• 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.

• Maritime Security
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• v.1 no.1
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• pp.215-240
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• 2020

In 2017, the U.S. DARPA coined 'mosaic warfare' as a new way of warfighting. According to the Timothy Grayson, director of DARPA's Strategic Technologies Office, mosaic warfare is a "system of system" approach to warfghting designed around compatible "tiles" of capabilities, rather than uniquely shaped "puzzle pieces" that must be fitted into a specific slot in a battle plan in order for it to work. Prior to cover mosaic warfare theory and recent development, it deals analyze its background and several premises for better understanding. The U.S. DoD officials might acknowledge the current its forces vulnerability to the China's A2/AD assets. Furthermore, the U.S. seeks to complete military superiority even in other nation's territorial domains including sea and air. Given its rapid combat restoration capability and less manpower casualty, the U.S. would be able to ready to endure war of attrition that requires massive resources. The core concept of mosaic warfare is a "decision centric warfare". To embody this idea, it create adaptability for U.S. forces and complexity or uncertainty for the enemy through the rapid composition and recomposition of a more disag g reg ated U.S. military force using human command and machine control. This allows providing more options to friendly forces and collapse adversary's OODA loop eventually. Adaptable kill web, composable force packages, A.I., and context-centric C3 architecture are crucial elements to implement and carry out mosaic warfare. Recently, CSBA showed an compelling assessment of mosaic warfare simulation. In this wargame, there was a significant differences between traditional and mosaic teams. Mosaic team was able to mount more simultaneous actions, creating additional complexity to adversaries and overwhelming their decision-making with less friendly force's human casualty. It increase the speed of the U.S. force's decision-making, enabling commanders to better employ tempo. Consequently, this article finds out and suggests implications for Korea armed forces. First of all, it needs to examine and develop 'mosaic warfare' in terms of our security circumstance. In response to future warfare, reviewing overall force structure and architecture is required which is able to compose force element regardless domain. In regards to insufficient defense resources and budget, "choice" and "concentration" are also essential. It needs to have eyes on the neighboring countries' development of future war concept carefully.

• Korean small business review
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• v.42 no.3
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• pp.101-121
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• 2020

Marking the 40th anniversary of the founding of The Korean Association of Small Business Studies, this paper was carried out to shed light on the historical trend of 40 years of small and medium business research through the papers published in the Asia Pacific Journal of Small Business and to consider the direction of future small and medium business research. In particular, we will focus on small and medium venture business policies and strategic management aspects of small and medium venture businesses to analyze the contents of published papers related to the subject and contribute to finding implications and future research directions. In order to analyze the research trends of small and medium venture business policies and strategic management sectors of small and medium venture companies covered in the Asia Pacific Journal of Small Business from 1979 to 2019, the analysis was divided by time and item based on research subjects, research methods, researchers, etc., and the primary analysis results are as follows: First, out of a total of 1,056 research papers, research papers on small and medium venture enterprise policy and strategic management showed a ratio of about 14% and 11% of the total research. Second, in terms of research subjects, the proportion of policy research on funds and start-ups and ventures was high in the field of small and medium venture enterprise policy, and the research on internationalization strategy was carried out the most in the area of strategic management. Third, qualitative research was more prominent until the 1980s, but the proportion of quantitative research began to increase after the 1990s, and since then, quantitative research has been carried out more than qualitative research. Fourth, over the past 40 years, Hanyang University, Kyungpook National University, Konkuk University, etc. were the institutions that presented research papers most actively in the areas of small and medium venture business policy and strategic management, and the research institute's participation was somewhat insufficient. The main implications of this study for the continuous development of the Asia Pacific Journal of Small Business are as follows. First, it is necessary to enhance the link between research on policy research and strategic management of small and medium venture companies in terms of research subject matter. Second, more diversity should be pursued in terms of research methods. Third, it is necessary to increase the participation rate of public and private research institutes related to small and medium venture enterprises in academic societies.

• Korean small business review
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• v.42 no.2
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• pp.69-92
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• 2020

This study is aimed at the growth and development of family businesses that greatly contribute to Korea's economic development, but the specific research purpose is to firstly examine the research trends and current status of Korean family businesses and compare them with those of developed countries such as the United States. Second, I would like to look at the future research for revitalizing Korean family business research. In addition, we intend to contribute to increasing the interest in this field and the number of researchers involved. The research target of this paper is 212 papers published in professional academic journals for 13 years from 2006 to 2018 when family businesses began to be fully researched in Korea, 112 master's and doctoral dissertations (graduate schools), and 324 totals. As a result of empirical analysis, the number of published papers is increasing more than the initial ones, but it has been on the decline recently. In addition, 57.5% of the journals are papers that do not have specific definitions or simply list the claims of several scholars by analyzing content. Thesis was 33.9%. As for the type of research, qualitative research, which is a conceptual research, is a small number, and empirical research occupies most of the research topics. Research topics and academic dissertations also have a large proportion of management, management strategy, succession, financial accounting, and business performance. In other words, it can be said that the research on family business in Korea corresponds to the early childhood of the United States. First of all, in the future, we need to put more effort into increasing the qualitative research, starting with the definition of a family business, which is an essential problem, in addition to the theory building of family business. Second, as an analysis level of research, we should make family an important level of analysis for existing individuals, groups, and organizations. Third, the research subject and research area should be expanded. It is desperately necessary to study large companies including chaebols, mainly from small and medium-sized companies, which are the existing research areas of family business. In addition, it is considered that it is necessary to appropriately introduce various theories suitable for the interdisciplinary study, which is the characteristic of the family business, for example, theories of family science, psychology, and sociology. Fourth, it should build the research infrastructure.

• (The) Research of the performance art and culture
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• no.40
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• pp.223-268
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• 2020

In contemporary Theatre, the case of inducing direct communication between the audience and the performance is prominent. Especially with the development of digital technology, the audience wants a personalized experience. The emergence of 'immersive Theatre' in this trend has attracted great attention both at home and abroad. In particular, the most important role in the emergence of the concept of 'immersive Theatre' is the British punchdrunk Theatre. Their representative performance began to premiere in London in the UK in 2003 and has expanded to include New York and China in Shanghai and continues to be extremely popular until 2019. In general, a review of existing studies on the role of the audience in shows that the focus is on the participation of the audience. What experience will be given to the audience can not be emphasized in contemporary Theatre. In order to satisfy the diverse needs of the audience, contemporary Theatre are increasingly showing complexity that cannot be explained by any one theory. The same goes for . This is because each audience wants a personalized experience, and there are differences in experience depending on the environment in which the audience also grew up, knowledge, culture, and taste. This study selected Punch Drunk's as a performance that can represent contemporary Theatre, and conducted a study on the role of audience in contemporary Theatre. To this end, we have historically explored past discussions about the role of the audience and discussed the characteristics of the role of the audience in contemporary Theatre. Next, I analyzed in detail the experience of the researcher "He" who watched the performance with the researcher on the role of the audience in . In conclusion, the experience of the audience in is diverse and complex. In other words, the role of the traditional audience in the proscenium play, as well as the audience as a participant in the post-drama play, was also complex in the performance. And this complexity was not a coincidence, but a planning strategy for the Punchdrunk Theatre. Therefore, when discussing the role of the audience in contemporary Theatre, there should be a discussion that clearly sees the complex characteristics of contemporary Theatre through the approach from various perspectives, rather than merely one view of the audience as a participant. something to do.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.15-31
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• 2022

This study was conducted to suggest a start-up policy that includes start-up education and support for active seniors with various careers who try to change their careers before and after retirement. From this point of view, this study divided the factors affecting the entrepreneurial will of active seniors into entrepreneurship organizational and functional competency and identified the effect of these competencies on entrepreneurial efficacy and entrepreneurial intention. In the proposed model, start-up competency is divided into organizational competency (leadership, creativity problem-solving, communication, decision-making) and functional competency (management strategy, marketing, business plan). And this study examined the mediating role of entrepreneurial efficacy in the relationship between entrepreneurial competency factors and entrepreneurial intention. Meanwhile, PLS-POS analysis was performed to uncover the heterogeneity and pattern in the proposed structural model. The survey was conducted with the help of an online survey company from November 27 to December 15, 2020 for the active senior age group from 40 to under 65 years old. Data were collected from a total of 433 panelists and analyzed using SPSS 22.0 and SmartPLS 3.3.7 programs. The findings are as follows. First, the finding shows that the entrepreneurial organizational and functional competencies of active seniors had significant positive(+) effects on entrepreneurial efficacy. Second, the result shows that entrepreneurial organizational and functional competencies of active seniors had significant positive(+) effects on entrepreneurial intention. Third, the findings show that entrepreneurship efficacy had a significantly positive(+) effect on entrepreneurial intention. The findings of PLS-POS show that entrepreneurship education needs to be carried out by identifying the needs that require entrepreneurial organizational and functional competency when training for entrepreneurship competency. In summary, the findings of the current study are to determine what the competency factors are for the government (local government) to increase the policy direction necessary for establishing and implementing entrepreneurship education and training programs to develop policies to enhance the economic activity participation rate of active seniors.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.