• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.5
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• pp.15-27
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• 2016

This paper examined the effects of youth entrepreneurship on entrepreneurial intention. Especially, we considered scholastic performance as a moderator on the relationship between youth entrepreneurship and their entrepreneurial intention. An empirical analysis on 251 students attending their third year of Suncheon High School revealed the following results. First, the youth entrepreneurship(risk taking, innovativeness and proactiveness) significantly positive affected entrepreneurial intention. The result corresponds to what many preceding studies emphasize, implying that when risk taking, which enables perseverance through uncertain situations, increases; innovativeness, which enables breaking away from existing frameworks, increases; and proactiveness, which creates new opportunities through future-oriented behavior, increase, the entrepreneurial intention of teenagers also increases. Second, a review of the interaction effect of scholastic performance discovered evidence that scholastic performance moderates the relationship between proactiveness and entrepreneurial intention of youth toward a negative(-) direction. In other words, proactiveness positively effects on entrepreneurial intention, but higher scholastic performance imply that such positive tendencies become weakened. The results of the present study will be able to provide significant theoretical and practical implications in carrying out follow-up studies on the youth entrepreneurship, which has been, up to now, relatively neglected.

• Women's Health Nursing
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• v.4 no.2
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• pp.173-186
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• 1998

In this study, both the literary survey as well as empirical research has been executed to test the validity of the scales that measure the construct of self-monitoring scale could not be classified into five factors as Snyder suggested. Many other scholars (Briggs, Cheek and Buss, 1980) suggested 3 different classifications which was accepted by Snyder and Gangestad (1986). John, Cheek and Klohnen (1996) claimed a two-factor classification. As has been discussed, factor analysis is used to prove convergent validity within the factor and discriminant validity between the factors. However, depending on the researchers, many variations in classification of the factors were found and a lack of content and discriminant validity was found in the previous research findings. It is also important to note that Snyder's self-monitoring scale, did not factor-load at over 30 for all 25 items, regardless of how many factors could be classified. According to findings of this study, the self-monitoring scale neither classified as five, three or two factors nor factor loaded as hypothesized. It is also clear that Snyder's self-monitoring scale lack convergent validity as the sub-factors of the scale fail to prove its uni-dimensionality. The A self-monitoring scale not only fail to overcome the problems of Snyder's self-monitoring scale but even lost the attractiveness of the self-monitoring scale. In this study, it was also found that the A self-monitoring scale was not classified as hypothesized in either in a two or three-factor classification. It is, of course, not desirable to use any scale that lacks convergent and discriminant validity even though it has been widely used but also has held a great deal of influence on the field of social psychology. To overcome the shortcomings of Snyder's self-monitoring scale, Lennox and Wolfe(1984) suggested 13 items. This study 1. was dedicated to test the validity and reliability of the scale, in which we found that the data presented in validity as the two factors were classified and loaded as expected. Reliability was also proven by checking Cronbach's alpha for each factor and for the total items. In addition, a confirmatory factor analysis was executed for the 13 items using LISREL 8.12 program to confirm convergent validity in a two-factor classification. The model was fitting and sound ; however, the self-monitoring scale was unfitted and not validated. Thus, it is recommended to use not the original or the abbreviated self-monitoring scale but the 13 items in future studies. It should also be noted that items 7 and 13 should be removed to obtain better uni-dimensionality for the 13 items. These items loaded at over .30, too high for the two factors in the test results of factor analysis. In addition, it is necessary to double-check the cause of two-hold loading at over .30 for the two factors. It could be a problem caused by data or by the scale itself. Therefore, additional studies should follow to better clarify this matter.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.95-118
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• 2009

Virtual community, which is formed on the internet, is expected to serve the needs of members for communication, information, and knowledge sharing. The executives of organizations should consider operating strategy of virtual community as a new innovation or knowledge pool since members share knowledge. However, many virtual community have failed due to members' low willingness to engage and furthermore to share knowledge with other members. Thus, there is a need to understand and foster the determinants of members' loyalty in virtual community. The objective of this study is to develop an integrated model designed to investigate and explain the relationships between contextual factors, personal perceptions of virtual community, usefulness, ease of use, familiarity, members' trust, reputation, community trust, attitude, satisfaction and loyalty. Empirical data was collected from 286 internet users and tested using structural equation modeling to verify the fit of the hypothetical model. The results show that the usefulness, familiarity significantly influences attitude and members' trust is significantly influence the community trust. And I confirmed that ease of use and attitude play the role of determinants in making the satisfaction, community trust and reputation influence the satisfaction that have the direct effect to making the loyalty. The results of the study can be used to identify the loyalty in virtual community. By investigating the impacts of contextual factors and personal perceptions on virtual community, the integrated model better explains behavior than other proposed models. This study might help executives of virtual communities and organizations to manage and promote community trust, attitude, satisfaction to stimulate members' willingness to revisit the community and futhermore enhance their virtual community loyalty.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.1-17
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• 2009

E-Catalogs which describe products or services are one of the most important data for the electronic commerce. E-Catalogs are created, updated, and removed in order to keep up-to-date information in e-Catalog database. However, when the number of catalogs increases, information integrity is violated by the several reasons like catalog duplication and abnormal classification. Catalog search, duplication checking, and automatic classification are important functions to utilize e-Catalogs and keep the integrity of e-Catalog database. To implement these functions, probabilistic models that use statistics of index words extracted from e-Catalogs had been suggested and the feasibility of the methods had been shown in several papers. However, even though these functions are used together in the e-Catalog management system, there has not been enough consideration about how to share common data used for each function and how to effectively manage statistics of index words. In this paper, we suggest a method to implement these three functions by using simple SQL supported by relational database management system. In addition, we use materialized views to reduce the load for implementing an application that manages statistics of index words. This brings the efficiency of managing statistics of index words by putting database management systems optimize statistics updating. We showed that our method is feasible to implement three functions and effective to manage statistics of index words with empirical evaluation.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.1-22
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• 2018

The value chain has been utilized as a strategic tool to improve competitive advantage, mainly at the enterprise level and at the industrial level. However, in order to conduct value chain analysis at the enterprise level, the client companies of the parent company should be classified according to whether they belong to it's value chain. The establishment of a value chain for a single company can be performed smoothly by experts, but it takes a lot of cost and time to build one which consists of multiple companies. Thus, this study proposes a model that automatically classifies the companies that form a value chain based on actual transaction data. A total of 19 transaction attribute variables were extracted from the transaction data and processed into the form of input data for machine learning method. The proposed model was constructed using the Random Forest algorithm. The experiment was conducted on a automobile parts company. The experimental results demonstrate that the proposed model can classify the client companies of the parent company automatically with 92% of accuracy, 76% of F1-score and 94% of AUC. Also, the empirical study confirm that a few transaction attributes such as transaction concentration, transaction amount and total sales per customer are the main characteristics representing the companies that form a value chain.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.83-107
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• 2020

Selecting business charts based on the nature of the data and the purpose of the visualization is useful in business analysis. However, current visualization tools lack the ability to help choose the right business chart for the context. Also, soliciting expert help about visualization methods for every analysis is inefficient. Therefore, the purpose of this study is to propose an accessible method to improve business chart productivity by creating rules for selecting business charts from online published documents. To this end, Korean, English, and Chinese unstructured data describing business charts were collected from the Internet, and the relationships between the contexts and the business charts were calculated using TF-IDF. We also used a Galois lattice to create rules for business chart selection. In order to evaluate the adequacy of the rules generated by the proposed method, experiments were conducted on experimental and control groups. The results confirmed that meaningful rules were extracted by the proposed method. To the best of our knowledge, this is the first study to recommend customizing business charts through open unstructured data analysis and to propose a method that enables efficient selection of business charts for office workers without expert assistance. This method should be useful for staff training by recommending business charts based on the document that he/she is working on.

• KDI Journal of Economic Policy
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• v.26 no.2
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• pp.63-104
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• 2004

Economists have long been involved in various studies, theoretical and empirical, on the economic gains from innovative activities and as their outcome, intellectual properties. In Korea, however, research in this field has experienced rather slow progress, partly due to the lack of data availability and the awareness of its importance. This study attempts to measure the economic impact of patents on market value of firms from a microeconomic point of view. Analyses are performed to examine the ex-ante market valuation of patent acquisition activities by investigating the effect of patent acquisitions on daily stock prices as well as on annual market values. The study on the effect of a disclosure of granted patents on daily stock prices reveals that the economic value of a firm's patent acquisition is fairly high. The study on listed firms also reveals that a firm's patent registration stock has a positive and statistically significant effect on its year-end market value. Therefore, it can be concluded that the analysis performed in this study supports the validity of Korea's current patent system. The result, however, does not guarantee the optimality of current system. Studies on various aspects of intellectual property should follow to shape the system into a socially optimal one.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.141-153
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• 1991

The optimal choice of the tax rate and the inflation rate framework is extended to yield relevant interpretations for the optimal fiscal and monetary policy regime in Korea. To study the relationship between the government budget and monetary growth in different environments of policy coordination, two models assuming different degrees of fiscal dominance are developed. By modelling differing institutional arrangements of the fiscal and the monetary authority from an optimal government finance viewpoint, we find the optimal relationship among some important fiscal and monetary variables. By testing the existence of the relationship empirically, we find the characteristics of the optimal policy-mix regime in Korea. The first model-the strong from of fiscal dominance-studies the optimal collection of seigniorage in a period-by-period optimization with standard assumptions on the income velocity of money, deriving a general testable result: the optimal inflation/tax rate ratio co-vary with the marginal revenue ratio. The second model-the weak form of fiscal dominance-studies an implication of the inflationary bias of discretionary monetary policy in the presence of fiscal side distortions. This model shows that the tax rate and the inflation rate can have a positive correlation. Empirical tests of the theoretical results are done for the Korean economy for 1972-1989 period. The test results show that the macroeconomic policy regime in Korea can be characterized by the strong form of fiscal dominance, implying the importance of the government budget in explaining money growth and inflation.

• The Journal of Society for e-Business Studies
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• v.16 no.2
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• pp.1-18
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• 2011

Context-aware computing aims to enable the on-line applications and services to be executed in a timely and automated manner. Many of such applications and services involve group-level interactions. For more smoothing communication within a community, specific group-level issues such as group dynamics must be considered. To do so, obtaining group-level contexts such as the role, conflict resolution and norms, are key ingredients to improve group performance. Since group context is not the same as a simple summation of individual context, as group is not just a simple set of individuals, awaring individual context is not sufficient for group-level communication support. However, context-aware computing research still has stressed more on individual context. This leads us to the motivation of searching for group context aware method. Hence, the of this paper is to propose a novel methodology which automatically recognizes group context. Especially, we focus on group conhesiveness in this paper just because group cohosiveness is one of the important variables to control the performance of group interaction. To verify the applicability of the proposed method, an empirical test has been conducted to compare the performance of the proposed methodology with that of conventional methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.678-689
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• 2016

This study examined the effect of the internal marketing policies of financial institutions on the job satisfaction and customer orientation of employees. Many studies have examined internal marketing policies. On the other hand, these studies focused the employees in the service industries (e.g. travel agencies, airlines and hotel, etc.) With the drastic change in financial institutions in recent years, financial institutions are conscious of the importance of customer service and have increased their efforts to manage and train their employees (e.g. expansion of empowerment, education and training, management support, and compensation system). The authors conducted an empirical analysis based on the assumption that these internal policies are effective in increasing the job satisfaction of employees and further influence the customer orientation. The results showed that 'empowerment, management support and compensation system' of internal marketing policies have meaningful effects on job satisfaction, whereas the education and training does not. In addition, job satisfaction has a meaningful effect on the customer orientation and on a mediating effect between internal marketing policies and customer orientation. These results indicate that the internal marketing policies of financial institutions can help improve job satisfaction and customer orientation.