• Title/Summary/Keyword: Tourists

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Tourism policy establishment plan using geographic information system and big data analysis system -Focusing on major tourist attractions in Incheon Metropolitan City- (지리정보시스템과 빅데이터 분석 시스템을 활용한 관광 정책수립 방안 -인천광역시 주요 관광지 중심으로-)

  • Min, Kyoungjun;Lim, Heuiseok
    • Journal of the Korea Convergence Society
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    • v.12 no.8
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    • pp.13-21
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    • 2021
  • This study aims to analyze tourist inflow trends and consumption patterns using a geographic information system and big data analysis system. Songdo Central Park and Chinatown were selected among the major tourist destinations in Incheon, and floating population analysis and card sales analysis were conducted for one month in June 2017. The number of tourists visiting Songdo Central Park from metropolitan cities across the country was highest in the order of Incheon Metropolitan City, Gyeonggi-do, and Seoul Metropolitan City, and the proportion of foreign tourists was the highest in China. The number of card consumption used by Chinatown tourists was 12.4% higher for men than for women, and the amount of card consumption was also higher for men by 18%. This study has implications for proposing a strategic plan for tourism policy by analyzing the inflow trend and consumption pattern of tourists and deriving major issues in the establishment of tourism policy. Based on this study, it is expected that it can be helpful in improving the construction of tourism infrastructure in the future.

Sentiment Analysis and Star Rating Prediction Based on Big Data Analysis of Online Reviews of Foreign Tourists Visiting Korea (방한 관광객의 온라인 리뷰에 대한 빅데이터 분석 기반의 감성분석 및 평점 예측모형)

  • Hong, Taeho
    • Knowledge Management Research
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    • v.23 no.1
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    • pp.187-201
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    • 2022
  • Online reviews written by tourists provide important information for the management and operation of the tourism industry. The star rating of online reviews is a simple quantitative evaluation of a product or service, but it is difficult to reflect the sincere attitude of tourists. There is also an issue; the star rating and review content are not matched. In this study, a star rating prediction model based on online review content was proposed to solve the discrepancy problem. We compared the differences in star ratings and sentiment by continent through sentiment analysis on tourist attractions and hotels written by foreign tourists who visited Korea. Variables were selected through TF-IDF vectorization and sentiment analysis results. Logit, artificial neural network, and SVM(Support Vector Machine) were used for the classification model, and artificial neural network and SVR(Support Vector regression) were applied for the rating prediction model. The online review rating prediction model proposed in this study could solve inconsistency problems and also could be applied even if when there is no star rating.

Multi-dimensional Analysis and Prediction Model for Tourist Satisfaction

  • Shrestha, Deepanjal;Wenan, Tan;Gaudel, Bijay;Rajkarnikar, Neesha;Jeong, Seung Ryul
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.2
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    • pp.480-502
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    • 2022
  • This work assesses the degree of satisfaction tourists receive as final recipients in a tourism destination based on the fact that satisfied tourists can make a significant contribution to the growth and continuous improvement of a tourism business. The work considers Pokhara, the tourism capital of Nepal as a prefecture of study. A stratified sampling methodology with open-ended survey questions is used as a primary source of data for a sample size of 1019 for both international and domestic tourists. The data collected through a survey is processed using a data mining tool to perform multi-dimensional analysis to discover information patterns and visualize clusters. Further, supervised machine learning algorithms, kNN, Decision tree, Support vector machine, Random forest, Neural network, Naive Bayes, and Gradient boost are used to develop models for training and prediction purposes for the survey data. To find the best model for prediction purposes, different performance matrices are used to evaluate a model for performance, accuracy, and robustness. The best model is used in constructing a learning-enabled model for predicting tourists as satisfied, neutral, and unsatisfied visitors. This work is very important for tourism business personnel, government agencies, and tourism stakeholders to find information on tourist satisfaction and factors that influence it. Though this work was carried out for Pokhara city of Nepal, the study is equally relevant to any other tourism destination of similar nature.

Cross-Cultural Study of Tourism Shopping Behavior Based on Escaping-Seeking Theory - Focused on Korean, Chinese, and Japanese fashion consumers - (탈출-추구이론을 중심으로 본 관광쇼핑행동에 대한 비교문화연구 - 한국, 중국, 일본 소비자의 패션쇼핑을 중심으로 -)

  • Hee Jin Hur
    • Fashion & Textile Research Journal
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    • v.24 no.6
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    • pp.744-755
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    • 2022
  • This study sought to verify the shopping values that tourists pursue by purchasing at travel destinations based on tourists' motivation and identify the effects of these values on the types of fashion items preferred by tourists. Furthermore, this study verified the tourist shopping behavior of three Asian countries-Korea, China, and Japan-from a cross-cultural perspective. To obtain a sample that represents tourist shoppers in each country, a survey was conducted on adult men and women in their 20s to 60s, and 986 subjects were collected: 300 Koreans, 385 Chinese, and 301 Japanese. Factor analysis, structural equation modeling, and multigroup SEM were performed on the collected data using SPSS Statistics and AMOS. Based on escaping-seeking theory, tourist intentions were divided into escaping and seeking motivations, and tourist shopping values were divided into functional, emotional, and social. The shopping items were divided into materials and experiential goods to understand the difference between the types preferred by tourists according to the perceived value. In addition, differences in tourist shopping behaviors according to the three nationalities were identified. The findings illustrate that the escaping motive affects emotional and social values, whereas the seeking motive affects all three. Moreover, it was confirmed that functional and emotional values affect preference for material and experiential goods, but social value only affects preference for material goods. For the cross-cultural study, differences in tourist shopping behavior according to nationality were identified.

A Study on Artificial Intelligence Model for Forecasting Daily Demand of Tourists Using Domestic Foreign Visitors Immigration Data (국내 외래객 출입국 데이터를 활용한 관광객 일별 수요 예측 인공지능 모델 연구)

  • Kim, Dong-Keon;Kim, Donghee;Jang, Seungwoo;Shyn, Sung Kuk;Kim, Kwangsu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.35-37
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    • 2021
  • Analyzing and predicting foreign tourists' demand is a crucial research topic in the tourism industry because it profoundly influences establishing and planning tourism policies. Since foreign tourist data is influenced by various external factors, it has a characteristic that there are many subtle changes over time. Therefore, in recent years, research is being conducted to design a prediction model by reflecting various external factors such as economic variables to predict the demand for tourists inbound. However, the regression analysis model and the recurrent neural network model, mainly used for time series prediction, did not show good performance in time series prediction reflecting various variables. Therefore, we design a foreign tourist demand prediction model that complements these limitations using a convolutional neural network. In this paper, we propose a model that predicts foreign tourists' demand by designing a one-dimensional convolutional neural network that reflects foreign tourist data for the past ten years provided by the Korea Tourism Organization and additionally collected external factors as input variables.

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A Study on Behavioral Intention of Eco-tourists through the Extended Theory of Planned Behavior : Focused on Sustainable Intelligence as Moderate Variable (확장된 계획행동이론을 통한 생태관광객의 행동의도에 대한 연구: 조절변수로서의 지속가능지능을 중심으로)

  • Chai-hwan Ko
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.315-330
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    • 2023
  • The purpose of this study is to explain eco-tourists' behavioral intention based on exploring Extended Theory of Planned Behavior and Sustainable Intelligence as moderating variable. To do so, the survey was conducted on eco-tourists from Dongbaek-Dongsan wetland, Jeju-do between March. 12th and 30th, 2023. As a result, eco-tourists aged 50 years old and over, and from Jeju-do with their family members have more possibilities to visit Dongbaek-Dongsan wetland. Also, this study analyzed that independent variables including subjective norm, epistemic value, emotional value and attitude showed significant effects on behavioral intention. Further, sustainable intelligence as the moderating variable showed its moderation effects between independent variables including attitude and subjective norm, and behavioral intention as dependent variable.

Determinants of Satisfaction, Revisit Intention, and Recommendation Intention Using Decision Tree Analysis - Foreign Tourists Visiting Korea during the COVID-19 Pandemic - (의사결정나무분석을 활용한 방문 만족도, 재방문 의사, 타인 권유 의사 결정요인 분석 - 코로나19 상황에서의 한국 방문 외래관광객을 대상으로 -)

  • Won-Sik Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.129-136
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    • 2023
  • The study aims to examine the determinants that affect satisfaction, revisit intention, and recommendation intention with foreign tourists who visited Korea despite the threat of COVID-19. This study employs the survey data collected by the Korea Tourism Organization from 8,135 foreign tourists who visited Korea in 2020. As the survey data contains a mixture of continuous and categorical variables, decision tree analysis can ensure analytical validity for the research. According to the analytical results, the determinants affecting satisfaction are the purpose of the visit and acceptance of self-quarantine during their stay. The factors influencing revisit intention are the purpose of the visit, frequency of the visit, and acceptance of self-quarantine during their stay. The determinants affecting recommendation intention are the purpose of the visit, length of stay, and gender. Based on the results of this analysis, this study not only explains the relationship between these determinants and tourism satisfaction, revisit intention, and recommendation intention, but also suggests implications for revitalizing tourism activities.

The Effects of Local Agricultural/special Products on the Intention for Tourists to Revisit the Yesan Area (지역 농특산물에 대한 구매의사가 여행자의 재방문 의도에 미치는 영향 - 충남 예산지역을 중심으로 -)

  • Yoon, Hei-Ryeo
    • Journal of the Korean Society of Food Culture
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    • v.25 no.6
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    • pp.746-754
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    • 2010
  • Rural tourism is primarily a domestic tourism activity with visitors traveling to non-urban areas. The development of local and regionally denominate food is a way to distinguish agricultural production and to promote rural tourism. Therefore, this study addressed how utilizing regional agricultural products results in increasing the intention of tourists to revisit an area. The purposes of this study were 1) to identify the image and motives for visiting Yesan, 2) to determine the importance of purchasing intention and the regional menu produced from local agricultural/special products, and 3) to identify the impact of purchasing local agricultural/special products and regional menus on the intention to revisit. A total of 202 usable questionnaires were collected at Ducksan Hotsprings and Suduck Temple in Yean area, which are known tourist attractions. The major findings obtained were as follows: First, Yesan was considered a relaxing place ($3.46{\pm}1.09$), which was the highest ranked image score for a tourist attraction. Second, the highest ranked motive for visiting Yesan was to rest ($3.77{\pm}1.18$). According to these findings, Yesan is a relaxing place, as it is a rural area with no known defined attractions. Third, most tourists (78.7%) recognized the apple as a local agricultural/special product. The intentions to purchase local agricultural/special products and the need for regional dishes in the local restaurant was higher than average. Tourists showed interests ($3.88{\pm}1.16$) in eating regional dishes made with local agricultural/special products at the restaurants. Fourth, a significant impact of purchasing local agricultural/special products and the regional menu was observed on the intention to revisit (p<0.000). The results indicate that it is very important to develop proper regional menus that concur with images of the location and the regional farming products.

Development of Native Local Foods Associated with Regional Festival - Focused on Hampyeong "Butterfly Festival" - (지역 축제와 연계한 향토 음식 개발 방안 - 함평 "나비축제"를 중심으로 -)

  • Jang, Jeong-Oak;Yoon, Hae-Kyung;Lee, Young-Mi;Jung, Jae-Hong;Yang, Mi-Ok
    • Journal of the East Asian Society of Dietary Life
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    • v.18 no.4
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    • pp.428-435
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    • 2008
  • This study was conducted to provide the information necessary for the development of native local foods associated with the "2008 World Insect Festival in Hampyeong" and to contribute to the efforts to market the festival as tourist attraction and increase the income of the local community. To assess the local foods and restaurants, we investigated the principal products, inclination for sightseeing and recognition of the "Butterfly festival" by distributing questionnaires to local restaurant operators, employees and general tourists. The result was as follows: 1. The general tourists chose scenery as the most important factor in a sightseeing tour, followed by food, lodging, and transportation. 2. The tourists enjoyed eating native local foods, and they indicated that the taste was important. 3. Regarding the cost of food, 53.6% of the respondents answer that 10 to 20 thousand won was a resonable price, and they also reported wanting to eat seafood in Hampyeong. Thus the Menu of seafood to be served at the Hampyeong festival needs to be developed first followed by that of the healthy food. This result showed that individuals prefer fish to meat and healthy food to high-calorie foods.

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Key Factors Affecting Sustainable Tourism in the Region of South Central Coast of Vietnam

  • NGUYEN, Cong De;NGO, Thang Loi;DO, Ngoc My;NGUYEN, Ngoc Tien
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.12
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    • pp.977-993
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    • 2020
  • Sustainable tourism is the development of tourism activities to meet the current needs of tourists and indigenous peoples while paying attention to the conservation and improvement of resources for the development of tourism activities in the future (World Tourism Organization, 2013). With the aim of identifying factors affecting the development of sustainable tourism in the South Central Coast of Vietnam, the study conducted a typical survey of 160 tourism managers and 240 tourists traveling or have participated in tourism activities of 8 provinces in the South Central Coast of Vietnam, and used the exploratory factor analysis (EFA) analysis and regression analysis for analyzing the data. The research results show that 11 factors impact the development of sustainable tourism in the South Central Coast namely Institutions and policies for tourism development, Infrastructure, Tourism resources, Human resources for tourism, Diversity of tourism services, Relevant support services, Activities of association and cooperation for tourism development, Tourism promotion and encouragement, Tourists' satisfaction, Local community, and Other factors. At the same time, among the above factors, the factors Institutions and policies for tourism development, Infrastructure, Tourism resources, and Local community strongly impact the development of sustainable tourism in the region.