• Journal of the Economic Geographical Society of Korea
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• v.4 no.2
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• pp.79-96
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• 2001

This paper introduces a new type of industrial cluster developed at the CBD of Seoul. Conventionally, clusters are said to be consisted of hi-tech, often If activities, manufacturing industries or artisan craft industries with increasing vertical integration and performance usually supported by venture capitals and favorable business infrastructure, not to mention governments', be it central or local, incentive plans. The study area, Cheonggyechon region has long been a traditional CBD frame of Seoul, Korea, being troubled by deterioration, traffic jams, and environmental degradation as most inner cities experience. Recently. this region has transformed to the most dynamic and productive area not by IT industries but by apparel and fashion activities. The study of the developmental trajectory and key characteristics for this kind of industrial cluster can give us insight both for the transition of inner city and for the cluster theory. This Paper firstly briefly Profiles the growth of the Cheonggyechon region over the past decade. It then shows the current spatial and business structure of the new industrial cluster, focusing on the fact that transactions costs are reduced, the creation and flow of information improves. and the local institutions are prone to be most responsive to the new cluster's specialized needs. The third section presents the key components of the customized production-distribution-shopping cluster development process, emphasizing the localized networking. social capital, spontaneous institutionalization of associational economic climate, and cultural economy based on place-specific inertia. The paper concludes with some comments about the prospects and perils of the new industrial cluster of Seoul.

• Korean Journal of Social Welfare Studies
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• no.39
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• pp.315-342
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• 2008

The aim of this study was to examine growth trajectories of delinquent behaviors during adolescence. In addition, the effects of protective and risk factors that might account for individual difference in the level of delinquent behaviors and in the rate of change were examined. Four waves of data in the Korea Youth Panel Survey(KYPS) were used to analyze the linear growth modeling. The sample consisted of 3346 adolescents who were assessed at 4 measurement waves with approximately 1-year intervals. The results showed significant individual differences in both final level of delinquent behaviors and in the rate of change across 3 measurement occasions. Adolescent gender, family's socioeconomic background predicted the final level and the rate of change of delinquent behaviors. The protective effects of positive parenting and self-control were significantly associated with problem behaviors and the risk effects of the association with deviant peers and negative stigma were significant on the final level of delinquency. Self-control and deviant peer affiliation had differential influences over time significantly. Practice and policy implications as well as further research topic were discussed in the light of searching for important factors in preventing adolescent problem behaviors.

• Journal of Korean Society of Forest Science
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• v.100 no.2
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• pp.240-245
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• 2011

Vegetation changes were studied for 16 yr in clearcut logged Pinus densiflora forests in the southern Gangwon-do province in Korea by applying chronosequence approach. Ambient temperature and relative humidity, Detrended Correspondence Analysis (DCA), Multiple Responses Permutation Procedure (MRPP), Indicator Species Analysis (ISPAN) were used to examine successional trajectory and compositional changes. After clearcutting, canopy openness was increased abruptly at three folds (1yr 68.3% and R1 23.0%) and then decreased, but relative moisture was slightly decreased (6%) compare to control site. In the result of DCA, right after clear cutting, vegetation composition was developed heterogeneously compared to control sites, and then approached to control sites within 16 years. Based on MRPP, species composition of each developmental stages (1yr, 3yr, 10yr and 16yr) revealed signigicant differences to that of control vegetation (R1, R3, R10 and R16). Indicator species in 1yr and 3yr samples included various woody species rather than herbaceous species, but in 10yr and 16yr, herbaceous were more abundant. Earlier succession of pine forests likely can explain to Initial Floristic Composition (IFC) Model.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.142-148
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• 2023

Objectives : The purpose of this study is to investigate the relationships between premonitory urge, tic severity, and comorbidities in children and adolescents with chronic tic disorders. Methods : In this study, scales for tic symptoms, premonitory urge, obsessive-compulsive symptoms, and ADHD symptoms were repeatedly measured twice in 26 children and adolescents aged 10 to 18 years with chronic tic disorders. Correlations between scales were confirmed through repeated measures correlation analysis, and causal relationships between scales were confirmed through regression analysis using a linear mixed model. Results : The degree of premonitory urges showed a significant positive correlation with the severity of tic symptoms, the severity of obsessive-compulsive symptoms, and the severity of ADHD symptoms. The ADHD symptoms showed a significant positive correlation with the severity of tic symptoms. These results were the same even in children and adolescents with tic disorders who were not diagnosed with obsessive-compulsive disorder. Additionally, premonitory urges were found to have a significant positive effect on the severity of tic symptoms. Conclusions : These results may be helpful in treating tic disorders and can be used in future tic disorder research considering developmental trajectory.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.21-35
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• 2023

Expectations surrounding generative AI technology and its profound ramifications are sweeping across various industrial domains. Given the anticipated pivotal role of the startup ecosystem in the utilization and advancement of generative AI technology, it is imperative to cultivate a deeper comprehension of the present state and distinctive attributes characterizing venture capital (VC) investments within this domain. The current investigation delves into South Korea's landscape of VC investment deals and prognosticates the projected VC investments by juxtaposing these against the United States, the frontrunner in the generative AI industry and its associated ecosystem. For analytical purposes, a compilation of 286 investment deals originating from 117 U.S. generative AI startups spanning the period from 2008 to 2023, as well as 144 investment deals from 42 South Korean generative AI startups covering the years 2011 to 2023, was amassed to construct new datasets. The outcomes of this endeavor reveal an upward trajectory in the count of VC investment deals within both the U.S. and South Korea during recent years. Predominantly, these deals have been concentrated within the early-stage investment realm. Noteworthy disparities between the two nations have also come to light. Specifically, in the U.S., in contrast to South Korea, the quantum of recent VC deals has escalated, marking an augmentation ranging from 285% to 488% in the corresponding developmental stage. While the interval between disparate investment stages demonstrated a slight elongation in South Korea relative to the U.S., this discrepancy did not achieve statistical significance. Furthermore, the proportion of VC investments channeled into generative AI enterprises, relative to the aggregate number of deals, exhibited a higher quotient in South Korea compared to the U.S. Upon a comprehensive sectoral breakdown of generative AI, it was discerned that within the U.S., 59.2% of total deals were concentrated in the text and model sectors, whereas in South Korea, 61.9% of deals centered around the video, image, and chat sectors. Through forecasting, the anticipated VC investments in South Korea from 2023 to 2029 were derived via four distinct models, culminating in an estimated average requirement of 3.4 trillion Korean won (ranging from at least 2.408 trillion won to a maximum of 5.919 trillion won). This research bears pragmatic significance as it methodically dissects VC investments within the generative AI domain across both the U.S. and South Korea, culminating in the presentation of an estimated VC investment projection for the latter. Furthermore, its academic significance lies in laying the groundwork for prospective scholarly inquiries by dissecting the current landscape of generative AI VC investments, a sphere that has hitherto remained void of rigorous academic investigation supported by empirical data. Additionally, the study introduces two innovative methodologies for the prediction of VC investment sums. Upon broader integration, application, and refinement of these methodologies within diverse academic explorations, they stand poised to enhance the prognosticative capacity pertaining to VC investment costs.