• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제23권3호
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• pp.35-43
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• 2023

The purpose of this study is to research digital twin policies for the use of administrative services. The study was conducted through a mobile survey of 1,000 participants, and the results are as follows. First, in order to utilize digital twin technology, it is necessary to first identify appropriate services that can be applied from the perspective of Gyeonggi Province. Efforts to identify digital twin services that are suitable for Gyeonggi Province's field work should be prioritized, and this should lead to increased efficiency in the work. Second, Gyeonggi Province's digital twin administrative services should prevent duplication with central government projects and establish a model that can be connected and utilized. It should be driven around current issues in Gyeonggi Province and the demands of citizens for administrative services. Third, to develop Gyeonggi Province's digital twin administrative services, a standard model development plan through participation in pilot projects should be considered. Gyeonggi Province should lead the project as the main agency and promote it through a collaborative project agreement. It is suggested that a support system for the overall project be established through the Gyeonggi Province Digital Twin Advisory Committee. Fourth, relevant regulations and systems for the construction, operation, and management of dedicated departments and administrative services should be established. To achieve the realization of digital twins in Gyeonggi Province, a dedicated organization that can perform various roles in project promotion and operation, as well as legal and institutional improvements, is necessary. To designate a dedicated organization, it is necessary to consider expanding and reorganizing existing departments and evaluating the operation of newly established departments. The limitation of this study is that it only surveyed participants from Gyeonggi Province, and it is recommended that future research be conducted nationwide. The expected effect of this study is that it can serve as a foundational resource for applying digital twin services to public work.

• Korea Science and Art Forum
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• 제29권
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• pp.319-331
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• 2017

South Korea has entered the age of aging society since the elderly population over 65 reached 13.1% in 2015. This increase rate is the fastest in the OECD members. as a part of the precaution, the Korean government has enforced the long term care insurance from July 2008 and the increase of related nursing homes until 2015 was 220.2% which is rapid and quantitative. It was natural that quantitative expansion leads to qualitative improvement. With regard to service environment conditions, color environment draws attention as one of the most effective measures. color environment supports nursing home's spatial functions and the aged class is subject to the research as the potential customers. This study aims to understand color environment, conduct surveys for color preference and attitude toward color environment, and suggest directions for color environment plan. The ultimate goal is to improve the quality of Korean nursing home environment. It studied definition, state, color environment and space functions of nursing homes as well as the preceding researches. With 100 people over 60s in Busan and Gyeongnam area (52 male and 48 female), the survey examined attitudes for color environment and color preference by space functions in nursing home. The research method is as follows. First, as a result of the consciousness survey on color environment in elderly nursing home, it considers service (37%), medical service (20%), and location (19%) heavily in order. color environment plan is not recognized significantly. However, the need of indoor color plan in the elderly nursing homes has "agree (32%) and "strongly agree (25%), which suggests that color introduction is required to the nursing homes. Second, the indoor coloration for the elderly nursing homes has various color preferences. The color preference order for bedroom was R, P, and G but this order changes in nursing space (program room) to G, R, and Y. The communal space such as lobby prefers R, G and Y in order. R color was preferred in general.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제18권1호
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• pp.203-223
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• 2023

Recently, the platform industry is rapidly growing in the global market, and competition is intensifying at the same time. Therefore, in order for domestic platform companies to have global competitiveness in the platform market, it is necessary to study the platform business ecosystem and success factors. However, most of the recent platform-related studies have been theoretical studies on the characteristics of platform business status analysis, platform economy, and indirect network externalities of platforms. Therefore, this study comprehensively analyzed the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzed the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. And based on these factors, an IPA analysis was conducted as a way to propose a success plan to stakeholders in the platform business ecosystem. As a result of the analysis, among the success factors collected through previous studies, manpower, capital, and challenge culture were identified as factors that are relatively well maintained in both importance and satisfaction in Silicon Valley. In the end, it can be seen that the creation of an environment and culture in which Silicon Valley can use it to challenge itself based on excellent human resources and abundant capital contributes the most to the success of Silicon Valley's platform business. On the other hand, although it is of high importance to Silicon Valley's platform corporate ecosystem, the factors that show relatively low satisfaction among stakeholders are 'learning and benchmarking among active companies' and 'strong ties and cooperation between members', and it is analyzed that interest and effort are needed to strengthen these factors in the future. Finally, the systems and policies necessary for market autonomous competition, 'business support service industry', 'name value', and 'spin-off start-up' were important factors in literature research, but the importance and satisfaction of these factors were lowered due to changes in the times and environment. This study has academic implications in that it comprehensively analyzes the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzes the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. In addition, there is another academic implications that importance and satisfaction were simultaneously examined through IPA analysis based on these various extracted factors. As for academic implications, it is meaningful in that it contributed to the formation of the domestic platform ecosystem by providing the government and companies with concrete information on the success factors of the platform business ecosystem and the theoretical grounds for the growth of domestic platform businesses.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제17권5호
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• pp.169-185
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• 2022

This study analyzed the effect of entrepreneurial competency on entrepreneurial intentions by using the entrepreneurial opportunity recognition as a mediator for middle and middle-aged office workers. The sub-variables of entrepreneurial competency are classified into management competency, technology competency, business competency and funding competency. 222 copies of questionnaires collected from middle-aged and elderly office workers residing across the country centered on the metropolitan area were used for empirical analysis. Based on a simple mediating model with singular mediator using SPSS v22.0 and PROCESS macro v4.0. was analyzed. As a result of the analysis, first, among entrepreneurial competencies, business competency and funding capacity were found to have a positive (+) significant effect on the entrepreneurial intentions, but management and technical competency did not have a significant effect. The higher the business competency and funding competency. Second, it was found that all of the sub-variables of entrepreneurial competency had a significant effect in the positive (+) direction on the recognition of entrepreneurial opportunities. It was confirmed that management competency has the greatest influence on the entrepreneurial opportunity recognition and technology competence has the smallest effect. Third, it was found that the entrepreneurial opportunity recognition had a significant effect on entrepreneurial intentions. The discovery of an opportunity recognizing opportunities for start-up is a prerequisite for entrepreneur. Fourth, it was found that the entrepreneurial opportunity recognition mediates between the management competency, technological competency, business competency, funding competency, and entrepreneurial intention. It suggests that opportunity discovery by recognizing opportunities for entrepreneurship is a prerequisite for start-up. As implications of this study, it suggests that in order to inspire middle-aged and elderly office workers to start their own business, it is necessary to have indirect experience with education and to establish and promote a government support system for financing.. Second, It suggests that education on leadership and organizational management is particularly necessary to strengthen the opportunity recognition. Third, it suggests that the discovery of opportunities to recognize opportunities for start-up is a prerequisite for entrepreneur. Therefore, it is necessary to prepare a manual and conduct training on opportunity search, recognition, evaluation, and utilization according to the stage of opportunity development. Fourth, it suggests that in order to strengthen the intention to start a business, ALso, it is necessary to manage both the entrepreneurial competency and entrepreneurial opportunities recognition at the same time. By presenting the practical directions that can be given differentially, we intend to contribute to the provision of practical directions and policy establishment for the promotion of entrepreneurial activities of office workers who can give vitality to the ecosystem.

• Journal of Fisheries and Marine Sciences Education
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• 제10권2호
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• pp.139-161
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• 1998

This thesis includes a study on the legal regulation, the system and formalities on the control of illegal fishing. And the author analyzed the details of the lists of illegal fishing controlled by fishing patrol vessels of Ministry of Maritime Affairs and Fisheries from 1994 to 1996 in adjacent sea area of Korea. The results are summarized as follows ; 1. The fishing patrol vessels controlled total 826 cases in 2,726 days of 292 voyages by 17 vessels in 1994, total 1,086 cases in 3,060 days of 333 voyages by 18 vessels in 1995 and total 933 cases in 3,126 days of 330 voyages by 19 vessels in 1996. 2. The fishing period of illegal fishing was generally concentrated from April to September. But year after year, illegal fishing was scattered throughout the year. 3. The most controlled sea area of illegal fishing was the south central sea area in the sea near Port of Tongyeong. The sea area occupied about 36~51% of totality and the controlled cases were gradually increased every year. The second was the south western sea area in the sea near Port of Yosu. The sea area occupied about 18-27% and the controlled cases were a little bit increased every year. The third was the south eastern sea area in the sea near Pusan. The sea area occupied about 13~23% and the controlled cases were gradually decreased year by year. 4. The most controlled kind of illegal fishing was the small size bottom trawl. This occupied about 81-95% of totality and the controlled cases were gradually increased year by year. The second was the medium size bottom trawl. This occupied about 4-7% and the controlled cases were gradually decreased year by year. The third was the trawl of the coastal sea, this occupied about 2~4% and the controlled cases were a little bit decreased every year. 5. The most controlled address of illegal fishing manager was Pusan city which occupied about 33-51% of totality. The second was Cheonnam which occupied about 24-29%. The third was Kyungnam which occupied about 16~35%. 6. The most controlled violation of regulations was Article 57 of the Fisheries Act which occupied about 56-64% of totality. The second was Article 23 of Protectorate for Fisheries Resources which occupied about 21-36%. And the controlled cases by it were gradually increased every year.

• Journal of Intelligence and Information Systems
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• 제27권1호
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.