• International journal of advanced smart convergence
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• v.12 no.3
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• pp.68-74
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• 2023

The food industry has been hit hard since the first outbreak of COVID-19 in 2019. However, as of April 2022, social distancing has been resolved and the restaurant industry has gradually recovered, interest in restaurant start-ups is increasing. Therefore, in this paper, 'restaurant start-up' was cited as a key keyword through social media big data analysis using TexTom, and word frequency and cone analysis were conducted for big data analysis. The keyword collection period was selected from May 1, 2022, when social distancing due to COVID-19 was lifted, to May 23, 2023, and based on this, a plan to develop chatbot services for restaurant start-ups was proposed. This paper was prepared in consideration of what to consider when starting a restaurant and a chatbot service that allows prospective restaurant founders to receive information more conveniently. Based on these analysis results, we expected to contribute to the process of developing chatbots for prospective restaurant founders in the future

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• Knowledge Management Research
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• v.22 no.3
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• pp.235-252
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• 2021

The development of information and communication technology and COVID-19 have caused an unusual change in the hotel industry, and the demand for the contactless services such as service robots from hotel customers has surged. Therefore, this study investigates the perception of hotel customers on contactless services by applying a mixed-method analysis. Specifically, this study identified the causal correlations between variables through the structural equation model, and further applied the fuzzy set qualitative comparison analysis to derive patterns of variables that form the intention to use the non-face-to-face services. As a result of the analysis, it was shown that service experience co-creation, palyfulness, personalization, and trust had a significant effect on intention to use through the contactless service use desire. On the other hand, in the results of fuzzy-set qualitative comparison analysis, playfulness was derived as a core factor in all patterns. Based on these analysis results, this study provides academic basis for in-depth understanding of hotel customers' perception of contactless service and specific guidelines for hotel managers on the contactless service strategies in the era of COVID-19 pandemic.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1609-1618
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• 2012

We can easily acknowledge the facts that the e-market is increasingly and quickly changed by the smart phone user's. This research focuses the e-service quality and relationship between the e-service quality, customer satisfaction and behavioral intention in the AppShopping Mall. Based on the documentary research, the empirical study was followed by the questionnaire. The 313 usable questionnaires were collected by a self-administered survey. The results reveal that the e-service quality determinants are factors including customer service, app design, security, connectivity and user's convenience, and that the e-service quality is directly or indirectly related to customer satisfaction and behavioral intention. The AppShopping mall managers have to try on their best to find out the customer's needs, manage the lists of the e-service quality and develop the app.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.55-60
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• 2020

Adaptive recommendation systems have been developed with big data processing as a system that provides services tailored to users based on user information and usage patterns. Deep learning can be used in these adaptive recommendation systems to handle big data, providing more efficient user-friendly recommendation services. In this paper, we propose a system that uses deep learning to categorize and recommend tourism types to suit the user's personality. The system was divided into three layers according to its core role to increase efficiency and facilitate maintenance. Each layer consists of the Service Provisioning Layer that real users encounter, the Recommendation Service Layer, which provides recommended services based on user information entered, and the Adaptive Definition Layer, which learns the types of tourism suitable for personality types. The proposed system is highly scalable because it provides services using deep learning, and the adaptive recommendation system connects the user's personality type and tourism type to deliver the data to the user in a flexible manner.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.45-51
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• 2023

As COVID-19 made it difficult to travel abroad and attract domestic tourists to foreigners, the phenomenon of MZ generations flocking to Jeju through consumption patterns occurred. In this study, if Jeju Island uses Jeju's rural tourism and smart glasses to study how to attract and cope with domestic tourists after the pandemic and build a mobile application or smart glass to tour based on village maps, the docent guide service through smart glasses will help tourists. Furthermore, it would be very beneficial to introduce a location-based service to provide the necessary information at the location according to the movement path of tourists. In fact, we conclude that it can be implemented through the development of the Hansung Baekje Museum, and hope that the actual media can be applied to free tourist courses such as Jeju Olle Trail, as it provides various contents in selective development such as AR and VR.

• Journal of Industrial Convergence
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• v.16 no.2
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• pp.1-14
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• 2018

The interconnectedness of all things is continuously expanding. For example, bluetooth low energy (BLE) beacons are wireless radio transmitters that can send an identifier to nearby receivers and trigger a number of applications, from proximity marketing to indoor location-based service. iBeacon technology which is one of the newest technologies in the smart tourism field, is reckoned as being very useful for travelers in enhancing the experience with visiting places. However, there is consequently not much existing research yet about the connection between iBeacon technology and tourism destination. Considering that, this study analyzes the adoption of iBeacon in tourism destination, this study examine the interrelationships and feedback structures of key factors in iBeacon adoption. To serve the purpose, this study used system dynamics approach to develop a model of iBeacon adoption in tourism destination. The analysis results showed that the concept of 'Social Influences' is one of the significant predictors for individual's intention behavior to accept iBeacon, and word of mouth (WOM), subjective norm, privacy concern, and perceived usefulness are key factors influencing the iBeacon adoption.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.579-586
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• 2021

This study examines the application of big data and tasks of tourism based on the case of Jeju Special Self-Governing Province, which used big data for regional tourism policy. Through the use of big data, it is possible to understand rapidly changing tourism trends and trends in the tourism industry in a timely and detailed manner. and also could be used to elaborate existing tourism statistics. In addition, beyond the level of big data analysis to understand tourism phenomena, its scope has expanded to provide a platform for providing real-time customized services. This was made possible by the cooperative governance of industry, government, and academia for data building, analysis, infrastructure, and utilization. As a task, the limitation of budget dependence and institutional problems such as the infrastructure for building personal-level data for personalized services, which are the ultimate goal of smart tourism, and the Personal Information Protection Act remain. In addition, expertise and technical limitations for data analysis and data linkage remain.

• Journal of Smart Tourism
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• v.3 no.2
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• pp.23-36
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• 2023

Due to the phenomenon of aging, a new consumer segment known as the "new-silver generation" is emerging. Unlike the previous silver generation, this generation possesses significant economic power and consuming willingness, attracting attention from consumer goods companies. However, both the new-silver generation and the elderly face challenges in adopting contactless or self-service technologies such as self-order kiosks, resulting in negative reactions. Therefore, this study aims to investigate the attitude and response of the newsilver generation towards kiosks, as well as the factors influencing their resistance to such technology. By applying theoretical perspectives from the innovation resistance model, technostress theory, and the value-based model, this study identifies influencing factors for innovation resistance among the new-silver generation when using contactless technologies implemented in fast-food restaurants. The findings indicate that a lower awareness of new technologies and services corresponds to decreased adoption resistance, while a higher perceived value leads to more positive behaviors and attitudes among the new-silver generation utilizing kiosks at fast-food restaurants.

• Journal of the Korean Society for Library and Information Science
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• v.41 no.3
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• pp.165-179
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• 2007

This study regards the evaluation for the main contents of the 'Library Development Plan(2003-2011)' promoted by the Ministry of Culture and Tourism for the library development plan in Korea. SMART evaluation method was introduced for the evaluation of vision, objective, core project of library development plan. Following result was acquired as a result of the study. First. as a result of SMART vision, objective, core projects and main business of library development plan was presented to be 3.05, 3.09, 3.15 and 3.12 respectively. Thus, in the evaluation for components of development Plan, it was excellent in core projects. Second, as a result of SMART, concreteness, measurability, achievability, relevance and time frame of library development plan was presented to be 3.09. 2.99. 3.12. 3.24 and 3.10 respectively. Thus, in the evaluation components of development plan. it was excellent in relevance but it has been found that supplementary measures should be taken on measurability. Third, 'culture-oriented room with knowledge and information' was found to be superior to the 'information library with up-to-date technology' in evaluation of the objective. Fourth, 'substantiality in user service with the supplement of library contents' was excellent in evaluation of core projects but there is some problem with 'activation of library function through training and supplement of professional manpower.' Fifth. 'Enhancement in library information service' was presented to be excellent in evaluation of main business but there was problem in 'reinforcement in function of library for each location and type,' 'partnership of public-private enterprises' and 'promotion for book culture of the public' thus it need to be revised and supplemented hereafter.