• Title/Summary/Keyword: Global Economy

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A Study on the Perceptions of Confucius and Mencius over Yi-Li Issues (의리(義利) 문제에 대한 공자와 맹자의 인식 연구)

  • Bahk, Yeong-Jin
    • (The)Study of the Eastern Classic
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    • no.68
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    • pp.283-317
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    • 2017
  • Issues over morality and profit usually address relations between moral principles and material gains. In the history of traditional Oriental philosophy, discussions about them were called "Yi-Li zhi bian." The ideas of Confucius and Mencius also contain various discussions about Yi-Li. Both Confucius and Mencius defined Yi as a value concept to represent "natural," "appropriate" or "just" and regarded Yi as an external moral principle on the one hand and an internal moral emotion on the other hand. They had, at the same time, differences, as well. While Confucius placed importance on the external and acquired nature of Yi as a goal of morality, Mencius argued for the internal and innate nature of Yi as the nature of morality partially while recognizing its externality overall. Such Yi is a general term for subjective moral emotions and objective moral principles. Li was a concept of fact to represent "gain," "profit" or "profit-making." Both of them were against private interest and emphasized public interest. As for their differences, Confucius was positive about Li to some degree by saying "One should think of Yi when making profit," whereas Mencius was almost negative about Li and perceived it to be for Yi by saying "One should give up even his own life for Yi." He meant Li's dependence on Yi and also Yi's absoluteness for Ri. Both of them found a mix of opposite features in Yi such as internality and externality, subjectivity and objectivity, specificity and generality, and uniqueness and universality and also in Li such as individuality and specialty and public and private interest. Those features have both disadvantages including theoretical irrationality and logical contradiction and advantages including ideological diversity and conceptual polysemy. If efforts are made to avoid their disadvantages and highlight their advantages, they will provide some elements to consult in the creation of new global ethics required today when East and West are becoming one. In the modern society, the Yi-Li issues can be divided into the issues of morality and economy, personal and social profit, and moral ideal and material gain. If these modern Yi-Li issues are combined with the traditional Yi-Li issues, two paths will emerge over the order of Yi-Li. Of the many perceptions of Yi-Li issues of Confucius and Mencius, the idea of "Yi First, Li Later" can be very useful for creating a new ethics theory to represent "humanism" that we all need today when everyone considers their own pursuit of profit and satisfaction of needs as the best values. Sound Yi-Li relations will be possible only through Yi's orientation toward externality based on internality and Li's pursuit of private interest on the premise of public interest according to the spirit of "Yi First, Li Later."

Analysis of News Agenda Using Text mining and Semantic Network Analysis: Focused on COVID-19 Emotions (텍스트 마이닝과 의미 네트워크 분석을 활용한 뉴스 의제 분석: 코로나 19 관련 감정을 중심으로)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.47-64
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    • 2021
  • The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

An Exploratory Study on the Status of and Demand for Higher Education Programs in Fashion in Myanmar (미얀마의 패션 고등교육 현황과 수요에 대한 탐색적 연구)

  • Kang, Min-Kyung;Jin, Byoungho Ellie;Cho, Ahra;Lee, Hyojeong;Lee, Jaeil;Lee, Yoon-Jung
    • Journal of Korean Home Economics Education Association
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    • v.34 no.3
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    • pp.1-23
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    • 2022
  • This study examined the perceptions of Myanmar university students and professors regarding the status and necessity of higher education programs in fashion. Data were collected from professors in textile engineering at Yangon Technological University and Myanmar university students. Closed- and open-ended questions were asked either through interviews or by email. The responses were analyzed using keyword extraction and categorization, and descriptive statistics(closed questions). Generally, the professors perceived higher education, as well as the cultural industries including art and fashion, as important for Myanmar's social and economic development. According to the students interests in pursuing a degree in textile were limited, despite the high interest in fashion. Low wages in the apparel industry and lack of fashion degrees that meet the demand of students were cited as reasons. The demand was high for educational programs in fashion product development, fashion design, pattern-making, fashion marketing, branding, management, costume history, and cultural studies. Students expected to find their future career in textiles and clothing factories. Many students wanted to be hired by global fashion brands for higher salaries and training for advanced knowledge and technical skills. They perceived advanced fashion education programs will have various positive effects on Myanmar's national economy.

Mediating Effect of Customer Orientation and Customer Satisfaction Between Entrepreneurship and Financial Performance: Focusing on the Beauty Service Industry (기업가정신과 재무적 성과 간의 고객지향성, 고객만족의 매개효과: 미용 서비스산업 중심으로)

  • Kwak, jinman;Lee, sehee
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.16 no.6
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    • pp.197-211
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    • 2021
  • In the service industry the types are diversifying and the scale of service companies is greatly improving. Such a phenomenon is caused by economic growth and technological development diversifying consumer needs creating demand for new services maturing the service industry and intensifying competition among companies in the form of global competition. It can be said that this is because it is necessary to improve competitiveness by utilizing the economy of scale. Research is needed on the impact of entrepreneurship on various outcome variables in order for service organization managers to respond quickly to diverse and rapidly changing environments and achieve organizational outcomes and corporate goals of management outcomes. The purpose of this study was to empirically analyze the relationship in which the entrepreneurial spirit of a manager influences the relationship between customer orientation, which is an organizational result, customer satisfaction, and financial result, which is a management result. In order to verify such research, the questionnaire was composed of one business owner questionnaire, two employee questionnaires, and two customer questionnaires. The questionnaire was distributed to a total of 400 companies, and the questionnaires of 340 companies were collected. Of these, 303 companies, excluding the questionnaires of 37 companies with many dishonest or missing values, were used for hypothesis testing. The results of this study can be summarized as follows. First, entrepreneurship had a positive (+) effect on customer orientation, supporting the hypothesis. Second, customer orientation showed a positive (+) effect on customer satisfaction, supporting the hypothesis. Third, customer satisfaction showed a positive (+) effect on financial outcomes, supporting the hypothesis. Fourth, it was found that entrepreneurship influences customer satisfaction through customer orientation, and customer satisfaction affects financial outcomes. It turns out that customer orientation between entrepreneurship and customer satisfaction is completely mediated, and customer satisfaction is completely mediated by customer orientation and financial outcomes. The relationship between entrepreneurship and management improved employee behavior and attitudes, which is an individual outcome, and this change was found to improve customer satisfaction, which is an organizational outcome. It makes frequent contact with customers in the process of servicing them. Employee roles are important at service contacts and influence service purchases. Employees facing customers through service contacts act as a decisive factor in maintaining a continuous relationship with customers. Within a beauty service company, it is necessary to create a customer-oriented environment among workers. It suggests that customer-oriented companies and employees can anticipate their desires and provide products or services of superior value to achieve greater customer satisfaction and a competitive advantage. In addition, it was clarified that customer satisfaction has an aspect relationship with financial management, which is a management result. Therefore, it is suggested that the entrepreneurial spirit is an important factor for the management of a beauty service company to secure competitiveness and improve results.

An Analysis of the 20th National Congress Report through Text-mining Methods (텍스트 마이닝을 활용한 중국공산당 20차 당대회 보고문 분석)

  • Kwon, Dokyung;Kim, Jungsoo;Park, Jihyun
    • Analyses & Alternatives
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    • v.7 no.1
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    • pp.115-145
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    • 2023
  • The 20th National Congress of the Chinese Communist Party (hereafter referred to as "the 20th National Congress") was under the global spotlight long before it was held for seven days from 16 to 22 October 2022. People wondered whether Xi Jinping would secure a third term as China's leader or whether he would lay the foundations to be in power forever during the third term. In Korea, the press and media questioned whether the event would become the "crowning of Emperor Xi (Xi Huangdi)," whose power rivaled that of the first emperor in China, Shi Hunagdi, and featured the scene where Hu Jintao was forced to leave the venue during the Congress. On the other hand, many Korean academics focused more on how Xi would organize the Politburo and its Standing Committee and whether the outline of his heirs would appear during the event. This tendency in academia in turn worsened the media's concerns. This paper presents a quantitative analysis of the 20th National Congress Report, as opposed to an analysis of Xi's political intentions at the event. The National Congress Report outlines the Party's visions, goals, and strategies for the next five years in politics, economy, society, culture, foreign affairs, and relationship with Taiwan. The authoritative document is rich in narrative and logic and deserves academic study. This research analyzes the 18th, 19th, and 20th Reports by identifying their keywords and regular expressions and checking their frequency and percentage through text-mining methods. This approach enables the quantification and visualization of the significant changes in the Party's sovereign vision over the fifteen years of Xi's rule from 2013 to 2027.

Analysis on Dynamics of Korea Startup Ecosystems Based on Topic Modeling (토픽 모델링을 활용한 한국의 창업생태계 트렌드 변화 분석)

  • Heeyoung Son;Myungjong Lee;Youngjo Byun
    • Knowledge Management Research
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    • v.23 no.4
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    • pp.315-338
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    • 2022
  • In 1986, Korea established legal systems to support small and medium-sized start-ups, which becomes the main pillars of national development. The legal systems have stimulated start-up ecosystems to have more than 1 million new start-up companies founded every year during the past 30 years. To analyze the trend of Korea's start-up ecosystem, in this study, we collected 1.18 million news articles from 1991 to 2020. Then, we extracted news articles that have the keywords "start-up", "venture", and "start-up". We employed network analysis and topic modeling to analyze collected news articles. Our analysis can contribute to analyzing the government policy direction shown in the history of start-up support policy. Specifically, our analysis identifies the dynamic characteristics of government influenced by external environmental factors (e.g., society, economy, and culture). The results of our analysis suggest that the start-up ecosystems in Korea have changed and developed mainly by the government policies for corporation governance, industrial development planning, deregulation, and economic prosperity plan. Our frequency keyword analysis contributes to understanding entrepreneurial productivity attributed to activities among the networked components in industrial ecosystems. Our analyses and results provide practitioners and researchers with practical and academic implications that can help to establish dedicated support policies through forecast tasks of the economic environment surrounding the start-ups. Korean entrepreneurial productivity has been empowered by growing numbers of large companies in the mobile phone industry. The spectrum of large companies incorporates content startups, platform providers, online shopping malls, and youth-oriented start-ups. In addition, economic situational factors contribute to the growth of Korean entrepreneurial productivity the economic, which are related to the global expansions of the mobile industry, and government efforts to foster start-ups. Our research is methodologically implicative. We employ natural language processes for 30 years of media articles, which enables more rigorous analysis compared to the existing studies which only observe changes in government and policy based on a qualitative manner.

Export Prediction Using Separated Learning Method and Recommendation of Potential Export Countries (분리학습 모델을 이용한 수출액 예측 및 수출 유망국가 추천)

  • Jang, Yeongjin;Won, Jongkwan;Lee, Chaerok
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.69-88
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    • 2022
  • One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

Study on Basic Elements for Smart Content through the Market Status-quo (스마트콘텐츠 현황분석을 통한 기본요소 추출)

  • Kim, Gyoung Sun;Park, Joo Young;Kim, Yi Yeon
    • Korea Science and Art Forum
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    • v.21
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    • pp.31-43
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    • 2015
  • Information and Communications Technology (ICT) is one of the technologies which represent the core value of the creative economy. It has served as a vehicle connecting the existing industry and corporate infrastructure, developing existing products and services and creating new products and services. In addition to the ICT, new devices including big data, mobile gadgets and wearable products are gaining a great attention sending an expectation for a new market-pioneering. Further, Internet of Things (IoT) is helping solidify the ICT-based social development connecting human-to-human, human-to-things and things-to-things. This means that the manufacturing-based hardware development needs to be achieved simultaneously with software development through convergence. The essential element the convergence between hardware and software is OS, for which world's leading companies such as Google and Apple have launched an intense development recognizing the importance of software. Against this backdrop, the status-quo of the software market has been examined for the study of the present report (Korea Evaluation Institute of Industrial Technology: Professional Design Technology Development Project). As a result, the software platform-based Google's android and Apple's iOS are dominant in the global market and late comers are trying to enter the market through various pathways by releasing web-based OS and similar OS to provide a new paradigm to the market. The present study is aimed at finding the way to utilize a smart content by which anyone can be a developer based on OS responding to such as social change, newly defining a smart content to be universally utilized and analyzing the market to deal with a rapid market change. The study method, scope and details are as follows: Literature investigation, Analysis on the app market according to a smart classification system, Trend analysis on the current content market, Identification of five common trends through comparison among the universal definition of smart content, the status-quo of application represented in the app market and content market situation. In conclusion, the smart content market is independent but is expected to develop in the form of a single organic body being connected each other. Therefore, the further classification system and development focus should be made in a way to see the area from multiple perspectives including a social point of view in terms of the existing technology, culture, business and consumers.

A Study on Factors Affecting BigData Acceptance Intention of Agricultural Enterprises (농업 관련 기업의 빅데이터 수용 의도에 미치는 영향요인 연구)

  • Ryu, GaHyun;Heo, Chul-Moo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.1
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    • pp.157-175
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    • 2022
  • At this moment, a paradigm shift is taking place across all sectors of society for the transition movements to the digital economy. Various movements are taking place in the global agricultural industry to achieve innovative growth using big data which is a key resource of the 4th industrial revolution. Although the government is making various attempts to promote the use of big data, the movement of the agricultural industry as a key player in the use of big data, is still insufficient. Therefore, in this study, effects of performance expectations, effort expectations, social impact, facilitation conditions, based on the Unified Theory of Acceptance and Use of Technology(UTAUT), and innovation tendencies on the acceptance intention of big data were analyzed using the economic and practical benefits that can be obtained from the use of big data for agricultural-related companies as moderating variables. 333 questionnaires collected from agricultural-related companies were used for empirical analysis. The analysis results using SPSS v22.0 and Process macro v3.4 were found to have a significant positive (+) effect on the intention to accept big data by effort expectations, social impact, facilitation conditions, and innovation tendencies. However, it was found that the effect of performance expectations on acceptance intention was insignificant, with social impact having the greatest influence on acceptance intention and innovation tendency the least. Moderating effects of economic benefit and practical benefit between effort expectation and acceptance intention, moderating effect of practical benefit between social impact and acceptance intention, and moderating effect of economic benefit and practical benefit between facilitation condition and acceptance intention were found to be significant. On the other hand, it was found that economic benefits and practical benefits did not moderate the magnitude of the influence of performance expectations and innovation tendency on acceptance intention. These results suggest the following implications. First, in order to promote the use of big data by companies, the government needs to establish a policy to support the use of big data tailored to companies. Significant results can only be achieved when corporate members form a correct understanding and consensus on the use of big data. Second, it is necessary to establish and implement a platform specialized for agricultural data which can support standardized linkage between diverse agricultural big data, and support for a unified path for data access. Building such a platform will be able to advance the industry by forming an independent cooperative relationship between companies. Finally, the limitations of this study and follow-up tasks are presented.

The Effects of Technological Competitiveness by Country on The Increase of Unicorn Companies (국가별 기술경쟁력이 유니콘기업 증가에 미치는 영향에 관한 연구)

  • Kyu Hoon Cho;Dong Woo Yang
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.1
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    • pp.55-73
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    • 2024
  • Unicorn companies are attracting attention around the world as they are recognized for their high corporate value in a short period of time as an innovative business models. Their growth process presents good lessons for the startup ecosystem and have a positive impact on national economic development and job creation. However, previous studies related to unicorn companies are focused on 'event studies' and 'case studies' such as characteristics of founders, environmental factors, business models and success/failure cases of companies already recognized as unicorns rather than a multifaceted approach. The occurrence of unicorn companies and Macroscopic analysis of related factors is lacking. Against this background, this study are considering the characteristics of unicorns examined through previous research and the current status unicorns with a high proportion of technology companies, the purpose was to analyze the impact of the country's technological competitiveness, such as 'technology human resource index', 'R&D index', and 'technology infrastructure index', on the increase in unicorn companies. For statistical analysis, data published by various international organizations, the Bank of Korea, and Statistics Korea from 2017 to 2020 and unicorn company data compiled by CB Insights were used as panel data for 44 countries to be tested by multiple regression analysis. As a result of the study, it was confirmed that the number of science majors had a positive (+) effect on the increase of unicorn companies in the case of technology human resource index, and in the case of R&D index, the total amount of R&D investment had a positive (+) effect on the increase of unicorn companies, while the number of Triad Patents Families and the number of scientific and technological papers published had a negative (-) effect on the increase of unicorn companies. Finally, in the case of technology infrastructure index, it was confirmed that the number of the world's 500th-ranked universities had a positive (+) effect on the increase of unicorn companies. This study is the first to reveal the causal relationship between national technological competitiveness and unicorn company growth based on country-specific and time-series empirical data, which were insufficiently covered in previous studies. and compared to the UN's ranking of the global industrial competitiveness index and the OECD's total R&D investment by country, Korea is considered to have technological and growth potential, while the number of unicorn companies driving growth as leaders of the innovative economy is relatively small, so the research results can be used when establishing policies to discover and foster unicorn companies in the future.

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