• 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.

• Analyses & Alternatives
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• v.6 no.1
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• pp.115-162
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• 2022

The Rules of the Workers' Party of Korea (WPK), revised at the eighth Party Congress in 2021, reflect the Kim Jong Un regime's changes in strategic lines and ideological justifications on North Korea's socialism and communism, and its recent stances against the external environment. Moreover, they contain critical changes in the party's organizational system encompassing the central and the provinces. This study explores the organizational changes of the "monolithic guidance system of the party core" stipulated by the new party rules in January 2021, based on the analysis of the entire nine revised rules of the WPK since 1945. In the 2021 Party Congress, the Kim Jong Un regime, which officially came to power after the fourth Party Conference in 2012, has institutionalized the monolithic guidance system centered on the party core, or the head of state, Kim Jong Un. The newly set leadership and execution system, which reorganized party, government, and military organizational structure and accompanied the relevant personnel changes, was derived from the attempts for reinstating the Kim Jong Un regime as a more normalized party-state structure before its 10th year in power in April 2022. The "monolithic leadership system of the party core" established a system of "organizational leadership" through the organization of the Central Committee, directed by the Party Head, or General Secretary. The institutionalization of the new system resulted from the ten-year development of the revival of the party-state structure, which compromised the status of the military and reconfirmed the party's control of the military. This study explains the new system from the perspectives of both institutionalization and top-down unity, shedding light on the new party-military-government relations of the Kim Jong Un regime. The analysis contributes to a better understanding and forecasting of the Kim Jong Un regime's governance, which currently strengthens the monolithic leadership system as a crisis management system in the face of the "triple hardships" of sanctions, Covid and disaster.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.377-388
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• 2023

Carbon management is emerging as an important factor for global warming control, and land use change is considered one of the causes. To quantify the changes in carbon stocks due to development, this study attempted to calculate carbon storage by borrowing the formula of the InVEST Carbon Storage and Sequestration Model (InVEST Model). Before analyzing carbon stocks, a carbon pool was compiled based on previous studies in Korea. Then, we estimated the change in carbon stocks according to the development of Osong National Industrial Park (ONIP) and the application of alternatives. The analysis shows that 16,789.5 MgC will be emitted under Alternative 1 and 16,305.3 MgC under Alternative 2. These emissions account for 44.4% and 43.1% of the pre-project carbon stock, respectively, and shows that choosing Alternative 2 is advantageous for reducing carbon emissions. The difference is likely due to the difference in grassland area between Alternatives 1 and 2. Even if Alternative 2 is selected, efforts are needed to increase the carbon storage effect by managing the appropriate level of green cover in the grassland, creating multi-layered vegetation, and installing low-energy facilities. In addition, it is suggested to conserve wetlands that can be lost during the stream improvement process or to create artificial wetlands to increase carbon storage. The assessment of carbon storage using carbon pools by land cover can improve the objectivity of comparison and evaluation analysis results for land use plans in Environmental Impact Assessment and Strategic Environmental Impact Assessment. In addition, the carbon pool generated in this study is expected to be used as a basis for improving the accuracy of such analyses.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.141-157
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• 2024

This study analyzes the effect of enterepreneurial competencies on start-up performance through network activities for young entrepreneurs. Enterepreneurial competencies are composed of opportunity recognition competencies, marketing competencies, technical competencies, and creative competencies. A total of 354 questionnaires collected from young entrepreneurs residing in the country were used for empirical analysis. SPSS v28.0 and PROCESS macro v4.3 were analyzed based on the research model of a single-parameter single-mediated model. As a result of the analysis, first, it was found that among the enterepreneurial competencies, opportunity recognition competencies, marketing competencies, technical competencies, and creative competencies have a positive (+) significant effect on network activities. Among them, it was found that marketing competence has the greatest effect on network activities and technical competence has the least effect. Second, network activities were found to have a significant effect on start-up performance in a positive (+) direction. Third, among enterepreneurial competencies, opportunity recognition competence, marketing competence, technical competence, and creative competence were found to have a positive (+) effect on start-up performance. Among them, it was found that creative competence had the greatest effect and technical competence had the smallest effect. Fourth, network activities were found to mediate between enterepreneurial competencies and start-up performance. As for the relative effect size of the indirect effects of independent variables, it was found that marketing competence had the greatest effect on start-up performance and technology competence had the smallest effect. The academic implications of this study include investigating the significance and relationship of various variables, providing verification of theoretical frameworks related to entrepreneurship, identifying the main drivers of start-up success, and suggesting the importance of the network between enterepreneurial competencies and start-up performance. In addition, the practical implications of this study suggest the importance of marketing competencies for networking, and suggest differentiation of competencies. It emphasizes the strategic role of creative competence and provides guidance to policymakers for supporting start-ups on customized policies for fostering valuable start-ups.

• Public Diplomacy: Theory and Practice
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• v.3 no.1
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• pp.1-19
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• 2023

Objectives: This study aims to discover how the spread of K-POP and the diversification of the Korean Wave affects Korea's national reputation. K-POP stars are diversifying their interactions with fandom by creating an online space to consume various products and services related to their stars and engage in fan activities. Because of this, this study aims to examine the relevance of K-POP to national reputation through a parasocial relationship with K-POP stars by fandom forming a community and utilizing media. Methods: An online survey was conducted in English using the Amazon survey company Mechanical Turk for BTS fans living in the United States. A total of 195 people's data, excluding incomplete responses, were used for the analysis. Results: It was found that BTS fans' social media participation activities themselves did not directly affect Korea's national reputation. But the mediating effect of BTS fans' parasocial relationship was found. That is, BTS fans' social media participation activities had a positive effect on their parasocial relationships with BTS which in turn had a positive effect on their national reputation. Conlusions: The use and participation of BTS fans in social media in Korea's national reputation has no significant effect on itself, but it has been found that it affects the national reputation through forming parasocial relationships. From the study results, the parasocial relationship of K-POP fans can be used as a strategic mechanism to enhance the national image and Korea's national reputation.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.15-26
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• 2010

Due to the globalization across various industries and cultural trade among many countries, oriental concepts have been attracting world’s attentions. In fashion industry, one's traditional culture is often developed as fashion theme for designers' creation and became strong strategies to stand out among competitors. Because of the increase of preferences for oriental images, opportunities abound to introduce traditional fashion goods and expand culture based business to global fashion markets. However, global fashion brands that include Korean traditional culture are yet to be developed. In order to develop a global fashion brand with Korean taste, it is very important for native citizen to accept their own culture in domestic apparel market prior to expansion into foreign market. Loungewear is evaluated to be appropriate for adopting Korean traditional details into clothing since this wardrobe category embraces various purposes which will easily lead to natural adaptation and wide spread use. Also, this market is seeing an increased demand for multipurpose wardrobes and fashionable underwear (Park et al. 2009). Despite rapid growth in the loungewear market, specific studies of loungewear is rare; and among research on developing modernized-traditional clothing, fashion items and brands do not always include the loungewear category. Therefore, this study investigated the Korean loungewear market and studied consumer evaluation toward loungewear with Korean traditional fashion design elements. Relationship among antecedents of purchase intention for Korean traditional fashion design elements were analyzed and compared between lifestyle groups for consumer targeting purposes. Product quality, retail service quality, perceived value, and preference on loungewear with Korean traditional design elements were chosen as antecedents of purchase intention and a structural equation model was designed to examine their relationship as well as their influence on purchase intention. Product quality and retail service quality among marketing mixes were employed as factors affecting preference and perceived value of loungewear with Korean traditional fashion design elements. Also effects of preference and perceived value on purchase intention were examined through the same model. A total of 357 self-administered questionnaires were completed by female consumers via web survey system. A questionnaire was developed to measure samples' lifestyle, product and retail service quality as purchasing criteria, perceived value, preference and purchase intention of loungewear with Korean traditional fashion design elements. Also, loungewear purchasing and usage behavior were asked as well in order to examine Korean loungewear market status. Data was analyzed through descriptive analysis, factor analysis, cluster analysis, ANOVA and structural equation model was tested via AMOS 7.0. As for the result of Korean loungewear market status investigation, loungewear was purchased by most of the consumers in our sample. Loungewear is currently recognized as clothes that are worn at home and consumers are showing comparably low involvement toward loungewear. Most of consumers in this study purchase loungewear only two to three times a year and they spend less than US$10. A total of 12 items and four factors of loungewear consumer lifestyle were found: traditional value oriented lifestyle, brand-affected lifestyle, pursuit of leisure lifestyle, and health oriented lifestyle. Drawing on lifestyle factors, loungewear consumers were classified into two groups; Well-being and Conservative. Relationships among constructs of purchasing behavior related to loungewear with Korean traditional fashion design elements were estimated. Preference and perceived value of loungewear were affected by both product quality and retail service quality. This study proved that high qualities in product and retail service develop positive preference toward loungewear. Perceived value and preference of loungewear positively influenced purchase intention. The results indicated that high preference and perceived value of loungewear with Korean traditional fashion design elements strengthen purchase intention and proved importance of developing preference and elevate perceived value in order to make sales. In a model comparison between two lifestyle groups: Well-being and Conservative lifestyle groups, results showed that product quality and retail service quality had positive influences on both preference and perceived value in case of Well-being group. However, for Conservative group, only retail service quality had a positive effect on preference and its influence to purchase intention. Since Well-being group showed more significant influence on purchase intention, loungewear brands with Korean traditional fashion design elements may want to focus on characteristics of Well-being group. However, Conservative group's relationship between preference and purchase intention of loungewear with Korean traditional fashion design elements was stronger, so that loungewear brands with Korean traditional fashion design elements should focus on creating conservative consumers' positive preference toward loungewear. The results offered information on Korean loungewear consumers' lifestyle and provided useful information for fashion brands that are planning to enter Korean loungewear market, particularly targeting female consumers similar to the sample of the present study. This study offers strategic and marketing insight for loungewear brands and also for fashion brands that are planning to create highly value-added fashion brands with Korean traditional fashion design elements. Considering different types of lifestyle groups that are associated with loungewear or traditional fashion goods, brand managers and marketers can use the results of this paper as a reference to positioning, targeting and marketing strategy buildings.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.151-171
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• 2014

Firms today have sought management effectiveness and efficiency utilizing information technologies (IT). Numerous firms are outsourcing specific information systems functions to cope with their short of information resources or IT experts, or to reduce their capital cost. Recently, Software-as-a-Service (SaaS) as a new type of information system has become one of the powerful outsourcing alternatives. SaaS is software deployed as a hosted and accessed over the internet. It is regarded as the idea of on-demand, pay-per-use, and utility computing and is now being applied to support the core competencies of clients in areas ranging from the individual productivity area to the vertical industry and e-commerce area. In this study, therefore, we seek to quantify the value that SaaS has on business performance by examining the relationships among firm strategies, SaaS technology maturity, and business performance of SaaS providers. We begin by drawing from prior literature on SaaS, technology maturity and firm strategy. SaaS technology maturity is classified into three different phases such as application service providing (ASP), Web-native application, and Web-service application. Firm strategies are manipulated by the low-cost strategy and differentiation strategy. Finally, we considered customer acquisition as a business performance. In this sense, specific objectives of this study are as follows. First, we examine the relationships between customer acquisition performance and both low-cost strategy and differentiation strategy of SaaS providers. Secondly, we investigate the mediating and moderating effects of SaaS technology maturity on those relationships. For this purpose, study collects data from the SaaS providers, and their line of applications registered in the database in CNK (Commerce net Korea) in Korea using a questionnaire method by the professional research institution. The unit of analysis in this study is the SBUs (strategic business unit) in the software provider. A total of 199 SBUs is used for analyzing and testing our hypotheses. With regards to the measurement of firm strategy, we take three measurement items for differentiation strategy such as the application uniqueness (referring an application aims to differentiate within just one or a small number of target industry), supply channel diversification (regarding whether SaaS vendor had diversified supply chain) as well as the number of specialized expertise and take two items for low cost strategy like subscription fee and initial set-up fee. We employ a hierarchical regression analysis technique for testing moderation effects of SaaS technology maturity and follow the Baron and Kenny's procedure for determining if firm strategies affect customer acquisition through technology maturity. Empirical results revealed that, firstly, when differentiation strategy is applied to attain business performance like customer acquisition, the effects of the strategy is moderated by the technology maturity level of SaaS providers. In other words, securing higher level of SaaS technology maturity is essential for higher business performance. For instance, given that firms implement application uniqueness or a distribution channel diversification as a differentiation strategy, they can acquire more customers when their level of SaaS technology maturity is higher rather than lower. Secondly, results indicate that pursuing differentiation strategy or low cost strategy effectively works for SaaS providers' obtaining customer, which means that continuously differentiating their service from others or making their service fee (subscription fee or initial set-up fee) lower are helpful for their business success in terms of acquiring their customers. Lastly, results show that the level of SaaS technology maturity mediates the relationships between low cost strategy and customer acquisition. That is, based on our research design, customers usually perceive the real value of the low subscription fee or initial set-up fee only through the SaaS service provide by vender and, in turn, this will affect their decision making whether subscribe or not.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.3
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• pp.419-436
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• 2011

Korean farm villages are locked in vicious circle, as lots of their problems related to low income and hollow matters are geared and multiply. To get over those problems, various plans to develop Korean farm villages are being pushed ahead. In addition, since the early of 1990s, Korea has been projects to develop settlement zones and culture villages. It has been also preceeding with a comprehensive development project of farm villages and a new vitalizations project, etc. All of these projects aim to reorganize and expand life environments, industrial bases, and convenience and welfare facilities. The existing studies on a comprehensive project to develop farm villages have been focusing on evaluation indexes, problems, investment priorities, etc. But in fact, studies on a comprehensive development project of farm villages are not thoroughgoing enough in aspects of residents' attitude and their recognition on the influence on tourist development. Thus, this study aims to present strategic schemes to allow residents to actively participate in a stage of promoting a comprehensive development project of farm villages, a stage of making the plan, and a stage of the implementation. For this, this study analyzes a comprehensive development project of farm villages and attempts to figure out which influence the tourist development in farm villages has on residents' attitude and recognition resulting from changes in economic, social cultural, and environmental aspects. Especially, this study previously examines what influential factors there exists are and what influences the development of farm villages has on residents. Based on the results from the above analysis, schemes to enable residents to actively a comprehensive development project of farm villages are presented as follows. First, it is necessary to raise our recognition on tourism and tourism development of farm villages. If the main theme of a comprehensive development project of farm villages intends farm village development, it is required to educate residents and let them clearly raise their recognition on tourism, and the effect of the project is guaranteed. Second, it is highly required to make a plan so that we can feel economic effects of revenues through project promotion and positive effects including the expansion of infrastructures and welfare facilities, etc. Third, it is necessary to bring into relief the positive recognition and attitude of a comprehensive development project of farm villages. As for the negative recognition and attitude, it is very important to change negative residents' recognition to the positive direction and to allow them to participate in and to take an interest in the project, so that the project can be effectively promoted.