• Journal of the Korean association of regional geographers
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• v.15 no.4
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• pp.510-523
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• 2009

Geodemographics(GD) can be defined as an analytical approach of socio-economic and behavioral data about people to investigate geographical patterns. GD is based on the assumptions that demographical and behavioral characteristics of people who live in the same neighborhood are similar and then the neighborhoods can be categorized with spatial classifications with the geographical classifications. Thus, this paper, in order to identify the applicability of the geographical classification of the GD, explores the concepts of the geodemographics into Seoul city areas with Korea census data sets that contain key characteristics of demographic profiles in the area. Then, this paper attempt to explain each area classification profile by using clustering techniques with Ward's and k-means statistical methods. For this as as as, this paper employs 2005 Census dataset released by Korea National Statistics Office and the neighborhood unit is based on Dong level, the smallest administrative boundary unit in Korea. After selecting and standardizing variables, several areas are categorized by the cluster techniques into 13, this paps as distinctive cluster profiles. These cluster profiles are used to cthite a short description and expand on the cluster names. Finally, the results of the classification propose a reasonable judgement for target area types which benefits for the people who make a spatial decision for their spatial problem-solving.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.195-209
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• 2021

According to the 2019-2020 social media usage survey conducted by the Seoul e-commerce center, 5 out of 10 consumers have experienced shopping through social media. The cost of traditional advertising media has been reduced and advertising spending on social media has risen by 74%, indicating that social media is becoming a more important marketing element. While the number of users of social media has increased and corporate marketing activities have increased accordingly, research has been conducted in various aspects of marketing such as user motivation for social media, satisfaction, and purchase intention. There was no subdivided study on the differences in the social media usage frequency of consumers in actual purchasing behavior. This study attempted to identify differences in consumer characteristics by cluster in the agrifood purchase situation by grouping them by type according to the frequency of use of social media for consumers who purchase agri-food online. Product involvement, product need, and online purchase channel Consumer characteristics such as demographic distribution, perceived risk, and eating and lifestyle in each cluster were checked for the three agrifood purchase situations including choice, and types for each cluster were presented. To this end, questionnaire data on the frequency of social media use and online agrifood purchase behavior were collected from 245 consumers, and the validity of the measurement variables was secured through factor analysis and reliability analysis. As a result of cluster analysis according to the frequency of social media use, it was divided into three clusters. The first cluster was a group that mainly used open social media, and the second cluster was a group that used both open and closed social media and online shopping malls; The third cluster was a group with low online media usage overall, and the characteristics of each cluster appeared. Through regression analysis, the effect on product involvement, product need, and purchase channel selection when purchasing agri-food online through each of the three clusters was confirmed through regression analysis. As a result of the regression analysis, the characteristic of cluster 1 in the situation of purchasing agri-food online is a male in his 30s living in a rural area who has no reluctance to purchase agri-food on social media or online shopping malls. The characteristics of cluster 2 are mainly consumers who are interested in purchasing health food, and the consumer characteristics are represented. In the case of cluster 3, when purchasing products online, they purchase after considering quality and price a lot, and the consumer characteristics are represented as people who are more confident in purchasing offline than online. Through this study, it is judged that by identifying the differences in consumer characteristics that appear in the agri-food purchase situation according to the frequency of social media use, it can be helpful in strategic judgments in marketing practice on social media customer targeting and customer segmentation.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.191-206
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• 2016

Pedestrian performance measurement has generally used the average values of pedestrian volumes and speeds from a sample, although each individual's pedestrian behavior of the sample is mainly affected by his/her socio-economic and physical characteristics. In particular, if such individual characteristics of the sample have wide variations, the average values are hard to be representative. In this respect, this study found that a platoon of pedestrians had a major effect on their pedestrian flows on sidewalks. The more platoons was mixed on pedestrian roads, the lower pedestrian flow rate was. The indexes such as a pedestrian flow rate and an occupancy space are typically calculated by pedestrian volumes in a given period of time regardless of the existence of a platoon. However, it is plausible that a pedestrian speed and a level of pedestrian congestion can be different under the equal amount of pedestrian volumes. Therefore, this study suggested criteria for determining level of service for pedestrian considering platoon effects and confirmed that two places had different pedestrian LOSs because of the platoon effects, even if they showed the same pedestrian flow rate.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.1
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• pp.19-30
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• 2021

This research studied the effect of visual improvement of "72 Hour Project" that has regenerated small scale derelict spaces in Seoul through citizen participation. 29 projects built form 2016 to 2019 were analyzed. The research analyzed landscape image preference of before and after status of projects using 12 pairs of landscape adjectives. Basic statistical analysis, correlation analysis, factor analysis, cluster analysis, and ANOVA were performed based on the survey results. Since the satisfaction level of the projects compared with the before-condition was 3.63 higher than 3.00, it could be concluded that there was an meaningful effect of visual improvement after completion of the projects. As the result of the factor analysis, landscape adjective pairs were categorized into two factors: harmony and aesthetics. Through the cluster analysis, four clusters were formed and characteristics of each cluster were identified. As the result of rhe cluster analysis, the cluster with the high harmony level and the aesthetics level showed the highest overall satisfaction level. Comparing each cluster, it could be concluded that the factor of harmony was more important than the factor of aesthetics in evaluating the satisfaction level of projects. Analyzing qualitative aspects of project groups, spatially well-balanced design with generous vegetation areas was more effective in landscape improvement than artistic design with visually strong installations. Further researches based on behavior studies of actual users are required to compensate the limits of this research. This research can contribute to establish the improved direction of policies to regenerate various types of small scale derelict spaces.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.167-181
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• 2023

This study utilized TEXTOM, a social network analysis program to analyze changes in current tourism behavior after travel restrictions were eased after the outbreak of COVID-19. Data on the keywords 'domestic travel' and 'overseas travel' were collected from blogs, cafes, and news provided by Naver, Google, and Daum. The collection period was set from April to December 2022 when social distancing was lifted, and 2019 and 2020 were each set as one year and compared and analyzed with 2022. A total of 80 key words were extracted through text mining and centrality analysis was performed using NetDraw. Finally, through the CONCOR, the correlated keywords were clustered into 4. As a result of the study, tourism behavior in 2022 shows tourism recovery before the outbreak of COVID-19, segmentation of travel based on each person's preferred theme, prioritization of each country's corona mitigation policy, and then selecting a tourist destination. It is expected to provide basic data for the development of tourism marketing strategies and tourism products for the newly emerging tourism ecosystem after COVID-19.

• Culinary science and hospitality research
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• v.16 no.2
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• pp.232-242
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• 2010

The purpose of this study is to provide basic data for forthcoming liquor development and market diversification by finding out the consumers' characteristics related to their patterns of choosing liquor and identifying the liquor consuming patterns. For the study, a survey questionnaire was composed of 11 questions related to the considerations by the consumers in choosing liquor, 5 questions on their demographics, and 5 questions on the types of choosing liquor. The survey was conducted between October 21st and November 1st of 2007 to 400 adults over 19 years old residing in Korea, and then sorted out 377 out of 400 for the analysis. As for the analysis, frequency analysis, K-means clustering, and correspondence analysis were employed. In order to find out the choice considerations associated with the perception of liquor, consumers were divided into four equivalent groups, and liquor consuming patterns and demographics were investigated based on the empirical study.

• The Journal of Bigdata
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• v.6 no.2
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• pp.139-149
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• 2021

Ddareungi, a public bicycle service in Seoul, establishes itself as a means of daily transportation for citizens in Seoul. We speculated that the pattern of using Ddareungi may have changed since COVID-19. This study explores changes in using Ddareungi after COVID-19 with descriptive statistical analysis and network analysis. The analysis results are summarized as follows. The average traveling distance and average traveling speed have decreased over the entire time in a day since COVID-19. The round trip rate has increased at dawn and morning and has decreased in the evening and night. The average weighted degree and average clustering coefficient have decreased, and the modularity has increased. The clusters, located north of the Han River in Seoul, had a similar geographic distribution before and after COVID-19. However, the clusters, located south of the Han River, had different geographic distributions after COVID-19. Traveling routes added to the top 5 traffic rankings after COVID-19 had an average traveling distance of fewer than 1,000 meters. We expect that the results of this study will help improve the public bicycle service in Seoul.

• Korean Journal of Environment and Ecology
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• v.9 no.2
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• pp.250-268
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• 1996

1992년 브라질 리우데자네이루에서 개최된 유엔환경개발회의(UNCED)이후 세계는 환경보전의 중요성이 크게 제고되었고, 다가올 21세기는 환경의 시대라 불리고 있으며, 특히 국립공원은 생물다양성을 보존하는 성역으로서의 역할을 담당하게 되었다. 그러므로 이제는 인류가 생각한 최고의 이념이라고도 불리는 국립공원의 숭고한 정신을 살리고 21세기 환경시대를 살아갈 후손들이 지속적으로 이용할 수 있도록 하는 국립공원의 관리정책이 요구된다고 할 수 있겠다. 본 고는 환경생태학회의 국립공원분과에서 1995년 1년동안 오대산 국립공원을 대상으로 실시한 식물상, 식물군집구조, 조류 및 곤충상, 등산로훼손 및 주연부 식생구조, 산림경관인식 및 이용자 행태 등의 조사결과를 바탕으로 오대산 국립공원의 현황과 문제점을 검토하고 관리개선방안을 제시하는 것을 목적으로 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.394-395
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• 2023

본 연구는 최근 서울시의 모든 지역이 과밀억제권역에 해당되는 문제를 해결하는 방법을 분석하였다. 서울시 행정동별 소득수준, 사업체 통계, 거주인구 데이터, 매출액, 대중교통 승차 승객 수 등의 변수를 활용하여 2번의 클러스터링을 거쳐 진행하였다. 2번에 걸쳐 클러스터링 된 군집별 특징을 바탕으로 서울시 내 미비 업종 진단을 제안한다.

• Economic Analysis
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• v.27 no.1
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• pp.67-90
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• 2021

This study found an interesting fact that the nonlinear relationship structure between volatility and trading volume changed before and after the COVID-19 pandemic according to empirical analysis using Bitcoin (BTC) market data that sensitively reflects investors' trading behavior. That is, their relationship appeared positive (+) in a stable market state before COVID-19 pandemic, as in theory based on the information flow paradigm. In a state under severe market stress due to COVID-19 pandemic, however, their dependence structure changed and even negative (-). This can be seen as a consequence of increased market stress caused by COVID-19 pandemics from a behavioral economics perspective, resulting in structural changes in the asset market and a significant impact on the nonlinear dependence of volatility and trading volume (in particular, their dependence at extreme quantiles). Hence, it should be recognized that in addition to information flows, psychological phenomena such as behavioral biases or herd behavior, which are closely related to market stress, can be a key in changing their dependence structure. For empirical analysis, this study performs a test of Ross (2015) for detecting a structural change, and proposes a Copula Regression Quantiles (CRQ) approach that can identify their nonlinear relationship structure and the asymmetric dependence in their distribution tails without the assumption of i.i.d. random variable. In addition, it was confirmed that when the relationship between their extreme values was analyzed by linear models, incorrect results could be derived due to model specification errors.