• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.74-82
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• 2014

Automatic identification is pervasive in many areas and its applicable areas are increasing gradually. 2D bar-code, NFC, and RFID technologies are representative examples of the automatic identification. This paper explains the implementation of mobile tourism application software on RFID technology. The mobile application provides the location and navigation information by combining the tag inventory and web database. The interactions among the user, application and database server are described in detail. This paper proposes a simple way of minimizing the efforts to build the entire system by storing the URLs for the tag and accessing existing tourism information services through the URLs.

• Journal of Platform Technology
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• v.11 no.6
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• pp.21-27
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• 2023

In this paper, we introduce a reinforcement learning-based algorithm for personalized tourist path recommendations. The algorithm employs a reinforcement learning agent to explore tourist regions and identify optimal paths that are expected to enhance tourism experiences. The concept of tourism experience is defined through points of interest (POI) located along tourist paths within the tourist area. These metrics are quantified through aggregated evaluation scores derived from reviews submitted by past visitors. In the experimental setup, the foundational learning model used to find tour paths is the Deep Q-Network (DQN). Despite the limited availability of historical tourist behavior data, the agent adeptly learns travel paths by incorporating preference scores of tourist POIs and spatial information of the travel area.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.383-390
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• 2014

In recent years, the convergence of IT and IT sightseeing tour has emerged as a fusion of academic disciplines in the future. Convergence study of social data analysis, raising the heat. Social Network Services (SNS) being utilized in many areas of marketing and to apply the case study is also increasing. This study is based u-smart tourist information systems for mobile learning content design. This is the pattern of things in the template library for things to increase the effectiveness of the learning content to mobile learning content to be converted to a. Design of mobile learning content using u-smart things smart phone app (App) and XMI to go through the design process of utilizing the heat. Future through the design process by implementing a mobile learning content to meet information quality tourist information content to create mobile learning content and learning things that can be content to live it up advantage.

• The Journal of Information Systems
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• v.26 no.3
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• pp.247-271
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• 2017

Purpose This study aims to propose a framework for safety in domestic walking tourism, which defines the scope and type of safety information for tourists. Also, the framework provides a systematic classification for safety information in walking tourism. As the importance of safety in walking tourism due to the frequent occurrence of crimes and unexpected accidents increases, it is necessary to provide tourists with safety information on walking courses rapidly and systematically. However, most administrators (e.g., local governments) have mainly focused on providing tour information on walking courses through Internet websites or mobile apps, overlooking the safety issue. Besides, there is a lack of understanding of safety not only in walking tourism but also in the whole tourism industry. Design/methodology/approach This study proposes the framework that covers all possible safety-related information in walking tourism. Furthermore, to validate its availability, this study analyzes eight major platforms which offer tour information to tourists by applying the framework. Findings The major findings of this study are as follows. First, all platforms considered in this study do not provide any information on tourism safety, focusing on the provision of tour information. Second, three platforms currently provide an SOS function which means post-safety information. That is, no safety information is provided to prevent safety issues in advance. Finally, despite the increase of social concerns, all platforms do not provide safety information on public order and diseases in the social disaster classification as well as environmental pollution in the natural disaster classification. The details and implications of the findings are presented.

• The Journal of Industrial Distribution & Business
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• v.12 no.7
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• pp.27-39
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• 2021

Purpose: The researchers reviewed the previous studies on the psychological anxiety and economic damage during the recent COVID-19 pandemic to understand the satisfaction, awareness and attitude of the residents in Jeju, Korea. Research design, data and methodology: 215 samples based on self-reported survey were collected for path analysis focused on controlling variables in demographic characteristics in PLS-SEM using Smart PLS 3.0. Results: The researchers found the Satisfaction with COVID-19 Prevention Measures and the Awareness of Tourism Crisis affect Attitude toward Tourism of the residents with the explanatory power (R² = 0.209). Age was found to be the only significant controlling variable in this model for the Awareness of Tourism Crisis to Attitude toward Tourism. Conclusions: The attitude toward tourism is influenced by the level of satisfaction of the prevention service for COVID-19 as well as the awareness of the crisis. Residents have different level of the tourism crisis awareness by the status of their economic activities while there is no differences in all age groups for satisfaction in the quarantine service. The study suggests that the importance of the public health service should be preferentially concerned for residents to have stable economic activities where the tourism is the major industry.

• Information Systems Review
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• v.21 no.1
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• pp.113-133
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• 2019

Gentrification, caused by residents who are being forced out due to the rise of rent with vitalization by an excessive increase of city tourists and Touristification, meaning of phenomenon of residents' migration caused by residential area turning into tourist attraction have recently pointed out as a global problem. In Korea, the phenomenon such as environmental pollution, the rise of land value and rent, and the weakening of community culture in Jeju island and Bukchon Hanok Village has appeared as well. This phenomenon has become a serious problem by hindering resident's quality of life. In this circumstance, Smart tourism city has been regarded as a solution of these problems. Hence, this study chose Busan city, which has been designated as a smart city since 2015, and examined the complex impacts of the economic benefits, social costs, environmental substantiality, cultural benefits, and technical effects derived from tourism development on the residents' deteriorated quality of life based on Fuzzy-set Qualitative Analysis (fsQCA). As a result, three patterns of the hindrance to residents' quality of life were derived. If social costs of tourism development are perceived to be large, the residents perceive deteriorated quality of life, even if they recognize essential benefits (technological and economic benefits) (Pattern #1) or secondary benefits (environmental and cultural benefits) (Pattern #2) of tourism development. In addition, some residents were found not to recognize any benefits of tourism development (Pattern #3).

• Knowledge Management Research
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• v.17 no.1
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• pp.155-174
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• 2016

Recent years, a smartphone has been playing a role of searching, booking, and decision-makings in the tourism industry through tourists' user experiences and engagements. This study investigated the tourists' behavior toward smartphone usage regarding Chinese visitors who were ranked in Korea inbound tourism. This research model formulated two types of usage which identified explorlative use and exploitive use and the antecedent relationships of user empowerment including user competence, user impact, usage meaning, user trust. We analyzed SmartPLS2.0 for the hypotheses and found that first, user competence has a positive influence both of exploitative use and explorative use, second, user impact has a positive influence on exploitative use, but has not influenced on explorative use, third, usage meaning has not influence on exploitive use, but has a postitive influence on explorative use, and finally user trust has influence on both of exploitive and explorative use. Based on the results we found, we suggested Chinese tourists' smartphone usages' behaviors and theoretical and practical implications.

• The Journal of Information Systems
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• v.26 no.3
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• pp.273-293
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• 2017

Purpose The purpose of this study is to introduce a framework that helps Muslims to determine whether a food can be consumed. It can complement existing Halal food classification services having a difficulty of constructing Halal food database. Design/methodology/approach The proposed framework includes two components. First, OCR(Optical Character Recognition) technique is utilized to read the food additive information. Second, machine learning methods were used to trained and predicted to determine whether a food can be consumed using the provided information. Findings Among the compared machine learning methods, SVM(Support Vector Machine), DT(Decision Tree), and NB(Naive Bayes), SVM with linear kernel and DT had excellent performance in the Halal food classification. The framework which adopting the proposed framework will enhance the tourism experiences of Muslim tourists who consider keeping the Islamic law most importantly. Furthermore, it can eventually contribute to the enhancement of smart tourism ecosystem.

• Journal of Smart Tourism
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• v.1 no.1
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• pp.53-64
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• 2021

Upselling is often a critical factor in revenue generation for businesses in the tourism and travel industry. Utilizing passenger data from a major international airline company, we develop the PAX (Passenger, Airline, eXternal) model to predict passengers that are most likely to accept an upgrade offer from economy to premium. Formulating the problem as an extremely unbalanced, cost-sensitive, supervised binary classification, we predict if a customer will take an upgrade offer. We use a feature vector created from the historical data of 3 million passenger records from 2017 to 2019, in which passengers received approximately 635,000 upgrade offers worth more than $422,000,000 U.S. dollars. The model has an F1-score of 0.75, outperforming the airline's current rule-based approach. Findings have several practical applications, including identifying promising customers for upselling and minimizing the number of indiscriminate emails sent to customers. Accurately identifying the few customers who will react positively to upgrade offers is of paramount importance given the airline 'industry's razor-thin margins. Research results have significant real-world impacts because there is the potential to improve targeted upselling to customers in the airline and related industries.

• Journal of Smart Tourism
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• v.1 no.3
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• pp.7-16
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• 2021

Promotional videos have been increasingly adopted in social media marketing. Given that video production incurs high costs, evaluating the effectiveness of promotional videos is necessary. This research examines the effect of promotional video on visit intention through affective and cognitive destination images, respectively. Furthermore, grounded in the theoretical reasoning of social ties and persuasive intent, the effects of promotional videos disseminated by different sources (i.e., unknown users, friends, and marketers) are compared. Two experimental studies were carried out with 200 participants in Study 1 and 243 participants in Study 2. Study 1 revealed that the presence of promotional video induces visit intention through affective and cognitive destination images. Study 2 found that promotional videos disseminated by friends (versus unknown users) are more effective to induce visit intention because of positive cognitive destination image, while the video effects are indifferent between marketers and users. Meaningful implications are provided for destination marketers.