• Asia pacific journal of information systems
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• v.29 no.3
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• pp.468-488
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• 2019

As the growth of online travel agencies (hereafter OTAs) accelerates, competition among hotels to gain exposure on the first page of OTA websites, and the financial burden, such as commissions hotels have to pay in return, are increasing. Therefore, to facilitate successful management in the tourism industry, it is important to establish what makes people continue the practice of using OTAs to book rooms in hotels and other accommodation outlets. By adopting the heuristic-systematic model (HSM), this study explores the factors that drive consumers' continued use of OTA and classifies them into heuristic cues (brand awareness, cost saving, and scarcity message) and systematic cues (recommendation quality and the ability to provide reputation). Furthermore, we divided the sample based on the location of hotels within and outside Korea, and investigated the different roles of the cues between two models. The results are expected to provide theoretical and practical implications for both OTAs and hotels.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.95-101
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• 2022

The development of the 4th industry has increased social media, and the rise of COVID-19 has stimulated non-face-to-face services. People's consumption patterns are also changing a lot due to non-face-to-face services. In this paper, food content keywords are derived through social network-based semantic network analysis, emotions are analyzed, and keywords applied to food recommendation platforms are input. We collected food, influencer, and corona keyword analysis data through Textom. A lot of research has been done through online reviews of existing influencer content. However, there is a lack of research on keyword sentiment analysis provided by influencers rather than consumers and research perspectives. This paper uploads language and topics derived through online reviews of existing publications and subscribers, and goes beyond the limits used in marketing methods. By analyzing keywords that influencers suggest when uploading content, you can apply data that applies them to food recommendation platforms and applications.

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.819-832
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• 2022

Cross-domain recommender system transfers knowledge across different domains to improve the recommendation performance in a target domain that has a relatively sparse model. However, they suffer from the "negative transfer" in which transferred knowledge operates as noise. This paper proposes a novel Multiple Fusion-based Deep Cross-Domain Recommendation named MFDCR. We exploit Doc2Vec, one of the famous word embedding techniques, to fuse data user-wise and transfer knowledge across multi-domains. It alleviates the "negative transfer" problem. Additionally, we introduce a simple multi-layer perception to learn the user-item interactions and predict the possibility of preferring items by users. Extensive experiments with three domain datasets from one of the most famous services Amazon demonstrate that MFDCR outperforms recent single and cross-domain recommendation algorithms. Furthermore, experimental results show that MFDCR can address the problem of "negative transfer" and improve recommendation performance for multiple domains simultaneously. In addition, we show that our approach is efficient in extending toward more domains.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.155-162
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• 2021

With the global COVID-19 pandemic, the tourism sector and all consumption have contracted with the untact era. Wine will also be sold and developed in various ways non-face-to-face in the future. Therefore, it is necessary to develop apps and web servers that focus on health in the era of single-person households and non-face-to-face. This study used facial recognition data based on photos of adult men and women in their 40s and 50s to analyze the Sasang constitution through a mobile app and web server, and suggested wine recommendations suitable for their constitution. First, the user's body information is entered. And through the facial recognition mobile app, recommend the right wine after analyzing the body type. if it's not like the first recommended wine, it is configured to receive another wine recommendation. In the future, the number of single-person households will increase further, and in the age of well-being, wine recommendations that fit my body will be useful. Wine recommendation suitable for Sasang constitution will be a useful mobile application to manage personal healt

• Smart Media Journal
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• v.12 no.8
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• pp.9-17
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• 2023

The development of information and communication technology and the improvement of the development and dissemination of smart devices have caused changes in the form of tourism, and the concept of smart tourism has since emerged. In this regard, researches related to smart tourism has been conducted in various fields such as policy implementation and surveys, but there is a lack of research on application reviews. This study collects Trip Advisor application review data in the Google Play Store to identify usage of the application and user satisfaction through Latent Dirichlet Allocation (LDA) topic modeling. The analysis results in four topics, two of which are positive and the other two are negative. We found that users were satisfied with the application's recommendation system, but were dissatisfied when the filters they set during search were not applied or that reviews were not published after updates of the application. We suggest more categories can be added to the application to provide users with different experiences. In addition, it is expected that user satisfaction can be improved by identifying problems within the application, including the filter function, and checking the application environment and resolving the error occurring during the application usage.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.267-273
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• 2020

Beacon is a wireless communication device that can automatically recognize the smart device in the short distance and transmit the necessary data, Beacon is a representative Internet of Things (IoT) facility in the era of the 4th Industrial Revolution, which is utilized in various fields such as short-distance information delivery, mobile location service, shopping, and marketing, and is constantly evolving. In this paper, it is based on tourist site-based recommendation information service. A system is proposed that recommends customized information according to the user's interest, preference, etc. by incorporating beacon technology. In other words, it acts as an information agent that informs tourists of desired information. In order to meet the needs of tourists, it is necessary to build an intelligent tourism recommendation system. The personalized Korean food and tourism recommendation management system using the beacon technology proposed in this paper is expected to provide high-quality services not only to foreigners visiting Korea but also to Korean tourists.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.263-270
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• 2020

The growth of the mobile app markets has made it popular among people who recommend relevant information about restaurants. The recommendation service app based on AI Chatbot is that it can efficiently manage time and finances by making it easy for restaurant consumers to easily access the information they want anytime, anywhere. Eating out consumers use smartphone applications for finding restaurants, making reservations, and getting reviews and how to use them. In addition, social attention has recently been focused on the research of AI chatbot. The Chatbot is combined with the mobile messenger platform and enabling various services due to the text-type interactive service. It also helps users to find the services and data that they need information tersely. Applying this to restaurant recommendation services will increase the reliability of the information in providing personal information. In this paper, an artificial intelligence chatbot-based smartphone restaurant recommendation app using personalization information is proposed. The recommendation service app utilizes personalization information such as gender, age, interests, occupation, search records, visit records, wish lists, reviews, and real-time location information. Users can get recommendations for restaurants that fir their purpose through chatting using AI chatbot. Furthermore, it is possible to check real-time information about restaurants, make reservations, and write reviews. The proposed app uses a collaborative filtering recommendation system, and users receive information on dining out using artificial intelligence chatbots. Through chatbots, users can receive customized services using personal information while minimizing time and space limitations.

• The Korean Journal of Franchise Management
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• v.8 no.1
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• pp.43-53
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• 2017

Purpose - The coffee market in Korea has been dramatically developed and coffee chains dominate the Korean coffee market recently. Customer's perceived value is one of the marketing tools to get competitive advantages of coffee chains, and plays a critical role to study on coffee franchise industry. Thus, this study is to identify the effect of customer's perceived value (price, brand, service, and quality) on revisit intentions and word-of-mouth(WOM). Research design, data. and methodology - Customer's perceived values consists of four dimensions. 253 samples of 320 were used for data analyses excluding unusable responses. The data were analyzed with SPSS 21.0 and SmartPLS 3.0. Result - First, customer's perceived brand value and service value have a significant, positive effect on revisit intentions. Second, Price value and brand value have a positive influence on WOM. Third, gender difference plays a moderating role in the relationship between brand value and price value and WOM, and between brand value and revisit intentions. Conclusions - Males tend to focus more on their perceived brand value of coffee shops for revisit and recommendation, otherwise females consider price value to give an advice to others. Based on the results of this study, the marketers of coffee chains can develop effective strategies regarding gender difference as well.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.957-976
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• 2023

ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT's early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users' experiences.