japan's public facilities management policies that faced population change and deterioration of public facilities before Korea. The key change in Japan's public facilities management policy is the transition from new to maintenance, which has managed public facilities in terms of existing safety management and asset management.

• The Korean Journal of Financial Management
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• v.21 no.2
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• pp.153-181
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• 2004

This study is to explore whether the relationship among financial markets changed according to financial development. For this study, data analysis was conducted through analytic methods incorporated structural breaks such as Zivot and Andrews'(1992) unit root test Gregory and Hansen's(1996a,b) cointegration test, etc. In study results, it was found that dynamic relationship between stock price and interest rate was changed from negative to positive after the structural break(Oct 1999). It may be resulted from the fact that asset substitutability between stock and bond was increased since stock investment became popularized The negative relationship between stock price and exchange rate was reinforced after the structural break(the foreign currency crisis). Also, the negative relationship between interest rate and exchange rate was strengthened after the structural break(Oct. 1999).

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.385-396
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• 2014

With development of Information Security industry and recognizing value of information as an asset, demand for information protection is foreseen to be expanding gradually. The Information Security industry in this paper defines as an industry where relative products as well as consulting services are developed, produced, and distributed. This study reclassifies sub-sectors of the Information Security industry based on the definition of product and services defined above, and it uses the RAS technique to broaden a scope of an input-output table to include the Information Security industry with purpose of analyzing economic spill-over effects industry will encounter during 2013~2017. Results show that investment in the Information Security industry during 2013-2017 induces total economic outputs to KRW 3,206.9 billion and is expected to employ additional 27,406 workforce.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.165-173
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• 2017

The purpose of this study was to analyze the correlation and volatility of Korea and neighboring East Asia stock markets. East Asian stock markets were selected for Japan, China, Hong Kong and Taiwan by economically and geographically close with Korea. If you understand the volatility and the correlation between Korea and the East Asian stock market, it may be helpful in predicting investment. And It may reduce the risk of investing of asset allocation in global portfolio level. For this using the national monthly return data for the last 163 months, I was calculating and comparison the rate and correlation, and regression analysis. Result of the correlation analysis, Korea have shown a low correlation with China. while showing a high correlation with Taiwan and Hong Kong. China has been forming its own market in East Asia and showing a low correlation with other countries exception Hong Kong. Hong Kong has been determined as the highest harmonization within the East Stock Market.