• 디지털융복합연구
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• 제20권4호
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• pp.699-704
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• 2022

본 연구는 전국 226개의 기초자치단체를 대상으로 2020년 기준 지역사회 통합건강증진사업 내 한의약건강증진사업 예산편성여부의 관련 요인을 파악하는데 목적이 있다. 2020년도 지역별 예산서를 활용하여 지역사회 통합건강증진사업 내 한의약건강증진사업 예산편성여부를 파악한 후 예산편성여부의 관련 요인을 분석하고자 기술통계 및 차이검정과 이분형 로지스틱 회귀분석을 실시하였다. 분석 결과 한의약난임치료지원 예산편성여부, 한의사수, 65세이상 인구수, 고령인구비율의 변수 차이는 다르게 나타났고, 한의약난임치료지원 예산편성여부, 고령인구비율, 건강도시가입여부에서 영향을 미치는 것으로 나타나 향후 한의학관련 정책 및 사업예산을 편성하는데 참고자료로 활용될 것으로 생각된다.

• 산업경영시스템학회지
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• 제45권2호
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• pp.65-76
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• 2022

Recently, not only traditional statistical techniques but also machine learning algorithms have been used to make more accurate bankruptcy predictions. But the insolvency rate of companies dealing with financial institutions is very low, resulting in a data imbalance problem. In particular, since data imbalance negatively affects the performance of artificial intelligence models, it is necessary to first perform the data imbalance process. In additional, as artificial intelligence algorithms are advanced for precise decision-making, regulatory pressure related to securing transparency of Artificial Intelligence models is gradually increasing, such as mandating the installation of explanation functions for Artificial Intelligence models. Therefore, this study aims to present guidelines for eXplainable Artificial Intelligence-based corporate bankruptcy prediction methodology applying SMOTE techniques and LIME algorithms to solve a data imbalance problem and model transparency problem in predicting corporate bankruptcy. The implications of this study are as follows. First, it was confirmed that SMOTE can effectively solve the data imbalance issue, a problem that can be easily overlooked in predicting corporate bankruptcy. Second, through the LIME algorithm, the basis for predicting bankruptcy of the machine learning model was visualized, and derive improvement priorities of financial variables that increase the possibility of bankruptcy of companies. Third, the scope of application of the algorithm in future research was expanded by confirming the possibility of using SMOTE and LIME through case application.

• 융합정보논문지
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• 제12권4호
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• pp.212-218
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• 2022

본 연구는 의료소비자의 만성질환 유무에 따른 정보탐색행태를 파악하고자 수행되었다. 이를 위해 2016년 2월 9일에서 2월 11일까지 서울 소재 대학병원에 방문한 환자들을 대상으로 설문조사를 실시하였으며, SPSS 26.0 통계 패키지를 활용하여, 총 240명의 자료를 분석하였다. 주요 분석 결과는 다음과 같다. 첫째, 만성질환자들은 만성질환이 없는 사람들보다, 전문가 정보원과 경험적 정보원을 많이 이용한 것으로 나타났다. 둘째, 질환과 관련해서는 영양관리, 운동 관리 및 동일 질환자들의 사례를 많이 탐색하는 것으로 나타났다. 마지막으로 병원과 관련해서 만성질환자들은 대기시간과 진료비를 많이 알아본 것으로 나타났다. 본 연구는 만성질환자들의 수요를 반영한 효율적인 정보제공과 마케팅전략 수립의 기초자료를 제공한 의의가 있다.

• 한국융합학회논문지
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• 제13권3호
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• pp.217-225
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• 2022

본 연구는 2020년부터 코로나 바이러스의 영향을 받고 있는 인도 손해보험시장의 효율성과 생산성을 분석하였다. 비모수적 연구방법인 자료포락분석(DEA)을 사용하여 FY2013년부터 FY2019년까지 인도에서 건강보험 상품을 판매하고 있는 손해보험회사들을 표본으로 하였다. 분석 결과는 다음과 같다. 첫째, 전체 보험산업의 평균 효율성은 표본기간 동안 효율성이 감소하다가 개선되는 결과를 보여주었다. 둘째, 효율성 측정치를 그룹별로 살펴보면 민영보험회사가 효율성이 가장 높았으며 국영보험회사와 순수건강전문보험회사가 그 뒤를 따르고 있었다. 셋째, 연평균 생산성을 측정한 결과 전통적인 대면채널보다 텔레마케팅을 포함한 비대면채널을 운영한 보험회사의 연평균 생산성 증가율이 더 높은 것으로 파악되었다. 따라서 코로나 바이러스의 창궐로 인하여 비대면영업환경이 주를 이루는 가운데 향후 인도 손해보험회사는 영업전략 수립 시 비대면채널의 발전에 자원과 노력을 집중해야 할 것으로 보인다. 더불어 본 연구의 분석을 코로나 바이러스 창궐 이후 기간에 적용하는 것도 흥미로워 보인다.

• 디지털융복합연구
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• 제19권7호
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• pp.175-188
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• 2021

수익성을 앞세운 과열 경쟁으로 인한 경영 여건의 악화에도 불구하고 중국의 치과 수는 매년 증대되고 있다. 이에 본 연구는 상하이 지역의 치과 서비스품질이 만족도에 미치는 영향과 지각된 가치의 매개효과를 검증하는 데에 목적을 두고 있다. 이를 위해 중국 상하이 지역 치과 환자를 대상으로 전자 설문을 실시하고 유효표본 345부를 회수하여 연구의 목적에 맞게 SPSS 26.0을 이용하였다. 결과를 요약하면 다음과 같다. 첫째, 서비스품질의 모든 요인은 만족도와 지각된 가치에 긍정적 영향을 주었다. 둘째, 지각된 가치는 만족도에 긍정적인 영향을 미치는 것으로 나타났다. 셋째, 지각된 가치는 서비스품질과 만족도 간의 관계에서 부분 매개효과를 보이는 것으로 분석되었으며, 중국과 한국의 치과 사용자들에 대한 연구는 거의 유사한 결과를 나타내고 있다. 따라서 치과의 고품질 서비스가 경영능력 제고에 필수적이라는 것을 확인할 수 있다.

• Journal of Korea Trade
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• 제25권3호
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• pp.48-64
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• 2021

Purpose - This study examined the effect of tariff cuts on productivity in Korea's manufacturing industries and the effect of initial productivity level before tariff cuts on productivity improvement after tariff cuts. We also attempted to identify whether import-driven or export-driven factors are more important for productivity improvement, especially in low productivity industries. Design/methodology - Since tariff reduction is a policy decision that can affect cross-industry, its impact is spread across all industries beyond the scope of a single firm through the input and output network of industry structure. Accordingly, we proposed a new method to measure the change in productivity to reflect the impact of tariff cuts across industries. Through an Armington CGE analysis, changes in endogenous variables can be directly measured after the exogenous shock of tariff reduction, and the amount of movements in productivity triggered by tariff cuts can also be calculated. We can thus assess the effectiveness of exogenous policy, such as tariff cuts, through the difference between the benchmark and counterfactual values of endogenous variables. Findings - This study confirmed that tariff reduction positively affected productivity improvement in Korea's manufacturing industries. It also confirmed that productivity gains occur in Korea's leading export industries. Finally, greater productivity gains were recorded in the group with additional high-export-share or high-import-share conditions for low productivity industries. These results are, in a limited sense, consistent with the existing studies that emphasize the importance of exports and imports on productivity improvement, especially for low productivity industries. Originality/value - The results of our experiments are different from those of non-CGE studies, which measure the industry-level change in productivity with dummy coefficients, in terms of directly calculating the amount of change in productivity. In addition, we propose that the Armington CGE model is more appropriate than the Melitz CGE model to directly measure the productivity after tariff cuts. This is because the Melitz CGE model assumes the given specific productivity density, which does not change after an overall drop of tariffs. To the best of our knowledge, this approach to directly calculating productivity by reflecting the impact of tariff reduction across industries through CGE analysis, is unprecedented in this literature.

• 지능정보연구
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• 제29권3호
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• pp.103-123
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• 2023

본 연구에서는 기업 내 근로자의 안전 행동과 관리자의 안전 리더십, 리더 신뢰, 근로자 참여, 안전 지식과의 관계를 실증적으로 규명하고, 요인들이 어떤 역할을 하는지 분석함으로써 기업의 중대재해 예방에 기여하는 근로자의 안전 행동을 강화하는 요인을 파악하고 분석하였다. 산업재해가 발생하게 되면 기업 입장에서는 재해자를 대상으로 보상을 하는 직접비와 더불어 인적 손실, 물적 손실, 생산 손실, 시간 손실 등 간접비의 발생으로 막대한 손실비용을 감수해야 한다. 본 연구에서는 선행 연구들의 결과를 바탕으로 제조업에 종사하는 생산, 기술, 노무직 근로자를 대상으로 관리자의 안전 리더십과 근로자의 리더 신뢰가 근로자 참여, 안전 지식을 매개로 안전 행동에 미치는 영향에 대해 연구하였다. SPSS 와 PLS를 이용하여서 제조업체 근로자 271명을 대상으로 통계분석을 실시하였다. 분석 결과는 안전 리더십과 리더 신뢰는 근로자의 참여를 유도하고 근로자의 안전 지식 습득에 긍정적인 영향을 미쳐 근로자의 안전 행동을 이끌어낼 수 있다는 것이다.

• International journal of advanced smart convergence
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• 제12권1호
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• pp.164-172
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• 2023

In this study, we identify the recognition of 'The First Slam Dunk', which is gaining popularity as a sports-based cartoon through big data analysis of social media channels, and provide basic data for the development and development of various contents in the sports industry. Social media channels collected detailed social big data from news provided on Naver and Google sites. Data were collected from January 1, 2023 to February 15, 2023, referring to the release date of 'The First Slam Dunk' in Korea. The collected data were 2,106 Naver news data, and 1,019 Google news data were collected. TF and TF-IDF were analyzed through text mining for these data. Through this, semantic network analysis was conducted for 60 keywords. Big data analysis programs such as Textom and UCINET were used for social big data analysis, and NetDraw was used for visualization. As a result of the study, the keyword with the high frequency in relation to the subject in consideration of TF and TF-IDF appeared 4,079 times as 'The First Slam Dunk' was the keyword with the high frequency among the frequent keywords. Next are 'Slam Dunk', 'Movie', 'Premiere', 'Animation', 'Audience', and 'Box-Office'. Based on these results, 60 high-frequency appearing keywords were extracted. After that, semantic metrics and centrality analysis were conducted. Finally, a total of 6 clusters(competing movie, cartoon, passion, premiere, attention, Box-Office) were formed through CONCOR analysis. Based on this analysis of the semantic network of 'The First Slam Dunk', basic data on the development plan of sports content were provided.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.193-202
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• 2023

Numerous articles under the study and the examination of heavy metals in human teeth have been published in recent years. The heavy metal poisoning is a widespread issue emerged in toxicology area these days. It has been discovered that long-term exposure to heavy metals typically present in traces, in our everyday meals, drinking water, and in the environment as pollution causes heavy metal poisoning in human beings. Industrial effluents, Coal and Oil, as well as a variety of consumer items, such as cosmetics, can all cause this type of exposure. Teeth, which are often thought of as exoskeleton parts, store heavy metals with a high affinity and represent long-term exposure information. In this study, we have chosen and examined the sections of dentine instead, then examined the entire tooth. We have combined the work done on the examination of heavy metals in human teeth using several instrumental approaches e.g. "Optical Spectroscopic Techniques" to detect elemental profile of human teeth in the current study.

• Journal of Korea Trade
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• 제26권4호
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• pp.63-82
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• 2022

Purpose - Drawing on relational institutional theory, we explored how demographic similarity between board members of a firm and newly emerged political elites led to firms' increased financial resource acquisition such as leverage ratio and decreased export intensity amidst the Asian financial crisis. We also studied how a firm's leverage ratio and export intensity can further affect firm profitability and financial credit rating. Design/methodology - We revisited and explored a unique, unprecedented crisis that affected most Korean firms: the Asian financial crisis that coincided with a governmental shift from a conservative to a liberal party. We collected demographic information from 432 listed Korean firms' board members and 43 political elites of the Blue House from 1998-2000 to create a demographic similarity measurement. We collected firms' financial information, built panel data, and used ordinary least squares regression to test our theory. Findings - Our results showed that demographic similarity between a firm's directors and newly emerged politicians had a positive association with a firm's leverage ratio but a negative association with a firm's export intensity. A firm's leverage ratio had a negative relationship with firm performance measured by firm profitability and financial credit rating. A firm's export intensity showed a positive effect on firm performance. Originality/value - We highlighted that during an economic crisis that coincided with a governmental shift and change of leading political actors, firms exerted efforts to survey the environment and build new external stakeholder relationships to cope with the changing landscape. We proposed that in an emerging market like Korea where low levels of trust and favoritism are prevalent across society, one of the relational institutional strategies that firms can employ is the selection of directors with similar demographic characteristics to political elites based on factors including birthplace and school affiliations. We examined the efforts of firms to build political networks with newly empowered political elites during a financial crisis, and the consequences of establishing such networks. We highlighted that during a financial crisis, the demographic similarity between a firm's board members and newly emerged politicians can provide firms with access to financial resources but can also result in poor management and reduced effort to enhance its international competitiveness.