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Controversy occurs among professionals, such as veterinarians and zookeepers in Japan, as to whether a zoo should be educational or recreational. The purpose of this paper is to examine how a zoo's culturally crafted entertainment value conflicts with educational value. Using a front/back framework of the zoo, both entertainment and educational values are negotiated.

This paper conceptualizes differences between a zoo's front and back regions to examine operations and visitor behavior. Observing and interpreting visitor and zoo employee interactions provide rich data about the educational versus recreational dynamic. The author observes visitor behavior in both zoo regions and interprets their cognitive schema.

Animal representation in mass media reinforces the zoo animal's amusement value to visitors, leading to the construction of tourist texts. Tourist text images affect the viewer's perception of reality, sometimes conflicting with the animal's reality. The zoo's back region helps alleviate this paradox. In this process, tour guides play a mediatory role between entertainment and educational values.

The author argues about zoos and zoo animals from the Cartesian dualism view of “culture/nature”. A zoo represents culture's triumph over nature. This paper develops this idea and discusses how entertainment and educational values conflict, and are reconciled, from the perspective of symbolic and pragmatic dimensions.

This study aims to explore the success factors of tourism performing arts (TPA) programs by analyzing a large data set of online reviews.

A total of 195,230 reviews from Ctrip.com were collected and preprocessed. A deep learning method was leveraged to estimate the similarity between words. Then, regression analysis was conducted to determine success factors.

This study extracted four positive and two negative factors affecting tourist satisfaction with tourism performance arts. The results demonstrate that the tourists paid the most attention to the traditional Chinese cultural aspects, audiovisual effects and the actors’ performing enthusiasm.

Despite this study’s large data set, the focused was only on Chinese reviews. It would be useful and interesting to compare the success factors of tourism performance arts programs offered in different countries.

The study findings can contribute to the development of TPA programs to attract tourists to travel destinations.

This study demonstrates that analyzing online reviews of TPA through text mining technology is an effective method of understanding tourist satisfaction.

在线点评分析探析旅游演艺成功因素

本研究旨在通过分析大型在线评论数据集来探索旅游表演艺术项目的成功因素。

共收集和预处理来自携程网的 195,230 条评论。利用深度学习方法来估计单词之间的相似性。然后, 进行回归分析以确定成功因素。

本研究提取了影响游客对旅游表演艺术满意度的四个积极因素和两个消极因素。结果表明, 游客最关注中国传统文化方面、视听效果和演员的表演热情。

尽管我们的数据集很大, 但它只关注中文评论。比较不同国家提供的旅游表演艺术项目的成功因素将是有用和有趣的未来研究方向。

研究结果有助于发展旅游表演艺术项目, 以吸引游客前往旅游目的地。

研究表明, 通过文本挖掘技术分析旅游表演艺术的在线评论是了解游客满意度的有效方法。

This study aims to identify motivations for visiting Kyoto's prominent religious attractions using latent Dirichlet allocation (LDA) text analysis of online reviews; establish linkages between push motivational factors and pull factors of the religious sites, forming distinct tourist typologies; and suggest strategies for Kyoto's destination marketing based on the findings.

This study analyzed 37,772 TripAdvisor reviews for Kyoto's top 25 religious sites from the pre-pandemic period (March 2020). LDA topic modeling extracts 18 underlying thematic dimensions from the review texts. Axial coding of these dimensions revealed five distinct tourist motivation typologies.

Five motivation typologies emerged: cultural seekers drawn to Japan's unique heritage, nature lovers attracted by scenic landscapes, chrono-seasonal experiencers seeking distinct seasonal views, crowd-avoiders prioritizing less congested visits and city wanderers engaging in local activities.

The findings offer valuable guidance for destination marketers and managers in Kyoto, enabling the development of targeted strategies to enhance visitor experiences and manage overcrowding at popular religious sites.

This research provides novel insights into nonreligious tourists' motivations for visiting religious sites in a crowded destination. By identifying distinct motivation-based tourist typologies, the study informs strategies for enhancing visitor experiences tailored to diverse needs, contributing to tourism literature and practical destination management.

By conducting a longitudinal study, this study aims to investigate how the role of hotel attributes in destination competitiveness changed through the stages of pre-, amid and recovery from the crisis.

First, the latent Dirichlet allocation method was used to identify hotel attributes from 15,137 online reviews, and then a sentiment analysis was performed to determine tourist satisfaction with the subject attributes. Second, separate asymmetric impact competitor analyses were conducted for the three stages of the crisis, and their results were compared with understand how the role of the hotel attributes changed throughout the crisis.

The results revealed that the impacts of hotel attributes on tourist satisfaction and destination competitiveness differed significantly at each stage of the crisis.

This research expands the existing literature by offering valuable insights by elucidating the changing characteristics of hotel attributes at each crisis stage. The results extend the body of knowledge in destination management by providing evidence on the validity of asymmetric impact competitor analysis.

To fully understand the impact of a crisis (e.g. COVID-19) on destination competitiveness with a focus on the hotel sector, this research conducted a longitudinal study that covers three stages of the crisis (i.e. pre-, amid and post-crisis). Moreover, unlike previous studies, this research considers the asymmetric relationships between service attributes and overall tourist satisfaction, as well as competitors’ information.

In the era of information overload, the density of tourism information and the increasingly sophisticated information needs of consumers have created information confusion for tourists and scenic-area managers. The study aims to help scenic-area managers determine the strengths and weaknesses in the development process of scenic areas and to solve the practical problem of tourists' difficulty in quickly and accurately obtaining the destination image of a scenic area and finding a scenic area that meets their needs.

The study uses a variety of machine learning methods, namely, the latent Dirichlet allocation (LDA) theme extraction model, term frequency-inverse document frequency (TF-IDF) weighting method and sentiment analysis. This work also incorporates probabilistic hesitant fuzzy algorithm (PHFA) in multi-attribute decision-making to form an enhanced tourism destination image mining and analysis model based on visitor expression information. The model is intended to help managers and visitors identify the strengths and weaknesses in the development of scenic areas. Jiuzhaigou is used as an example for empirical analysis.

In the study, a complete model for the mining analysis of tourism destination image was constructed, and 24,222 online reviews on Jiuzhaigou, China were analyzed in text. The results revealed a total of 10 attributes and 100 attribute elements. From the identified attributes, three negative attributes were identified, namely, crowdedness, tourism cost and accommodation environment. The study provides suggestions for tourists to select attractions and offers recommendations and improvement measures for Jiuzhaigou in terms of crowd control and post-disaster reconstruction.

Previous research in this area has used small sample data for qualitative analysis. Thus, the current study fills this gap in the literature by proposing a machine learning method that incorporates PHFA through the combination of the ideas of management and multi-attribute decision theory. In addition, the study considers visitors' emotions and thematic preferences from the perspective of their expressed information, based on which the tourism destination image is analyzed. Optimization strategies are provided to help managers of scenic spots in their decision-making.

Travel websites allow tourists to share their thoughts, beliefs and experiences regarding various travel destinations. In this paper, the researchers demonstrated an approach for destination marketing organisations to explore online tourist-generated content and understand tourists' perceptions of the destination image (DI). Specifically, the researchers initiated an investigation examining how the destination image of Macau changed during the period of 2014–2018 based on user-generated content on travel websites.

Web crawlers developed by Python were employed to collect tourists' reviews from both Ctrip and TripAdvisor regarding the theme of “Macau attraction”. A total of 51,191 reviews (41,352 from Ctrip and 9,839 from TripAdvisor) were collected and analysed using the text-mining technique.

The results reveal that the frequency of casino-related words decreased in reviews by both international and mainland Chinese tourists. Additionally, international and mainland Chinese tourists perceive the DI of Macau differently. Mainland Chinese tourists are more sensitive to new attractions, while international tourists are not. The study also shows that there are differences between the government-projected DI and the tourist-perceived DI. Only the “City of Culture” and “A World Centre of Tourism and Leisure” have built recognition with tourists.

Given the easy accessibility of online information from various sources, it is important for destination marketing organisations to analyse and monitor different DI perspectives and adjust their branding strategies for greater effectiveness. This study uncovered the online DI of Macau by using text mining and content analysis of two of the largest travel websites. By analysing and comparing the differences and relationships among the frequently used words of tourist-generated content on these websites, the researchers revealed some interesting findings with important marketing implications.

The purpose of this research is to analyze the shifting perceptions of international tourists to Jeju Island and provide practical lessons to the tourism industry. Specifically, in regard to three United Nations Educational, Scientific and Cultural Organization (UNESCO) natural World Heritage sites in Jeju, this research measures the most salient topics mentioned by tourists to inform a more accurate perception of the island’s most valuable natural assets as reported by tourism experiences.

This study used a Web crawler to gather over 1,500 English language reviews from international tourists from a famous travel information website. The collected data were then preprocessed for stemming and lemmatization. After this, the processed text data were analyzed through a latent Dirichlet allocation (LDA)-based topic modeling approach to identify the most prominent clusters of ideas mentioned and represent them visually through graphs, tables and charts.

The findings from this research suggest that there are ten identifiable topics. Topics focusing on “adventure,” “summits” and “winter” showed noticeable increases, whereas topics focusing on “sunrise peak” and “UNESCO” have decreased over time. There is a trend for international tourists to be ever more conscious of the adventurous and rugged aspects of Jeju, and the novelty of mentioning UNESCO status seems to have worn off. Furthermore, there is the proclivity for tourists to mention “worth” and “enjoy” more as time goes on.

This study applies LDA-based topic modeling and LDAvis using user-generated online reviews with time-series analyses. Consequently, it provides unique insights into the changing perceptions of ecotourism on Jeju today, as well as contribution to smart tourism fields.

This paper aims to expose the evolution in the use of the so-called reception tools and tourist information that are present at the time of consumption of a trip towards an interest in and a willingness to link local residents and tourists in a friendly, inclusive and conciliatory way. This is the case of territorial signage designed for pedestrians, a growing protagonist of the urban landscape of many cities, which has found in its formulation the appropriate response to unify the messages and criteria that are addressed to all audiences and people with all types of sensitivities.

Based on an extensive fieldwork study conducted in 2013 and 2017 in the 62 most populated cities of Catalonia, different variables related to the shape of the signage and the content presented in them were analysed. To this end, a specific pattern of ad-hoc observation and structured interviews were applied to determine the social transition of the content and approaches used in the signage.

While signage is initially considered to be a basic solution with purely informative content, poor in qualitative aspects and often neglected by those responsible for its management, over time it has emerged as a tool that serves to unify the interests of the citizens who share the same space for mutual interaction. It is characterised by providing open and transversal information for all citizens without focussing on or thematising tourism in an exclusive and segregated way, separating it from the rest of the aspects that make up the nature of the urban landscape.

This paper confirms that these tangible instruments of support for tourists, beyond seeking a harmonic fit in the urban planning of today's cities, are also complicit in seeking social cohesion in the present-day paradigm of the conflicts created by urban tourism.

The purpose is to provide decision support for tourists recommending scenic spots and corresponding suggestions for the management of scenic spots.

Based on the Baidu index data generated, this paper analyzes the temporal and spatial characteristics of network attention of 5A scenic spots in Sichuan Province. The online comment data are used to build the assessment model of scenic spots based on network attention, and the comment information of tourists is mined and analyzed through statistical analysis. At the same time, the key attributes of scenic spots from the perspective of network attention are evaluated and analyzed by using the probabilistic linguistic term set. Finally, this paper further constructs a recommendation model based on the key attribute set of scenic spots.

This paper uses different types of tourism network information, integrates multi-types of data and methods, fully excavates the value information of tourism network information, constructs the research framework of “scenic spot assessment + scenic spot recommendation” from the perspective of network attention, analyzes the network attention characteristics of scenic spots, evaluates the performance of scenic spots, and implements scenic spot recommendation.

This paper integrates multi-source data and multidisciplinary theoretical methods to form a scenic spot research framework of “assessment + recommendation” from the perspective of network attention.

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.

The digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.

(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.

This research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.