• Journal of Service Research and Studies
• /
• v.10 no.4
• /
• pp.1-19
• /
• 2020

It is very important to explore new management theories that are better in line with the modern service economy era in order to cement the foundation of the service industry in this rapidly changing business environment. This study examined the relationship between service essentials and job performance by service industry, and verified and discussed in depth whether there is difference between service essentials and job performance by demographic characteristics. The results of this study are as follows: First, an analysis of the effect of service essentials on job performance found the interaction, horizontality and harmony of service essentials had positive effects on performance, but the relationship didn't. Next, an analysis of the effect of service essentials on job performance by representative service industry showed that in the transportation industry, interaction and harmony had positive effects on performance, but relationship and horizontality didn't affect performance. In the financial and insurance industries, horizontality and interaction had positive effects on performance, but harmony and relationship didn't affect performance. Accommodation and food industries, interaction, horizontality and harmony had positive effects on performance, but relationship didn't affect performance. In the medical and health industries, interaction and horizontality had positive effects on performance, but relationship and harmony didn't affect performance. In terms of demographic characteristics, in the financial and insurance industries, interaction and harmony showed a significant difference by age, but only horizontality showed a difference by the number of years of service. In the accommodation and food industries, only horizontality showed a difference depending on the number of years of service. In the medical and health industries, relationship, horizontality and harmony showed a difference depending on the number of years of service, but only horizontality showed a significant difference by marital status. In the future, comparative national studies are needed for all industrial groups.

• Journal of Mushroom
• /
• v.21 no.1
• /
• pp.1-7
• /
• 2023

This study addresses the current demand of the Korean mushroom export industry to establish an export strategy and governing policies.The enoki mushroom exports increased by 89% in 2009 and 23% in 2010, resulting in the largest export volume (17,163 tons) and export value ($26,292,000) being recorded in 2010. In contrast, exports in 2020 yielded only $18,525,000, which was 29% lower than that in 2010. In case of king oyster mushrooms, exports increased by 10% in 2012, 13% in 2013, and 2% in 2014, maintaining a moderate-growth trend. Moreover, Korea's mushroom exports are focused on a few specific countries. Enoki mushrooms accounted for more than 50% of the total exports to North America and Vietnam from 2012 to 2022, whereas king oyster mushrooms accounted for more than 50% of the total exports to Europe and North America (USA and Canada) from 2009 to 2022. Another characteristic trend in Korean mushroom exports is the diversification of export markets. The number of countries importing enoki mushrooms and king oyster mushrooms from Korea is increasing.

• Journal of agricultural medicine and community health
• /
• v.48 no.2
• /
• pp.103-117
• /
• 2023

Objectives: This study aims to reveal the relationship between social relations and physical activity in the young-old and old-old elderly. Methods: Data from 2020 National survey of Older Koreans were used, and a total of 10,097 subjects over the age of 65 were included in analysis. The dependent variable was physical activity, and the independent variables were social relations barrier and motivational factors. x²-test and binary logistic regression were performed for data analysis. Results: The physical activity rate in the elderly were 40.8% in the young-old and 29.2% in the old-old. The socio-demographic characteristics affecting physical activity were the young-old elderly were sex, residential area, employment status and household income, and the old-old elderly were sex, age, residential area, education level and household income. The social relations barrier factors affecting physical activity were the young-old elderly were number of close friends, family care, exercise information search and video viewing, and the old-old elderly were household type, number of close friends, participation in exercise education, exercise information search and video viewing. The social relations motivational factors affecting physical activity were the young-old elderly were call with children/relative/friend, participation in sports activity, access time from home to parks, and the old-old elderly were call with children/relative/friend, participation in sports activity, satisfaction with green spaces. Conclusions: It was found that social relations barrier and motivational factors of the elderly are important factors to consider when developing physical activity promotion strategy, and there are also difference between the age of the elderly.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.149-169
• /
• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.91-108
• /
• 2020

Korea's famous soccer players are steadily performing well in international leagues, which led to higher interests of Korean fans in the international leagues. Reflecting the growing social phenomenon of rising interests on international leagues by Korean fans, the study examined the overall consumer perception in the consumption of uniform by domestic soccer fans and compared the changes in perception following the transfers of the players. Among others, the paper examined the consumer perception and purchase factors of soccer fans shown in social media, focusing on periods before and after the recruitment of Heung-Min Son to English Premier League's Tottenham Football Club. To this end, the EPL uniform is the collection keyword the paper utilized and collected consumer postings from domestic website and social media via Python 3.7, and analyzed them using Ucinet 6, NodeXL 1.0.1, and SPSS 25.0 programs. The results of this study can be summarized as follows. First, the uniform of the club that consistently topped the league, has been gaining attention as a popular uniform, and the players' performance, and the players' position have been identified as key factors in the purchase and search of professional football uniforms. In the case of the club, the actual ranking and whether the league won are shown to be important factors in the purchase and search of professional soccer uniforms. The club's emblem and the sponsor logo that will be attached to the uniform are also factors of interest to consumers. In addition, in the decision making process of purchase of a uniform by professional soccer fan, uniform's form, marking, authenticity, and sponsors are found to be more important than price, design, size, and logo. The official online store has emerged as a major purchasing channel, followed by gifts for friends or requests from acquaintances when someone travels to the United Kingdom. Second, a classification of key control categories through the convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm shows differences in the classification of individual groups, but groups that include the EPL's club and player keywords are identified as the key topics in relation to professional football uniforms. Third, between 2002 and 2006, the central theme for professional football uniforms was World Cup and English Premier League, but from 2012 to 2015, the focus has shifted to more interest of domestic and international players in the English Premier League. The subject has changed to the uniform itself from this time on. In this context, the paper can confirm that the major issues regarding the uniforms of professional soccer players have changed since Ji-Sung Park's transfer to Manchester United, and Sung-Yong Ki, Chung-Yong Lee, and Heung-Min Son's good performances in these leagues. The paper also identified that the uniforms of the clubs to which the players have transferred to are of interest. Fourth, both male and female consumers are showing increasing interest in Son's league, the English Premier League, which Tottenham FC belongs to. In particular, the increasing interest in Son has shown a tendency to increase interest in football uniforms for female consumers. This study presents a variety of researches on sports consumption and has value as a consumer study by identifying unique consumption patterns. It is meaningful in that the accuracy of the interpretation has been enhanced by using a cluster analysis via convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm to identify the main topics. Based on the results of this study, the clubs will be able to maximize its profits and maintain good relationships with fans by identifying key drivers of consumer awareness and purchasing for professional soccer fans and establishing an effective marketing strategy.

• Journal of Intelligence and Information Systems
• /
• v.26 no.4
• /
• pp.149-171
• /
• 2020

The period at university is to make decision about getting an actual job. As our society develops rapidly and highly, jobs are diversified, subdivided, and specialized, and students' job preparation period is also getting longer and longer. This study analyzed the log data of college students to see how the various activities that college students experience inside and outside of school might have influences on employment. For this experiment, students' various activities were systematically classified, recorded as an activity data and were divided into six core competencies (Job reinforcement competency, Leadership & teamwork competency, Globalization competency, Organizational commitment competency, Job exploration competency, and Autonomous implementation competency). The effect of the six competency levels on the employment status (employed group, unemployed group) was analyzed. As a result of the analysis, it was confirmed that the difference in level between the employed group and the unemployed group was significant for all of the six competencies, so it was possible to infer that the activities at the school are significant for employment. Next, in order to analyze the impact of the six competencies on the qualitative performance of employment, we had ANOVA analysis after dividing the each competency level into 2 groups (low and high group), and creating 6 groups by the range of first annual salary. Students with high levels of globalization capability, job search capability, and autonomous implementation capability were also found to belong to a higher annual salary group. The theoretical contributions of this study are as follows. First, it connects the competencies that can be extracted from the school experience with the competencies in the Human Resource Management field and adds job search competencies and autonomous implementation competencies which are required for university students to have their own successful career & life. Second, we have conducted this analysis with the competency data measured form actual activity and result data collected from the interview and research. Third, it analyzed not only quantitative performance (employment rate) but also qualitative performance (annual salary level). The practical use of this study is as follows. First, it can be a guide when establishing career development plans for college students. It is necessary to prepare for a job that can express one's strengths based on an analysis of the world of work and job, rather than having a no-strategy, unbalanced, or accumulating excessive specifications competition. Second, the person in charge of experience design for college students, at an organizations such as schools, businesses, local governments, and governments, can refer to the six competencies suggested in this study to for the user-useful experiences design that may motivate more participation. By doing so, one event may bring mutual benefits for both event designers and students. Third, in the era of digital transformation, the government's policy manager who envisions the balanced development of the country can make a policy in the direction of achieving the curiosity and energy of college students together with the balanced development of the country. A lot of manpower is required to start up novel platform services that have not existed before or to digitize existing analog products, services and corporate culture. The activities of current digital-generation-college-students are not only catalysts in all industries, but also for very benefit and necessary for college students by themselves for their own successful career development.

• Journal of Intelligence and Information Systems
• /
• v.26 no.4
• /
• pp.1-25
• /
• 2020

Sentiment Analysis (SA) is a Natural Language Processing (NLP) task that analyzes the sentiments consumers or the public feel about an arbitrary object from written texts. Furthermore, Aspect-Based Sentiment Analysis (ABSA) is a fine-grained analysis of the sentiments towards each aspect of an object. Since having a more practical value in terms of business, ABSA is drawing attention from both academic and industrial organizations. When there is a review that says "The restaurant is expensive but the food is really fantastic", for example, the general SA evaluates the overall sentiment towards the 'restaurant' as 'positive', while ABSA identifies the restaurant's aspect 'price' as 'negative' and 'food' aspect as 'positive'. Thus, ABSA enables a more specific and effective marketing strategy. In order to perform ABSA, it is necessary to identify what are the aspect terms or aspect categories included in the text, and judge the sentiments towards them. Accordingly, there exist four main areas in ABSA; aspect term extraction, aspect category detection, Aspect Term Sentiment Classification (ATSC), and Aspect Category Sentiment Classification (ACSC). It is usually conducted by extracting aspect terms and then performing ATSC to analyze sentiments for the given aspect terms, or by extracting aspect categories and then performing ACSC to analyze sentiments for the given aspect category. Here, an aspect category is expressed in one or more aspect terms, or indirectly inferred by other words. In the preceding example sentence, 'price' and 'food' are both aspect categories, and the aspect category 'food' is expressed by the aspect term 'food' included in the review. If the review sentence includes 'pasta', 'steak', or 'grilled chicken special', these can all be aspect terms for the aspect category 'food'. As such, an aspect category referred to by one or more specific aspect terms is called an explicit aspect. On the other hand, the aspect category like 'price', which does not have any specific aspect terms but can be indirectly guessed with an emotional word 'expensive,' is called an implicit aspect. So far, the 'aspect category' has been used to avoid confusion about 'aspect term'. From now on, we will consider 'aspect category' and 'aspect' as the same concept and use the word 'aspect' more for convenience. And one thing to note is that ATSC analyzes the sentiment towards given aspect terms, so it deals only with explicit aspects, and ACSC treats not only explicit aspects but also implicit aspects. This study seeks to find answers to the following issues ignored in the previous studies when applying the BERT pre-trained language model to ACSC and derives superior ACSC models. First, is it more effective to reflect the output vector of tokens for aspect categories than to use only the final output vector of [CLS] token as a classification vector? Second, is there any performance difference between QA (Question Answering) and NLI (Natural Language Inference) types in the sentence-pair configuration of input data? Third, is there any performance difference according to the order of sentence including aspect category in the QA or NLI type sentence-pair configuration of input data? To achieve these research objectives, we implemented 12 ACSC models and conducted experiments on 4 English benchmark datasets. As a result, ACSC models that provide performance beyond the existing studies without expanding the training dataset were derived. In addition, it was found that it is more effective to reflect the output vector of the aspect category token than to use only the output vector for the [CLS] token as a classification vector. It was also found that QA type input generally provides better performance than NLI, and the order of the sentence with the aspect category in QA type is irrelevant with performance. There may be some differences depending on the characteristics of the dataset, but when using NLI type sentence-pair input, placing the sentence containing the aspect category second seems to provide better performance. The new methodology for designing the ACSC model used in this study could be similarly applied to other studies such as ATSC.

• Journal of Intelligence and Information Systems
• /
• v.26 no.4
• /
• pp.27-65
• /
• 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
• /
• v.1 no.1
• /
• pp.215-240
• /
• 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
• /
• v.42 no.3
• /
• pp.101-121
• /
• 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.