• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.15-23
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• 2023

Through the revision of the Framework Act on Administrative Regulations (July 17, 2019), the government minimized regulations and applied the comprehensive negative regulation principle to enhance economic vitality. However, a legally mandatory certification system has been applied to marine pollution prevention materials and chemicals, and inspection is conducted every time a product is sold, suppressing the autonomy of manufacturers. In addition, the majority of manufacturers of marine pollution prevention materials and chemicals are small businesses; therefore, they take the approach of producing small quantities of products whenever a buyer requests an order. Consequently, the need for deregulation was raised to ensure autonomy of the market and industry, and improve efficiency in accordance with the current trend of approval, performance test, and inspection systems for marine pollution prevention materials and chemicals. In this study, problems within the current system were identified and improvement plans are proposed through comparison and analysis of domestic and foreign systems.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.431-438
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• 2022

With the technical development of fourth industrial revolution, VR game market is rapidly expanding. Meanwhile, heavy user group means the group consisting of people consuming certain media or contents more than others, which is the core constituency of the media industry, and there have been only a few studies on them. This study identified the factors that influenced the continuous intention of use of VR game heavy users and figured out their characteristics by verifying the difference in variables with the light user group. According to the results, the heavy user group showed higher behaviors than the light user group in terms of personal innovation, presence, and continuous intention of use variables. In addition to this, it was found that personal innovation, perceived quality, and presence had a significant influence on the continuous intention of use. This study is intended to empirically analyze the characteristics of heavy VR game users and influential factors, thereby preparing baseline data for VR game development and other relevant studies.

• Korea Trade Review
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• v.43 no.5
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• pp.67-91
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• 2018

A number of studies have been conducted on the evaluation of bi-national products, but studies that may be applied in practice are lacking. This study suggests several implications for bi-national products in the sub-market using a more specific approach than previous studies. To this end, this comprehensive comparative study reflects the purchasing routes, product category, and consumers' personal characteristics (regulatory focus, prior knowledge) of bi-national products. Results found the evaluation of bi-national products according to purchase routes showed that consumers in offline stores were more favorable than consumers in online stores. In comparison with product categories, necessities were more positive than luxury goods. On the other hand, according to consumer's personal characteristics, consumers with promotion focus tendency perceived brand preference more highly than consumers with preference focus tendency. Also, it was found that groups with high prior knowledge had a positive evaluation of products compared to low knowledge groups.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.115-127
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• 2023

Video stabilization is one of the camera technologies that the importance is gradually increasing as the personal media market has recently become huge. For deep learning-based video stabilization, existing methods collect pairs of video datas before and after stabilization, but it takes a lot of time and effort to create synchronized datas. Recently, to solve this problem, unsupervised learning method using only unstable video data has been proposed. In this paper, we propose a network structure that learns the stabilized trajectory only with the unstable video image without the pair of unstable and stable video pair using the Convolutional Auto Encoder structure, one of the unsupervised learning methods. Optical flow data is used as network input and output, and optical flow data was mapped into grid units to simplify the network and minimize noise. In addition, to generate a stabilized trajectory with an unsupervised learning method, we define the loss function that smoothing the input optical flow data. And through comparison of the results, we confirmed that the network is learned as intended by the loss function.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.29-37
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• 2023

Due to climate change, interest in crop production and distribution is increasing, and attempts are being made to use bigdata and AI to predict production volume and control shipments and distribution stages. Prediction of agricultural product imports not only affects prices, but also controls shipments of farms and distributions of distribution companies, so it is important information for establishing marketing strategies. In this paper, we create an artificial intelligence prediction model that predicts the future import volume based on the wholesale market melon import volume data disclosed by the agricultural statistics information system and evaluate its accuracy. We create prediction models using three models: the Neural Prophet technique, the Ensembled Neural Prophet model, and the GRU model. As a result of evaluating the performance of the model by comparing two major indicators, MAE and RMSE, the Ensembled Neural Prophet model predicted the most accurately, and the GRU model also showed similar performance to the ensemble model. The model developed in this study is published on the web and used in the field for 1 year and 6 months, and is used to predict melon production in the near future and to establish marketing and distribution strategies.

• Journal of Service Research and Studies
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• v.11 no.3
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• pp.17-30
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• 2021

In the context of Sharing Accommodation has become a new type of accommodation choice for customers. The purpose of this study is to improve the existing defects of Sharing Accommodation Services through insight into the pain points of customer experience, so as to improve customer satisfaction. In this study, Airbnb and Tujia were selected as the subjects for comparative study. By collecting and sorting out references, the research background of Sharing Accommodation is analyzed in depth. Research methods of Service Design, such as Customer Journey Map and Service Blueprint, are adopted to gain insight into customer needs, identify pain points and propose hypothesis of service optimization. Tools such as Kano Model and Potential Customer Satisfaction are used to test and determine three schemes for optimizing the service. Finally, the results are displayed through Service Scenario. The research results can help operators of Sharing Accommodation to identify and improve the elements of service and provide a higher quality customer experience, thus promoting the healthy development of Sharing Accommodation market.

• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.51-58
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• 2024

This paper examines the differences between the Korean and American stock markets using the Kospi and S&P 500 indices and discusses policy implications through them. To this end, in addition to the existing time series analysis method, a deep learning method was used to compare markets, and the comparison was made in terms of stock price forecasting ability and data generation ability. In monthly data, the difference between time series was not large, and in daily data, the difference in terms of stability was weak, and there was no significant difference in predictive power or simulation data generation. As shown in the results of this study, if there is not much difference in market price movement patterns between Korea and the United States, tax benefits for long-term stocks investment will be effective against the side effects of short selling.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.178-186
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• 2024

While in high-income countries the development of digital technology began in the 1970s, in low- and middle-income countries it began in the 1990s and even after 2005, due to the political regime that constrained economic development and innovation. At the same time, there are no studies of the relationship between technological development and structural changes through innovation in low- and middle-income countries. The article aims to quantify the relationship of the introduction of digital technologies on innovation, structural transformation of low- and middle-income economies. The industrial-agrarian economy of Uzbekistan with an authoritarian regime is in a state of transition to a market economy, while in Ukraine, there are active processes of Europeanization and integration into the EU. Ukraine's economy is commodity-based (the export of raw materials of industries and the agricultural sector in developed countries predominates) and industrial-agrarian. Digital technologies and the service sector are little developed in Uzbekistan. On the other hand, Ukraine has a more developed ICT sector. Uzbekistan is gradually undergoing an innovative and structural transformation of the economy: the productivity of the agricultural, industrial, and service sectors is growing, but the ICT sector is virtually undeveloped. In comparison, in Ukraine, there are no significant structural transformations due to a significant drop in productivity of the industrial sector, with stable growth of productivity of the agricultural sector due to technology and a slight increase in productivity of the service sector. It is revealed that Ukraine and Uzbekistan have undergone structural transformations of the economy in favor of the service sector, while the agricultural and industrial sectors produce less and less. If Uzbekistan remains the industrial-agrarian country with an aggregate share of the added value of these sectors 59% in 2019, Ukraine transits to the post-industrial type of economy where the added value of the service sector in GDP grows (55% compared to agrarian and industrial sectors at 42%).

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.319-334
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• 2024

Purpose - The purpose of this study is to examine the gravity model commonly used for demand forecasting upon the implementation of new tourist facilities and analyze the main causation of forecasting errors to provide a suggestion on how to improve. Design/methodology/approach - This study first measured the errors in predicted values derived from past feasibility study reports by examining the cases of five national science museums. Next, to improve the predictive accuracy of the gravity model, the study identified the five most likely issues contributing to errors, applied modified values, and recalculated. The potential for improvement was then evaluated through a comparison of forecasting errors. Findings - First, among the five science museums with very similar characteristics, there was no clear indication of a decrease in the number of visitors to existing facilities due to the introduction of new facilities. Second, representing the attractiveness of tourist facilities using the facility size ratio can lead to significant prediction errors. Third, the impact of distance on demand can vary depending on the characteristics of the facility and the conditions of the area where the facility is located. Fourth, if the distance value is below 1, it is necessary to limit the range of that value to avoid having an excessively small value. Fifth, depending on the type of population data used, prediction results may vary, so it is necessary to use population data suitable for each latent market instead of simply using overall population data. Finally, if a clear trend is anticipated in a certain type of tourist behavior, incorporating this trend into the predicted values could help reduce prediction errors. Research implications or Originality - This study identified the key factors causing prediction errors by using national science museums as cases and proposed directions for improvement. Additionally, suggestions were made to apply the model more flexibly to enhance predictive accuracy. Since reducing prediction errors contributes to increased reliability of analytical results, the findings of this study are expected to contribute to policy decisions handled with more accurate information when running feasibility analyses.

• Journal of Information Technology Services
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• v.23 no.3
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• pp.1-16
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• 2024

As the COVID-19 pandemic confirmed the culture of non-face-to-face consumption. In retail commerce, the 'live commerce' market, where sales are made by communicating with customers in the form of live streaming broadcasts, has grown rapidly. Although previous studies have consistently confirmed the phenomenon of "influencers" in society and culture, there is a lack of research on the "sales expertise" of live commerce broadcasters such as Wang Hong in China. In China, "Wang Hong" is short for "Wang Luo Hong Ren", a combination of "Wang Luo", which means the Internet, and "Hong Ren", which means star, and refers to a person who is popular through social platforms and is gaining popularity from many fans. Therefore, this study focuses on Wang Hong's developing "selling expertise" and examines it from the perspective of a shopping curator. In particular, we applied Harold Jarche(2011)'s "Seek-Sense-Share" model to influencers to verify their influence on trust and purchase intention in live commerce. Furthermore, we analyzed the differences between Korea and China.A survey was conducted among live commerce users in Korea and China, and a total of 228 questionnaires were used in the final analysis. Basic statistical analysis was conducted using SPSS and hypotheses were tested using PLS 3.0. The results of the hypothesis testing showed that influencers' curatorial competence "Seek-Sense-Share" had a significant effect on trust, and trust had a positive effect on purchase intention. In addition, there is a significant difference between Korean and Chinese consumers in this relationship.