• Information Systems Review
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• v.19 no.2
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• pp.1-19
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• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.

• Journal of the Korean Geographical Society
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• v.47 no.4
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• pp.522-540
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• 2012

The main aim of the paper is to identify the position or status of Korean economic geography in changing global economic geography by reviewing papers published in Korean geographical journals since the mid-1950s. Since the late 20th century as economic geography has developed significantly with the introduction of new research issues, methodologies, and theory and concepts, economic geography in Korea also has gone through rapid development in terms of both quantitative and qualitative perspectives. The paper attempts to analyze trends in Korean economic geography by reviewing agricultural, industrial, commercial geographies, and others since the mid-1950s. The review of economic geography in Korea would be based on four periods classified by research issues and approaches; foundation (~1950s), positioning (1960s and 1970s), jump and rush (1980s and mid-1990s), and transitional period (late 1990s~). Agricultural geography in Korea has decreased due to increases of the interests in industrial geography since the 1980s. In particular, since the late 1990s industrial geography has undergone a significant transition in accordance with the emergence of new theories of institutional perspectives, centering around issues on value chains, innovative cluster, cooperative and competitive networks, foreign direct investment, flexible specialization and venture ecology. Along with this, there has been changes in the interest of commercial geography in Korea from researches on periodical markets, the structure of store formats, and distributions by commodity, to researches on producer services and retailer's locational behaviors and commercial supremacy according to the emergence of new store formats. Since the late 1990s, many researches and discussions associated with the new economic geography began to emerge in Korea. Various research issues are focused on analyzing changes of local, regional and global economic spaces and their processes in relation to institutional perspectives, knowledge and innovation, production chain and innovative networks, industrial clusters and RIS, and geographies of service. Although economic geography in Korea has developed significantly both in quantitative and qualitative perspectives, we pointed out that it has still limited in some specific scope and issues. Therefore, it is likely to imply that its scope and issues should be diversified with new perspectives and approaches.

• Asia Marketing Journal
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• v.10 no.1
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• pp.25-64
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• 2008

Third-Party awards are growing in popularity. They are the hit product of the year chosen by The Korea Economic Daily, the best 10 products of the year chosen by Sports paper, the best hit product chosen by consulting firm and the best venture company of the year chosen by Information and Communication Ministry. Then these questions may be followed. Why industry likes this type of advertisement? Does this type of advertisement influences consumers' purchase intention? And if it does, how? Many researchers have been interested in external cue of product quality by focusing research effort on brand, price, producer, warranty etc. However, important but under-explored area is the role of third-party reference for signaling product quality. This paper comes from the idea that the third-party reference may signal consumers like manufacturer brand, product brand, product price, and shop brand. We develop a related theories to address research questions and drive some research hypotheses based on the previous studies probing source credibility, attribution, and signal theory. We put more emphasis on source credibility. We conducted the research based on 3x2x2x2 between group factorial design to explore causal relationship between the third party award winning advertising(real, fictional, no) and the purchase intention of consumers exposed to other information simultaneously such as product type(experience, search), distribution channel(direct, indirect) and perceived price(high, low). Since subjects are divided into 2 groups based on the means of response without extra experimental stimulus in case of perceived price. 12 different advertisements are used for conducting this study. The results are followings. First, the source credibility of the third party goes up, consumers' purchase intention would go up. It seems that consumers think the credibility of the third-party most when they are exposed to the third party award winning advertisement. Second, the product type does moderate the relationship between the third-party award winning advertisement and purchase intention. And the type of the distribution channel also moderates this relationship. The consumers' purchase intention goes up higher when they buy experience good and there is significant difference of purchase intention when consumers are exposed to direct channel treatment condition. But, perceived price has nothing to do with the third-party winning advertisement context for raising consumer intention to buy advertised product.

• Information Systems Review
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• v.18 no.3
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• pp.209-233
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• 2016

Internet companies that utilize social network have increased in number. The introduction of diverse social media services facilitated innovative changes in e-business. Social network service (SNS), which is a domain of social media, is a web-based service designed to strengthen human relations in the Internet and build new social relations. The remarkable growth of social network services and the profit generation and perception of this service are the new growth engines of this digital age. Given this development, many global IT companies views SNS as the most powerful form of social media. Thus, they invest efforts to develop business models using SNS.2) This study verifies the impact of privacy exposure in SNS as a result of privacy invasion. This study examines the purpose of using the SNS and user's awareness of the significance of personal information, which are key factors that affect self-disclosure of personal information. This study utilizes theory of reasoned action (TRA) to provide a theoretical platform that describes the specific behavior and emotional response of individuals. This study presents a research model that considers negative attitude (negatude). In this model, self-disclosure in SNS is considered a TRA. TRA is a subjective norm, a behavioral intention, and a key variable of exposure behavior. A survey was conducted on college students at Y university in Seoul to empirically verify the research model. The students have experiences in using SNS. A total of 198 samples were collected. Path analysis was applied to analyze the relations of factors. The results of path analysis show the statistically insignificant impact of privacy invasion on negatude, subjective norm, behavioral intention, and exposure behavior. The impact of unrecognized privacy invasion was also considered insignificant. The impacts of intention to use SNS on negatude, subjective norm, behavioral intention, and exposure behavior was significant. A significant impact was also found for the significance of personal information on subjective norm, behavioral intention, and exposure behavior, whereas the impact on negatude was insignificant. The impact of subjective norm on behavioral intention was significant. Lastly, the impact of behavioral intention on exposure behavior was insignificant. These findings are significant because the study examined the process of self-disclosure by integrating psychological and social factors based on theoretical discussion.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• The Journal of Small Business Innovation
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• v.19 no.2
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• pp.53-68
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• 2016

Motivation and activities for technological learning, entrepreneurship, innovation, and creativity are driving forces of economic development in Asian countries. In the early stages of technological development, technological learning and entrepreneurship are efficient ways in which to catch up with advanced countries because firms can accumulate skills and knowledge quickly at relatively low risk. In the later stages of technological development, however, innovation and creativity become more important. This study aims to identify a) the factors (learning capabilities) that influence technological learning performance and b) barriers to enhancing innovation capabilities for the creative economy and organizations. The major part of this study is related to learning capabilities in the post-catch-up era. Based on a literature review and observations from Korean experiences, this study proposes a technological learning model composed of various influencing factors on technological learning. Three hypotheses are derived, and data are collected from Korean machine tool manufacturers. Intense interviews with CEOs and R&D directors are conducted using structured questionnaires. Statistical analysis, such as correlation and ANOVA are then carried out. Furthermore, this study addresses how to enhance innovation capabilities to move forward. Innovation enablers and barriers are identified by case studies and policy analysis. The results of the empirical study identify several levels of firms' learning capabilities and activities such as a) stock of technology, b) potential of technical labor, c) explicit technological efforts, d) readiness to learn, e) top management support, f) a formal technological learning system, g) high learning motivation, h) appropriate technology choice, and i) specific goal setting. These learning capabilities determine firms' learning performance, especially in the early stages of development. Furthermore, it is found that the critical factors for successful technological learning vary along the stages of technology development. Throughout the statistical and policy analyses, this study confirms that technological learning can be understood as an intrinsic principle of the technology development process. Firms perform proactive and creative learning in the late stages, while reactive and imitative learning prevails in the early stages. In addition, this study identifies the driving forces or facilitating factors enhancing innovation performance in the post catch-up era. The results of the preliminary case studies and policy analysis show some facilitating factors such as a) the strategic intent of the CEO and corporate culture, b) leadership and change agents, c) design principles and routines, d) ecosystem and collaboration with partners, and e) intensive R&D investment.

• Journal of Korea Multimedia Society
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• v.9 no.7
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• pp.872-893
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• 2006

In this study, I classify the elements of physiognomic judgment of character with regard to form and meaning from a visual perspective based on physiognomic judgment of character study in 'the cosmic dual forces and the Five Elements theory'. Individual characters for each type are designed using graphic data. Based on that, design system of individual characters for each personality type is investigated using Neural Network system. Faces with O-Haeng (Five Elements) shapes are shown to constitute the system with ${\pm}0.3%$ degree of error tolerance for the non-loaming input data. For the shapes of Chinese characters 'tree, fire, soil, gold and water', their MSE(Mean Square Error) are 0.3, 0.3, 0.2, 0.5, 0.2. It seems to be the best regarding the scoring system which ranges from 0 to 5. Therefore, this system might be regarded to produce the most accurate facial shape of character automatically when we input character's personality we desire to make.

• The Journal of Small Business Innovation
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• v.20 no.3
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• pp.1-17
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• 2017

There is a serious information asymmetry between internal managers and outside investors in the process during IPOs. One mechanism that mitigates this information asymmetry is a high quality auditor. Since prior research document auditors' effect on newly listed firms at the IPO year, what has not yet been revealed in previous studies is the behavior of firms and auditors after listing. In this study, we investigate (i) the firms tendency of contracting with Big N auditors, and (ii) the effect of Big N auditors on accounting quality after the years of IPOs. Using a sample of 7,678 (1,892 firm-years of after IPOs, and 5,786 control firm-years) KOSDAQ observations between 2002 and 2012, we find that the likelihood of contracting with Big N auditor lasts only for two years after IPO compare to that of non-IPO control years. Secondly, we find that the effect of Big N auditors on clients' earnings management lasts for a very short period after IPO. These findings suggest that although prior literature argue that Big N auditors reduce earnings management of their clients, at least the period right after IPO, it is not consistent. Our study contributes to the existing literature in several ways. First, we provide new evidences of firms' auditor selection decisions by investigating years after the listing. In second, as an evidence of accruals reversal, we document decrease in discretionary accruals after IPOs. Third, we find that there is not always a positive relation between Big N auditor and accounting quality by showing the insignificant Big N auditor effect after IPOs. Our results also suggest several implications to IPO related stakeholders. First, to IPO firms, we provide evidences that decisions of hiring auditors affect firms earnings. Also, lead IPO underwriters may consider how these decisions influence future performance. Second, investors may want to use information not only in the preofferings but also after public offerings. Our study insists that auditor hiring decisions affects their own welfare. Finally, accounting standard setters may find these results useful for evaluating how much discretion they should allow corporate managers to hire auditors. In addition, our result casts doubt on auditor designation.

• Journal of Korea Technology Innovation Society
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• v.12 no.4
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• pp.687-714
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• 2009

In this paper, we study empirically the relations between financial constraints and dividend adjustment speed of innovative small and medium sized enterprises (SMEs) listed on Kosdaq Market of Korea Exchange. The main results of this study can be summarized as follows. Determinants suggested by the major theories of dividends, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend payout policy of Kosdaq SMEs. Lintner's dividend adjustment model indicates that Kosdaq SMEs have long run target payout ratio, and that Kosdaq SMEs adjust partially the gap between actual and target payout ratio each year. In the core variables of Lintner (1956) dividend adjustment model, past DPS has more effect than current EPS. These results suggest that Kosdaq SMEs maintain stable dividend policy which maintain past DPS level without corporate special reasons. Dividend adjustment speed of innovative Kosdaq SMEs is more fast than that of uninnovative Kosdaq SMEs, and dividend adjustment speed of financial unconstrained innovative Kosdaq SMEs is faster than that of financial constrained innovative Kosdaq SMEs. Futhermore, dividend adjustment speed of innovative Kosdaq SMEs classified by Small and Medium Business Administration is faster than that of unclassified innovative Kosdaq SMEs. The former is linked with financial policies and services like credit guaranteed service, venture investment fund, insurance program, and so on. In conclusion, past DPS and current EPS suggested by the Lintner's dividend adjustment model explain mainly dividend adjustment speed, and financial constraints explain also partially. Therefore, if managers of innovative Kosdaq SMEs can properly understand of the effects of financial constraints on dividend smoothing, they can maintain constantly dividend policy. This is encouraging result for Korea government as it has implemented many policies to commit to innovative Kosdaq SMEs.

• Korean small business review
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• v.31 no.4
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• pp.67-93
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• 2009

The purpose of this paper is to explore the relations between financial constraints and dividend smoothing of innovative small and medium sized enterprises(SMEs) listed on Korea Securities Market and Kosdaq Market of Korea Exchange. The innovative SMEs is defined as the firms with high level of R&D intensity which is measured by (R&D investment/total sales) ratio, according to Chauvin and Hirschey (1993). The R&D investment plays an important role as the innovative driver that can increase the future growth opportunity and profitability of the firms. Therefore, the R&D investment have large, positive, and consistent influences on the market value of the firm. In this point of view, we expect that the innovative SMEs can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. And also, we expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Aivazian et al.(2006) exert that the financial unconstrained firms with the high accessibility to capital market can adjust dividend payment faster than the financial constrained firms. We collect the sample firms among the total SMEs listed on Korea Securities Market and Kosdaq Market of Korea Exchange during the periods from January 1999 to December 2007 from the KIS Value Library database. The total number of firm-year observations of the total sample firms throughout the entire period is 5,544, the number of firm-year observations of the dividend firms is 2,919, and the number of firm-year observations of the non-dividend firms is 2,625. About 53%(or 2,919) of these total 5,544 observations involve firms that make a dividend payment. The dividend firms are divided into two groups according to the R&D intensity, such as the innovative SMEs with larger than median of R&D intensity and the noninnovative SMEs with smaller than median of R&D intensity. The number of firm-year observations of the innovative SMEs is 1,506, and the number of firm-year observations of the noninnovative SMEs is 1,413. Furthermore, the innovative SMEs are divided into two groups according to level of financial constraints, such as the financial unconstrained firms and the financial constrained firms. The number of firm-year observations of the former is 894, and the number of firm-year observations of the latter is 612. Although all available firm-year observations of the dividend firms are collected, deletions are made in the case of financial industries such as banks, securities company, insurance company, and other financial services company, because their capital structure and business style are widely different from the general manufacturing firms. The stock repurchase was involved in dividend payment because Grullon and Michaely (2002) examined the substitution hypothesis between dividends and stock repurchases. However, our data structure is an unbalanced panel data since there is no requirement that the firm-year observations data are all available for each firms during the entire periods from January 1999 to December 2007 from the KIS Value Library database. We firstly estimate the classic Lintner(1956) dividend adjustment model, where the decision to smooth dividend or to adopt a residual dividend policy depends on financial constraints measured by market accessibility. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between current payout rato and target payout ratio each year. In the Lintner model, dependent variable is the current dividend per share(DPS_t), and independent variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t). We hypothesized that firms adjust partially the gap between the current dividend per share(DPS_t) and the target payout ratio(Ω) each year, when the past dividend per share(DPS_t-1) deviate from the target payout ratio(Ω). We secondly estimate the expansion model that extend the Lintner model by including the determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory. In the expansion model, dependent variable is the current dividend per share(DPS_t), explanatory variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t), and control variables are the current capital expenditure ratio(CEA_t), the current leverage ratio(LEV_t), the current operating return on assets(ROA_t), the current business risk(RISK_t), the current trading volume turnover ratio(TURN_t), and the current dividend premium(DPREM_t). In these control variables, CEA_t, LEV_t, and ROA_t are the determinants suggested by the residual dividend theory and the agency theory, ROA_t and RISK_t are the determinants suggested by the dividend signaling theory, TURN_t is the determinant suggested by the transactions cost theory, and DPREM_t is the determinant suggested by the catering theory. Furthermore, we thirdly estimate the Lintner model and the expansion model by using the panel data of the financial unconstrained firms and the financial constrained firms, that are divided into two groups according to level of financial constraints. We expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, because the former can finance more easily the investment funds through the market accessibility than the latter. We analyzed descriptive statistics such as mean, standard deviation, and median to delete the outliers from the panel data, conducted one way analysis of variance to check up the industry-specfic effects, and conducted difference test of firms characteristic variables between innovative SMEs and noninnovative SMEs as well as difference test of firms characteristic variables between financial unconstrained firms and financial constrained firms. We also conducted the correlation analysis and the variance inflation factors analysis to detect any multicollinearity among the independent variables. Both of the correlation coefficients and the variance inflation factors are roughly low to the extent that may be ignored the multicollinearity among the independent variables. Furthermore, we estimate both of the Lintner model and the expansion model using the panel regression analysis. We firstly test the time-specific effects and the firm-specific effects may be involved in our panel data through the Lagrange multiplier test that was proposed by Breusch and Pagan(1980), and secondly conduct Hausman test to prove that fixed effect model is fitter with our panel data than the random effect model. The main results of this study can be summarized as follows. The determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend policy of the innovative SMEs. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between the current payout ratio and the target payout ratio each year. In the core variables of Lintner model, the past dividend per share has more effects to dividend smoothing than the current earnings per share. These results suggest that the innovative SMEs maintain stable and long run dividend policy which sustains the past dividend per share level without corporate special reasons. The main results show that dividend adjustment speed of the innovative SMEs is faster than that of the noninnovative SMEs. This means that the innovative SMEs with high level of R&D intensity can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. The other main results show that dividend adjustment speed of the financial unconstrained SMEs is faster than that of the financial constrained SMEs. This means that the financial unconstrained firms with high accessibility to capital market can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Futhermore, the other additional results show that dividend adjustment speed of the innovative SMEs classified by the Small and Medium Business Administration is faster than that of the unclassified SMEs. They are linked with various financial policies and services such as credit guaranteed service, policy fund for SMEs, venture investment fund, insurance program, and so on. In conclusion, the past dividend per share and the current earnings per share suggested by the Lintner model explain mainly dividend adjustment speed of the innovative SMEs, and also the financial constraints explain partially. Therefore, if managers can properly understand of the relations between financial constraints and dividend smoothing of innovative SMEs, they can maintain stable and long run dividend policy of the innovative SMEs through dividend smoothing. These are encouraging results for Korea government, that is, the Small and Medium Business Administration as it has implemented many policies to commit to the innovative SMEs. This paper may have a few limitations because it may be only early study about the relations between financial constraints and dividend smoothing of the innovative SMEs. Specifically, this paper may not adequately capture all of the subtle features of the innovative SMEs and the financial unconstrained SMEs. Therefore, we think that it is necessary to expand sample firms and control variables, and use more elaborate analysis methods in the future studies.