Tourist Behavior Research Articles

Current challenges and opportunities in cultural heritage preservation through sustainable tourism practices

ABSTRACT The preservation of cultural heritage (CH) through sustainable tourism (ST) practices is vital for maintaining the authenticity and value of cultural sites worldwide. This research investigates the impact of ST on CH conservation in China, focusing on iconic heritage sites such as the Great Wall and the Forbidden City. The study aims to understand how ST contributes to safeguarding cultural assets by assessing the perceptions and behaviors of tourists who visited these sites within the past five years. A quantitative approach was adopted, utilizing a structured questionnaire to collect data from 500 tourists, with 420 complete responses analyzed using SPSS software. The analysis involved descriptive statistics, correlation, and regression techniques to explore the relationship between ST practices and CH preservation. Findings reveal strong positive perceptions of ST practices, particularly in areas of preservation, understanding, and sustainability. The study highlights the significant role of ST in fostering CH conservation and provides empirical insights into its impact. Its novelty lies in its focus on diverse communities and its in-depth analysis of the complex interplay between ST and CH preservation within the Chinese context. This research offers valuable contributions to the field by emphasizing the role of ST in preserving cultural assets for future generations.

Engaging with AI in tourism: a key to enhancing smart experiences and emotional bonds

PurposeThis study aims to explore how engagement with AI mediates the relationship between AI adoption in tourism and the resulting smart experiences, which ultimately foster both smart tourism love and perceived happiness among tourists.Design/methodology/approachData were collected from 622 domestic Thai tourists aged 19 and above who visited Khon Kaen Province within the past three months and used AI-powered tools for tourism. The hypothesised model was tested using structural equation modelling (SEM) through a two-step approach.FindingsThe study reveals that the successful integration of AI in tourism largely depends on the depth of tourists’ engagement with these technologies. Greater engagement fosters enriched smart experiences and stronger emotional bonds.Research limitations/implicationsThis study utilises the stimulus-organism-response (S-O-R) model to examine the impact of AI adoption on tourist behaviour, making substantial theoretical contributions to the expanding body of literature on AI in tourism.Practical implicationsTourism operators and policymakers should prioritise fostering meaningful engagement with AI technologies to enhance tourist experiences and strengthen emotional connections to destinations, aligning with Thailand’s digital transformation initiatives.Originality/valueThis study emphasises the crucial role of engagement with AI – rather than mere adoption – in shaping smart tourism experiences and emotional outcomes, thereby contributing to the literature on AI in tourism.

A Dynamic Theoretical Model Based on Compensatory Ethics: How Religious Belief Shapes Tourists’ Pro-Environmental Behavior

The neoclassical economic view, which posits that individuals’ behavioral motivations stem from utility maximization, overlooks the crucial role of ethical dimension. This oversight limits its ability to adequately explain tourist behavior, particularly in religious tourism and pro-environmental contexts where morality is a crucial determinant of tourist actions. Therefore, this paper aims to employ the compensatory ethics model as the intrinsic mechanism to elucidate how religious belief shapes tourists’ pro-environmental behavior. By using data derived from the WVS database and field survey, this interdisciplinary study develops a dynamic theoretical model based on compensatory ethics theory by integrating theories from religious tourism, behavioral economics, and religious studies. The results demonstrate that religious beliefs can attenuate tourists’ time preference and positively impact their pro-environmental behavior. Tourists exhibit different willingness for pro-environmental behavior during the moral licensing and moral cleansing phases. Furthermore, it provides beneficial practical insights for the religious tourism domain.

Bibliometric analysis of trends and development in religion and green tourism behavior

Bibliometric analysis of trends and development in religion and green tourism behavior

Tourists Behavior Prediction through Online Reviews by Analyzing their Sentiments using Machine Learning Approach

Sentiment Analysis is that part of research area where different people opinions or sentiments are extracted in form of textual data from various websites. In this paper sentiment analysis has been described along with machine learning techniques on tourist’s reviews to see their behavior towards various tourist places, hotels and other services provided by tourism industry. Emotions in the form of tourist’s reviews extracted are interpreted and classified by preprocessing of data and further feature extraction is done through machine learning highly efficient technique called deep learning. In this paper, the proposed idea has been given to use deep learning methods like CNN, RNN and LSTM rather than using machine learning classical algorithms like SVM, Naive Bayes, KNN, RF etc. Also, comparison of various machine learning and deep learning techniques working on tourist sentiments has been done here in this paper to show that deep learning techniques analyze and classify emotions and polarity with deep layers efficiently where on the other hand classical algorithms of machine learning give results not better than deep learning techniques. In this way sentiment analysis has been done and the proposed idea of this research paper is change in the machine learning techniques or methods from classical algorithms to neural network deep learning methods which in future definitely will give better results to analyze deeply the sentiments of tourists to find out the liking and disliking of various tourist places, hotels and related tourism services that will help tourism business industry to work on the gap in existing services provided by them and system can become more efficient in future. Such improved tourism system will give benefits to tourists or users in terms of better services and undoubtedly it will help tourism industry to enhance business in future. Keywords—sentiment analysis, machine learning, deep learning, tourist reviews.

Formation mechanism of tourists’ pro-environmental behavior in plateau ecotourism destination

In response to the scarcity of research on the psychological factors and formation mechanism of tourists’ pro-environmental behavior in plateau ecotourism destinations, this study takes the Shangri-la in Yunnan-Guizhou Plateau as a case, developed an integrated model and tested with structural equation model to obtain accurate and unbiased path coefficients, and jointly exploring the formation mechanism of tourists’ pro-environmental behavior in plateau ecotourism destination. Based on the stimulus-body-response theory and rational behavior theory, this study conducted field investigations and acquired 516 questionnaires. Through analysis, it was discovered that the pro-environment behavior of tourists in plateau ecotourism destinations is influenced by external contextual factors and internal psychological factors. The natural environment and the cultural atmosphere can evoke tourists’ awe, and then awe can directly and positively influence pro-environment behavior, and indirectly influence pro-environment behavior through the dual paths of self-attitude and subjective norms. The conclusion explains the internal logic and action mechanism of tourists’ pro-environment behavior in plateau ecotourism destination, and provides a reference for decision-making in plateau ecotourism destination’s construction and the cracking of tourists’ negative environmental impacts.

Does Nationality Moderate Tourists’ Intention to Co-Create? Investigating Tourist Behavior in a Developing Country

Does Nationality Moderate Tourists’ Intention to Co-Create? Investigating Tourist Behavior in a Developing Country

The Transformative Power of Embodied Behaviour: Influencing Tourists' Experience in the Guangzhou Marathon as a Mass Participant Sports Event.

Mass-participation sports events (MPSEs) are of significant value to the fields of sports, culture, and tourism. MPSEs have witnessed a remarkable surge in popularity, which has led to a complex interplay of factors influencing participants' overall experience, making it crucial to understand the role of embodied behaviour. However, the existing literature is deficient in terms of providing substantial evidence, particularly with regard to the growing significance of experience planning as a core aspect of event design. This research employed the Guangzhou Marathon, one of the most renowned MPSEs in China, as a case study. The objective of this research is to investigate and extend the knowledge of the embodied behaviour of MPSE tourists through the mixed method of a questionnaire survey together with interviews. Furthermore, this research aimed to explore the antecedents and consequences of the embodied experience formation process. The findings demonstrated the pivotal role of the embodied experience in shaping tourist perceptions and subsequent intentions. Specifically, this research suggested that tourist behaviour with experience and attachment influenced the perceived value and cost of participation willingness through moderating and mediating effects. The findings contribute to the existing knowledge on sports tourism and behavioural studies and provide sustainable event management strategies.

Transformative adventure experiences scale: validation and behavioral impacts

ABSTRACT This study validates the Transformative Outdoor Adventure Experiences (TOAE) scale and examines its impact on tourist behavior in the Kullu Valley, a Himalayan tourist destination known for outdoor adventure activities. Surveying 412 tourists participating in outdoor adventures, the research confirms the TOAE scale's validity and identifies its positive influence on destination image, revisit intentions and recommendation intentions. Utilizing CB-SEM for analysis, the study also finds that destination image mediates the relationship between TOAEs and revisit and recommendation intentions. Notably, an improved destination image positively affects recommendation intentions. These findings offer insights for destination managers and suggest potential avenues for future research in different tourism contexts.

Understanding travel behaviour patterns and their dynamics: Applying fuzzy clustering and age-period-cohort analysis on longterm data of German travellers

This study examines how travel behaviour patterns change over time. It addresses the limitations of traditional segmentation studies, which often focus on static snapshots of travel behaviour. A comprehensive approach is proposed, integrating multi-dimensional segmentation and temporal analysis. Based on a large, repeated, cross- sectional dataset (1983–2018) from Germany, the study employs a research design that combines fuzzy clustering, to identify distinct tourist types including their heterogeneous behaviour, and additive logistic regression analysis, to analyse temporal changes in travel behaviour patterns. The findings reveal five tourist types based on their travel behaviour. These tourist types differ in sociodemographic characteristics and are related to each other. The chance of belonging to those tourist types changes over a tourists' life cycle (age), over time due to external factors (period) and across generations (cohort), providing insights into evolving travel behaviour. The findings from this study can help tourism stakeholders to adapt their strategies to changing tourist behaviour and improve destination management and marketing efforts.

The polycentric consumer in tourism: ethnocentrism and xenocentrism profiles’ interplay with authenticity in tourists’ destination choices

PurposeConsumer centrism’s perspectives serve as crucial determinants in decision-making processes, yet the burgeoning discourse on global marketing’s interplay with tourism scarcely addresses the nuanced interconnections between consumer dispositions toward global or local destinations, which assert a global preference bias in developing countries and their predilections for tourist destination selection. This study aims to elucidate the dynamics between ethnocentric and xenocentric dispositions and the selection of domestic tourist locales within developing countries, conditioned to perceived authentic experiences.Design/methodology/approachBased on a sample of 264 tourists, we employed structural equation modeling and mediation analysis to determine the direct and indirect interplay of consumer centrism and the mechanisms of authenticity for destination choice and latent class analysis to unveil consumer heterogeneous profiles and their implications.FindingsThe results suggest the existence of a polycentric consumer due to the strong preference for domestic destinations among ethnocentric consumers. While xenocentrism did not have a similar direct impact, its influence on local destination choice emerged through the mediating effect of perceived authenticity. This finding provides evidence for the assumption of a global preference bias in developing nations, even within tourism contexts. Additionally, we identified four distinct heterogeneous tourist profiles based on consumer inclinations toward global and local aspects, allowing for a detailed exploration of their specific influences on tourism destinations.Practical implicationsEffective tourism strategies in developing countries can boost the economy based on authenticity, creating experiences that consider the duality of tourist inclinations and promoting cultural preservation. Practical examples include cultural events, themed tours, personalized marketing, influencer partnerships, social media engagement and loyalty programs, all aimed at engaging diverse consumer groups and strengthening consumer connections toward the local and xenocentric dispositions.Originality/valueThe study advances our understanding by proposing a polycentric profile of consumer inclinations toward tourism in developing countries, driven by the perceived authenticity of destinations. This profile highlights the nuanced interplay between ethnocentric and xenocentric dispositions, illustrating how local and global preferences coexist and influence travel decisions. By emphasizing the role of authenticity, the study provides valuable insights into the factors shaping tourism behaviors in developing countries.

การพัฒนาแชทบอทเพื่อส่งเสริมการท่องเที่ยวชุมชนช่างศิลป์จังหวัดนครปฐม

The objectives of this research are to 1) develop an information system to promote tourism through the Chatbot application system in tourist attractions of the artisan community in Nakhon Pathom Province 2) study tourists' satisfaction with the Chatbot with Python language to promote tourism through the application system. LINE Chatbot in Nakhon Pathom Province The data was collected from a sample of 423 tourists and members of online social groups, which is a specific sample group. Statistics used in data analysis include frequency, percentage, mean, and standard deviation. The research results found that the study of tourist behavior in using chatbots in 4 areas: meeting needs, being able to work. according to function, ease of use, and efficiency It was found that tourists' satisfaction in using chatbots was at a high level, with an average of 4.20. The aspect that tourists are most satisfied with is the ease of use. has an average of 4.23 in terms of meeting the needs and system performance They have an average of 4.20 and the ability to work according to their duties. has an average of 4.18, respectively.

Media Exposure on Chinese Tourists’ Image Evaluations and Behavioral Intention Toward the US

ABSTRACT The media exposure of the United States in China has become more frequent in recent years. Understanding the factors that shape Chinese tourist behaviors is crucial for the China-US tourism industry. This study examines the influence of the US media exposure on Chinese tourists’ perceptions and travel intentions. Specifically, it investigates how social media and mass media impact their evaluations of product and destination images, subsequently affecting their intentions to travel to the United States. Using online data collection, 363 responses were analyzed through PLS-SEM with WarpPLS 7.0 software. The results indicate that media exposure significantly shaped tourists’ product and destination images. Additionally, a reverse halo effect was identified, where the product image influenced the destination image. Both images significantly impacted travel intentions. The study also revealed that tourists with prior travel experiences exhibit stronger relationships among the proposed constructs. These findings provide valuable insights for tourism organizations in China and the US to enhance their marketing strategies and better cater to Chinese tourists.

Research for the development and evaluation of instruments for measuring responsible tourism behavior of generation Y tourists in Thailand

Research for the development and evaluation of instruments for measuring responsible tourism behavior of generation Y tourists in Thailand

IoT Innovations for Transforming the Future of Tourism Industry: Towards Smart Tourism Systems

The Internet of Things (IoT) has significantly transformed the tourism industry, reshaping travel design, supply, and experiences. This paper reviews the key developments in tourism IoT from the mid-2010s, highlighting technological, economic, and socio-cultural impacts. It explores the adoption of IoT technologies –such as smart wearables, intelligent transportation systems, and augmented reality –across tourism sectors, emphasizing their effects on tourist behaviour and sustainable tourism development. A mixed-method approach, including literature reviews and expert interviews, is used to analyse these trends. Findings reveal that IoT enhances personalization, immersion, and sustainability in travel experiences, though privacy, security, and ethical issues pose challenges. Strategic planning and collaboration are necessary to leverage IoT innovations for sustainable tourism growth.

Analysis of the Impact of Media Cultural Exposure of Xunpu Female Hairpin Flower in Fujian Province on the Behavior of Surrounding Young Tourists from the Perspective of Social Media Interaction

With the rise of social media, the transmission of traditional culture has undergone fundamental changes. This study takes the Xunpu female hairpin flower culture in Fujian Province as an example to explore the impact of media cultural exposure and social media interaction on the behavior of young tourists in the surrounding areas. Using questionnaires and the Theory of Planned Behavior, the study analyzes the influence of social media interaction, media cultural exposure, personal attitudes, subjective norms, and perceived behavioral control on tourism intention. The findings reveal that social media interaction and media cultural exposure significantly affect young tourists’ attitudes, subjective norms, and perceived behavioral control, thereby influencing their tourism intention. This research provides new insights for the protection and inheritance of traditional culture, and also offers references for the development of the tourism industry.

Hierarchical Cluster Approach to Identify High-End Chinese Tourist Behavior: A Case Study in Phuket, Thailand

This study investigates the service touch points most influential to high-end Chinese tourists staying at five-star hotels in Phuket, Thailand, by segmenting them into distinct clusters based on their behaviors and preferences. Utilizing a quantitative research approach, the study employs descriptive statistics and hierarchical cluster analysis as the primary method of data analysis, supported by a structured questionnaire. The research identifies three clusters—Emerging Affluents, Urbanized Elites, and Established Opulence—each with unique demographic profiles in average monthly income and city of residence, as well as behavior, namely, source of search information, lead-time, preferred cancellation policies, expectations regarding hotel facilities, and conspicuous consumption activities.

A comprehensive model of the theory of planned behavior in explaining tourists’ littering behavior in a natural tourism destination

Background The tourism industry’s growth and environmental impact have prompted the need for sustainable tourism models. With the rising popularity of natural ecotourism in Indonesia, there are concerns about waste generation and environmental damage caused by tourists’ behavior, particularly littering. Focus of the Article This study employs the Theory of Planned Behavior (TPB) to understand the psychological factors influencing tourists’ intentions not to litter at natural tourism destinations. Research Question/Hypotheses This study investigates what influences tourists’ intentions and behavior not to litter. It hypothesizes that experiential attitude, instrumental attitude, injunctive norm, descriptive norm, and perceived behavioral control significantly affect intentions and examines the relationship between perceived behavioral control, intention, and actual behavior. Importance to the Social Marketing Field This study contributes by differentiating two key aspects in the constructs’ attitude, experiential and instrumental, toward behavior and subjective norm of tourists’ intention not to litter. This study provides insights into tourists’ littering behavior, aiding social marketing strategies for sustainable tourism in natural destinations. Methods A study at the Bogor Botanical Garden in Indonesia surveyed 400 respondents. A combination of structural equation modeling (SEM), confirmatory factor analysis (CFA), discriminant validity analysis, and goodness-of-fit (GoF) tests was used for the data analysis using LISREL 8.8. Results The study findings confirm and support all hypotheses, demonstrating that both affective and instrumental attitudes significantly influence intentions not to litter. Additionally, injunctive and descriptive norms play crucial roles in shaping these intentions, while perceived behavioral control significantly impacts both intentions and actual behavior. Recommendations for Research or Practice These findings suggest emphasizing instrumental attitudes is crucial for designing social marketing strategies to promote responsible behavior and environmental sustainability in natural tourism destinations.

The past scene of hospitality ethics: A citation analysis perspective

The literature on ethics research in hospitality has significantly expanded in recent years. The objective of this study is to present a comprehensive overview of ethical research in the field of hospitality literature. This will facilitate insight into future developments by examining the past. A two-step approach is employed, comprising citation analysis, a bibliometric analysis technique, and a systematic review. The former is used to identify themes, which are then discussed in the latter. The citation analysis revealed five main themes of the domain: environmental concerns, organisational citizenship behaviour, reputation management and ethical leadership. Environmental concerns were examined from two perspectives: the viewpoint of hotels and the environmental behaviours of tourists and consumers. Subsequently, a systematic review was conducted using the TCM framework (theory/context/methodology) with the objective of identifying the most prominent theories, contexts, and methodological issues associated with each theme. The issue has predominantly been discussed using quantitative analysis and social-based theories. Research has been mainly conducted in the US and the EU. Environmental ethics is likely to remain a significant area of concern in the future. This study offers a perspective that can aid researchers in developing future studies on ethics and help practitioners enhance the ethical climate of the industry.

Can I Trust GenAI to Plan My Next Trip? A Multi-Method Approach to Optimizing Media Mix

Although tourists can now book trips directly using generative artificial intelligence (GenAI), it remains unclear whether the real-time travel information it provides is comprehensive and sufficiently trustworthy enough to make booking decisions. The present research addresses this gap by integrating media richness, trust transfer, and the value-based adoption model (VAM) to investigate the impact of varying levels of travel information richness (text-only, text-image, and text-image-audio) on the booking behaviors of tourists using GenAI such as ChatGPT. With data from 578 participants, we tested the proposed structural and configurational models using a multi-analytical approach. Our findings revealed that the three media richness levels yield both analogous and distinctive effects on tourist perceptions regarding benefits, costs, trust formation, and intentions in ChatGPT online travel booking. Specifically, the text-image group demonstrated the strongest links from media richness to trust in ChatGPT, perceived benefit to value, and ultimately value to increased booking intention. Our findings from configurational modeling confirm a significant opportunity to harness the power of AI-empowered platforms for online travel booking.