• The Korean Journal of Financial Studies
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• v.12 no.1
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• pp.89-104
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• 2006

이 논문은 자본조달순위이론(pecking order theory)을 한국 유가증권시장에 상장된 제조기업을 대상으로 실증적 검정을 하였다. 설명변수로 기업의 자금부족(deficit)과 부채비율과의 관계를 분석한 결과 자본조달순위이론이 지지되는 결과를 얻지 못하였으며, 통제변수에 유형자산, 기업규모, 수익성 등 전통적인 자본구조영향요인 변수들을 포함시켜 분석한 결과, 정보비대칭이론에 의한 설명이 적합한 것으로 해석되었다. 유형자산이 증가할수록 부채비율은 감소하였고, 기업규모가 증가하면 레버리지가 감소하는 관계를 나타냈으며, 수익성이 증가함에 따라 부채비율이 감소하는 것으로 분석되었다. 직전년도의 부채규모가 높은 경우에는 당해 연도의 부채사용이 감소하고, 직전년도의 레버리지가 낮은 경우에는 당해 연도의 부채가 증가하는 평균회귀현상을 나타냈다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.733-734
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• 2009

현대사회에서 인터넷의 비약적인 발전과 빠른 보급으로 우리가 접할 수 있는 정보의 양이 늘어나고 이들 중에서 필요한 정보만을 얻어내기에는 쉽지 않다. 특히 비구조적이고 정형화되지 않은 텍스트 데이터인 기사들을 텍스트마이닝을 이용하여 기사 헤드라인을 용어 단위로 구분하여 추출하고 데이터마이닝의 연관 규칙을 적용하여 빈발항목의 지지도와 용어간의 연관성을 통해 기사의 내용에 효과적으로 접근하는 시스템을 제안하고자 한다.

• Management & Information Systems Review
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• v.37 no.2
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• pp.169-185
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• 2018

Customers are not merely responders but rather active value creators. As a result most researches related to customer value creation behavior focus on customer participation behavior and interaction between service provider and customer. This study set the research model to examine the correlation between customer to customer interaction, brand attachment and customer value creation behavior. For this study, the relationship among social support, C-to-C social interaction, similarity, brand attachment, and customer value creation behavior were modelled and used to validate our hypotheses. A path model was verified with structural equation modeling using dataset from survey. Results of this study are summarized as follows. First, this study show the C-to-C social interaction, such as social support, C-to-C social interaction, similarity have effects on brand attachment. Thus, this was statistically significant although dismissed from hypothesis verification. Second, the structural correlation shows brand attachment has positive effect on customer value creation behavior The findings suggest that managers need to identify and pay attention to positive customer to customer interaction in the service encounter so that it influence customer brand attachment and customer value creation behavior which is the competitive advantages of service brand.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.39-52
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• 2006

With the recent the use of spatio-temporal data mining which can extract various knowledge such as movement patterns of moving objects in history data of moving object gets increasing. However, the existing movement pattern extraction methods create lots of candidate movement patterns when the minimum support is low. Therefore, in this paper, we suggest the STMPE(Spatio-Temporal Movement Pattern Extraction) algorithm in order to efficiently extract movement patterns of moving objects from the large capacity of spatio-temporal data. The STMPE algorithm generalizes spatio-temporal and minimizes the use of memory. Because it produces and keeps short-term movement patterns, the frequency of database scan can be minimized. The STMPE algorithm shows more excellent performance than other movement pattern extraction algorithms with time information when the minimum support decreases, the number of moving objects increases, and the number of time division increases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.147-156
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• 2011

With the increasing utility of the recent information system, the methods to pick up necessary products rapidly by using a lot of data has been studied. Association rule search methods to find hidden patterns has been drawing much attention, and the Apriori algorithm is a major method. However, the Apriori algorithm increases search time due to its repeated scans. This paper proposes an algorithm to reduce searching time of frequent items. The proposed algorithm creates matrix using transaction database and search for frequent items using the mean number of items of transactions at matrix and a defined minimum support. The mean number of items of transactions is used to reduce the number of transactions, and the minimum support to cut down on items. The performance of the proposed algorithm is assessed by the comparison of search time and precision with existing algorithms. The findings from this study indicated that the proposed algorithm has been searched more quickly and efficiently when extracting final frequent items, compared to existing Apriori and Matrix algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.548-560
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• 2018

This study was conducted to evaluate the effects of SCM on PM's capabilities and sustainable benefit sharing in leading global companies. To achieve this, statistical analyses were carried out through an empirical questionnaire survey of 426 PMs in SCM companies. The results showed that SCM commitment, vision and goal sharing have positive effects on PM's capabilities in leading global companies, boosting PM capability. Moreover, sustainable benefit sharing was improved along with SCM trust building, vision and goal sharing in global leading companies, supporting the usefulness of these variables. In contrast, SCM information sharing and trust building did not lead to significant acceleration of PM's capabilities, rejecting these variables. These findings indicate that SCM information sharing or trust building does not really help simple members to accelerate PM's capabilities.

• Research in Community and Public Health Nursing
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• v.12 no.1
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• pp.175-186
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• 2001

To evaluate the effect of informational support by hospice team on family caregivers of terminally ill cancer patients. 22 family caregivers of D University Hospital in Daegu city were participated. The research was conducted from Aug. 16th to Oct. 28th 2000 by using self-reported questionnaires. The instruments used in this study were the Weinert's scale of perceived social support. Spielberger's state anxiety inventory. CES-D. and Ellison and Paloutzian's spiritual well-being scale. The intervention was designed to give educational and counselling program up to 7 times within 4 weeks. Educational and counselling booklets which made by the researcher were used step by step by hospice team, he data were analysed frequency. percentage. Wilcoxon Singed Ranks Test with SPSS Win l0.0/PC. The results obtained from this study were as follows; 1. The perceived social support of family caregivers was significantly increased after ready planned informational support was applied by hospice team(z=-3.045. p=0.002). 2. The anxiety of family caregivers was significantly reduced after ready planned informational support was applied by hospice team(z =-3:348. p=0.001). 3. The depression of family caregivers was significantly reduced after ready planned informational support was applied by hospice team(z=-3.641. p=0.000). 4. The spiritual well-being score of family caregivers was not significantly improved after ready planned informational support was applied by hospice team(z=-0.422. p=0.673). In conclusion. the results of this study clearly suggests that the informational support provided by hospice team not only increased the family caregivers' who are caring for terminally ill cancer patients. Therefor the informational support program designed by researcher for family caregivers who are caring for terminally ill cancer patients should be utilized and expended.

• 한국벤처창업학회:학술대회논문집
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• 2020.11a
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• pp.55-59
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• 2020

정부는 고용 없는 성장이 이어지는 현재의 경제구조에서 국가 경제의 활력을 위한 실마리를 찾고자 한다. 새로운 일자리를 창출하고 기업 활동에 새로운 혁신을 도입하여 국가 경제의 성장과 발전에 기여할 수 있는 방안으로 창업을 활성화하는 정책개발과 지원에 적극적인 노력을 기울이고 있다. 많은 국가들이 창업을 촉진하여 일자리를 제공하고 있으며 우리나라 역시 창업을 활성화하기 위하여 정부 차원에서 창업 지원정책을 확대해 나가고 있다. 창업 활성화를 위해서는 창업을 기회로 인식하거나 지지하는 문화가 성숙하는 개인의 창업에 대한 인식 개선과 더불어 창업의지 함양 등이 필요하다. 이들 요인에 영향을 주는 요인으로 개인적 특성, 심리적 특성, 기업가정신, 창업 교육, 멘토링, 창업지원 프로그램 등의 요인에 대하여 개별적으로 많은 연구가 수행되어 왔다. 이들 개별적인 요인들과 창업 의지와의 관계를 잘 확인하기 위해서 자기효능감, 위험감수성, 실패부담감, 환경적 요인 등을 확인하는 연구가 다수 시도되었다. 본 연구에서는 예비창업자의 창업의지에 미치는 창업지원정책과 창업가 역량을 중심으로 실증연구를 진행하고자 한다. 또한 창업지원정책과 창업가 역량과 창업의지의 관계에서 멘토링의 조절효과를 검증하고자 한다.

• Journal of dental hygiene science
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• v.15 no.4
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• pp.465-471
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• 2015

The purpose of this study was to investigate the effects of educational training and psychosocial characteristics such as self-efficacy and social support on job involvement in dental hygienists. A total of 418 dental hygienists who were working in S, I and G area were recruited in this study. A self-administered questionnaire was used to evaluate individual and job characteristics, educational training, self-efficacy and social support of the study subjects. Hierarchical regression analysis was performed to examine the relationship of individual and job characteristics, educational training, self-efficacy and social support to job involvement. All statistical analyses were performed using the IBM SPSS Statistics ver. 20.0 for Windows, and p<0.05 was considered significant. The results show that learning experiences of liberal arts or social sciences as a part of college curriculum (t=-2.406), self-efficacy (t=3.728) and social support at work (t=4.391) were significantly associated with job involvement in dental hygienists. Dental hygienists who were having experiences of liberal arts or social sciences as a part of college curriculum, showing higher levels of self-efficacy, and receiving adequate social support from supervisors or coworkers at work were more likely to feel job involvement. They explained 17.4% of total variance of job involvement. This result suggests that experiences of liberal arts or social sciences as a part of college curriculum, higher levels of self-efficacy, and adequate social support from supervisors or coworkers at work might play an important role in increasing job involvement of dental hygienists. It is strongly required to develop individual and organizational program or training to promote a positive attitude to their job as a key professionals in the field of dental health, and to increase job involvement of dental hygienists.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.293-302
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• 2016

Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.