• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.4
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• pp.408-420
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• 2011

This study identifies the fashion luxury customer segments grouped by expenditures and the number of purchasing brands to verify the effects of perceived luxury consumption values on the intention to maintain a brand relationship for each group. A survey questionnaire was developed and implemented to collect data to measure fashion luxury expenditures, number of purchasing brands, luxury customer values, intention to maintain brand relationships, and demographic variables. A total of 326 responses were analyzed by factor analysis, multiple regression, one-way ANOVA, and $X^2$ analysis with SPSS18.0. Respondents were grouped by luxury expenditures; in addition, the number of purchasing brands were grouped into four segments of Switching/Heavy (31.6%), Switching/Light (19.9%), Loyal/Heavy (31.3%), and Loyal/Light (7.2%) Customer Group, that was different in terms of age and marital status. When the luxury customer value for the most patronized luxury brand was factor analyzed, five distinctive sub dimensions were identified, such as Social Value, Aesthetic/Expressive Value, Experiential Value, Quality Value, and Economic Value. For the Loyal/Heavy Group, the Experiential Value had a significant effect on the customer intention to maintain a brand relationship. For the Loyal/Light group, the Aesthetic /Expressive and Economic Value had a significant effect, and for the Switching/Heavy and Switching/Light Group, Quality and Economic Value had a significant effect on the customer intention to maintain a brand relationship. In conclusion, each luxury customer value in the behavioral segments works differently in influencing the intention to maintain a brand relationship. In addition, the implications for retail strategy were discussed based on the findings.

• Economic and Environmental Geology
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• v.47 no.3
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• pp.237-246
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• 2014

In this study, it is estimated how many changes of macroeconomic variables are happened under the proposition of import substitution of mining products 1% using macroeconometric input-output model. For this, used macroeconometric input-output model is composed of 141 behavioral equations representing the macroeconomy structure. In general, macroeconometrics models are constructed mainly on the side of the expenditure then it is not easy to estimate the effects of the shocks occurred from industry level. To mitigate that, this study tries to construct a macroeconometric input-output model. Macroeconometrics model which is useful to estimate the effects of macroeconomic shocks, economic policy and more, in this study, is linked with input-output table through the NDI(national disposable income) derived from compensation of employee. And this paper presents the estimation results of import substitution effects of mining products on Korean economy. As a results, GDP is increased 0.00073%, gross labor employed 0.00029%, current balanace 0.00010% and unemployment rate is mitigated 0.00233%.

• The Journal of Industrial Distribution & Business
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• v.9 no.10
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• pp.73-82
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• 2018

Purpose - Unstable vegetable prices have been one of the major concerns in Korean agricultural and food marketing system. The Korean government has implemented a number of policy instruments, including government purchasing programs in order to alleviate fluctuations in vegetable prices. The economic impact of policy instruments has been assessed based on the average monthly price change rate before and after the implementation of the policy. However, this approach failed to provide a net impact of policy measures on price stabilization in the vegetable markets, as policy impacts could not be successfully distinguished from other effects on price changes in the vegetable market. The purpose of this study is to evaluate the net impact of the government purchasing program on the price volatility of dried red pepper which is considered one of the major vegetables in Korea. Research design, data, and methodology - This study develops a monthly dynamic partial equilibrium model of Korean dried red pepper market. Behavioral equations in the model were estimated by OLS and synthetic method based on the annual and monthly time series data from 1993 to 2015. The model is first simulated to yield actual dried red pepper market conditions in 2015 as a baseline and then compared it to the scenario assuming that there were no government purchases of dried red pepper in 2015. Results - According to the ex-post scenario analysis using the developed model, without the government procurements in 2015, the average monthly price change rate and the value of coefficient of variation of dried red pepper in 2015 would be respectably 7.9 percent and 0.10. It is relatively higher than the actual average monthly price change rate and the value of coefficient of variation of dried red pepper in 2015 which were respectively 1.7 percent and 0.06. Conclusions - The ex-post simulation results in this study shows that if there were no government purchases of dried red pepper in 2015, the dried red pepper market would have had much higher volatile price movements. The results of this study would provide useful information for future price stabilization policy of vegetable markets in Korea.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.619-624
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• 2016

Social-aware video displays not only the relationships between characters but also diverse information on topics such as economics, politics and culture as a story unfolds. Particularly, the speaking habits and behavioral patterns of people in different situations are very important for the analysis of social relationships. However, when dealing with this dynamic multi-modal data, it is difficult for a computer to analyze the drama data effectively. To solve this problem, previous studies employed the deep concept hierarchy (DCH) model to automatically construct and analyze social networks in a TV drama. Nevertheless, since location knowledge was not included, they can only analyze the social network as a whole in stories. In this research, we include location knowledge and analyze the social relations in different locations. We adopt data from approximately 4400 minutes of a TV drama Friends as our dataset. We process face recognition on the characters by using a convolutional- recursive neural networks model and utilize a bag of features model to classify scenes. Then, in different scenes, we establish the social network between the characters by using a deep concept hierarchy model and analyze the change in the social network while the stories unfold.

• Journal of Distribution Science
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• v.13 no.8
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• pp.61-71
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• 2015

Purpose - Before the year 2000, the housing prices in Korea were increasing every decade. After 2000, for the first time, Korea experienced a decrease in housing prices, and the repetitive cycle of price fluctuation started. Such a "boom and bust cycle" is a worldwide phenomenon. The current study proposes a mathematical model to explain price fluctuation cycles based on the theory of consumer psychology. Specifically, the model incorporates the effects of buyer expectations of future prices on actual price changes. Based on the model, this study investigates various independent variables affecting the amplitude of price fluctuations in housing markets. Research design, data, and methodology - The study provides theoretical analyses based on a mathematical model. The proposed model uses the following assumptions of the pricing mechanism in housing markets. First, the price of a house at a certain time is affected not only by its current price but also by its expected future price. Second, house investors or buyers cannot predict the exact future price but make a subjective prediction based on observed price changes up to the present. Third, the price is determined by demand changes made in previous time periods. The current study tries to explain the boom-bust cycle in housing markets with a mathematical model and several numerical examples. The model illustrates the effects of consumer price elasticity, consumer sensitivity to price changes, and the sensitivity of prices to demand changes on price fluctuation. Results - The analytical results imply that even without external effects, the boom-bust cycle can occur endogenously due to buyer psychological factors. The model supports the expectation of future price direction as the most important variable causing price fluctuation in housing market. Consumer tendency for making choices based on both the current and expected future price causes repetitive boom-bust cycles in housing markets. Such consumers who respond more sensitively to price changes are shown to make the market more volatile. Consumer price elasticity is shown to be irrelevant to price fluctuations. Conclusions - The mechanism of price fluctuation in the proposed model can be summarized as follows. If a certain external shock causes an initial price increase, consumers perceive it as an ongoing increasing price trend. If the demand increases due to the higher expected price, the price goes up further. However, too high a price cannot be sustained for long, thus the increasing price trend ceases at some point. Once the market loses the momentum of a price increase, the price starts to drop. A price decrease signals a further decrease in a future price, thus the demand decreases further. When the price is perceived as low enough, the direction of the price change is reversed again. Policy makers should be cognizant that the current increase in housing prices due to increased liquidity can pose a serious threat of a sudden price decrease in housing markets.

• Health Policy and Management
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• v.29 no.4
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• pp.469-481
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• 2019

Background: As South Korea is becoming an aged society very rapidly, the increase in osteoarthritis prevalence raises various public health issues in this country. This study aimed to explore the socio-demographic factors associated with osteoarthritis in the current Korean elderlies. Methods: Using the National Survey of Korean Elderly data (2014, 2017), we analyzed 20,326 elderlies (males, 8,248; females, 12,078) and conducted multivariate logistic regression analyses by sex. The dependent variable is whether a participant was diagnosed with osteoarthritis or not. Independent variables of interest is socio-demographic factors such as age, marital status, household type, residential area, household income, religion, the longest job, the number of close relatives, the number of close friends, and survey year. Control variables are various health behavioral factors and disease-related factors. Results: Prevalence of osteoarthritis was 19.2% in male elderlies and 47.0% in female elderlies. According to the results of the multivariate logistic regression adjusted for all studied control variables, the odds ratio (OR) for having osteoarthritis of under-elementary school graduates (their counterpart was college graduate group) was 1.81 (95% confidence interval [CI], 1.29-2.52) in males and 1.67 (95% CI, 1.12-2.47) in females. The OR of those having a job in agriculture & forestry fishery as their longest job (their counterpart was those who had never participated in labor force during their lifetime) was 5.07 (95% CI, 1.46-17.58) in males and 1.49 (95% CI, 1.27-1.74) in females. In males, the second-low quartile group in household yearly income (their counterpart was the highest quartile group) had the OR of 1.22 (95% CI, 0.98-1.53). In females, the OR of those having a religion of Buddhism (their counterpart was those having no religion) was 1.20 (95% CI, 1.07-1.35) and the OR of those who had no relatives (their counterpart was those having more than 3 close relatives) was 1.31 (95% CI, 1.10-1.56). Conclusion: This study found that in Korean elderlies, education, the longest job, household income, religion, and the number of close relatives are associated with their suffering from osteoarthritis. Further study and designing appropriate interventions are needed to alleviate current and future individual and socioeconomic burdens of osteoarthritis in an aged society like South Korea.

• Journal of the Korean GEO-environmental Society
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• v.13 no.3
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• pp.53-58
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• 2012

In general, sand compaction pile(SCP) method and gravel compaction pile(GCP) method have been mainly used to reinforce soft soils such as soft clay or loose sandy ground. But the sand compaction pile method has problems such as lack of sand supply and destroying the nature while collecting sand, the gravel compaction pile method has a problem such as decreased permeability of the drainage material due to clogging. Recently, the study to replace sand with bottom ash which has similar engineering properties with sand is in active. As a fundamental research on bottom ash mixture compaction pile utilizing bottom ash, its behavioral characteristics depending on granular materials and replacement ratio has been simulated numerically. In particular, Settlement Reduction Ratio(SRR) according to the distance from the center of pile was calculated. The main findings were as follows. Change values of Mixture Compaction Pile's SRR according to granular materials showed similar patterns and stiffness of the composite soil is increased depending on the replacement ratio so SRR showed decreased patterns. Especially, when the replacement ratio is in 20~40%, it increase significantly. When the replacement ratio is over 40%, it increase slowly. When considering the economics, 30~40% replacement ratio is appropriate.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.169-185
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• 2017

Given that nowadays things get very fast due to the pervasive use of the Internet and mobile devices, decision-making time can be an important variable in the online economic decisions. Although in experimental and behavioral economics, measures like scores or earnings are usually preferred, this study argues that the time variable can be dealt with as a new decision outcome. Thus, by selecting some psychological factors presumably impactful in the online context (i.e., incidental emotions, psychological distances, and individual's impulsivity), this study tested their effect on decision time in the online centipede game. As a result, the mean decision time in the game was longer (1) in the happiness condition than in the anger condition and (2) in the friend condition than in the stranger condition. The people with attention difficulties spent a short time in the decision and the people who dislike complex problems spent a short time in explaining their decision. This study can contribute to the field as it used the decision time as the dependent variable and it tested the effect of psychological factors in the context of online decision-making. Future studies can be conducted in other online decision situations or by considering other psychological variables.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.9-16
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• 2017

Organizational culture provides organizational members with identity, homogeneity and behavioral guidance, and promotes organizational commitment and enhances the stability of social systems. What organizational culture positively influences organizational performance? In this study, we tried to categorize organizational culture as creativity, change, cooperation, trust and knowledge sharing for specific public institutions and to diagnose the organizational culture by examining the level of recognition of the organizational members. The purpose of this study is to investigate the effect of organizational culture on organizational culture. The result of this study shows that the degree of future - oriented and cooperative culture of the public institutions that are the subject of research is not so high. In order to improve the performance of the organization, it is necessary to create a futuristic and cooperative culture. In order to create such a culture, various efforts must be made to continuously communicate and build trust among the members of the organization. In particular, leadership efforts to distribute, transfer, and trust authority to subordinates are a priority. In other words, it is very difficult to build a future-oriented, collaborative culture successfully without the efforts of managers.

• Journal of Technology Innovation
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• v.30 no.1
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• pp.57-104
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• 2022

The government has supported the innovation of private firms by intervening the market for various purposes, such as preventing market failure, alleviating information asymmetry, and allocating resources efficiently. Although the government's R&D budget increased rapidly in the 2000s, it is not clear whether the government intervention has made desirable impact on the market. To address this, the current study attempts to explore this issue by doing a systematic literature review on foreign and domestic papers in an integrated way. In total, 168 studies are analyzed using contents analysis approach and various lens, such as policy additionality, policy tools, firm size, unit of analysis, data and method, are adopted for analysis. Overlapping policy target, time lag between government intervention and policy effects, non-linearity of financial supports, interference between different polices, and out-dated R&D tax incentive system are reported as factors hampering the effect of the government intervention. Many policy prescriptions, such as program evaluation indices reflecting behavioral additionality, an introduction of policy mix and evidence-based policy using machine learning, are suggested to improve these hurdles.