• East Asian Journal of Business Economics (EAJBE)
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• v.5 no.3
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• pp.33-40
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• 2017

Purpose - This paper suggests approaching methods for a way of strategies for traditional market extend and new ebusiness, market development, and plan of new product in the future and develop a way of method for cooperation through analysis on the smart phone market trend in different culture, effectively. Research design, data, methodology - As research design, data, and methodology, this paper suggests new idea and approaches from comparing characteristics analysis of smart phone market in different culture in AEC. This paper takes data to analysis from ITU, World Bank, AEC, and IMF. These organizer's data can be trusted as official society in the world. This paper can prove market and the characteristics of society through the corresponding results. Results - This paper can suggest the novel idea on market development and the big possibility depend on ACE country and can describe the possibility on new market because of low smart phone market penetration and low digital market penetration. Conclusions - This paper concludes to develop e-business, culture friendly ship, linking with education, development of appropriate technology depend on country, and should develop new strategy for market extend to low penetration.

• The Journal of Industrial Distribution & Business
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• v.9 no.8
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• pp.51-60
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• 2018

Purpose - Civil affairs are increasing in various forms, but civil servants who are able to handle them want to reduce the complaints and provide keywords that will help in the future due to their lack of time. While various ideas are presented and implemented as policies in solving civil affairs, there are many cases that are not policies that people can sympathize with. Therefore, it is necessary to analyze the complaints accurately and to present correct solutions to the analyzed civil complaint data. Research design, data, and methodology - We analyzed the complaints data for the last three years and found out how to solve the problems of Yongin City and alleviate the burdens of civil servants. To do this, the Hadoop platform and Design Thinking process were reviewed, and proposed a new process to fuse it. The big data analysis stage focuses on civil complaints - Civil data extraction - Civil data analysis - Categorization of the year by keywords analyzing them and the needs of citizens were identified. In the forecast analysis for deriving insights, - The case of innovation case study - Idea derivation - Idea evaluation - Prototyping - Case analysis stage used. Results - Through this, a creative idea of providing free transportation cards to solve the major issues of construction, apartment, installation, and vehicle problems was discovered. There is a specific problem of how to provide these services to certain areas, but there is a pressing need for a policy that can contribute as much as it can to the citizens who are suffering from various problems at this moment. Conclusions - In the past, there were many cases in which free traffic cards were issued mainly to the elderly or disabled. In other countries, foreign residents of other area visit the areas for accommodation, and may give out free transportation cards as well. In this case, the local government will be able to set up a framework to present with a win-win scenario in various ways. It is necessary to reorganize the process in future studies so that the actual solution will be adopted, reduce civil complaints, help establish policies in the future, and be applied in other cities as well.

• Journal of Distribution Science
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• v.13 no.7
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• pp.53-61
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• 2015

Purpose - This research analyzes overseas expansion support systems for small- and medium-sized enterprises in Germany and Japan. Germany and Japan have developed overseas expansion support policies for such enterprises. The study then explores the implications for Korea and its local governments. Research design, data, and methodology - We did a comparative analysis of Japan and Germany and their support for overseas expansion of small and medium companies. Data were mainly collected from the Ministry of Economy, Trade and Industry (Japan) and the Germany Trade and Invest (Germany) agency through statistics and literature surveys, and analysis studies. Results - First, human resources cultivation and funding support policies, which both Germany and Japan use as part of small- and medium-sized enterprise policies, should be modified to Korean circumstances and to reflect its own small- and medium-sized enterprise support needs. Second, both the German policies that support overseas expansion of small- and medium-sized enterprises and those of Japan's include the philosophy and methods that put an emphasis on these enterprises, despite the fact that there are big differences in the overseas policies in these two countries. Third, German and Japanese governments are embracing the idea that small- and medium-sized enterprises are key to their national economies and implementing policies based on the ratio occupied by these enterprises in the domestic consumption or GDP. In other words, Germany and Japan consider small- and medium-sized enterprises as central to their nation's industry, and assess them as economic industry that should definitely exist for the continued survival of big businesses, and not just as merely supplemental to big business. Fourth, whereas Germany emphasizes support to product exhibition in its overseas expansion support policies, Japan is providing integrated support containing foreign direct investment to small- and medium-sized enterprises. Fifth, there are differences in the overseas expansion support in Germany and Japan in terms of their support to big business. Whereas Germany considers support to big business unnecessary, Japan is implementing active support policies to areas corresponding to big business. Korea will have to benchmark the policies of Germany and Japan, and decide whether or not to give full support to small- and medium-sized enterprises, while excluding areas supporting big business. Conclusions - Based on this analysis of German and Japanese overseas expansion support policies, we need to choose the policies that will engender a solid outcome and derive modified policies for the circumstances of Korea. Additionally, we can use the comparison of the overseas support policies of Japan and Germany to choose small- and medium-sized enterprise overseas expansion support policies for Korea. However, we cannot provide specific overseas support policies by industry. This point will be referenced as a limitation of this study. In future research, we expect that some researchers will take an empirical approach to exploring Korean overseas expansion support through collecting cases of overseas support policies and interviewing policy authorities.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.83-92
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• 2023

The purpose of this research is to develop a creative education program that utilizes AI education program based on big data for general education high schools, and to investigate its effectiveness. In order to achieve the purpose of the research, we developed a creative education program using artificial intelligence based on big data for first-year general high school students, and carried out on-site classes at schools and a validation process by experts. In order to measure the creative problem-solving ability and class satisfaction of high school students, a creative problem-solving ability test was conducted before and after the program application, and a class satisfaction test was conducted after the program. The results of this study are as follows. First, AI education program based on big data were statistically effective to improve the creative problem solving ability according to independent sample t test about 'problem discovery and analysis', 'idea generation', 'execution plan', 'conviction and communication', and 'innovation tendency' except 'execution', 'the difference between pre- and post-scores of male student and female student' on first year high school students. Secondly, in satisfaction conducted after classes of AI education program based on big data, the average of 'Satisfaction', 'Interest', 'Participation', 'Persistence' were 3.56 to 3.92, and the overall average was 3.78. Therefore, it was investigated that there was a lesson effect of the AI education program based on big data developed in this research.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.39-50
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• 2018

Today, gamification that appeal to people and provide fun by applying game thinking and elements in many non-game fields is becoming a big issue. This study analyzed the case of 'Idea Community' in Creative Economy Town that combines online mentoring and gamification. In order to foster and select ideas, we conducted the open simulated investment and mentoring. In this process, members are able to acquire experience points and raise the level when doing certain activities. Besides, members felt their sense of accomplishment by receiving internal/external rewards for their activities. The results will be an importance reference for the application of gamification in various fields.

• International Journal of Contents
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• v.13 no.2
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• pp.21-28
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• 2017

Abnormal data in the manufacturing process makes it difficult to find useful information that can be applied in data management for the manufacturing industry. It causes various problems in the daily process of production. An issue from the abnormal data can be handled by our method that uses big data and visualization. Visualization is a new technology that transforms data representation into a two-dimensional representation. Nowadays, many newly developed technologies provide data analysis, algorithm, optimization, and high efficiency, and they meet user requirements. We propose combined production of the data visualization approach that uses integrative visualization of sources of abnormal pattern analysis results. The perceived idea of the proposed approach can solve the problem as it also works for big data. It can also improve the performance and understanding by using visualization and solving issues that occur in the manufacturing process with a calendar heat map.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.609-619
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• 2016

RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. In this paper, we implement K-Means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. The main idea introduces a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. We showed that our K-Means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases. We also implemented Elbow method with MapReduce for finding the optimum number of clusters for K-Means clustering on large dataset. Comparison with our MapReduce implementation of Elbow method and classical kmeans() in R with small data showed similar results.

• Education of Primary School Mathematics
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• v.21 no.2
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• pp.193-208
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• 2018

Classification is presented in the curriculum of elementary school mathematics, science, Korean language, and integrated subjects as the major function that needs to be learned. In addition, mathematics textbooks teach the classification as a basic process for organizing and interpreting collected materials in a separate unit. So, we analyzed the curriculum documents and textbooks of mathematics, science, Korean language, and integrated subjects. And we explored how to teach the classification in the context of mathematics subject. As a result, it is necessary to find different classification criteria in conjunction with detailed observation and investigation activities, and to teach that considering the circumstances and purpose of the classification. It also provided implications on how to revive converged classes that focus on big ideas and skills, which are commonly offered by various subjects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2194-2210
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• 2018

In the era of big data, consumers capture more and more economic surplus yet the seed of distrust also grows with the fast-spreading of social commerce, this paper began with the idea that product types may determine the degree of consumers' distrust even when identical discounts are offered for those products on Chinese social commerce websites. We also attempted to determine if distrust negatively affected consumers' purchase attitudes. 20 representative products that are commonly sold on social commerce websites in China were chosen to examine the relationships among product types, discount rates, distrust levels, and purchase attitudes. Inductive interview was used to collect the data as well as consumers' perceptions of the relationships. Data analysis results suggested that consumers like deep discounts, but their distrust levels increase along with the discount rates, however, the levels of increasing distrust vary according to product types. High, medium, and low discount rate categorizations were made and three propositions were suggested. This paper will contribute to the body of knowledge on online social commerce market and provide valuable implications for e-retailers and general consumers in online social commerce websites in China.

• Journal of Korean Society for Quality Management
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• v.48 no.4
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• pp.553-566
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• 2020

Purpose: The purpose of this study was to design a framework for generating one-class classification algorithm based on Hyper-Rectangle(H-RTGL) in a distributed environment connected by network. Methods: At first, we devised one-class classifier based on H-RTGL which can be performed by distributed computing nodes considering model and data parallelism. Then, we also designed facilitating components for execution of distributed processing. In the end, we validate both effectiveness and efficiency of the classifier obtained from the proposed framework by a numerical experiment using data set obtained from UCI machine learning repository. Results: We designed distributed processing framework capable of one-class classification based on H-RTGL in distributed environment consisting of physically separated computing nodes. It includes components for implementation of model and data parallelism, which enables distributed generation of classifier. From a numerical experiment, we could observe that there was no significant change of classification performance assessed by statistical test and elapsed time was reduced due to application of distributed processing in dataset with considerable size. Conclusion: Based on such result, we can conclude that application of distributed processing for generating classifier can preserve classification performance and it can improve the efficiency of classification algorithms. In addition, we suggested an idea for future research directions of this paper as well as limitation of our work.