• Journal of the Korean Society of Costume
• /
• v.51 no.7
• /
• pp.49-62
• /
• 2001

The purposes of this study were to find out the catalogue and online-order apparel shoppers' impulsive purchase orientation and impulsive purchase stimuli. Self-administered questionnaires were distributed to women over than 20 years, and collected from middle to the end of November in 2000. Frequencies, percentages, and mean were calculated. One-way ANOVA, chi-square test, factor analysis, and cluster analysis were used, and Duncan's Multiple Range test was followed. 1. Factors of impulsive purchase orientation were relax from negative moods, design property, inducement from neighbors, taste congruence, price property of apparel, positive moods, and loose-control, and were segmented into the low impulsive purchaser, the reasonable purchaser, the fulfilled with positive moods, and the high impulsive purchaser. The factors of impulsive purchase stimuli were apparel property, consumer service, sales promotion on the point of sales, and low price. 2. The low impulsive Purchaser was affected little by impulsive purchase stimuli, spent a little money on apparel, and the married with high education level were the most. The reasonable purchaser was affected by sales promotion on the point of sales or low price, spent a little money on apparel, and students or house-wives were the most The fulfilled with positive moods was affected by low price, and students or career women with high education level were the most, but spent less money on apparel. The high impulsive purchaser was affected by various impulsive purchase stimuli, the young unmarried with high education level were the most, and spent more money on apparel. 3. The younger, the unmarried, students or career women, and shoppers with higher income or apparel expenditure showed a higher impulsive purchase tendency for relax from negative mood, design property, for inducement from neighbor, taste congruence, and positive moods. 4. The older, the married, house wives, and shoppers with higher apparel expenditure were stimulated by apparel property or consumer services.

• Journal of Cadastre & Land InformatiX
• /
• v.45 no.2
• /
• pp.203-216
• /
• 2015

This study focuses on the relationship between housing sale prices and Jeonse prices, amid a recent surge of Jeonse price and Jeonse-to-housing sale price ratio. There are many studies about the relationship between house prices and Jeonse, but they couldn't fully explain what makes them spike up. In addition to this relationship, this paper deals with the difference of Jeonse system on regions and price levels. Using Granger causality and Spearman's Correlation Coefficient, the outcome is drawn. As the result, the expected rate for housing sale prices effects on the Jeonse-to-housing sale price ratio. The higher on sale price, the lower the Jeonse-to-housing sale price ratio regarding the region difference.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.9
• /
• pp.6315-6324
• /
• 2015

This study analyses the effects of household finances on rental price of apartment in Seoul which play a major role in real estate policy. We estimate VAR models using time series data. Economy variables such as sales price of apartment in Seoul, consumer price index, hiring rate, real GNI and loan amount of housing mortgage, which relate to household finances and influence the rental price of apartment, are used for estimation. The main findings are as follows. In the short term, the rental price of apartment is impacted by economy variables. Specifically, Relative contributions of variation in rental price of apartment through structural shock of economy variables are most influenced by their own. However, in the long term, household variables are more influential to the rental price of apartment. These results are expected to contribute to establish housing price stabilization policies through understanding the relationship between economy variables and rental price of apartment.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.31 no.4 s.163
• /
• pp.519-530
• /
• 2007

This study is an exploratory research on the brand architecture of Korean apparel enterprises and the differentiation strategy among in-house competing brands. For data analysis, secondary data was used. 20 apparel enterprises were used as the subjects. The results are as following. First, as a result of brand architecture composition, apparel enterprises used the strategy that initially paved the way launching several brands in a specific item category and after that diversified to other categories. Most enterprises used the multi-brand strategy operating plural brands in a same zoning. The terms for launching succeeding brands were about $1{\sim}5$ years. Second, as a result of analysing the cases which several brands competes within a same zoning, all the posterior brands had some differences from the prior ones. The most frequent differentiation factor was price. Concept, target age, and distribution channel followed. The order of the factors was somewhat different among the item categories. The differentiation strategy among in-house competing brands meant that the enterprises manage plural brands in a same zoning for the growth of whole market share instead of the direct competition among in-house brands. The results of this study can suggest a growth direction to the enterprises planning to launch new brands.

• International Area Studies Review
• /
• v.15 no.1
• /
• pp.219-240
• /
• 2011

The main purpose of this study is to analyze the effects of stock price and real estate price on the money demand. We investigated the demand for money for 25 money units of 10 countries. To estimate the money demand functions, Johansen's cointegration and ARDL-bounds test were employed. Additionally, Stock and Watson's DOLS method was applied to estimate long-run cointegration vectors. According to the results of cointegration test, stock price and real estate price are crucial in the long-run equilibrium relationship. There were no cointegration relationships among money demand, real income, interest rate, and exchange rate in 12 money unit models. However, by including stock price and real estate price on the tested models, we could find strong cointegration relationships, using ARDL-bounds test. The results of DOLS confirm that stock price and real estate price are effective factors influencing on money demands. Especially, the coefficient of real estate price is statistically significant in the 19 out of 20 money unit models. However, the direction and magnitude of coefficients of asset prices are different across countries and money units.

• Journal of Distribution Science
• /
• v.11 no.10
• /
• pp.63-72
• /
• 2013

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.

• Korean Journal of Agricultural Science
• /
• v.43 no.4
• /
• pp.603-611
• /
• 2016

The aim of this study was to analyze the contribution factors (backfat thickness, eye muscle area, carcass weight, marbling score, and feeding period) affecting meat unit price (South-Korean Won / Kg of meat). The best slaughtering age to maximize unit price was also assumed. All data used in this study were acquired from the Korea Institute for Animal Products Quality Evaluation from 2010 to 2014. Contributions to the estimated unit price of cows by the following factors, backfat thickness, eye muscle area, carcass weights, feeding period, and marbling score were 2.65%, 0.04%, 1.58%, 1.58%, and 95.72%, respectively. Contribution to estimated unit price of steers by the same factors (backfat thickness, eye muscle area, carcass weights, feeding period, and marbling score) were 7.88%, 1.24%, 0.07%, 90.81%, and 95.72%, respectively. Slaughtering ages ranged from 26 to 36 months and the data were separated into each month for an 11 month period. The unit price of meat from Hanwoo slaughtered at 30 months was highest among groups. The lowest unit price was observed in the group belonging to the Hanwoo slaughtered at 36 months. In conclusion, of all contributing factors, marbling score affected unit price the most. Based on our results, it is recommended that the optimal slaughtering age be set at 30 months to maximize unit price. Moreover, the feeding of beef cattle past 30 months of age is not recommended because of the increase in feeding costs.

• Land and Housing Review
• /
• v.10 no.1
• /
• pp.9-18
• /
• 2019

This study examined the dynamic change in the co-movement between the house price rates with the network methods of Mantegna (1999). First, Capital area and non-capital area form independent clusters which have the heterogeneous co-movement pattern. In other words, Capital and non-capital areas have low connectivity in the housing market. Also, if the co-movement between capital areas have been strengthened, the co-movement between non-capital areas have been weakened. The results of the dynamic analysis show that the degree of the co-movement in the housing market is continuously increased. The members of the co-movement group in the capital area are strongly steadied by all periods. However, the members in the non-capital area have been changed according to the period. Accordingly, it is necessary to establish policies based on various information for the housing market of the non-capital area rather than policies targeting the capital area. In addition, Apartments in Korea are more likely to be used as investment or speculative assets than other types of houses. It has been confirmed that this is Gangbuk, which is locatied in the northern part of Seoul, appears to be a region where the Spillover Effects of price fluctuation can be triggered in the housing and apartment market. However, the housing market in Gangnam, which is locatied in the southern part of Seoul, was divided into low systematic risk.

• Journal of Korean Society of Rural Planning
• /
• v.22 no.1
• /
• pp.93-100
• /
• 2016

Land price can be affected by convenience or psychological repulsion like PIMFY (Please In My Front Yard) or NIMBY (Not In My Back Yard) for various facilities. Services related to public establishment, welfare, medical attention, and amenities in rural areas are comparatively poorer than those in urban areas. The purpose of this study is to estimate the implications of the accessibility to community facilities in rural areas for land prices using a hedonic price model. The accessibility to facilities is estimated by real road distances and the land prices are applied for four types of land usages: field, rice paddy, building lots, and village halls. Community facilities are classified from public and community services view: education, safety, culture, transport, environment, health care, and finance. The results show that the accessibility to health care and transport can positively affect land prices and the accessibility to environment (waste facilities and junkyard) and unpleasant services (funeral hall and charnel house) can negatively affect land prices. Especially, the accessibility to hospital is the most positive influential factor for all types of land usages.

• Journal of Information Technology Services
• /
• v.21 no.3
• /
• pp.63-72
• /
• 2022

The extinction crisis of local cities, caused by a population density increase phenomenon in capital regions, directly causes the increase of vacant houses in local cities. According to population and housing census, Gunsan-si has continuously shown increasing trend of vacant houses during 2015 to 2019. In particular, since Gunsan-si is the city which suffers from doughnut effect and industrial decline, problems regrading to vacant house seems to exacerbate. This study aims to provide a foundation of a system which can predict and deal with the building that has high risk of becoming vacant house through implementing a data driven vacant house prediction machine learning model. Methodologically, this study analyzes three types of machine learning model by differing the data components. First model is trained based on building register, individual declared land value, house price and socioeconomic data and second model is trained with the same data as first model but with additional POI(Point of Interest) data. Finally, third model is trained with same data as the second model but with excluding water usage and electricity usage data. As a result, second model shows the best performance based on F1-score. Random Forest, Gradient Boosting Machine, XGBoost and LightGBM which are tree ensemble series, show the best performance as a whole. Additionally, the complexity of the model can be reduced through eliminating independent variables that have correlation coefficient between the variables and vacant house status lower than the 0.1 based on absolute value. Finally, this study suggests XGBoost and LightGBM based machine learning model, which can handle missing values, as final vacant house prediction model.