Online Tourism Research Articles

한국관광공사 1330 관광안내 문자채팅 서비스에 대한 연구

The 1330 Korea Travel Helpline is a public service that provides tourists with customized travel information in order to promote tourism. 1330 Travel Helpline differs from other online tourism information platforms in that users can interact with certified tourism specialists throughout their journey. Furthermore, the service is run by the Korea Tourism Organization. Taking these distinguishing characteristics into account, the purpose of this study is to investigate the factors influencing the service user's information processing process and the tourist's destination visit intention. This study specifically employs the Elaboration Likelihood Model to examine the impact of information quality and source credibility on destination visit intention. Furthermore, using data collected from tourists who have used this service, this paper investigates whether the interaction quality with service representatives acts as a predictor of visit intention. The PLS-SEM approach reveals that interaction with service representatives gives users a social presence, which influences their information processing path positively. Information usefulness and visit intent are significantly influenced by information quality and source credibility. In addition, the research demonstrates that the interaction quality has a mediating effect on both of the central and the peripheral paths. The findings contribute to a better understanding of the live chat service in the context of the hospitality and tourism industries, as well as suggestions for future research.

Selling mode choice and information sharing in an online tourism supply chain under channel competition

Selling mode choice and information sharing in an online tourism supply chain under channel competition

THE CHALLENGE OF LEARNING TOURISM ONLINE DURING A PANDEMIC: STUDENTS’ VIEWPOINT

The impact of the COVID-19 outbreak has caused every college and school to stop offline learning activities. For one year, online tourism learning has become a learning option, as well as a new challenge for students and lecturers. This study aims to find out the problems and challenges faced by students during online tourism learning during the pandemic. Respondents from this study were 67 students who took tourism courses. The results showed that students experienced a number of difficulties during online learning such as signal difficulties, lack of motivation to study, difficulty concentrating, and difficulties in practicing tour guiding online. The positive sides of online learning include; unlimited distance, prevent the transmission of the covid-19 virus, no need to meet in person. Overall, students prefer offline tourism learning compared to online learning due to the difficulties they face during the implementation of online learning. It is hoped that lecturers can convey interesting methods and techniques in online tourism teaching to boost student motivation and performance to study tourism in this pandemic situation.

Development Trends and Potential in the Field of Virtual Tourism after the COVID-19 Pandemic: Generation Z Example

Until the outbreak of the COVID-19 pandemic, virtual tourism was not as popular as during its duration in 2021, when traveling in the real world was not possible due to social isolation and forced quarantine. In response to the lockdown and the lack of freedom of movement around the world, tourists decided to travel in cyberspace during the COVID-19 pandemic. In this way only, and without leaving home, could they visit tourist attractions, watch museum exhibitions, participate in various media events and take virtual walks. After the “unfreezing” of tourism, the time has now come to adapt tourism to the post-pandemic normality. The aim of the paper is to discover whether the new trend of online tourism that developed during the pandemic will stay with us forever and how it will evolve, especially for Generation Z, who are just entering the labor market but who, at the same time, will determine the future of tourism soon. The research results show that as the pandemic restrictions disappear, the need to experience various forms of tourism in places previously viewed in cyberspace (virtually), occurs among the representatives of Generation Z. Thus, virtual tourism is a form that precedes and complements a real journey. The qualitative method was chosen for the research conducted in Poland. The research was carried out in 2022. A total of 40 focus groups of 7 people each (N = 280) participated in the research. They consisted of Generation Z representatives born after 1995; the oldest of them will be 27 in 2022. In parallel, the method of in-depth individual interviews was used in the research. In order to reach the participants, a non-random sample was chosen using the “snowball” method. In total, 100 people took part in the in-depth individual interview. The two-track research allowed to obtain a total sample of N = 380.

FEATURES OF DIGITALIZATION IN THE PROCESS OF PROFESSIONAL TRAINING OF SPECIALISTS IN THE TOURISM INDUSTRY

The article analyzes the features of digitization in the process of professional training of future specialists in the tourism industry in higher education institutions. It is summarized that digitization in higher education is important for teaching and studying the features of the functioning of the tourism industry, which will ensure the competitiveness of graduates for the tourism industry. It is found out that the forms of teaching used in the process of professional training of future specialists in the tourism industry in institutions of higher education should be integrated with the needs of tourism organizations and aimed at generating innovative digital ideas, where any person in the organization can propose new production methods for implementation processes or apply new technologies so that the business creates additional material values and services that will allow to obtain profits, as well as to have a favorable competitive position in the market. Emphasis is placed on the fact that one of the forms of training specialists of the specialty tourism in higher education institutions is the use of non-formal education opportunities, including online tourism courses, internships, practical courses in hotels, and educational (excursion) trips. Real-time hands-on research and learning have been found to help students better understand «real-life» tourism situations and issues. In the article, we have summarized the ways of digitalization of professional training of future specialists in the tourism industry, which can be used by higher education institutions today. Digitalization in the process of professional training of future specialists in the field of tourism is due to the development of scientific and technical progress and active digitalization of the field of tourism. Active digitization of the educational process allows the use of digital technologies and at the same time the use of blended learning, which is a challenge for teachers and students. Therefore, taking into account the increased requirements for specialists in the field of tourism, in the educational process of professional training in higher education institutions, digital competences should be formed.

Opinion Mining from Online Travel Reviews: An Exploratory Investigation on Pakistan Major Online Travel Services Using Natural Language Processing

Online tourism evaluations are a valuable origin of data for traveler organizations, defining as they could be excellently recognized critically prompting traveler opinion-designing using opinion mining. As technology advanced, online review forums of any organization become an attractive source of communication with them, where people can share their views in the form of comments. The main determination of this research article is to recognize normal topics and connect them to contrasts in web-based travel reviews. Online millions of reviews, got from two significant web-based travel organizations (Uber, and Careem) in Pakistan, and a semantic affiliation examination was utilized to extract thematic words and construct a semantic affiliation organization. In the Python programming language, we use natural language processing (NLP), which includes data cleansing and tokenization. The results of network visualization are able to evidently recognize main topics and thematic words with social network associations. The proposed logical system extends our grip on the strategic complications and gives new points of view on the best way to dig popular assessments to assist vacationers, inns, and travel industry organizations.

The Role Of Online Tourist Communication In The Promotion Of Medical Tourism: Study With A Sample Of Algerian Tourists Who Have Chosen Tunisia As A Treatment Destination

The Role Of Online Tourist Communication In The Promotion Of Medical Tourism: Study With A Sample Of Algerian Tourists Who Have Chosen Tunisia As A Treatment Destination

Pemanfaatan Teknologi : Strategi Promosi Potensi Desa Melalui Blog Desa

Efforts to achieve independent welfare for rural communities are closely related to the development of existing village potential. Medium Micro Small Enterprises (MSMEs) and tourism are one of the fastest growing village potentials and contribute to the progress of the village economy. MSMEs in Bekulap Village have the potential to be marketed to a larger segment. However, as the obstacles faced by business actors in general, namely knowledge and management of digital technology which are still not well controlled by MSME actors, lack of capital for business development and others. This activity aims to introduce and promote Bekulap Village outside the region, especially knowing the various economic potentials of Bekulap Village such as MSMEs and online tourism. The methods used are presentations, outreach and case studies. The results of this activity provide public understanding about the importance of using and utilizing digital technology in marketing MSME products which can be increased by conducting education/socialization on the use of blogs.

Business Development Analysis Of Online Travel Enterprises Under The New Trend - Using Ctrip As An Example

The COVID-19 pandemic has had a systemic negative impact on China's economy and social development. Tourism industry has been hit hard. The capital chain of many small and medium-sized enterprises has been broken, and some have even gone bankrupt. Of course, some companies have successfully transformed themselves in the process. But on the other hand, this public health emergency has provided new opportunities for major online travel companies to solve the problems of stagnation in the tourism industry and open up new areas under the new trend of the epidemic. Therefore, taking Ctrip as an example, this paper first analyzes Ctrip's online tourism business, and then analyzes Ctrip's competitive advantages and existing problems in the market. Finally, this paper puts forward some suggestions for the existing problems of the company, hoping that Ctrip can establish a more diversified enterprise system in the future and become more competitive in the same type of enterprises.

A New Trend of Tourism in the Post-COVID-19 Era: Big Data Analysis of Online Tours in Korea

In this study, big data analysis on Korea’s “online tour”, which emerged as an alternative to satisfy tourism needs after COVID-19, was conducted. After extracting keywords through text mining for 24,073 posts from the top three most frequently visited social media platforms, Naver, Daum, and Google, to gather tour information in Korea, frequency analysis and TF-IDF analysis were run. In addition, network analyses, such as centrality and convergence of iteration correlation (CONCOR) analyses, were performed. The results showed: First, the sense of presence via local live streaming is crucial. It is vital to prepare a suitable video environment where tourists can immerse themselves in the tour. Second, the interaction between travel agencies, local guides, and tourists is important because it can expand tourists’ travel experiences. Third, the importance of online tour program content was revealed. It is necessary to increase the demand by designing various programs tailored to the audience. Fourth, new possibilities for local travel that had been neglected were uncovered. Fifth, the importance of online tourism production support was highlighted. The role of the government must be expanded to reinforce the digital capabilities of small- and medium-sized enterprises (SMEs) and to create jobs. Although the scope of this study is limited to Korea, it can definitely be used as a regional strategy.

Influence of the Covid‐19 Pandemic on the Development of Tourism and Measures of Creating Sustainable Tourism in Uzbekistan

Abstract The Covid‐19 pandemic plunged the whole world into a protracted economic crisis, dealing a significant blow to all branches of human activity. Some areas have suffered serious losses, in particular, the tourism industry. This article discusses measures to restore and strengthen the tourism and hospitality sector after the pandemic in the Republic of Uzbekistan. A Safe Tourism program has been developed in the Republic of Uzbekistan; tourists will use tourist services, follow the sanitary and hygienic rules during trips. This project will provide travelling individually, choosing a destination and booking what they need during travelling online. The purpose of the article is to analyse the situation in the world and Uzbekistan as well, during the pandemic, as well as to develop practical measures to rehabilitate the tourism sector from the consequences of the economic crisis associated with the pandemic. New offers are being considered in the tourism market to attract tourists to our country. The primary attention in the paper is focused on the development of electronic platforms for the formation of "online tourism", architectural sights and monuments combining the history of different peoples and religious denominations. The article also provides information about alternative medicine, and lists of several of treatment methods used by our ancestors and actual nowadays. The report summarizes some of the study results, concluding that the tourism business of Uzbekistan needs to radically rethink existing business models through innovation and digitalization of tourism. Examples of the development of such market segments as agro and eco‐tourism are given. This segments are currently beginning to develop and are of interest to tourists. It is mentioned that Uzbekistan is among the top 10 countries in terms of security.

Automating tourism online reviews: a neural network based aspect-oriented sentiment classification

自动化旅游在线评论：基于神经网络的面向方面的情感分类研究目的本文旨在从方面级对在线旅游-酒店评论的情感进行分类。提出了一种基于神经网络模型的面向方面的情感分类新方法。研究设计/方法/途径本研究使用集成的四层神经网络构建面向方面的情感分类模型：BERT 词向量模型、LSTM、IAOA 机制和线性输出层。该模型在一个开放的训练数据集和从东京餐厅推断的 92,905 条评论上进行了训练、测试和验证。研究发现与其他神经网络相比, 该模型实现了显着更好的性能。研究结果提供了经验证据, 以验证这种新方法在旅游酒店领域的适用性。研究原创性该研究提供了有关神经网络如何提高旅游酒店在线评论的面向方面的情感分类性能的新文献。研究研究局限应该识别更多的情感从而来更加细化衡量旅游酒店体验, 并推荐新的方面/维度可以被自动添加到方面集中, 为新的用餐体验提供动态支持。

Exploring the effect of the knowledge redundancy of online reviews on tourism consumer purchase behaviour: based on the knowledge network perspective

ABSTRACT Online reviews often contain considerable information redundancy. Understanding how to mine and identify valuable information is an important research topic. Based on knowledge-based theory and social network theory, this study discusses the impact of knowledge redundancy in online travel reviews on consumer purchase behaviour from the perspective of knowledge networks. By crawling 943,516 online reviews of 609 tourism products from Trip and Tuniu, we conduct an empirical analysis of the relationships among knowledge redundancy, knowledge diversity and consumer purchase behaviour. The results show that there is a U-shaped relationship between knowledge redundancy in online tourism reviews and consumer purchase behaviour, and knowledge diversity plays an intermediary role in the relationship between knowledge redundancy and consumer purchase behaviour. The results provide valuable and timely insights for the development of the online tourism industry.

Heritage tourism evolution in Guangfu Ancient City, Hebei Province, China: an analysis with the improved creative destruction model

Ancient cities and towns are popular tourism destinations worldwide. In this paper, Guangfu Ancient City in Yongnian County, Hebei Province, China, is taken as the case study and the modified creative destruction model is applied as the analytical framework to evaluate the multiactor dynamics of heritage tourism development. A mixed method approach is adopted, including a local resident survey, in-depth interviews with staff of the Guangfu Ancient City tourism site and government officials responsible for the heritage conservation and tourism development of the site, and a review of online tourist reviews, relevant government documents and reports. Based on the modified creative destruction model, local residents’ attitudes towards tourism development, changes in tourist numbers, the level of business and government investments, and the motivations of different stakeholders in tourism development are assessed by synthesising on-site research, historical data and other materials. Then, the tourism development stages for Guangfu Ancient City are identified as the precommodification stage before 2006, the early commodification stage from 2006 to 2011 and the advanced commodification stage from 2012 to 2017. The findings indicate that with rapid increases in investments from both corporate and government sources and in the number of tourists, the attitude of local residents towards tourism development remained positive. The results show that instead of entering the initial destruction stage, Guangfu Ancient City is in the transition stage from advanced commodification to creative enhancement given the government’s dominant role in tourism development, the heritage conservation motives of tourism entrepreneurs, the benefits to residents from tourism development ensured by government policies, and the shift in tourist type to postmodern tourists with double demands. The applicability of the modified creative destruction model is further discussed, and policy and management recommendations are generated to support the sustainable development of Guangfu Ancient City after the COVID-19 pandemic.

On the Integrated and Innovative Development of "Internet+Online Tourism" under Demand Orientation Taking the Development of Tourism in Yunnan as an Example

The rapid development of Internet technology in today's era has provided more possibilities for the transformation, upgrading and in-depth development of all walks of life. In the face of the large-scale spread of new domestic and international epidemics, most traditional industries have encountered difficulties in their development. This paper focuses on the development of China's tourism industry, taking Yunnan Province of China as the exploration direction, starting from the analysis of the integration of tourism and Internet technology in Yunnan, and the possibility of promoting its online tourism development, points out its current shortcomings, and puts forward the development countermeasures of its online tourism, so as to boost the development of new forms of tourism in Yunnan and the deep transformation and integration of Internet technology.

Clustering using ordered weighted averaging operator and 2-tuple linguistic model for hotel segmentation: The case of TripAdvisor

With the growth of online tourism, it is important to analyze the reviews left by numerous customers on social networks to improve the hotel's online reputation. Hotel segmentation based on online reviews has attracted an increasing interest from many academics. The problem is that many hotel segmentation models overlook the fact that some customers focus on positive reviews when choosing a hotel, while others focus on negative ones. To address this shortcoming, this paper develops a novel approach to classify hotels using the ordered weighted averaging (OWA) operator, the 2-tuple linguistic model, and K-means clustering. The proposed approach has been evaluated with a real dataset from TripAdvisor, which contains more than 50 million customer online reviews on eight aspects of the hotel. The results show that the proposed model can produce denser and more separated clusters than the model without linguistic quantifiers. From a business point of view, this model enables hotels to distinguish customers' perceptions (from the less demanding to the most demanding) about their eight aspects, allowing them to specify which of them need to be improved and develop strategies more quickly. At the same time, it introduces a new way of ranking hotels online, allowing customers to create personalized rankings of hotels based on their degree of demand for various hotel aspects (better location, cleaner rooms, etc.) rather than the average ratings, so that they can select the most suitable hotels more quickly.

The role of psychological safety in online tourism and hospitality learning

This study proposes and tests a conceptual framework to examine how tourism and hospitality students’ psychological safety and personal resourcefulness in online learning reach their tourism and hospitality threshold learning outcomes. This research develops a conceptual framework integrating the conservation of resources and social information processing theories and the findings of a qualitative study through a sequential mixed-methods approach. Subsequently, the model is tested with online survey data using a structural equation modelling technique. The results suggest that, for psychological safety, students’ computer self-efficacy and peer collaboration significantly affect overall students’ perceived graduate outcomes, whereas lecturer support has no significant impact. Further analysis of the results, along with theoretical and practical implications, are likewise discussed.

Research on the Relationship Between Attitude and Intention for the Development Sharing Economy Model of E-Tourism Enterprises in Vietnam

The study aims to explore the relationship between the attitude and the intention to develop the sharing economy model of enterprises in the field of online travel services in Vietnam. Based on using the method of interviewing experts and processing, analyzing, and evaluating the results of the investigation and survey of 263 enterprises (notified and registered with the Ministry of Industry and Trade of Vietnam under Decree 52/ND-CP) or foreign enterprises with representative offices/authorized agents in Vietnam), research shows perceived benefits of the sharing economy model, state support, willingness to of enterprises, market readiness is related to the development attitude and intention to develop the sharing economy model of enterprises. In addition, the authors used multi-group structural analysis among business types to assess the differences of business types towards the intention and attitude of developing the sharing economy model. such as the difference in the impact of variables in the research model between types of businesses in the field of online tourism services in Vietnam. From these results, the study implies several policies to develop the sharing economy model of enterprises in the field of online tourism services in Vietnam, as well as proposes further research directions as follows: develop a sharing economy model suitable to the scale and application of e-commerce and each type of business in the field of online tourism in Vietnam.

Optimization of Digital Recommendation Service System for Tourist Attractions Based on Personalized Recommendation Algorithm

With the deepening of tourists’ demand for tourism services, the personalization of online tourists has gradually become an application of personalized recommendation technology. According to the application requirements of personalized scenic spot recommendation, this paper uses social networks and Bayesian networks to fully mine the matching degree between users and scenic spots for personalized recommendation. Add social network factors to the recommendation of tourist attractions, and fully tap the social network relationship between users. First, the users are clustered by the coupling bidirectional clustering algorithm. Then, DBSCAN (density-based noise application spatial clustering) algorithm is used to cluster scenic spots. Finally, two stable user sets and scenic spot sets are applied to the personalized recommendation algorithm to predict the user’s next upcoming scenic spot. The algorithm is compared with some traditional algorithms in the dataset. The algorithm deals with the similarity of user attributes and user behavior and uses content-based algorithm to deal with the relationship between scenic spots; com datasets have better performance.

Sentiment Classification of Educational Tourism Reviews Based on Parallel CNN and LSTM with Attention Mechanism

With the rapid development of the Internet and tourism, the Internet has been widely used in the tourism industry. Tourism enterprises and tourists use the Internet to publish and obtain travel-related information. Educational tourism is a new type of tourism activity. As a combination of “tourism + education,” it has gradually attracted the attention of tourists. With its convenience, fast speed, and low barrier, tourism text data provide great convenience for tourists’ sentiment calculation and have become one of the main sources of big data for tourism. However, the reviews of educational tourism have a lot of redundant information and complex sentence patterns, leading to a relatively low classification accuracy of the existing sentiment analysis algorithms. In order to effectively obtain the implicit semantic information of short text reviews for sentiment orientation recognition, a sentiment classification model for educational tourism online reviews based on parallel CNN and LSTM with multichannel attention mechanism is proposed. Firstly, Word2Vec technique is used, and based on noise word filtering, the feature words of educational tourism reviews are extracted to preprocess the input data set. Then, parallel CNN and LSTM are used to extract text local information and contextual features, and a multichannel attention mechanism is used to extract the attention values from the LSTM output. Finally, the output information of the multichannel attention mechanism is fused to effectively extract text features and focus on important words. The experimental results show that compared with other advanced methods, the proposed algorithm achieves improvements in terms of precision, recall, and F1 value and improves the AUC performance. It will help the educational tourism bases to carry out targeted development and construction in response to tourists feedback, enhance the sense of gain and happiness of tourists in educational tourism activities, improve tourism experience, and promote the rapid development of high-quality educational tourism.