• The Journal of Korean Philosophical History
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• no.23
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• pp.7-65
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• 2008

The object of this essay is to apply the Leadership Theory, current interest in Asian Philosophy, to Korean appliance. This is to associate contemporary Leadership Theory with Chosun Confucianism in order to discover the Korean Leadership Prototype, and seek the possibility of applying it for modern usage. The essay uses two analysis models. The tools used for the methodology consists of the personal characteristics of the leader as one axis and ruling out the roles in order to develop the discussion as the other axis. First axis is the process of the leader setting the identity and strengthening the ability to successfully deploy his/her leadership. The second axis is comprised of four specific fields where the leadership is deployed. The four sectors are Self Sector, Relationship Sector, Team Sector and Community Sector. Core values of each sector have been set up and specific competences have been presented. In the Self Sector, $zh{\grave{i}}x{\bar{i}}n$(治心) and $ch{\acute{i}}j{\grave{i}}ng$(持敬) have been set as core values and $l{\grave{i}}zh{\grave{i}}$(立志) and $sh{\acute{i}}x{\bar{i}}n$(實心) as their competences. In the Relationship Sector and Team Sector, circumstances(時宜) and $sh{\acute{i}}sh{\grave{i}}g{\bar{e}}ngzh{\bar{a}}ng$(實事更張) were set as core values, accordingly. Lastly for the Community sector, the core value, 'Ideal Leader and the Visions of and Ideal Community', was conceptualized as '$m{\grave{ui}}m{\acute{i}}nzh{\grave{i}}zh{\grave{i}}$(牧民至治)'. The leadership is then expanded from the Self Sector to the final stage through its processes. Through this research, it can be found out that the Korean Leadership Model is not rigid to just cover a specific point in time or situation, but embraces many contemporary leadership concepts, thus having the characteristics of a comprehensive leadership theory.

• The Southeast Asian review
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• v.27 no.1
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• pp.95-129
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• 2017

This study surveys and reviews political change, economic performance, and regional cooperation that were carried out in 2016 by Southeast Asian countries and ASEAN. This paper reports that what has followed the inauguration of new governments in Myanmar, the Philippines, Vietnam, and Laos fails to live up to the expectation and optimism that arose in the aftermath of elections and party congresses that took place in the first half of the year. In other countries such as Malaysia, Thailand, and Cambodia, where authoritarian regimes are faced with strong oppositions, the prospects for democratic change worsened to a substantial degree, as schisms and internal strives complicated the opposition camp as a result of instigation and intervention by the authoritarian leaders and their followers. In stable political systems, both democratic and authoritarian, no significant changes that may entail serious political implications were noticed. In 2016, the national economy of almost each and every country continued its slow but steady recovery that had started in 2014 and grew by 5% on the average. For 2017 onward, however, the earlier optimism that it would grow at least as fast dimmed down as uncertainty about the world economy looms larger due to the unexpected win by Donald Trump as U.S. president and the expected 'hard landing' of the Chinese economy around 2018. ASEAN declared the launch of the ASEAN Economic Community (AEC) only one day before the New Year, but its track record looked already bad and unpromising by the end of 2016. ASEAN leaders were tied up by their domestic politics and affairs too tightly to take time off to work seriously to observe the schedule as laid out in the AEC Blueprint 2025. Korea's relationship with Southeast Asian countries and ASEAN was "as good as it gets" in 2016 as ever but could become subject to tough review in the near future, if the Ministry of Foreign Affairs is found out to have been implicated in the ongoing Choi Sun Sil scandal and if the opposition wins the next presidential election to be held by this year.

• (The)Study of the Eastern Classic
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• no.36
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• pp.163-202
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• 2009

The poems of Shin Suk-ju can be divided into two periods around the political change by King Sejo; his poems from the former period show that the poet enjoyed abundant pride and leisurely spirit in the self-satisfying world driven by his determination to maintain a pure heart and save and awaken the people during the reign of King Sejong. His ideology of awakening the people, however, was the product of his heroic consciousness to achieve immortal fame. It was his heroic consciousness and determination to sacrifice his life for fame according to the mandate from Heaven that made him join the political change by King Sejo. His poems from the latter period clearly reveal that the way of his life to pursue fame didn't bring him spiritual satisfaction and happiness. He confessed that his conscience was destroyed as he joined King Sejo in his political change and the deeds he achieved and further his life itself were all in vain. He lost the values or orders he pursued, which caused instability in his life. Facing such instability head-on, he argued that right and wrong, true and false, and good and evil mentioned in the world were all subjective and groundless. Furthermore, he realized all the things and creatures of the world were nothing but phantoms. Those perceptions he had were based on Madhyamaka of Buddhism. Going through such a thinking process, the poet wrote about his mentality of a false reputation with ideal mentality. Heroic consciousness, Buddhist thinking, and pursuit of mentality of a false reputation found in his poems make also frequent appearances in the poems by major literary men in the latter half of the 15th century such as Seo Geo-jeong. His serious searches to overcome his conscientious agony and sense of futility about life had influences on the attitudes toward life and literature of the official literary men of the times. Seong Hyeon's statement that the major literary figures of the times inherited the literary tradition of Shin Suk-ju was not a rhetoric by courtesy.

• Korean Journal of Construction Engineering and Management
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• v.22 no.4
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• pp.59-65
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• 2021

Since the 2016 "Housing Act Partial Amendment" and the "2018 Housing Comprehensive Amendment Plan", interest in the pre sale system and post sale system of apartment houses has been on the rise. In order to compare the advantages and disadvantages of the pre sale system and the post sale system of apartment houses, and to establish the basis for the institutional policy of the post sale system, a questionnaire survey method was used for tenants of the apartment house from the public side, and issues of time and cost. The time series analysis method is intended to suggest an appropriate time for payment of contributions. Accordingly, through a review of existing theories and literature, the post sale system of public and private institutions was organized, and through a questionnaire survey, the path to securing pre sale money, product information of the model house, and the degree of awareness of the effect of the post sale system were investigated. For the post sale fund support and payment method, it is necessary to increase the commercial line for existing financiers from the user's point of view, and it is necessary to operate in consideration of the economic power of the pre sale market by region. Both 60% post sale and 80% post sale have a price range of up to KRW 10 million, and the total interest rate is 5.0%, and the annual interest rate is about 2.8% for 60% post sale, and about 2.1% for 80% post sale, which is lower than the current 3.1%. I need an interest rate. The research is a perception survey targeting a total of 5,213 households in a sample of after sale apartments in public institutions. As the actual values are analyzed using a time series on the effects of market supply and demand and market prices, there is a limit to applying them to prospective residents of private apartments. In addition, to respond to first time tenants, a questionnaire survey was conducted on five complexes that have moved in within the last five years.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.57-70
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• 2021

As COVID-19 spreads, people's interest in smart learning that can do non-face-to-face learning is increasing nowadays. In this study, we aim to empirically analyze how users' thoughts on COVID-19 and the information quality and system quality of smart learning systems affect users' acceptance of smart learning and examine the effect of perceived sensitivity and severity of COVID-19 on the satisfaction and use of smart learning through concerns about the risk of transmission. In addition, we examined the influence of information quality composed of content quality and interaction quality and system quality composed of system accessibility and functionality on the use of smart learning through user satisfaction. To verify the validity of the proposed model, we conducted a survey on 334 users with experience in using smart learning, and performed the analysis using Smart PLS 3.0. According to the analysis results, among information quality and system quality, only functionality has a positive (+) effect on the satisfaction of smart learning, and satisfaction has a positive (+) effect on the usage behavior. However, it is found that accessibility among system quality do not affect satisfaction, and concern about the risk of transmission has a negative effect on satisfaction. This study can provide meaningful guidelines to researchers when researching smart learning to support students' learning in a pandemic situation of a new infectious disease, such as COVID-19. It will also be able to provide useful implications for educational institutions and companies related to smart learning.

• Applied Chemistry for Engineering
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• v.32 no.3
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• pp.268-276
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• 2021

As wireless communication devices become more common, interests in how to control the electromagnetic waves generated from the devices are increasing. One of the most commonly used electromagnetic wave control materials is magnetic one, but due to the features that make the product heavy and thick when applied to the product, it is difficult to use them in curved electronic devices. Therefore, a polymer flexible meta electronic device has been presented to sort out the problem, which is thin and can have various curvatures. However, it requires an additional evaluation of curvature reliability. In this study, we developed a method to predict electromagnetic wave control characteristics through the resistance/length of the conductive ink line patterns of polymer flexible meta electronic devices, which is inversely proportional to the electromagnetic wave control characteristics. As the radius of curvature decreased, the resistance/length increased, and there was little variations with the duration times of curvature. We also found that both permanent and recoverable changes along with the removal of curvature were occurred when the curvature was applied, and that the cause of these changes was newly created vertical cracks in the conductive ink line pattern due to the tensile stress applied by applying curvature.

• Journal of The Korean Association For Science Education
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• v.41 no.1
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• pp.33-46
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• 2021

Inquiry occupies an important place in science education, and research related to inquiry is widely conducted. However, due to the inclusiveness of the concept of "exploration," each researcher perceives its meaning differently, and approaches may vary. In addition, criticisms have been raised that the results of classes using inquiry in science education do not guarantee meaningful changes to students. Therefore, this study attempts to identify the trend of SSCI-level research papers dealing with inquiry in science education over the past three years to confirm the current status and effectiveness of the inquiry. Researches used in the analysis are International Journal of Science Education, Journal of Research in Science Teaching, Research in Science Education, and Science Education, and limited to those that directly suggest "inquiry (enquiry)" as a keyword. Based on extracted 75 papers, the classification process was conducted, and an analysis frame was derived inductively by reflecting the subject and characteristics. Specific cases for each category were presented by dividing into three aspects: perception and perspective on inquiry, support and strategy for inquiry, and teacher professional development for inquiry. The results of examining the implications for scientific inquiry are as follows: First, rather than defining inquiry as an implicit proposition or presenting it as a step-by-step procedure, it was induced to grasp the meaning of inquiry more comprehensively and holistically. Second, as to whether the inquiry-based instruction is effective in all aspects of the cognitive, functional, and affective domains of science, the limitations are clearly presented, and the context-dependent and subject-specific properties and limitations of inquiry are emphasized. Third, uncertainty in science inquiry-based instruction can help learners to begin their inquiry and develop interest, but in the process of recognizing data and restructuring knowledge, explicit and specific guidance and scaffolding should be provided at an appropriate timing.

• Knowledge Management Research
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• v.22 no.2
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• pp.119-144
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• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.109-121
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• 2021

With the recent increase in senior retirement, and senior start-ups are becoming more active due to high interest in start-ups. Research on young entrepreneurship, including college students, is being actively conducted, but most of the preceding research on senior entrepreneurship was conducted mainly on personal characteristics and social environment, and there were not many empirical studies on the influencing factors of entrepreneurship support policies. In this study, research and discussion on the entrepreneurial support policy and entrepreneurial competence as the influencing factors of senior entrepreneurship. As the independent variable of this study, the founder's competency was adopted as two factors: technical competence and creative competency, and the entrepreneurial support policy was divided into education support and funding support. Mentoring was set as a controlling variable and entrepreneurial intention was set as a dependent variable. A total of 232 questionnaires collected from seniors in their 40s or older were empirically analyzed. To verify the hypothesis of the study, SPSS 23 was used for exploratory factor analysis and regression analysis, and Process 3.4 was used for moderation effect. As a result of the study, it was found that the factors of technical competence, creative competence, educational support, and funding all have a significant influence on the will of entrepreneurship. It was found that creative competency(𝛽=.318), funding support(𝛽=.188), educational support(𝛽=.152), and technical competence(𝛽=.139), in this order, influenced the entrepreneurial intention. It was verified that the moderating effect of mentoring was significant between technical competence, creative competence, and entrepreneurial intention, but the moderating effect of mentoring between educational support, funding and entrepreneurial intention was not. The implications of this study will contribute to the research of senior start-up support policies, institutional supplementation, and differentiated start-up support programs by studying the factors of senior start-up capabilities and start-up support policies. It is also believed that it will contribute to the search for ways to increase creative capabilities that have a high influence on the willingness to start a business and the expansion of mentoring functions.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.