• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.61-72
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• 2019

Since the financial crisis in 1997, large scale unemployment and poverty have become serious, but there has been a surge in public and social job creation projects. However, with the limitations of low-wage and short-term jobs, the need for long-term, high quality jobs gradually began to garner attention. In recent years, social enterprises have grown both quantitatively and qualitatively and interest in social enterprises has increased; more specifically, scholars are interested in the determinants of success and failure of social enterprises in the academic field. In this study, we examined the effects of social enterprise characteristics on financial and social performance. In particular, we empirically analyzed social enterprises registered in the Korea Social Enterprise Agency. The financial performance of the social enterprise was measured using the net income ratio, operating income ratio, and the return on asset. The social performance of the social enterprise was measured by the total number of workers and the employment rate of vulnerable social groups. The characteristics of the social enterprise included CEO characteristics (gender, age, experience in operating the social enterprise), firm size, and the elapsed time of authentication. The results of the empirical analysis are as follows. First, as a result of analysis for the effect on financial performance, we found that the financial performance has a statistically significant, positive relationship with firm size, organizational form, government subsidies, and capital adequacy ratio. And we found that the social performance has a statistically significant, negative relationship with CEO age and credit debt dependence. Second, as a result of analysis for the effect on social performance, we found that the total number of workers had a significant, positive relationship with CEO gender and CEO age, as well as firm size, government subsidies; whereas the total number of workers had a significant, negative relationship with certification type and industry dummy. Comparatively, the employment rate of the vulnerable social groups had a significant, positive relationship with CEO gender and certification type, but there was no statistically significant relationship with the government subsidies or firm size.

• (The) Research of the performance art and culture
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• no.32
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• pp.489-524
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• 2016

This study examines the birth of a genre, the $Sekky{\bar{o}}bushi$ Misemono Opera, focusing on how it accepted and modernized Katarimono $Sekky{\bar{o}}bushi$. Unlike earlier studies, it argues that Terayama was clearly different from other first-generation Angura artists, in that he rebirthed the medieval story $Sekky{\bar{o}}bushi$ as a modern Misemono Opera. Shintokumaru (1978) was directed by Terayama $Sh{\bar{u}}ji$, a member of the first generation of Japan's 1960s Angura Theatre Movement. It takes as its subject the Katarimono $Sekky{\bar{o}}bushi$ Shintokumaru, a story set to music that can be considered an example of the modern heritage of East Asian storytelling. $Sekky{\bar{o}}$ Shintokumaru is set in Tennoji, Japan. The title character Shintoku develops leprosy as a result of his stepmother's curse and is saved through his fiancee Otohime's devoted love and the spiritual power of the Bodhisattva Avalokitesvara. In this work, Terayama combined the narrative style of $Sekky{\bar{o}}bushi$ with J.A. Caesar's shamanistic rock music and gave it the subtitle 'Misemono Opera by $Sekky{\bar{o}}bushi$'. He transforms its underlying theme, the principle of goddesses and their offspring in a medieval religious world and the modori (return) instinct, into a world of mother-son-incest. Also, the pedestrian revenge scene from $Sekky{\bar{o}}bushi$ is altered to represent Shintokumaru as a drag queen, wearing his stepmother's clothes and mask, and he unites sexually with Sensaku, his stepbrother, and ends up killing him. The play follows the cause and effect structure of $Sekky{\bar{o}}bushi$. The appearance of katarite, a storyteller, propelling the narrative throughout and Dr. Yanagida Kunio is significant as an example of the modern use of self-introduction as a narrative device and chorus. Terayama $Sh{\bar{u}}ji^{\prime}s$ memories of desperate childhood, especially the absence of his father and the Aomori air raids, are depicted and deepened in structure. However, seventeen years after Terayama's death, the version of the play directed by Ninagawa Yukio-based on a revised edition by Kishida Rio, who had been Terayama's writing partner since the play's premier-is the today the better-known version. All the theatrical elements implied by Terayama's subtitle were removed, and as a result, the Rio production misses the essence of the diverse experimental theatre of Terayama's theatre company, $Tenj{\bar{o}}$ Sajiki. Shintokumaru has the narrative structure characteristic of aphorism. That is, each part of the story can stand alone, but it is possible to combine all the parts organically.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.770-788
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• 2021

This study aimed to determine whether middle school students could understand global warming and the greenhouse effect, and explain them in terms of global radiative equilibrium. From July 13 to July 24 in 2021, 118 students in the third grade of middle school, who completed a class module on 'atmosphere and weather', participated in an online assessment consisting of multiple-choice and written answers on radiative equilibrium, the greenhouse effect, and global warming; 97 complete responses were obtained. After analysis, it was found that over half the students (61.9%) correctly described the meaning of radiative equilibrium; however, their explanations frequently contained prior knowledge or specific examples outside of the presented data. The majority of the students (92.8%) knew that the greenhouse effect occurs within Earth's atmosphere, but many (32.0%) thought of the greenhouse effect as a state in which the radiative equilibrium is broken. Less than half the students (47.4%) answered correctly that radiative equilibrium occurs on both Earth and the Moon. Most of the students (69.1%) understood that atmospheric re-radiation is the cause of the greenhouse effect, but few (39.2%) answered correctly that the amount of surface radiation emitted is greater than the amount of solar radiation absorbed by the Earth's surface. In addition, about half the students (49.5%) had a good understanding of the relationship between the increase in greenhouse gases and the absorption of atmospheric gases, and the resulting reradiation to the surface. However, when asked about greenhouse gases increases, their thoughts on surface emissions were very diverse; 14.4% said they increased, 9.3% said there was no change, 7.2% said they decreased, and 18.6% gave no response. Radiation equilibrium, the greenhouse effect, and global warming are a large semantic network connected by the balance and interaction of the Earth system. This can thus serve as a conceptual system for students to understand, apply, and interpret climate change caused by global warming. Therefore, with the current climate change crisis facing mankind, sophisticated program development and classroom experiences should be provided to encourage students to think scientifically and establish scientific concepts based on accurate understanding, with follow-up studies conducted to observe the effects.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.191-200
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• 2020

Companies are seeking to maximize profits through exports and imports in the ultra-fast, ultra-high-speed modern society. It is only possible to sustain its survival if it targets the global market, not based on any specific region. The K-POP group is also targeting overseas markets in a manner similar to the various global strategies used when companies make inroads into foreign markets, including exports, contracts and direct investment. The K-POP group is engaged in various forms of activities, ranging from simple forms of performance (export) that are visited and staged by an invitation from a certain foreign country to series performances (license) by an invitation from a local promoter and tour performances using its capabilities. The K-POP group is seeking to go beyond the art of single-stage performances and make a systematic plan and make inroads into foreign countries in the form of direct investment suitable for each foreign country. The K-POP group made inroads into overseas markets in the form of simple performances from the late 1990s to 2005, when 'Korean Wave' was first introduced. Group H.O.T., etc. are typical examples. Since then, it has sought to enter overseas markets in the form of franchises by accepting overseas members by 2018, starting with Super Junior in 2005. Since then, the K-POP group in the form of joint investment attempted as group IZ*ONE in 2018 appeared, and a voice story came out in September 2018 when South Korea's JYP Entertainment and Tencent of China joined forces. Unlike K-POP Group, which has entered foreign markets with a global strategy based on the existing export method (H.O.T.), 'Boystory' is a representative group that is made with joint investment, which is a direct investment method. In February 2020, RBW released 'D1Verse,' a five-member group selected by Vietnam's reality show, as a joint investment-type group. This shows the possibility that domestic and foreign companies will release a group in the form of joint investment in order to pursue both globalization and localization.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.5
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• pp.431-449
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• 2022

As many tunnels generally have been constructed, various experiences and techniques have been accumulated for tunnel design as well as tunnel construction. Hence, there are not a few cases that, for some usual tunnel design works, it is sufficient to perform the design by only modifying or supplementing previous similar design cases unless a tunnel has a unique structure or in geological conditions. In particular, for a tunnel blast design, it is reasonable to refer to previous similar design cases because the blast design in the stage of design is a preliminary design, considering that it is general to perform additional blast design through test blasts prior to the start of tunnel excavation. Meanwhile, entering the industry 4.0 era, artificial intelligence (AI) of which availability is surging across whole industry sector is broadly utilized to tunnel and blasting. For a drill and blast tunnel, AI is mainly applied for the estimation of blast vibration and rock mass classification, etc. however, there are few cases where it is applied to blast pattern design. Thus, this study attempts to automate tunnel blast design by means of machine learning, a branch of artificial intelligence. For this, the data related to a blast design was collected from 25 tunnel design reports for learning as well as 2 additional reports for the test, and from which 4 design parameters, i.e., rock mass class, road type and cross sectional area of upper section as well as bench section as input data as well as16 design elements, i.e., blast cut type, specific charge, the number of drill holes, and spacing and burden for each blast hole group, etc. as output. Based on this design data, three machine learning models, i.e., XGBoost, ANN, SVM, were tested and XGBoost was chosen as the best model and the results show a generally similar trend to an actual design when assumed design parameters were input. It is not enough yet to perform the whole blast design using the results from this study, however, it is planned that additional studies will be carried out to make it possible to put it to practical use after collecting more sufficient blast design data and supplementing detailed machine learning processes.

• 한국노년학
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• v.40 no.4
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• pp.639-657
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• 2020

The purpose of this study is to analyze the effect of individual differences in recognition of retirement responsibility on financial preparedness for retirement and to examine moderating effect of income-level on the relationships between the two variables, using the 7th Korean Retirement and Income Study(KReIS). Two research methods, descriptive analysis and hierarchical multiple logistic regression(HMLR) analysis, have been conducted. The total number of sample was 3,869 subjects with an average age of 58.9 years and 55.3% males. The results show that only 35.8% of the respondents make financial plans for retirement, and 64.2% did not. Main findings are as follows. First, 65% of respondents take a responsibility for financial preparedness for retirement, compared to 37% in European countries. Second, people with responsibility for their own retirement are more likely to have a financial preparation for retirement than people who think others(family, society, government) have to take a responsibility for retirement instead of them. Third, there is a significant moderating effect of income-level on relationships between recognition of retirement responsibility and financial preparedness for retirement. As income level decreases, the moderating effect reduces the positive effect of recognition of retirement responsibility on financial preparedness for retirement and vice versa. Fourth, as income level increases and educational level is higher, the tendency to prepare financially for retirement is also increasing. Low-income and low-educated people are less likely to have a financial preparation for retirement than their counterparts. The findings suggest that it is necessary to design an effective incentive scheme for financial preparedness for retirement for low-income and low-educated people and to develop various policies and services to encourage them to prepare financially for retirement.

• Korean small business review
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• v.42 no.4
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• pp.69-102
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• 2020

Shedding new light on the research trend on entrepreneurial ecosystems in the 40-year history of the Asia Pacific Journal of Small Business, this study aims at exploring a potential measurement framework of ecological inputs and outputs in an entrepreneurial ecosystem that promotes entrepreneurship at geographical and spatial levels. As a result of the analysis of research on the entrepreneurial ecosystem in the journal, we found that prior studies emphasized the managerial importance of various ecological factors on the premise of possible causalities between the factors and entrepreneurship. However, empirical research to verify the premised causality has been underexplored yet. This literature gap may lead to unbalanced development of conceptual and case studies that identify requirements for successful entrepreneurial ecosystems based on experiential facts, thereby hindering the generalization of the research results for practical implications. In that there is a growing interest in creating and operating productive entrepreneurial ecosystems as an innovation engine that drives national and regional economic growth, it is necessary to explore and develop the measurement framework for ecological factors that can be used in future empirical research. Hereupon, we apply a conceptual model of 'input-output-outcome-impact' to categorize individual environmental factors identified in prior studies. Based on the model. We operationalize ecological input factors as the financial, intellectual, institutional, and social capitals, and ecological output factors as the establishment-based, innovation-based, and performance-based entrepreneurship. Also, we propose several longitudinal databases that future empirical research can use in analyzing the potential causality between the ecological input and output factors. The proposed framework of entrepreneurial ecosystems, which focuses on measuring ecological input and output factors, has a high application value for future research that analyzes the causality.