• Cartoon and Animation Studies
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• s.49
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• pp.53-85
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• 2017

This study deals with the production system of the superhero animation that are based on DC comic books and are produced by Warner Brothers company, and tries to find out ways in order to vitalize the new window of the animation market. 28 superhero animations released from 2007 until 2017 are analyzed. Several critical points are drawn out and can be applied to the Korean animation industry. There are two categories, one is about the management of the production system, and the other is about the subcontract system. In managing the production system, there are three points: First, there are several people who play the role of either a producer or a director many times. Second, producers used to work as a group. Third, some people work not only as a producer but also as a director. In carrying out outsourcing contracts, there are six points: First, only Korean and Japanese companies participate as subcontract companies. Second, about two companies used to take part in the subcontract production in a year. Third, in case of number of people involved in production, there are more Japanese than Korean. Fourth, Japanese companies deal with some parts of the pre-production as well as the main production in . Fifth, a Japanese company has a sub-subcontract with a Korean company in one episode of . Sixth, Korean companies mostly focus on the production part of key animation. Important points that the Korean production system has to consider are also suggested under the two categories. In the production system management, there are two points. It is needed to make use of the group producer system, and it is critical to develop the story line of universe type such as DC Universe. In case of the outsourcing production system, it is essential to keep up educating 2D type of animation and, at the same time, to participate actively in the global outsourcing production. By considering these crucial points, it is expected to keep producing animation that can be used for the media window such as IPTV.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.101-117
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• 2013

As the number of online game user has been rapidly increased thanks to the recent vitalization of online contents market, not only new business opportunity but also the opportunity to create high profits have been provided as well. However, the increase of the number of online game user and the rapid expansion of the market evoke a cutthroat completion among online game service providers, and also high barriers to entry to online game market have been erected. Thus, what kinds of efforts need for the business success and sales increase in online game market? In lots of researches regarding online contents business, the deepening of loyalty was considered as a critical factor for the business success. According to the study on user's behavior in online environment, users would experience the Flow while using online service, and then, if they were in state of the Flow, they would use the service constantly. High customer loyalty to online game means high will to use the online game too. The purpose of this research was i) to examine what factors enable users to be naturally immersed in online game while playing it, ii) to examine what properties of online game can make game more interesting and exciting, iii) to verify that such factors are critical in deepening customer loyalty, and iv) to suggest some essential factors to be fun and exciting games, on where the focus should be put, and the directionality for the development for sales expansion of online game developer or online game service provider. The research results are as below: First, the involvement and the perceived quality which were characteristics of brand appeared to be factors most affecting Flow. This shows that once game user get interested in online game that user has played frequently, even though new games are released, user will continuously flow the game not moving to new games, and also shows that users not only get more interested but also put more trust in games in the site to where users are frequently going than games in other sites, and consequently user can increasingly flow the game. Second, the compensation and graphics which are the characteristics of contents appeared to be factors affecting Flow. Proper compensation which is given to game users triggers fun and interests in game and makes them flow more and more. And graphics make users to feel game space as if real space and let them flow in game with more reality. Third, challenges, support, and the stability which are technical characteristics appeared to be factors affecting Flow. Challenges enable users to not only experience new virtual world but also solve various difficulties and obstacles. Once users feel fun and interests through this challenge, they can naturally flow games. In addition, the stability of network provides reliability in security and hacking. By doing so, it can induce users to flow more and more. Lastly, when aforementioned characteristics including contents characteristics, technical characteristics, and brand characteristics are organically combined each other, game users feel fun and total minutes are naturally increased, so that game users experience Flow, and consequently the customer loyalty will be deepened as well.

• Korean Security Journal
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• no.42
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• pp.59-85
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• 2015

The purpose of this study is to establish the structural relationship among organizational ethical climate, job satisfaction, and organizational citizenship behavior. It was intended for the private security guards who work in the security companies in Seoul and Gyeonggi from Jan. 1st, 2014 to Apr. 1st, 2014 to achieve the purpose like this. Purposive sampling was used as the sampling method according to this and sampling of 400 persons was done. However, the samples of 372 persons were finally used in the analysis through the process to check faithless answers, double answers, and abnormal data. The collected data was analyzed according to the purpose of the study by utilizing STATA 13.0 and AMOS 17.0. And for statistic techniques, frequency analysis, descriptive analysis, multivariate normality, confirmatory factor analysis(CFA), Pearson's correlation analysis, and structural equation model analysis were carried out. The conclusion gotten from this study through the data analyses according to the methods and procedure like this is as follow: First, organizational ethical climate has found to have the positive effect on job satisfaction(Non-standard $B=1.427^{***}$). That is, it can be interpreted that organizational ethical climate positively affects superiors, fellow employees, pay, current duties, and chances of promotion. Second, job satisfaction has found not to have the significant effect on organizational citizenship behavior. That is, it can be interpreted that job satisfaction does not affect altruism, conscience, and participation behavior. Third, organizational ethical climate has found to have the positive effect on organizational citizenship behavior (Non-standard $B=.361^{***}$). That is, it can be interpreted that organizational ethical climate positively affects altruism, conscience, and participation behavior. Fourth, the relationship between organizational ethical climate and organizational citizens has found that there is no any indirect effect in the bootstrapping estimation result to establish the indirect effect of job satisfaction. Fifth, the relationship between organizational ethical climate and job satisfaction has found that there are the moderating effects in the analytical result of the moderating effects of person-organization fit. That is, the effects of organizational ethical climate on job satisfaction have found that the groups with higher person-organization fit are more positive than those with lower person-organization fit. Sixth, the relationship between job satisfaction and organizational citizenship behavior has found that there are moderating effects in the analytical result of person-organization fit. That is, the effects of job satisfaction on organizational citizenship behavior have found that the groups with higher person-organization fit are more positive than those with lower person-organization fit.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.45-54
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• 2021

This study was written to create educational content in non-destructive fields based on Mixed Reality. Currently, in the field of radiation, there is almost no content for educational Mixed Reality-based educational content. And in the field of non-destructive inspection, the working environment is poor, the number of employees is often 10 or less for each manufacturer, and the educational infrastructure is not built. There is no practical training, only practical training and safety education to convey information. To solve this, it was decided to develop non-destructive worker education content based on Mixed Reality. This content was developed based on Microsoft's HoloLens 2 HMD device. It is manufactured based on the resolution of 1280 ⁎ 720, and the resolution is different for each device, and the Side is created by aligning the Left, Right, Bottom, and TOP positions of Anchor, and the large image affects the size of Atlas. The large volume like the wallpaper and the upper part was made by replacing it with UITexture. For UI Widget Wizard, I made Label, Buttom, ScrollView, and Sprite. In this study, it is possible to provide workers with realistic educational content, enable self-directed education, and educate with 3D stereoscopic images based on reality to provide interesting and immersive education. Through the images provided in Mixed Reality, the learner can directly operate things through the interaction between the real world and the Virtual Reality, and the learner's learning efficiency can be improved. In addition, mixed reality education can play a major role in non-face-to-face learning content in the corona era, where time and place are not disturbed.

• Journal of Korea Port Economic Association
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• v.38 no.1
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• pp.1-14
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• 2022

The change in the management environment of the logistics industry in the era of global competition is becoming an era in which customers choose companies. Differentiation from competitors through the provision of products and services suitable for customers As customers' choices change depending on their superiority, companies are constantly striving to receive or retain customers' choices. Ultimately, this competitive structure can be seen as the importance of long-term relationship building. Therefore, in this study, we examined how factors related to transaction characteristics performed by logistics companies for customer satisfaction in the transaction relationship between cargo companies and shippers affect performance and long-term transaction intentions. First, we derived the factors of logistics service, cost, logistics infrastructure, and company competency, which are transaction characteristics factors of a logistics company that must be specifically realized for customer satisfaction in transactions between logistics companies. Second, we analyzed how the transaction characteristics factors of a logistics company affect the company's performance, and finally, how the company's performance factors affect long-term transaction intentions. As a result of empirical analysis, there were no statistically significant results on the relationship between transaction characteristics and performance of logistics companies, which can be attributed to the small size of the logistics companies that were the sample. In other words, logistics companies that do not have sufficient capacity to provide services at low prices have no choice but to engage in constant bleeding competition. It can be seen that it reflects the characteristics of the industry. On the other hand, the relationship between corporate performance factors and long-term transaction intention was found to have a positive relationship. The higher the level of partnership with logistics companies and visible financial performance is, the higher the transaction will be in the future, and the more the transaction volume will be gradually increased. And even if it costs a little more, it can be seen that the intention to continue trading is greatly expressed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.135-145
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• 2022

Due to COVID 19, we are facing unprecedented phenomena. Among various industries, the aviation industry, as it is directly affected by the corona crisis is actively establishing various survival strategies, such as expanding cargo transportation. The market size of air cargo transportation is continuously increasing due to the characteristics that distinguish it from other transportation, and as individualism and selfishness deepen in the aftermath of COVID 19, it can be inferred that the concept of reciprocity within distribution channels will become important in the post-corona era. The specific contents of this study(research question) are as follows. First, as a central member of the air logistics distribution channel, logistics service companies business process and the sub-dimensions of trust of are identified, and how trust is built with transportation companies is investigated. Second, the effect of such trust on the various performances of logistics service companies is analyzed. Third, we examine whether the influences of the sub-dimensions of trust change according to the perceived reciprocity of logistics service companies. In addition, we investigate whether the perceived reciprocity changed before and after the corona situation. In particular, this study theoretically integrates the concepts of trust and commitment, which have been distinguished in many prior studies, to improve the parsimony and practicality of the research model. This study will be able to present useful academic and practical implications by empirically examining how trust is built between members of the air logistics distribution channel and furthermore, how much it affects the performance of logistics service companies, and by identifying the moderating effect of reciprocity.

• Journal of Environmental Impact Assessment
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• v.33 no.1
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• pp.30-41
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• 2024

The way we work is changing significantly with the rapid development of digitaltechnology, and paper documents are being replaced by electronic documents. However, in accordance with the Enforcement Decree and Enforcement Regulation of the Environmental Impact Assessment Act, the environmental impact assessment report must submit a set number of paper reports to organizations related to the project, and about 42 years have passed since it was submitted as a paperreport. In 2022, the National Institute of Ecology introduced a system to review paperreports as electronic documents in line with the trend of digital transformation. The cost reduction and carbon emission reduction effects of electronic document review were analyzed for 1,398 environmental impact assessments submitted and reviewed in 2022. In addition, a satisfaction survey was conducted targeting type 1 environmental impact assessment companies that were directly affected, and a total of 134 people responded. As a result of analyzing the effect of reviewing electronic documents, costs are reduced by a total of 101,424,900 won per year and carbon emissions are reduced by about 59.7 tons. As a result of the satisfaction survey, 94.8% of the respondents said electronic documentreview was very helpful, and 4.5% said it was helpful. The effectiveness of electronic documentreview was high, with 94.8% of respondents saying it was helpful in economic terms and 91.8% saying it was helpful in reducing work hours. If electronic documents are reviewed through the revisions to the Enforcement Decree and Enforcement Regulation of the Environmental Impact Assessment Act, the implementation of electronic document review is expected to have a ripple effect across the country, not only reducing costs and carbon emissions, but also reducing administrative time and saving storage space. Rapid changes in law and administration are needed to adapt to the digital transformation era.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Food Hygiene and Safety
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• v.28 no.1
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• pp.69-74
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• 2013

This study has been performed for 150 days from February 1 - June 31, 2012 aiming at analyzing biologically hazardous factors in order to develop HACCP system for the vinegared pickle radishes. A process chart was prepared as shown on Fig. 1 by referring to manufacturing process of manufacturer of general vinegared pickle radishes regarding process of raw agricultural products of vinegared pickle radishes, used water, warehousing of additives and packing material, storage, careful selection, washing, peeling off, cutting, sorting out, stuffing (filling), internal packing, metal detection, external packing, storage and consignment (delivery). As a result of measuring Coliform group, Staphylococcus aureus, Salmonella spp., Bacillus cereus, Listeria Monocytogenes, E. coli O157:H7, Clostridium perfringens, Yeast and Mold before and after washing raw radishes, Bacillus cereus was $5.00{\times}10$ CFU/g before washing but it was not detected after washing and Yeast and Mold was $3.80{\times}10^2$ CFU/g before washing but it was reduced to 10 CFU/g after washing and other pathogenic bacteria was not detected. As a result of testing microorganism variation depending on pH (2-5) of seasoning fluid (condiment), pH 3-4 was determined as pH of seasoning fluid as all the bacteria was not detected in pH3-4. As a result of testing air-borne bacteria (number of general bacteria, colon bacillus, fungus) depending on each workplace, number of microorganism of internal packing room, seasoning fluid processing room, washing room and storage room was detected to be 10 CFU/Plate, 2 CFU/Plate, 60 CFU/Plate and 20 CFU/Plate, respectively. As a result of testing palm condition of workers, as number of general bacteria and colon bacillus was represented to be high as 346 $CFU/Cm^2$ and 23 $CFU/Cm^2$, respectively, an education and training for individual sanitation control was considered to be required. As a result of inspecting surface pollution level of manufacturing facility and devices, colon bacillus was not detected in all the specimen but general bacteria was most dominantly detected in PP Packing machine and Siuping machine (PE Bulk) as $4.2{\times}10^3CFU/Cm^2$, $2.6{\times}10^3CFU/Cm^2$, respectively. As a result of analyzing above hazardous factors, processing process of seasoning fluid where pathogenic bacteria may be prevented, reduced or removed is required to be controlled by CCP-B (Biological) and threshold level (critical control point) was set at pH 3-4. Therefore, it is considered that thorough HACCP control plan including control criteria (point) of seasoning fluid processing process, countermeasures in case of its deviation, its verification method, education/training and record control would be required.