• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.635-645
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• 2020

This research was conducted to achieve several objectives and focus research was based on financial behavior theory and prospect theory as grounded theory e.g., investigate the financial decision-making behavior between financial and real assets investment, and confirm the relationship existing between herding behavior and overconfidence factors to the level of loss and regret aversion, and financial literacy into real assets investment decisions. The study used 220 real estate auction respondents as investor samples at the State Assets and Auction Service Office Makassar, South Sulawesi, Indonesia. Data was collected through the use of a questionnaire consisting of 23 questions to measure the variables. Moreover, the research data passed through several feasibility tests like the inner and outer modeling by Partial Least Square - Structural equation model (PLS-SEM) while the hypotheses formulated were also tested to determine the magnitude of the variable relationship. Through the use of the direct and intervening test, loss and regret aversion variables have a positive and significant effect while financial literacy variables have no significant effect. There is a slight difference in the decision-making process for real assets and financial assets investors. Investment decision making behavior in the financial assets sector requires less complicated decisions compared to the decisions related to real assets investments.

• Korea Real Estate Review
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• v.27 no.3
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• pp.23-40
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• 2017

This study examined the motive and incentive for the disposal and purchase of corporate real estate assets based on the various firm characteristics. It was empirically found that firms with a higher leverage ratio, lower cash holdings, and lower sales growth are more likely to dispose of their real estate assets. This implies that financial constraints, internal reserves, and growth opportunities are important factors affecting the corporate decisions regarding the disposal of real estate assets. Meanwhile, it was found that firms with a lower leverage ratio have a higher probability of purchasing real estate assets, suggesting that a stable financial structure enables firms to acquire more of such assets. Using the transaction amount of corporate real estate assets, consistent results were found. While varied opinions on the utilization of corporate real estate assets have been raised, this study broadened the understanding of such by performing rigorous analyses. The result of this study would have practical implications in terms of the introduction of regulations or the establishment of business strategies related to corporate real estate assets.

• Journal of Family Resource Management and Policy Review
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• v.16 no.4
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• pp.45-68
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• 2012

This study performed an analysis to determine if an individual can maintain the current consumption, in the case of a single retired elderly person's household using the accumulated assets. Assets are divided into three types, based on the behavioral economics life cycle hypothesis : financial assets, real assets excepting residential assets, and residential assets, and it is assumed that these assets were used on a step-by-step basis. Also, if the assets were sufficient, the maximum withdrawal amount was calculated. The results of the analysis are as follows. First, the monetary assets were sufficient to cover the cost of living for 2.7 years, 6.4 years by using the real assets of the non-occupied housing, and 26.3 years in the case of residential property. Second, in the case of preferentially using the financial assets, 4.4% of the sample households were able to cover the cost of living. Households that were not able to cover the cost of living used the next-stage assets, real assets of the non-occupied housing. Households that were not able to cover the cost of living by financial assets liquidated the real assets with the exception of residential assets and used these to cover the cost of living. A total of 4.8% of the households were able to maintain the current cost of living through the second stage and 25.5% supplemented their funds by using residential assets. That is to say, 35% of the sample households were able to maintain the current level of living by using their assets.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.221-226
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• 2007

This paper suggests a valuation framework of investment project using the concept of real options. We show the valuation process of real assets using the risk-neutral pricing. Especially, we focus on the investment lag. Real assets have investment lag in general. The decision time and the payment time are not identical. So the investment lag should be considered when valuing real assets for reality. We provide the valuation process for real assets, including R&D project. The results of this paper can be used for the real assets valuation and strategic decision analysis.

• The Journal of Industrial Distribution & Business
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• v.12 no.2
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• pp.41-52
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• 2021

Purpose: This study aims to provide implications for the government's housing supply policy by analyzing the factors that determine the type of real estate holding and household debt. This study started from the awareness that the determinants of household debt differ depending on the type of real estate holding. Research design, data and methodology: Real estate ownership type was classified and analyzed into 4 models: model 1 (1 household 1 house and self-resident), model 2 (1 household multiple real estate ownership and self-resident), model 3 (1 household 1 house and rent residence), model 4 (1 household holds a large number of real estate and rent residence). The analysis method used multiple regression analysis. The dependent variable was household total debt. As independent variables, household debt, annual gross household income, financial assets, real estate net assets, annual repayment, demographic & residential characteristics were used. Results: 1) Model 4 has the highest household debt and the highest gross income, Model 2 has the most real estate mortgage loans and real estate net asset, and Model 1 has the highest real estate mortgage payments. 2) The positive factor of common household debt determinants is real estate net assets, and the negative factor is financial assets. 3) It was the net assets of real estate that acted as a positive factor in common for the four models. In other words, the more financial assets, the less household debt. It was analyzed that the more net assets of real estate, the more household debt. The annual repayment of financial liabilities had no influence on household debt, while the annual repayment of loan liabilities and household debt had a positive relationship. Conclusions: 1) It is necessary to introduce benefits and systems that can increase the proportion of household financial asset. Specific alternatives include tax benefits and reduced fees for financial asset investment. 2) In the case where a homeless person prepares one house for one household, it is necessary to prepare various support measures according to the income level. The specific alternative is to give additional points for pre-sale or apply an interest rate cut incentive for mortgage loans.

• Journal of Arbitration Studies
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• v.33 no.3
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• pp.69-93
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• 2023

For many people, the digital domain is becoming as important as the real world. The virtual environment is no longer just a place for entertainment and leisure. Blockchain transactions are serious business. Digital assets are seen as investments, with as much real value as physical assets. Does the law protect rights in digital assets, such as cryptocurrencies and NFTs? This article discusses recent case law that expands the common law concept of property to digital assets.

• Journal of the Korean Home Economics Association
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• v.43 no.1 s.203
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• pp.85-103
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• 2005

This study attemped to analyze the financial stati of single households. The financial stati of single households were analyzed using the income and expense stati, balance sheet status and selected financial ratios as components. The data of 757 single household's from the 1998 Korean Household Panel Study were utilized. The major findings are summarized as follows; 1. Male single households had higher income and expense stati than those of females but lower holdings of other asset with the exception of liquid assets. Single elderly households had the highest holdings of both real assets and debt. 2. Usually single households were retained more short-term than long-term liquid assets. The debt burden ability in using net assets was the lowest of all assets. To accumulate capital those in single household were more likely to have savings than investment assets.

• Korean Journal of Human Ecology
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• v.15 no.6
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• pp.973-984
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• 2006

This study examined the asset allocation of the aged and analyzed the impact variables on the portfolio ratio of different kind of finanical assets. The aged was divided three groups, 55-65, 65-75 and 75 over. The results showed that the aged are not likely to invest on risky asset and their assets composed of mostly real estates and bank account. The study include four different assets, such as liquid asset, risky assets, horne equity and other real estates, which reflects the liquidity problems of households asset allocation for the aged in Korea. The aged who do not participate on stock market are likely to have more liquid assets. Households lived in Daegu, Kwangju, ChungCheong and CheonRa tend to have more liquid assets compared to those in Seoul. Total income is appeared having positive relationship with illiquid assets including stock, bonds, and private pension. Age group with 75yrs over tend to have greater mean of illiquid assets and it may caused by the polarization of assets, which gives intuition for the future study.

• The Journal of Information Technology and Database
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• v.8 no.2
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• pp.115-135
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• 2001

The objective of this paper is to develop a knowledge assets measurement model in Korea. There are relatively many researches on measuring knowledge assets of an organization. These previous researches, however, lack of comprehensive view of knowledge management and view of Korean organizational culture. We surveyed and analyzed previous researches, and found common factors to measure knowledge assets. We developed an updated version of knowledge assets index. The developed model has been validated for its fitness with real data of Korean companies. The result of this research can be used as a measurement tool for knowledge assets of public institutions as well as private companies.

• The Journal of Economics, Marketing and Management
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• v.11 no.4
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• pp.19-30
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• 2023

Purpose: This study examines the factors that the Millennials and Gen Z prefers to invest in assets. We look at the asset structure they want now and in the future and the idea of designing the future. This can be expected that the center of Korea's asset market will change to the structure they want in the future. Research design, data and methodology: The spatial extent of the study is all over Korea including Seoul, the metropolitan area, and local cities. The survey was conducted for about 16 days from May 7 to May 22, 2023. The survey was conducted by the surveyor visiting the subject in person, distributing the questionnaire, explaining it, and filling it out in person. For the analysis, descriptive statistics and logistic regression analysis were conducted using the SPSS 25.0 statistical package. Results: It was confirmed that the preferred assets of the Millennials and Gen Z were different by period. There was also a difference in the influencing factors between Millennial Generation and Generation Z in asset preference. Conclusions: The Millennials and Gen Z's preferred assets were different by period. The reason is interpreted as the current process of collecting assets during the asset formation period. In the future, they intend to purchase real estate assets by using financial assets as a lump sum of money. We learned the characteristics of the entire Millennials and Gen Z, in addition, the difference between income and assets is believed to have affected the difference in preference factors of Millennial Generation and Generation Z, respectively.