• Information Systems Review
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• v.25 no.1
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• pp.145-164
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• 2023

The proliferation of online reviews on dining experiences has significantly affected consumers' choices of restaurants, especially overseas. Food quality, service, ambiance, and price have been identified as specific attributes for the choice of a restaurant in prior studies. In addition to these four representative attributes, cultural factors, which may also significantly impact the choice of a restaurant for tourists, in particular, have not received much attention in previous studies. This study employs the text mining technique to analyze over 10,000 online reviews of 76 Korean restaurants posted by Chinese tourists on dianping.com to explore the influence of cultural factors on the consumer's choice of restaurants in the overseas travel context. The findings reveal that "Hallyu (Korean Wave)" influences Chinese tourists' dining experiences in Korea and their satisfaction. Moreover, Korean food-related words, such as cold noodle, bibimbap, rice cake, pig trotters, and kimchi stew, appeared across all the review topics. Our findings contribute to the existing tourism and hospitality literature by identifying the critical role of cultural factors on consumers', especially tourists', satisfaction with the choice of a restaurant using text mining. The findings also provide practical guidance to restaurant owners in Korea to attract more Chinese tourists.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.93-101
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• 2017

This study investigate the effect of each type of search volume on the number of Facebook fans and the number of tourists. According to the hierarchy effect model, the effect of communication appears to be the sequentiality of cognition-attitude-behavior. Applying this theory, this study predicted that when consumers who have higher involvement and knowledge on specific cities through search behavior, they will be more active in information search through Facebook fan page subscription and will lead to direct tourism behavior. To verify the prediction, we examined the influences among search volume of Seoul shown in Google Trend, the number of fans of official facebook page named 'Seoul Korea', and the number of foreign tourists. As a result, the type of search keyword was divided into four categories: tourism attraction keyword, natural environment keyword, symbolic keyword, and accessibility keyword. The regression analysis showed that tourism attraction keyword and symbolic keyword have influence on Facebook fanpage 'Like'. In addition, facebook fanpage fan size have mediation effect between search volume and number of tourists. All in all, it would be useful to appeal to foreign tourists with a message that emphasizes tourism attraction and Korea-related contents.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.577-582
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• 2021

This study was conducted to find ways to restore the domestic medical tourism industry, which was seriously hit by a sharp drop in foreign patients after the COVID-19 Pandemic. Kendall's W verification was used by asking expert panel for keyword advice by ranking. The conclusion of the study is that institutions attracting foreign patients need an opportunity to turn the crisis situation into an opportunity by expanding treatment for severe foreign patients. In addition, it is possible to gain familiarity and trust in hospitals in situations where it is difficult to visit overseas through virtual and augmented reality, and to prevent the risk of infection and protect patients in the untact era. In addition, the blockchain can maintain patient information supplementation, share it safely, minimize customer inconvenience by using payment means using virtual currency, and finally, smart healthcare can manage and provide information to patients regardless of location.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.87-96
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• 2023

ChatGPT, a leader in generative AI, can use natural expressions like humans based on large-scale language models (LLM). The ability to grasp the context of the language and provide more specific answers by algorithms is excellent. It also has high-quality conversation capabilities that have significantly developed from past Chatbot services to the level of human conversation. In addition, it is expected to change the operation method of the tourism industry and improve the service by utilizing ChatGPT, a generative AI in the tourism sector. This study was conducted to explore ChatGPT trends and paradigms in tourism. The results of the study are as follows. First, keywords such as tourism, utilization, creation, technology, service, travel, holding, education, development, news, digital, future, and chatbot were widespread. Second, unlike other keywords, service, education, and Mokpo City data confirmed the results of a high degree of centrality. Third, due to CONCOR analysis, eight keyword clusters highly relevant to ChatGPT in the tourism sector emerged.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.2
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• pp.37-47
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• 2024

The food tech market, which uses artificial intelligence robots for the restaurant industry, is gradually expanding. Among them, the robot barista, a representative food tech case for the restaurant industry, is characterized by increasing the efficiency of operators and providing things for visitors to see and enjoy through a 24-hour unmanned operation. This research was conducted through text mining analysis to examine trends related to robot baristas in the restaurant industry. The research results are as follows. First, keywords such as coffee, cafe, certification, ordering, taste, interest, people, robot cafe, coffee barista expert, free, course, unmanned, and wine sommelier were highly frequent. Second, time, variety, possibility, people, process, operation, service, and thought showed high closeness centrality. Third, as a result of CONCOR analysis, a total of 5 keyword clusters with high relevance to the restaurant industry were formed. In order to activate robot barista in the future, it is necessary to pay more attention to functional development that can strengthen its functions and features, as well as online promotion through various events and SNS in the robot barista cafe.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.373-380
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• 2013

Recently, AR(Augmented Reality) system as an information technology for the increased access of information has a potential possibility of next generation's system for tourism guide. In this regard, the objective of this study is to explore the technology acceptance factors of AR system on tourism destination. To achieve the objective of this study, logit regression model was used to analyze the influential level of the factors. This study was analyzed with the final 224 respondents and the results showed that if there will be assured with high trust and easy access via mobility device as smartphone, the AR system has the possibility of high acceptance level. The result of this study will be expected to be utilized as fundamental data from the viewpoint of the service providers and system developers that want to launch the appropriate service to users' needs of AR system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.103-107
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• 2010

게임이나 네비게이션 시스템, 관광경로 설계에 있어서 경로찾기는 매우 중요한 부분 중의 하나이다. 일반적으로 TSP(Traveling Salesman Problem), RPP(Rural Postman Problem), CPP(Chinese Postman Problem)와 같은 경로찾기 문제들은 일반적인 알고리즘으로 최적해를 구할 수 없다. 문제크기가 커질수록 해집합이 폭발적으로 커짐으로써 전체 해집합을 탐색하는데 많은 비용이 든다. 따라서, 이러한 문제들은 유전알고리즘이나 Simulated Annealing과 같은 휴리스틱 알고리즘을 이용하여 근사최적 경로를 찾는다. 본 논문에서는 이와 같은 경로찾기 문제의 근사 최적해를 구하기 위한 시뮬레이션 시스템을 설계하고 구현하였다. 본 연구에서 구현한 시뮬레이션 시스템에는 유전알고리즘 엔진(GA 엔진)과 사용자 인터페이스를 제공한다. 사용자 인터페이스는 유전알고리즘에 사용될 파라미터를 설정하는 부분이며, GA 엔진은 유전알고리즘의 연산자들을 제공하는 부분이다. 본 논문에서 구현한 시뮬레이션 시스템은 게임과 같은 경로찾기 등에 활용될 수 있다.

• Proceedings of the Korea Association of Information Systems Conference
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• 2004.11a
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• pp.57-66
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• 2004

인터넷의 발전과 더불어 날고 치열해 지는 경쟁 속에서 관광산업 웹사이트들의 생존 전략은 Reichheld(1993)의 연구결과처럼 고객 충성도의 유지를 통한 경쟁적 우위를 점하는 것이다. 인터넷을 이용함으로써 소비자는 교체비용의 감소, 탐색비용의 절감이 가능해짐(Bakos, 1997; Strader 등, 1997)에 따라 웹사이트에 대한 충성도 역시 현격히 낮아지게 된다. 왜냐하면 오프라인에서는 이동이 불편하고 힘들지만 인터넷상의 거래에서는 마우스 클릭만으로 간단하게 이뤄지기 때문이다. 국내 인터넷업체가 많은 고객을 끌어 모으는 반면 수익성 문제가 사라지지 않는 원인 중 하나는 이처럼 낮아진 고객 충성도에서 찾을 수 있다 (안준모 등, 2001). 오랜 기간에 걸쳐 지속적으로 거래할 가능성이 높은 고객확보는(Reichheld, 1993) 곧 기업의 성공과 연관되며, 이는 기업이 충성도를 중시해야 할 이유일 것이다. 따라서 본 연구는 인터넷 쇼핑몰 웹사이트의 환경특성에 따른 사용자의 만족, 신뢰, 몰입 등의 매개변수를 고려하여 최종적으로 사용자의 충성도를 분석하고자 한다. 쇼핑몰에서 충성도(loyalty)의 문제가 매우 중요한 것으로 파악되고 있다. 하지만, 기존 연구들에서는 관계몰입을 중심으로 한 연구는 별로 눈에 띄지 않고 있다. 따라서 관계몰입을 중심으로 한 종합적 인터넷 쇼핑몰의 연구모형의 제시와 검증은 매우 필요한 연구과제라 할 수가 있을 것이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.396-397
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• 2023

추천 시스템은 빅데이터 관련 기술과 알고리즘의 발달로 다양한 분야에서 사용되고 있다. 관광 산업도 예외는 아니다. 본 연구에서는 사용자들이 촬영한 사진을 기반으로 유사한 여행지를 추천하는 추천 시스템을 제안한다. 사용자가 입력한 이미지에서 언어적 특성과 비언어적 특성을 추출하고 이를 기반으로 유사한 이미지를 탐색하고, 이를 기반으로 사용자가 좋아할 다음 여행지를 추천한다. 사용자가 질의어를 입력하지 않고 이미지를 제공하여 추천이 이루어진다는 점과 사용자의실제 여행 여부를 이용해 모델의 성능을 평가했다는 점에서 연구의 의의가 있다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.117-125
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• 2022

Recently, as users' interest for travel increases, research on a travel route recommendation service that replaces the cumbersome task of planning a travel itinerary with automatic scheduling has been actively conducted. The most important and common goal of the itinerary recommendations is to provide the shortest route including popular tour spots near the travel destination. A number of existing studies focused on providing personalized travel schedules, where there was a problem that a survey was required when there were no travel route histories or SNS reviews of users. In addition, implementation issues that need to be considered when calculating the shortest path were not clearly pointed out. Regarding this, this paper presents a quantified method to find out popular tourist destinations using social big data, and discusses problems that may occur when applying the shortest path algorithm and a heuristic algorithm to solve it. To verify the proposed method, 63,000 places information was collected from the Gyeongnam province and big data analysis was performed for the places, and it was confirmed through experiments that the proposed heuristic scheduling algorithm can provide a timely response over the real data.