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의료기관의 소셜 미디어 마케팅 역량이 인지된 위험 및 의료관광 환자 만족도에 미치는 영향에 관한 연구
UGLI ANVARJONOV NODIRBEK BAKHROMZHON,엄기현 한국품질경영학회 2023 품질경영학회지 Vol.51 No.2
Purpose: The purpose of the research is to explore the role of social media in attracting international patients for cosmetic services in South Korea during the COVID-19 pandemic. The study aims to conceptualize social media as an effective marketing tool for minimizing perceived risks associated with cosmetic services and increasing patient satisfaction. Methods: The study validated proposed hypotheses using the PROCESS macro for SPSS with overseas patients who received cosmetic treatment in private Korean plastic surgery clinics in Busan. Results: This study found that information delivery capability reduced perceived risk and contributed to patient satisfaction, while communication capability did not show any significant relationship with perceived risk and satisfaction. In addition, information delivery capability had a significant direct effect on patient satisfaction, but communication capability did not. Conclusion: It is expected that the outcomes of this study will broaden our understanding of the use of social media in reducing perceived risk and increasing satisfaction.
The Panel Analysis of the Effects of FDI and Export on the Economic Growth of CIS Countries
Temurbek-Ulugbek Ugli Atajanov,이재득 한국무역연구원 2023 무역연구 Vol.19 No.1
Purpose – This paper aims to examine the effects of foreign direct investment (FDI) and export on the economic growth of the Commonwealth of Independent States (CIS) and, based on the research results, provide some policy implications for the government of Uzbekistan. Design/Methodology/Approach – A panel data regression model and a panel dataset covering the period 1997 to 2020 were utilized for empirical investigation. The collected data were divided into two groups by income level and two groups by period, namely before and after the global financial crisis of 2008. This paper analyzes the aforementioned groups separately and provides a summary. Pooled OLS, fixed-effects models, and random-effects models were applied through panel data, and the Hausman test and the Breusch-Pagan Lagrange Multiplier test were performed. Findings – The findings corroborate the study’s hypothesis by proving that FDI facilitates growth in the former Soviet republics. Similarly, the comprehensive findings demonstrate that export is crucial for the economic growth of CIS countries, but the fixed-effects regression results for the first country group indicate that the influence of export on economic growth is insignificant when examined separately. Research Implications – The paper recommends that the government of the Republic of Uzbekistan enhance multilateral trade agreements to improve its international trade balance and adopt an export-stimulating strategy. To encourage FDI, the government should take steps to improve the country’s investment climate.
Detection of Distracted Driving using Deep Learning
Ikromjanov Kobiljon Komil Ugli,Satyabrata Aich,Harin Ryu,Moon-Il Joo,Hee-Cheol Kim 한국정보통신학회 2021 2016 INTERNATIONAL CONFERENCE Vol.12 No.1
As the population growth day by day, the need of transportation also increases. As the result, there are more accidents on the roads then before. According to the United States National Highway Traffic Safety Administration (NHTSA), the main reason of roadway injuries and deaths is distracted drivers. Driver distraction is a specific type of driver inattention on the road. In this case, a deep learning-based system can detect and distinguish the source of distractions in real-time, to avoid traffic crashes and make better transport safety. In this paper, we try to develop the system using transfer learning methods with ResNet50 model architecture and pre-trained weights, as well as, compare different optimizers to use with transfer learning. Adam, SGD and RMSprop optimizers were used with transfer learning methods to improve accuracy. At the end, the results show that transfer learning on ResNet50 with SGD optimizer is better model compared to Adam and RMSprop models getting 98,4% (492 out of 500) of accuracy on the unseen distracted drivers’ test dataset.
( Anvarjonov Nodirbek Bakhromzhon Ugli ),배준영 ( Bae Jun-young ),채희선 ( Chae Heesun ),엄기현 ( Um Ki-hyun ) 경희대학교 경영연구원 2022 의료경영학연구 Vol.16 No.3
The occurrence of COVID-19 has jeopardized many businesses and, as a result, healthcare service providers are seeking to establish an effective strategy to survive in the short term and prosper in the long term. Appling the Stimulus-Organism-Response framework to medical tourism settings in South Korea, the present study seeks to examine the effect of social media marketing (i.e., stimulus) on overseas patient satisfaction (i.e., response) via attitude (i.e., organism). Survey data from international patients, who received cosmetic service from clinics located in Busan, South Korea, were employed to examine our hypotheses. The findings suggest that social media marketing strategy impacts oversea patient attitude that overseas patient attitude affects satisfaction, and that social media marketing strategy impacts satisfaction only through attitude (i.e., full mediation effect is observed). Based on our hypothesis testing results, we provide theoretical and managerial implications, followed by limitations and future study directions.
일홈존 ( Sadriddinov Ilkhomjon Rovshan Ugli ),박두순 ( Doo-soon Park ) 한국정보처리학회 2021 한국정보처리학회 학술대회논문집 Vol.28 No.2
Nowadays recommendation systems are so ubiquitous, where our many decisions are being done by the means of them. We can see recommendation systems in all areas of our daily life. Therefore the research of this sphere is still so active. So far many research papers were published for clothing recommendations as well. In this paper, we propose the clothingrecommendation system according to user emotion and weather information. We used social media to analyze users’ 6 basic emotions according to Paul Eckman theory and match the colour of clothing. Moreover, getting weather information using visualcrossing.com API to predict the kind of clothing. For sentiment analysis, we used Emotion Lexicon that was created by using Mechanical Turk. And matching the emotion and colour was done by applying Hayashi's Quantification Method III.