• Title/Summary/Keyword: International Tourist

Search Result 210, Processing Time 0.022 seconds

A Macro Analysis of Tourist Arrival in Nepal

  • PAUDEL, Tulsi;DHAKAL, Thakur;LI, Wen Ya;KIM, Yeong Gug
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.8 no.1
    • /
    • pp.207-215
    • /
    • 2021
  • The number of tourists visiting Nepal has shown rapid growth in recent years, and Nepal is expecting more tourist arrivals in the future. This paper, thus, attempts to analyze the tourist arrivals in Nepal and predict the number of visitors until 2025. This paper has examined the international tourist arrival trend in Nepal using the Gompertz and Logistic growth model. The international tourist arrival data from 1991 to 2018 is used to investigate international tourist arrival trends. The result of the analysis found that the Gompertz model performs a better fit than the Logistic model. The study further forecast the expected tourist arrival below one million (844,319) by 2025. Nevertheless, the government of Nepal has the goal of two million tourists in a year. The present study also discusses system dynamics scenarios for the two million potential visitors within a year. Scenario analysis shows that proper advertisement and positive word-of-mouth will be key factors in achieving a higher number of tourists. The current study could fill the gap of theoretical and empirical forecasting of tourist arrivals in the Nepalese tourism industry. Also, the study findings would be beneficial for government officers, planners and investors, and policy-makers in the Nepalese tourism industry.

A Study on Factors of T.I.C(tourist information center) in Seoul -Focus on Itaewon- (서울시 관광안내소(Tourist Information Center) 평가요소 연구 -이태원을 중심으로-)

  • Sung, Min-Ji;Kim, Seung-In
    • Journal of Digital Convergence
    • /
    • v.17 no.5
    • /
    • pp.347-351
    • /
    • 2019
  • The purpose of this study is to suggest the Assessment model for tourist information center in Seoul. As a research method, we analyzed international guideline and interview with tourism experts in order to rate the tourist centers in Seoul. Secondly, we renamed the international rating model to Itaewon information center as a typical landmark in Seoul. The assessment factors for T.I.C is assembled through researching of the centers' status in terms of overall service satisfaction. Via in - depth interview with 9 visitors, as a result, we were able to derive the possibility that new-designed rating model is able to be applied to the Tourist centers in Seoul. It is significant that this study suggests ways to improve domestic tourist center service. It is expected that the follow - up study will help improve the factors to Seoul T.I.C, not only Itaewon, with much more specific rating method.

A Study on the Improvement Elements of Tourism Preparedness for International Tourist Using Revised-IPA: Focusing on Comparison by Tourist Type and Time Period (R-IPA분석을 적용한 외래관광객의 관광수용태세 개선 요소 분석: 관광객 유형 및 시기별 비교를 중심으로)

  • Lee, Seung-Hun
    • Journal of Digital Convergence
    • /
    • v.16 no.6
    • /
    • pp.9-18
    • /
    • 2018
  • Recently, the necessity and interest to improve the tourism preparedness for enhancing the quality of foreign tourists is increasing, but the related research is insufficient. The purpose of this study is to identify the preferential improvement elements related to the tourism preparedness of foreign tourists. To do this, we applied the R-IPA analysis to analyze and compare the elements affecting the tourist preparedness according to tourist type and time period. As a result of R-IPA analysis for all tourists, the elements that need to maintain the current quality levels were food, security, transit, shopping, and tourist attractiveness and the elements that need to be improved but low priority were language communication, travel expenses, and tourist information service. As a result of R-IPA analysis by tourist type, for individual tourists it is necessary to maintain current quality levels of transit, food, shopping, tourist attractiveness, and security. For group tourists, it is necessary to maintain current quality levels of accommodation, shopping, tourist attractiveness, and tourist information service, but food needs to be urgent improvement.

A Study on Tourist Destinations Recommendation App by Medical Tourism Type Using User-Based Collaborative Filtering

  • Cai, Jin;Ryu, Gihwan
    • International Journal of Advanced Culture Technology
    • /
    • v.8 no.4
    • /
    • pp.255-262
    • /
    • 2020
  • Recently, medical tourism is recognized as a high value-added industry because of its longer period of stay and higher expenditure than general tourism. In particular, although the number of medical tourists visiting Korea is increasing, the perception of Korean medical services is low. The purpose of this paper is to develop the app which, based on medical tourism type, recommends tourism destinations. Additionally, this proposed app can expand general tourism as well. It can provide tourists with medical information easily by sorting types tourists. Besides, as medical tourists normally stay long, we can take the advantage of post-treatment time. This app collects medical information data and tourist destination data, and categorizes the types of medical tourists into four categories: disease medical tourism, traditional medical tourism, cosmetic medical tourism, and recreational medical tourism. It provides medical information according to each type and recommends customized tourist destinations. User-based collaborative filtering is applied for tourist destination recommendations.

The current state and prospects of travel business development under the COVID-19 pandemic

  • Tkachenko, Tetiana;Pryhara, Olha;Zatsepina, Nataly;Bryk, Stepan;Holubets, Iryna;Havryliuk, Alla
    • International Journal of Computer Science & Network Security
    • /
    • v.21 no.12spc
    • /
    • pp.664-674
    • /
    • 2021
  • The relevance of this scientific research is determined by the negative impact of the COVID-19 pandemic on the current trends and dynamics of world tourism development. This article aims to identify patterns of development of the modern tourist market, analysis of problems and prospects of development in the context of the COVID-19 pandemic. Materials and methods. General scientific methods and methods of research are used in the work: analysis, synthesis, comparison, analysis of statistical data. The analysis of the viewpoints of foreign and domestic authors on the research of the international tourist market allowed us to substantiate the actual directions of tourism development due to the influence of negative factors connected with the spread of a new coronavirus infection COVID-19. Economic-statistical, abstract-logical, and economic-mathematical methods of research were used during the process of study and data processing. Results. The analysis of the current state of the tourist market by world regions was carried out. It was found that tourism is one of the most affected sectors from COVID-19, as, by the end of 2020, the total number of tourist arrivals in the world decreased by 74% compared to the same period in 2019. The consequence of this decline was a loss of total global tourism revenues by the end of 2020, which equaled $1.3 trillion. 27% of all destinations are completely closed to international tourism. At the end of 2020, the economy of international tourism has shrunk by about 80%. In 2020 the world traveled 98 million fewer people (-83%) relative to the same period last year. Tourism was hit hardest by the pandemic in the Asia-Pacific region, where travel restrictions are as strict as possible. International arrivals in this region fell by 84% (300 million). The Middle East and Africa recorded declines of 75 and 70 percent. Despite a small and short-lived recovery in the summer of 2020, Europe lost 71% of the tourist flow, with the European continent recording the largest drop in absolute terms compared with 2019, 500 million. In North and South America, foreign arrivals declined. It is revealed that a significant decrease in tourist flows leads to a massive loss of jobs, a sharp decline in foreign exchange earnings and taxes, which limits the ability of states to support the tourism industry. Three possible scenarios of exit of the tourist industry from the crisis, reflecting the most probable changes of monthly tourist flows, are considered. The characteristics of respondents from Ukraine, Germany, and the USA and their attitude to travel depending on gender, age, education level, professional status, and monthly income are presented. About 57% of respondents from Ukraine, Poland, and the United States were planning a tourist trip in 2021. Note that people with higher or secondary education were more willing to plan such a trip. The results of the empirical study confirm that interest in domestic tourism has increased significantly in 2021. The regression model of dependence of the number of domestic tourist trips on the example of Ukraine with time tendency (t) and seasonal variations (Turˆt = 7288,498 - 20,58t - 410,88∑5) it forecast for 2020, which allows stabilizing the process of tourist trips after the pandemic to use this model to forecast for any country. Discussion. We should emphasize the seriousness of the COVID-19 pandemic and the fact that many experts and scientists believe in the long-term recovery of the tourism industry. In our opinion, the governments of the countries need to refocus on domestic tourism and deal with infrastructure development, search for new niches, formats, formation of new package deals in new - domestic - segment (new products' development (tourist routes, exhibitions, sightseeing programs, special rehabilitation programs after COVID) -19 in sanatoriums, etc.); creation of individual offers for different target audiences). Conclusions. Thus, the identified trends are associated with a decrease in the number of tourist flows, the negative impact of the pandemic on employment and income from tourism activities. International tourism needs two to four years before it returns to the level of 2019.

Tourism Service Quality and Tourism Product Availability on the Loyalty of International Tourists

  • RAHMIATI, Filda;OTHMAN, Norfaridatul Akmaliah;BAKRI, Mohammed Hariri;ISMAIL, Yunita;AMIN, Grace
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.7 no.12
    • /
    • pp.959-968
    • /
    • 2020
  • Tourist loyalty is created through good tourism service quality and the availability of tourism products. This study discussed the various attributes of tourism service quality, namely, tour agents, efficient personnel, accessible transportation, and information service quality. Whereas for tourism product availability attributes were varieties of product availability, wide selection of tour agents and tourist products, and wide variety of amenity services. As a general rule, the minimum is to have at least five times as many observations as the number of variables to be analyzed, and the more acceptable sample size would have a 10:1 ratio. A total of 424 questionnaires were returned, with 35 removed due to errors. Finally, 389 questionnaires respondents were used via accidental sampling method through the distribution of questionnaires to foreign tourists at Soekarno Hatta International Airport. In addition, AMOS 7.0 software is used to test models in confirmatory factor analysis (CFA) as well as hypothetical testing using structural equation modeling (SEM). The results showed that all hypotheses were accepted, except for the effect of tourism service quality on tourist loyalty in Indonesia. This research aims to contribute significantly to the existing knowledge of tourism, specifically from a foreign tourist perspective in Indonesia.

The Influence of SNS Characteristics on Tourist Attractions Preference : Focus on China

  • Yu, Wang;Lee, Jong-Ho;Kim, Hwa-Kyung
    • Journal of Distribution Science
    • /
    • v.12 no.9
    • /
    • pp.53-63
    • /
    • 2014
  • Purpose - The rapid spread of SNS and increase of SNS users have heralded great changes in the tourism industry. Therefore, this study focused on how SNS characteristics- usefulness, convenience, interactivity, and intimacy - influence diffusivity, reliability and, consequently, user's preference for tourist attractions. Research design, data, and methodology - This study is designed not only to collect data with a questionnaire survey but also to test hypotheses with SEM by SPSS 18.0 and AMOS 18.0. Results - Usefulness, interactivity, and intimacy positively affect diffusivity, whereas convenience does not positively affect diffusivity. In addition, intimacy has a negative influence on reliability. However, diffusivity and reliability have positive impacts on the preference for tourist places. Conclusions - Certain characteristics of SNS facilitates the spreading of SNS tourist information. Usability and interactivity have positive impacts on the reliance of tourist information. Better communication can enhance the reliance of travel information. The influence of spreading tourist information has a positive influence on its reliance. Extension and reliance can have positive effects on the preference for tourist attractions.

Deep Learning-based Tourism Recommendation System using Social Network Analysis

  • Jeong, Chi-Seo;Ryu, Ki-Hwan;Lee, Jong-Yong;Jung, Kye-Dong
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.12 no.2
    • /
    • pp.113-119
    • /
    • 2020
  • Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.

Determinants of BAOMAI of Chinese Customer in Duty-Free Shop: Analytical Framework and Empirical Analysis (중국관광객의 면세점 바오마이 결정요인에 대한 실증연구)

  • Sung-Hoon Lim;Song Gao;Jia-Ying Chen
    • Korea Trade Review
    • /
    • v.45 no.5
    • /
    • pp.201-222
    • /
    • 2020
  • This paper examines that determinants of BAOMAI, (i.e., behavior of Chinese tourist bulk purchase in duty free shop) with analytical framework and empirical tests. The results of applying the structural equation modeling to 196 samples suggest that Chinese tourist consumption orientations (conspicuous/compulsive/unplanned consumption) have a positive effect on BAOMAI decision value chain (perceived value and loyalty). The marketing mix of duty free shop as control variables in research framework also have a positive effect on BAOMAI perceived values (functional/social/emotional value). This paper has a contribution to prior literatures: the first empirical analysis on BAOMAI determinants with exploring scholarly definition.

AR Tourism Recommendation System Based on Character-Based Tourism Preference Using Big Data

  • Kim, In-Seon;Jeong, Chi-Seo;Jung, Tae-Won;Kang, Jin-Kyu;Jung, Kye-Dong
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.13 no.1
    • /
    • pp.61-68
    • /
    • 2021
  • The development of the fourth industry has enabled users to quickly share a lot of data online. We can analyze big data on information about tourist attractions and users' experiences and opinions using artificial intelligence. It can also analyze the association between characteristics of users and types of tourism. This paper analyzes individual characteristics, recommends customized tourist sites and proposes a system to provide the sacred texts of recommended tourist sites as AR services. The system uses machine learning to analyze the relationship between personality type and tourism type preference. Based on this, it recommends tourist attractions according to the gender and personality types of users. When the user finishes selecting a tourist destination from the recommendation list, it visualizes the information of the selected tourist destination with AR.