• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.1-13
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• 2021

In this study, we tried to present suggestions to the Gyeongsangbuk-do tourism officials to satisfy them with experiential tourism resources and to revitalize their participation in the program. Therefore, the implications of this study are as follows. First, research on the satisfaction of experiential tourism programs and the willingness to participate in them is carried out, suggesting that it is a prerequisite for the transformation of the perception of tourists' participation in the Corona era. Second, it is necessary to make it a small experience tourist space that can provide non-face-to-face service utilizing the characteristics of contact technology, and to provide tourists with unique attractions against product discrimination and customer service. Third, through the introduction of non-face-to-face experience programs and expansion of services, the limited and macroscopic environment and social phenomenon of tourism activities in the Corona era, a new perception can be instilled. Fourth, visitors can expect to revitalize the tourism industry through the development and discovery of various programs. Thirdly, it will be possible to revitalize the local economy by giving meaning to the satisfaction of experiential tourism programs to tourists from all over the region's tourism business.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.348-362
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• 2021

Real estate investment behavior factors are divided into profitability, risks (stability), liquidity, and regulation (deregulation) factors. The sub-attributes of the investment behavior factors are generally formative indicators. Unlike reflection indicators, formative indicators can identify not only the influence of investment behavior factors on dependent variables, but also the influence of sub-attributes on dependent variables. Therefore, theoretical and practical needs of comparing the influences of factors and sub-attributes on dependent variables has been suggested. In this study, in order to provide information that help marketing for lots shopping building, both the causality between investment behavior factors and investment intention and the causality between sub-attributes and investment intention were comparatively studied for each of the three investor groups: the whole group, the group with high investment intention and the group with low investment intention. For this purpose, a survey and multiple regression analyses were conducted on 237 existing investors in the customer DB of a company that have been developing and selling lots shopping building in the metropolitan area and Sejong City. At the factor level, the effects of profitability and regulation were significant in the whole group and the group with low investment intention, but the effects of risk and liquidity were significant in the group with high investment intention. At the sub-attribute level, all three groups showed different results.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.27-41
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• 2020

The purpose of the project is to identify the relationship between the sub-factors of SNS information characteristics (information quality, information reliability) and the impact of immersion on social capital (connected capital) on word of mouth intention, and to present measures to revitalize the tourism industry using the results obtained. The study conducted empirical analysis on 326 adults aged 19 and older. The results of the study are as follows: First, it has been confirmed that the sub-factors of SNS utilization (information quality, information reliability) have a positive effect on immersion. Second, immersion has been verified to have a significant influence relationship on the degree of word of mouth intention. Third, it was analyzed that social capital has positive interrelationships with immersion and word of mouth intention. Based on these findings, social network services (SNS) in the tourism industry can be used as basic data to attract potential tourism customers in the future by providing efficient information on tourism products by utilizing social network services (SNS) in the development of tourism contents and marketing strategies, and it is meaningful in that it is intended to help the tourism industry in practice.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.347-364
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• 2022

Fraudulent companies or sellers strategically manipulate reviews to influence customers' purchase decisions; therefore, the reliability of reviews has become crucial for customer decision-making. Since customers increasingly rely on online reviews to search for more detailed information about products or services before purchasing, many researchers focus on detecting manipulated reviews. However, the main problem in detecting manipulated reviews is the difficulties with obtaining data with manipulated reviews to utilize machine learning techniques with sufficient data. Also, the number of manipulated reviews is insufficient compared with the number of non-manipulated reviews, so the class imbalance problem occurs. The class with fewer examples is under-represented and can hamper a model's accuracy, so machine learning methods suffer from the class imbalance problem and solving the class imbalance problem is important to build an accurate model for detecting manipulated reviews. Thus, we propose an OpenAI-based reviews generation model to solve the manipulated reviews imbalance problem, thereby enhancing the accuracy of manipulated reviews detection. In this research, we applied the novel autoregressive language model - GPT-3 to generate reviews based on manipulated reviews. Moreover, we found that applying GPT-3 model for oversampling manipulated reviews can recover a satisfactory portion of performance losses and shows better performance in classification (logit, decision tree, neural networks) than traditional oversampling models such as random oversampling and SMOTE.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.419-437
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• 2023

As the number of thin filers in Korea surpasses 12 million, there is a growing interest in enhancing the accuracy of assessing their credit default risk to generate additional revenue. Specifically, researchers are actively pursuing the development of default prediction models using machine learning and deep learning algorithms, in contrast to traditional statistical default prediction methods, which struggle to capture nonlinearity. Among these efforts, Graph Neural Network (GNN) architecture is noteworthy for predicting default in situations with limited data on thin filers. This is due to their ability to incorporate network information between borrowers alongside conventional credit-related data. However, prior research employing graph neural networks has faced limitations in effectively handling diverse categorical variables present in credit information. In this study, we introduce the Transformer embedded Graph Convolutional Network (TeGCN), which aims to address these limitations and enable effective default prediction for thin filers. TeGCN combines the TabTransformer, capable of extracting contextual information from categorical variables, with the Graph Convolutional Network, which captures network information between borrowers. Our TeGCN model surpasses the baseline model's performance across both the general borrower dataset and the thin filer dataset. Specially, our model performs outstanding results in thin filer default prediction. This study achieves high default prediction accuracy by a model structure tailored to characteristics of credit information containing numerous categorical variables, especially in the context of thin filers with limited data. Our study can contribute to resolving the financial exclusion issues faced by thin filers and facilitate additional revenue within the financial industry.

• Journal of Service Research and Studies
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• v.12 no.4
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• pp.94-105
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• 2022

Urban Air Transportation (UAM) is a three-dimensional transport within the city using eVTOL as an alternative to the saturation of land transportation due to overcrowding in major cities around the world. Design has played its roles in various fields in the development of transport, but research on the design application of UAM, which will be commercialized soon, is insufficient. Accordingly, there is a growing need for prior research on the forecasting the future environment and the design application through phenomenon analysis. The purpose of this study is to derive mega trends through STEP analysis for UAM and present ways to apply design in the UAM field based on this. The research method was conducted in the following order. First, the theoretical background of UAM was established by analyzing prior art documents on UAM. Second, five trends in the future environment centered on UAM were derived through STEP analysis. Finally, in order to derive a design application, five experts in each design area (product, visual, video, environment, service) discussed the design application focusing on the results of STEP analysis and derived a design application plan for each design area in the UAM field. Through this study, it was found that the most frequent design area in the STEEP analysis is product design and service design, and therefore related design development is important. After analyzing UAM's information provision plan, display method, and usage process suggested in this study, it is expected that it will lead to various prior design studies related to UAM, such as customized service design, to establish an infrastructure environment for commercialization of UAM.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.127-143
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• 2023

Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.

• Knowledge Management Research
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• v.24 no.1
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• pp.73-97
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• 2023

Recently, the MyData market has been growing as the importance of data and issues related to personal information protection have drawn much attention together. MyData refers to the concept of guaranteeing an individual's right to personal information and providing and utilizing one's data according to individual consent. MyData service providers can combine and analyze customer information to provide personalized services. In the early days, the MyData business was activated mainly by private companies and the financial industry, but recently, public institutions are also actively taking advantage of MyData. Meanwhile, the importance of an individual's intention to provide MyData for the success of MyData businesses continues to increase, but research related to this is lacking. Moreover, existing studies have been mainly conducted on individual benefits of MyData; there are not enough studies in which both public benefit and perceived risk factors are considered at the same time. In this regard, this study intends to derive factors affecting the intention to provide MyData based on the privacy calculus model, examine their influencing mechanism, and further verify the moderating effects of individual capabilities and institutional type. This study can find academic significance in that it expanded and demonstrated the privacy calculus model in the context of MyData providing intention. In addition, the results of this study are expected to offer practical guidelines for developing and managing new services in MyData businesses.

• Knowledge Management Research
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• v.24 no.1
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• pp.147-172
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• 2023

This study aims to review the competitiveness of 'TVING', a Korean OTT player in Korean market. For this, this study extracts core business resources of TVING focusing on resource-based theory, and analyzes their competitiveness under VRIO framework. TVING has 4 tangible and intangible resources respectively and 1 human resource. Tangible resources of TVING are technology(recommendation, compression), content(original, exclusive, discriminative non-exclusive), production studio, and paid-subscribers. Intangible resources are content planing capability, distribution network(local, global), marketing promotion·PR, sales), brand preference. And human resource of TVING creates IP professionalism of the company. As a result of VRIO analysis, discriminative non-exclusive content, production studios, and domestic service channels are the most powerful resources of TVING to 'sustain competitive advantage'. Technology, original content, planning capability and IT professionalism bring 'temporary competitive advantage', while exclusive content, the number of paid-subscribers, global service network, and promotion capabilities are not core resources with staying in competitive rank stages. By the way, TVING has potential users for sales of KT and LGU+ thanks to partnership and M&A, but this is not effectively used at the organization level yet. The meaning of this study can be found in that this evaluated competitiveness by each resource of TVING and arranged its implications.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.9
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• pp.169-178
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• 2018

The ice machine is the machine for making ice. As most of the companies that manufactures and sells the ice machine are small and medium-sized companies, they have been they have been experiencing the trouble for the after-sales service after selling the machine. The difficulties of the after-sales service are mostly caused by unnecessary customer service requests of the purchaser, which eventually leads to the unnecessary expenditure of the seller and the purchaser. However, financially, the poor ice machine manufacturers want to reduce this cost as much as possible. Furthermore, even if they want to sell their products overseas, they are hesitating because of the after-sales service. For this reason, the companies making the ice machine need a system which checks the status of the ice machine and takes the proper actions without the visiting service. Therefore, this paper introduces the remote control and operational status monitoring systems which can monitor the status of the ice machine in the remote area and control it as needed. Through the developed system, the company manufacturing the ice machine and the manager of the ice machine can understand the current status of the ice machine and respond against the ice machine's trouble, immediately. In addition, it can be expected to have great effects on cost reduction because the maintenance and management after selling can be efficiently performed.