• Journal of Digital Convergence
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• v.15 no.5
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• pp.27-36
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• 2017

SNS has been emerged as an effective educational tool in college and many studies on various teaching models and methodologies have been made in order to utilize SNS in education. The purpose of this paper is to empirically investigate the effect of affecting factors of SNS on learner's attitude, intention to re-use and performance in converging college educational environment. Self-efficacy on media usage, educational expectancy, subjective norm, habit, and enjoyment were identified as affecting factors based on prior researches. An empirical analysis was attempted by survey targeting college students. The results of structural equation model using Smart PLS shows that educational expectancy, subjective norm, and enjoyment are significantly related to the learner's attitude on use of SNS in college education, but Self-efficacy on media usage and habit are not. Learner's attitude on SNS in college education was found to be significantly related to the intention to continuous use and performance. This study implicates that using SNS in university class makes learner's attitude positively and finally lead to good performance. The analysis results can provide a guideline of effective strategy for SNS utilization in college education.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.1
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• pp.56-70
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• 2020

This study identifies the impact of social network service (SNS) on the spatial characteristics of retail stores locations in the hyper-connected society, which have been closely related to the everyday lives of urban residents. In particular, we focus on the changes in the spatial distribution of restaurants since the information retrieval process was added to the decision-making process of a consumer's restaurant selection. Empirically, we analyze restaurants in Seoul, Korea since the smart-phone was introduced. By applying the kernel density estimation and Moran's I index, we examine the changes in the spatial distribution pattern of restaurants during the last ten years for running, newly-open and closed restaurants as well as SNS popular ones. Finally, we develop a spatial regression model to identify geographic features affecting their locations. As the results, we identified geographical variables and online factors that influence the location of restaurants. The results of this study could provide important groundwork for food and beverage location planning and policy formulation.

• Information Systems Review
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• v.13 no.2
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• pp.1-16
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• 2011

Recently, many companies have started to manage and support CoPs formally at the organizational level because of strategic usability of CoP. These companies are also seeking ways to motivate CoP members to actively participate in their groups. Accordingly, this paper proposes one way of increasing CoP activities by rearranging CoP members. In practice, active CoP members often lead their groups. Therefore, rearranging members can, eventually, be one method to motivate more individuals to participate in CoP activities. This paper first suggests a new approach in order to improve knowledge sharing activities at the organizational level based on rearranging members of current CoPs. Second, a mathematical model is presented which maximizes total BLS (Balanced Level Score) of company A with several constraints. Then a real world problem is changed to a popular problem, VRP to solve this problem. Third, the solution program was developed to find a meaningful solution.

• Management & Information Systems Review
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• v.35 no.1
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• pp.69-84
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• 2016

This study set the research model to examine the correlation between Word-of-Mouth constraint factors, efforts to negotiate pertaining to these, Flow and Word-of-Mouth intent based on the theory of leisure constrain when it comes to the correlation between consumers' Word-of-Mouth constraint factors and Word-of-Mouth. Correlation among the variables were verified in an empirical manner. Results of this study are summarized as follows. After verifying the hypotheses, all the hypotheses were adopted excluding the hypotheses of two results (Hypothesis 1, hypotheses 5). Detailed results regarding this are as follows. First, the following is the effect of the Intrapersonal Constraint and Word-of-Mouth constraint factors on the Word-of-Mouth constraint negotiation effort. Interpersonal Constraint and Structural Constraint exert positive (-) effect on the Word-of-Mouth constraint negotiation effort. In case of Intrapersonal Constraint, negative (-) effect was demonstrated. Thus, this was statistically significant although dismissed from hypothesis verification. Second, the following is the result of examining the structural correlation between Word-of-Mouth constraint negotiation effort, Flow and Word-of-Mouth. Word-of-Mouth constraint negotiation effort exerts positive (-) effect on the Flow, but it was not statistically effective in case of the Word-of-Mouth. Lastly, it is possible to see that the Flow plays the role of a medium since it exerted positive (-) effect on the Word-of-Mouth. Results of this study are expected to provide key theoretical and working level implications as well as general understanding of the Word-of-Mouth constraint factors, consumers' Flow and Word-of-Mouth.

• Journal of Software Engineering Society
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• v.23 no.4
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• pp.151-163
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• 2010

In the defense software domain where large-scale software products in various application areas need to be built, reusing software is regarded as one of the important practices to build software products efficiently and economically. There have been many efforts to apply various methods to support software reuse in the defense software domain. However, developers in the defense software domain still experience many difficulties and face obstacles in reusing software assets. In this paper, we analyze practical problems of software reuse in the defense software domain, and define core requirements to solve those problems. To meet these requirements, we are currently developing the Component Grid system, a reuse-support system that provides a developer-centric software reuse environment. We have designed an architecture of Component Grid, and defined essential elements of the architecture. We have also developed the core approaches for developing the Component Grid system: a semantic-tagging-based requirement tracing method, a reuse-knowledge representation model, a social-network-based asset search method, a web-based asset management environment, and a wiki-based collaborative and participative knowledge construction and refinement method. We expect that the Component Grid system will contribute to increase the reusability of software assets in the defense software domain by providing the environment that supports transparent and efficient sharing and reuse of software assets.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.100-111
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• 2019

The existing selected station analysis (SSA) method analyzes the link transfer mode data between origin and destination of individuals passing through stations from a microscopic standpoint. As such, existing SSA is insufficient as it uses integrated analysis using macroscopic data such as subway lines. This research builds a line chain OD based on path search of individual passenger's movement through the subway, and explores means to utilize the findings. First, a method is proposed that searches the traversed subway path from the linked passage modes that the passenger uses and applies the results to SSA line analysis. Compared to the existing SSA, this method provides for analysis of commonly conflicting features such as the line on which the station is passed, and the stations included on the line thanks to the presence of complete information of the individual passenger's traversed path. It also allows for integrated observation of the line chain OD that approaches a certain station. For enhanced understanding, Seoul Metro Line 9 is used as a case study to demonstrate the integrated formulation concept of line chain OD centered around a certain station as well as the macroscopic features of the traversed path that approaches stations included on the line.

• Korean small business review
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• v.42 no.4
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• pp.251-283
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• 2020

The purpose of this study is to provide assistance to the establishment of related policies to improve the level of acceptance and use of smart factories for SMEs in Korea. To this end, the Unified Technology Acceptance Model (UTAUT) was extended to select additional factors that could affect the intention to accept technology, and to demonstrate this. To achieve the research objective, a questionnaire composed of 7-point Likert scales was prepared, and a survey was conducted for manufacturing-related companies. A total of 136 questionnaires were used for statistical processing. As a result of the hypothesis test, performance expectation and social influence had a positive (+) positive effect on voluntary use, but effort expectation and promotion conditions did not have a significant effect. As an extension factor, the network effect and organizational characteristics had a positive (+) effect, and the innovation resistance had a negative effect (-), but the perceived risk had no significant effect. When the size of the company is large, the perceived risk and innovation resistance are low, and the level of influencing factors for veterinary intentions, veterinary intentions, and veterinary behaviors are excluded. Through this study, factors that could have a positive and negative effect on the adoption (reduction) of smart factory-related technologies were identified and factors to be improved and factors to be reduced were suggested. As a result, this study suggests that smart factory-related technologies should be accepted.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.589-601
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• 2022

Although drought is a natural phenomenon, its damage occurs in combination with regional physical and social factors. Especially, related to the supply and demand of various waters, drought causes great socio-economic damage. Even meteorological droughts occur with similar severity, its impact varies depending on the regional characteristics and water supply system. Therefore, this study assessed regional drought risk considering regional socio-economic factors and water supply system. Drought hazard was assessed by grading the joint drought management index (JDMI) which represents water shortage. Drought vulnerability was assessed by weighted averaging 10 socio-economic factors using Entropy, Principal Component Analysis (PCA), and Gaussian Mixture Model (GMM). Drought response capacity that represents regional water supply factors was assessed by employing Bayesian networks. Drought risk was determined by multiplying a cubic root of the hazard, vulnerability, and response capacity. For the drought hazard meaning the possibility of failure to supply water, Goesan-gun was the highest at 0.81. For the drought vulnerability, Daejeon was most vulnerable at 0.61. Considering the regional water supply system, Sejong had the lowest drought response capacity. Finally, the drought risk was the highest in Cheongju-si. This study identified the regional drought risk and vulnerable causes of drought, which is useful in preparing drought mitigation policy considering the regional characteristics in the future.

• 한국체육학회지인문사회과학편
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• v.55 no.1
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• pp.221-233
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• 2016

The purpose of this study was to prove a development and initial validation of the korean version of coach-athlete relationship maintenance scale that originated from the work of Rhind & Jowett(2012) in pro baseball. The items were then administered to 132 Participants(29 coaches and 103 athletes) completed the questionnaires of the coach-athlete relationship maintenance in First preliminary investigation. Maximum likelihood estimate was used to identify the latent underlying structure. In order to verify the validity of Korean version of coach-athlete relationship maintenance was administered to an independent sample of 273 coaches and athletes. Pro baseball coach-athlete relationship maintenance is consisted of six factors(25 items) with conflict management, motivational, preventative, openness/assurance, support, and social network. SPSS18.0 and AMOS16.0 were used to analyze the exploratory factor analysis, confirmatory factory analysis and internal consistency, test-retest with bootstrapping using of the data in this study. The results of the pro baseball coach-athlete relationship maintenance scale had six factors with 25 items, and each six factor was positively correlated. Overall, this study verified pro baseball coach-athlete relationship maintenance questionnaire. Thus, suggest that path of comparing the differences between the first division and farm team by using the test of the structural model invariance across the groups.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.