• Information Systems Review
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• v.6 no.2
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• pp.113-135
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• 2004

This paper defines appraisal items and weights of the items for the purpose of developing an appraisal instrument that objectively measures employee's effectiveness of knowledge contribution. Deductive research is used for the development of appraisal items and delphi method for the development of weights of the items. In the deductive research the term, "effectiveness of knowledge contribution" is first defined. Then knowledge contribution activities are classified as "dimension of explicit contribution" and " dimension of tacit contribution" due to the characteristics of knowledge. Each dimension is divided again by components. The dimension of explicit contribution is divided according to the content of knowledge, and the dimension of tacit contribution is divided according to the extent of tacitness of knowledge contribution. The total components of dimensions are 7. The dimension of explicit contribution is composed of factual knowledge and procedural knowledge. The factual knowledge is made up of "procedural knowledge outcome" and "other factual knowledge". The procedural knowledge is made up of "procedural knowledge manual" and "lessons-learned procedural knowledge". The dimension of tacit contribution is composed of "agency", "model" and "Q&A". The basic framework for measuring 7 components of knowledge contribution is quantitative and qualitative approach. This paper is premised on the assumption that the outcomes of employee's knowledge contribution activities are recorded in the knowledge management systems in order to evaluate them objectively. The appraisal items are defined as follows: at the dimension of explicit contribution, in quantitative approach, "the upload number" or "performance number", and in qualitative approach, other employee's "referred number" and other employee's "content and format satisfaction evaluation"; at the dimension of tacit contribution, "demanded number of performance" After the development of appraisal items by the deductive method, delphi method was used for the analysis of the weights of the items with the total degree of knowledge contribution, 100. This research does not include the standard marks of the appraisal items. It is because when companies apply this appraisal instrument, they could use their own standard appraisal marks of the appraisal items considering their present situations and companies' goals. Through this almost desert-like research about the appraisal instrument of employee's knowledge contribution effectiveness, it proposes a cornerstone in the research field of appraisal instrument, which provides a standard for employee's knowledge contribution appraisal, and appraisal items that make organizational knowledge to be managed more systemically in business sites.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.497-507
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• 2012

This study aims to verify how the characteristics of organizational supporting unit affect the effectiveness of company-wide HRD Education & Training program. To achieve this objective, we performed an empirical analysis, with the characteristics of organizational supporting unit comprising supervisor's support, job support, and company support as independent variables, and with the level of reaction stage, learning stage, transfer stage, and result stage as dependent variables. Empirical data was collected during the period from August 16, 2011 to September 9, 2011 by sending out questionnaires to employees of 5 securities firms listed on KOSDAQ where online and offline education & training program is running year-round with headquarter in Seoul. A total of 340 questionnaires were sent out three times for the survey, and total of 164 questionnaires were sampled for the final analysis. According to the outcome of the analysis, regarding the first hypothesis that tries to reveal how the characteristics affect the level of reaction stage, it is verified that all of supervisor's support, job support and company support have positive impact on the level of reaction stage with p value less than 0.01. In regard to the second hypothesis that tries to see how the characteristics affect the level of learning stage, it is confirmed that supervisor's support, job support and company support have significant impact on the level of learning stage with p value less than 0.05 or 0.01, respectively. Concerning the third hypothesis that aims to investigate how the characteristics affect the level of transfer stage, it is appeared that all of supervisor's support, job support and company support have positive impact on the level of transfer stage. And lastly, as for the fourth hypothesis that tries to see how the characteristics affect the level of result stage, it is analyzed that supervisor's support, job support and company support have positive impact on the level of result stage with p value less than 0.01. This study reconfirm the outcomes of previous research, which is that the effectiveness of company-wide education & training program depends not only on the contents and quality of education & training program, but also more importantly on the role of organizational supporting unit, and the working environment where what is learned in classroom can be applied to real business. Companies or experts that run education & training program in real world should recognize that the performance of training is dependent more significantly on the characteristics of organizational supporting unit rather than the design or features of education & training program.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Journal of dental hygiene science
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• v.15 no.5
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• pp.585-593
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• 2015

This study, the value of dental hygiene process and business performance among the dental clinics located in Gyeonggi province by comparing and analyzing the financial and non-financial results specifically in the department that provides and did not provide dental hygiene process (ADPIE). The collected data treated with percentage and t-test in utilization of IBM SPSS Statistics ver. 20.0. In terms of the medical cost per patient, the Department A (DA) that applied the dental hygiene process were 216,664 Korean Won (KRW) in 2013 and 324,810 KRW in 2014 whereas Department B (DB) which did not apply the dental hygiene process resulted in 184,655 KRW in 2013 and 225,698 KRW in 2014 (p<0.01). Regarding the number of daily patients, the DA showed increase of 8.08 (p=0.01) while DB showed increase of 2.42 patients (p>0.05). The medical consent rate was 89.17% in DA and 60.09% in DB in 2013 while showing 89.68% and 66.98% respectively in 2014 (p<0.001). The patients' revisit rate was 87.48% in DA and 44.92% in DB in 2013 and that of the DA and DB was 85.89% and 45.55% respectively in 2014 (p<0.001). The rate of regular check-up was 16.01% in DA and 2.53% in DB in 2013 and the same rate in 2014 showed 19.03% and 6.84% respectively in 2014 (p <0.001). The rate of referred patients was 38.46% and 29.98% respectively in DA and DB in 2013 whereas DA showed 47.59% and DB showed 30.77% in 2014 (p<0.05). According to the results, the medical system with dental hygiene process is verified to be a premium medical program that can improve satisfaction as well as management effectiveness in dental service.

• Cartoon and Animation Studies
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• s.44
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• pp.333-361
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• 2016

In general, content business companies include animation industry can have benefits, which they have higher incomes when they obtain wider markets. Therefore, they pursue to have diverse windows for content distribution or to reach the foreign markets for dealing their content products with potential customers. It have the greatest value. They can re-invest the incomes to produce their new products, and they can enhance the international competitiveness of their next products. As the results, the companies can have more incomes and wider markets in next business, and it will be the effectiveness of the good cycle of the animation industry. Animation industry has being undergone of its structure changes, more economical chances and viewers' attitudes changes through the all over the industry because of the acceptance of new digital technology. To response the changes or have the new chances from the changes, they should to review the existing system and the law concerned with the animation business as well as having the diverse new plans for supporting the industry like a construction of the online marketplace of Korean animation. It would make the Korean animation companies to meet foreign customers easily by making lower the entrance barrier of the foreign markets. Current Korean government needs to estimate the value of the Korean animation accurately and objectively by concerning its surroundings to support efficiently. However, it is very difficult to estimate the value of the content rightly because of its' intangible and subjective matter. For this, they should analyze the all the data of the information of the Korean animation content by accumulate, open to the public and manage. So if the government makes online marketplace for the Korean animation, which all the Korean animation companies get in, it would be a solution of estimating the value of the Korean animation rightly. In addition, it will be used as the role of archive of the government to lead the industry successfully. As a point of the small size of the Korean animation companies, they are government dependable because of its low budget, so they strongly expect the government to do the right role as the unique knowledge distributor. Therefore, the Korean animation online marketplace would make not only big companies, but also small companies to have the chances to increase the value of their content in the global markets by themselves without economic burdens.

• Management & Information Systems Review
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• v.31 no.2
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• pp.41-59
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• 2012

ERP is a new technique of process innovation. It indicates enterprise resource planning whose purpose is an integrated total management of enterprise resources. ERP can be also seen as one of the latest management systems that organically connects by using computers all business processes including marketing, production and delivery and control those processes on a real-time basis. Currently, however, it's not easy for local enterprises to have operators who will be in charge of ERP programs, even if they want to introduce the resource management system. This suggests that it's urgently needed to train such operators through ERP education at school. But in the field of education, actually, the lack of professional ERP instructors and less effective learning programs for industrial applications of ERP are obstacles to bringing up ERP workers who are competent as much as required by enterprises. In ERP, accounting is more important than any others. Accountants are assuming more and more roles in ERP. Thus, there's a rapidly increasing demand for experts in ERP accounting. This study examined previous researches and literature concerning ERP education, identified problems with current ERP education at college and proposed how to solve the problems. This study proposed the ways of improving ERP education at college as follows. First, a prerequisite learning of ERP, that is, educating the principle of accounting should be intensified to make students get a basic theoretical knowledge of ERP enough. Second, lots of different scenarios designed to try ERP programs in business should be created. In association, students should be educated to get a better understanding of incidents or events taken place in those scenarios and apply it to trying ERP for themselves. Third, as mentioned earlier, ERP is a system that integrates all enterprise resources such as marketing, procurement, personnel management, remuneration and production under the framework of accounting. It should be noted that under ERP, business activities are organically connected with accounting modules. More importantly, those modules should be recognized not individually, but as parts comprising a whole flow of accounting. This study has a limitation because it is a literature research that heavily relied on previous studies, publications and reports. This suggests the need to compare the efficiency of ERP education between before and after applying what this study proposed to improve that education. Also, it's needed to determine students' and professors' perceived effectiveness of current ERP education and compare and analyze the difference in that perception between the two groups.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.6
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• pp.25-39
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• 2017

The role of traditional universities has been emphasized as a career path to advance into society. Recently, it has become a new paradigm of university education by emphasizing entrepreneurship as a career aspect. While entrepreneurship education is constantly expanding for college students, relatively few young people choose to start their own business. Despite the fact that the government is continuing to expand the university's entrepreneurship education, there are very few achievements that lead to actual entrepreneurship and student start-up There is still a lack of research on ways to cultivate creative talents and increase practical entrepreneurial intention. The results of this study are as follows: First, the effects of creativity competency education on self-efficacy and entrepreneurial intention were analyzed. The effect of self-efficacy on the entrepreneurial intention. Finally This study examined the effects of social support (parent support) between self-efficacy and entrepreneurial intention. This study used 393 samples in August 2016 for university students who received entrepreneurship education. The results showed that the ability of communicative communication and creative problem solving had a positive effect on self-efficacy. On the other hand, innovative work behavior abilities did not directly affect self-efficacy. In addition, creative problem solving ability and innovative work behavior ability had a positive effect on the entrepreneurial intention. On the other hand, the ability to communicate in a collaborative manner has no direct effect on the entrepreneurial intention. In addition, self-efficacy has a positive effect on the entrepreneurial intention. Finally, the adjustment effect of social support (parent support) between self-efficacy and entrepreneurial intention has no effect. The implications of this study are empirically verified the effectiveness of creativity capacity through entrepreneurship education and the result of meaningful research that the social support through cooperation of parents is indispensable in order to increase the actual starting will of college students. Therefore, universities need to establish entrepreneurship education programs for their parents in order to increase the willingness of college students to start-up. This study can be used as a meaningful basic data for establishing policy for student start - up and suggesting the right direction of entrepreneurship education.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3062-3071
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• 2011

This study proposed to compare the performance differences between a manufacturing company and a construction company in accordance with the mutual relations and ownership structures with the management performance based on the increase or decrease of the large shareholders' share-holding ratio (insider ownership, foreign share-holding, institutional investors' share-holding) of a KOSPI listed company in Korea during 10 years(1998-2007). To sum up the research work, first, the increase of foreign share-holding supported the results of previous studies which foreign share-holding has a positive effect on the long term performance by having a positive(+) effect on MTB, and the increase of an insider ownership supported the management entrenchment hypothesis of previous studies by having a negative(-) effect on MTB. However, relations between institutional investors's share-holding and MTB could not find out linkages in spite of the results of previous studies where dealt with the active monitoring hypothesis. Also, to examine the linkages of ROA and the ownership structure, though the increases of foreign share-holding and insider ownership had a positive(+) effect on ROA, the increases of institutional investors' share-holding had a negative(-) effect on it. It showed different analysis results from the active monitoring hypothesis of institutional investors. As a result of verifying whether there is "any difference in the management performances between the construction industry and the manufacturing industry according to the equity structure" which is the second hypothesis, nothing of the insider ownership and whether or not there is the construction industry, foreign share-holding and whether or not there is the construction, and the institutional ownership and whether or not there is the construction industry gave a statistical difference to MTB and ROA. Accordingly, it was possible to find out there is no difference in the management performance between the construction industry and the manufacturing industry based on the ownership structure in spite of different characteristics from the manufacturing industry such as the revenue recognition in ordering, production and accounting.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.