Consumer Behaviour In Tourism Research Articles

Modelling tourists’ travel intention: Role of tourism destination image, perceived value and situational involvement

Promoting travelling intention within social media is significant for stakeholders to grasp a new tourism market and cultivate a new model for development of tourism industry. This study aims to understand path of destination image affecting travelling intention, and to investigate the mediation role of perceived value, furthermore, to uncover the role of moderator of situational involvement. This paper conducts a survey on tourists visiting Guilin, collecting 435 questionnaires, and uses the structural equation modeling method to explore how the image of the tourism destination affects tourists’ willingness to travel. The research results indicate that cognitive image, emotional image, and projected image all have a significant positive impact on perceived value, perceived value as a significant mediator to bridge the relationship among the destination image and tourists’ travel intention. Furthermore, situational involvement plays a negative moderating role in the mediating effect of emotional value. This study endeavor will serve to enrich the understanding of perceived value theory, destination image theory, and tourism consumer behavior theory. It will also provide theoretical foundations and policy recommendations for guiding tourism consumer behavior, analyzing destination image perception, and destination marketing.

Exploring the impact of AI-translated hotel reviews: the roles of reviewer nationality, cosmopolitanism, and review dispersion

ABSTRACT This study investigates how AI-translated reviews affect consumer behavior in tourism, emphasizing the roles of national stereotypes, cosmopolitanism, and review dispersion. Utilizing three experiments, it demonstrates that reviewer nationality significantly impacts hotel evaluations and booking intentions, with cosmopolitanism moderating this effect. High review dispersion further amplifies the influence of nationality among less cosmopolitan individuals. The findings highlight the complex interplay of AI translation, cultural biases, and consumer psychology in online hotel bookings, offering insights for managing AI tools and consumer perceptions in the hospitality industry.

Exploring the Impact of Celebrity Endorsements and Social Media Platforms on Sustainable Consumer Behavior in Tourism

Exploring the Impact of Celebrity Endorsements and Social Media Platforms on Sustainable Consumer Behavior in Tourism

The impact of the metaverse on consumer behaviour and marketing strategies in tourism

Objective and interest of the work: This paper focuses on analysing the existing literature on the impact of Metaverse technology on consumer behaviour, adoption and destination marketing. From a tourism perspective, Metaverse allows the fusion of physical and virtual realities, offering immersive experiences and the possibility of transforming the relationship between the destination and end user. Design of the methodology: A bibliometric analysis was performed using the Bibliometrix software, an R tool for the bibliometric study of scientific data sources. The database selected was Web of Science, and peer-reviewed articles in English published up to 10 October 2023 were analysed. A Boolean approach was used with the keywords "framework tourism Metaverse" and "framework tourist Metaverse". Results: Trends in the scientific production of subject matter analysed from 2011 to 2023 stand out, with a total of 72 articles identified according to the criteria discussed. An annual growth rate of 34.48% was observed during the production of the documents. It highlights how technology associated with the metaverse influences the decisions and experiences of tourism service users. Its value in terms of practical implications: This study examines the potential of Metaverse for ex situ immersive tourism and in situ experiences. It emphasizes the need for research on ethical behaviour, regulatory frameworks, and strategies for Metaverse integration in the tourism industry. Although it is not the first study on Metaverse, it is the only one known to focus on theoretical frameworks.

Understanding tourism consumer behavior using biometric technologies: bibliographic review and research agenda

Recent technological advances, particularly in biometrics, have significantly impacted the tourism industry. Amidst the COVID-19 pandemic, these technologies have grown rapidly, posing challenges and opportunities in utilizing the resulting data. This study aims to develop a research agenda concerning biometrics in tourism consumer behavior, detailing what biometric data entails and outlining its diverse applications. Through a bibliographic review of 422 recent papers, employing machine learning and artificial intelligence techniques, we extracted keywords, topics, and frequencies using the methodological approach of corpus linguistics and latent Dirichlet allocation algorithm. The results identified 26 topics, including “KPIs”,” Techniques”, “Personalization”, “Health”, and “Travel and transport”. Furthermore, we observed that the COVID-19 pandemic has dramatically impacted the tourism sector, with “Health” present in four categories. The practical implications of our study suggest that companies can find the issues that most concern the tourism consumer in the lines of research presented in the research agenda, paying particular attention to the lines developed in the research agenda involving “personalization”, "travel and transport" and "health".

Will Ecotourists Pay Premium Prices? An Explanatory Study on Motivations, Ecotourism Intention and Willingness to Pay Premium for Ecotourism

Purpose: Recent literature emphasizes that there is an ambiguity on ecotourism consumption as actual environmentally friendly behaviors deviate from the intentions. Further, it is identified that ecotourism offerings are higher in price and discourage consumption. Hence, this study examined ecotourism consumer behaviors focusing on motivation, ecotourism intention, and willingness to pay premium for ecotourism. It also aims to investigate the mediating effect of ecotourism intention between motivations and willingness to pay premium.
 Design/methodology/approach: The study undertook a quantitative approach with a cross-sectional design. Self-administrated questionnaires (online) were distributed employing purposive sampling technique to young domestic travelers who had purchased green travel products in the last six months in Sri Lanka. A total of 212 responses were analyzed by PLS-SEM approach using SmartPLS 4.0 software.
 Findings: The findings revealed that intrinsic motivation significantly influenced the willingness to pay premium whereas the impact of extrinsic motivation on willingness to pay premium was insignificant. Additionally, this study proved that ecotourism intention partially mediated the relationship between intrinsic motivation and willingness to pay premium while ecotourism intention fully mediated the relationship between extrinsic motivation and willingness to pay premium.
 Originality: This research contributes to extending knowledge of tourism consumer behaviour in the context of ecotourism. Moreover, this study examined how an individual is motivated towards ecotourism consumption and their willingness to pay premium for such consumptions. Thus, the present study integrates the actual behavior, willingness to pay premium to further explain the self-determination theory. Thus, it empirically contributes to broadening the understanding of comprehensive ecotourism consumer behaviour that has been paid little attention.
 Implications: The findings offer important practical implications for ecotourism providers, marketers, policymakers, and other decision-makers for planning and developing ecotourism offerings, effective marketing and promotion to encourage and ensure sustainable tourism consumption.
 Keywords: Ecotourism, Ecotourism Intention, Extrinsic Motivation, Intrinsic Motivation, Willingness to Pay Premium

An Innovative Model for the Intersection of Big Data and Artificial Intelligence in Tourism for Consumer Behavior Analysis

Abstract Currently, the development of tourism big data and artificial intelligence cross-technology provides an important role for the tourism industry to predict and analyze consumer behavior and help the development of the tourism industry. This paper discusses the relationship between tourism big data and tourism consumer behavior, and as a basis for consumer behavior, puts forward the ARMA model and LSTM model based on consumer behavior data and then combines them to design a single-layer LSTM-based combination prediction model. Finally, a famous tourist attraction in GD province is used as an empirical research object, and the model proposed in this paper is used to predict and analyze consumer behavior. The analysis of tourism shopping goods revealed that 44.97% of consumers preferred to buy tourism souvenirs, indicating that the cultural and creative products in Area A are more appealing to tourists.

Influencing factors and mechanisms on consumers' behavior: A case of tea tourism in China

AbstractThis study explores the factors affecting tea tourism, including the action mechanisms and the impact level of each factor influencing consumer behavior intentions, to contribute to predicting tea tourism consumer behavior. This study surveyed 377 potential tea tourists and constructed a theoretical model of tea tourism consumers' planned behavior using SPSS and AMOS. The results show that: (a) The experiential perception and opportunity perception of tea tourists can significantly affect their attitudes, (b) The self‐efficacy perception and convenience perception of tea tourists can significantly affect their perceptual control, and (c) The attitude of tea tourists can significantly positively influence their behavioral intention. This study not only broadens the applications boundary of the theory of planned behavior, but it also provides a new perspective for research on the behavioral awareness of tea tourism consumers. The findings have implications for predicting and promoting future tea tourism in China and beyond.

Beer Traveler, Wine Traveler, or Both? Comparing Beer Tourist and Wine Tourist Segments

Consumer behavior of wine tourists and beer tourists has typically been researched separately. This study considers the overlap in wine and beer travelers, investigating attitudinal and behavioral differences between the three groups of beverage travelers (beer-only, wine-only, beer + wine) and neither beer nor wine travelers. This study finds a large overlap between beer travelers and wine travelers (also called beer tourists and wine tourists). In most attitudinal and behavioral measures, there were no significant differences between the three types of beverage travelers, and all were higher than the “neither” group. Both wine and beer travelers travel to enjoy memorable eating and drinking experiences, influence others, and like to explore new foods–especially more than other travelers. They also use food and drink to differentiate between destinations to visit. Beverage travelers participate in more activities at the destination than other travelers and tend to spend more as well; 42.5% of American leisure travelers can be considered beer or wine travelers. These travelers can be divided into subsegments, revealing that 16.6% of American leisure travelers are beer-only travelers, 13.7% are wine-only travelers, and 12.2% are beer + wine travelers.

Consumer Behavior in Tourism in Health Crises: A Model Using the Theory of Protection Motivation in Farm Hotels

Consumer Behavior in Tourism in Health Crises: A Model Using the Theory of Protection Motivation in Farm Hotels

Consumer Behavior in Tourism in Health Crises: A Model Using the Theory of Protection Motivation in Farm Hotels

Consumer Behavior in Tourism in Health Crises: A Model Using the Theory of Protection Motivation in Farm Hotels

Sustainability of digital marketing strategies for driving consumer behaviour in the domestic tourism industry

This study examines the effectiveness and sustainability of digital marketing strategies for driving consumer behaviour in the domestic tourism industry. Based on the findings of a mixed research design involving 13 face-to-face interviews with tourism marketers as well as 401 surveys of domestic tourists, understanding tourism marketers’ digital marketing preferences, digital marketing platforms influencing travel decisions and factors motivating the use of digital platforms is crucial in developing sustainable digital marketing strategies. Digital marketing has the resilience to influence tourists’ decisions to engage in domestic tourism. Stakeholders must constantly adapt their digital marketing strategies to stay abreast of the changing trends in technology adoption. It is paramount that tourism destinations spearhead their tourism recovery strategies for increased competitiveness, sustainability and long-term recovery. As digital marketing becomes more sustainable for changing consumer behaviour, future studies can focus on artificial intelligence tools and consumer behaviour in tourism.

Halal Tourism in Theory of Planned Behavior: Intention to Recommend Variable Analysis

The purpose of this research is to examine hypotheses based on the theory of planned behavior (TPB) regarding the relationship between consumer behavior and behavioral factors of recommendation intention in halal tourism. Indonesia, with the world's largest Muslim population, stands as a significant market for halal tourism. However, despite being a prominent halal tourist destination, Indonesia lags behind Malaysia, which raises questions about the dynamics of consumer behavior in promoting halal tourism in Indonesia. Consumer satisfaction has been identified as a crucial determinant of behavioral intentions influenced by behavioral factors. To investigate this phenomenon, cross-sectional data were collected from Muslim tourists using quantitative approaches through questionnaires. Structural equation model (SEM) analysis techniques were applied to draw meaningful insights from the data. The findings revealed that the coefficient of halal attitude significantly impacts the level of satisfaction among tourists, ultimately motivating them to recommend halal tourism in Indonesia. These results validate the role of intervening satisfaction proposed within the framework and provide deeper insights into the variables and mediators of perceived behavior and attitudes. These findings are instrumental in understanding the development of theoretically planned behaviors in the context of halal tourism. Understanding the factors influencing consumer behavior and recommendation intention in halal tourism can be crucial for enhancing Indonesia's position as a top halal tourist destination. By catering to the specific needs and preferences of Muslim tourists, Indonesia can elevate its appeal and attract a larger share of the growing halal tourism market.

Application of Computer Big Data Modeling Based on Lagrangian Mathematical Equation in the Village Cultural Industry Model

Abstract To understand the Lagrangian mathematical equation, the author proposes an application study of big data modeling in the village cultural industry model. The author takes 20 traditional villages in Beijing as the object, and through crawling relevant Internet cultural and tourism big data, using the theory of tourism consumer behavior, from the aspects of consumer motivation behavior, food, housing, shopping, and other experience behavior, consumer evaluation behavior, and consumer space-time behavior, carry out targeted content analysis, aggregation analysis, etc, fully reveal the behavioral portrait of tourists in Beijing’s traditional villages. The results show that the overall tourism experience of Beijing’s traditional villages is good, but the development level is quite different, the cultural and tourism supply pattern of “some have boutiques, some have highlights, and the overall influence is weak” is presented to improve the overall level. At the same time, the computer big data based on tourists’ feedback can reasonably reveal the inherent characteristics and problems of traditional village tourism, which is innovative in the current situation where village tourism data is difficult to obtain.

CONSUMER BEHAVIOR IN TOURISM: FEATURES OF THE MODEL AND METHODS OF STUDY

The article examines the features of the model and methods of studying consumer behavior in tourism. The relevance of the chosen topic of the article is determined by the dynamics of changes in the consumer behavior of tourists, radical changes in their preferences and decision-making criteria under various external influences, primarily the COVID-19 pandemic and military operations. It is noted that the behavior of consumers of services in the market of the hospitality and tourism industry has its own characteristics related to the immateriality of tourist services, the delayed period and remoteness of the place of consumption, inflated expectations of tourists, reflection and evaluation of the tourist's own experience.
 A five-level model of consumer-tourist behavior has been adapted for the field of tourism and it is concluded that the greater is the gap between the expected and actual properties of the tourist product, the more acute is the consumer's dissatisfaction, which may affect the consumer's further behavior, his/her tourist motives, and re-appeal.
 The methods of research of consumer behavior in tourism are considered, the attention is focused on the survey method and focus groups, which are actively used in tourism practice. The results of the latest research on consumer behavior according to the own methods of global consulting agencies, travel aggregators, expert communities, professional organizations, travel portals, which should be taken into account by the players of the travel market, are described.
 In general, the understanding of the stages, a tourist goes through in the process of buying a tour, gives the travel company the opportunity to fully satisfy his/her needs, establish long-term interaction and increase loyalty. And the understanding of the role of various participants in the process of purchasing and the factors that influence purchasing behavior when buying a tourist product enables the travel company to develop an effective program to support the demand for tourist services.
 It is concluded that in order to increase the level of satisfaction of tourists, it is necessary to address the following factors: safety, emotions, hospitality of residents, ecology, tourist infrastructure, quality of service, logistics, availability and completeness of tourist information, convenience of planning and booking a trip, prices. It is also important to pay attention to the motives of tourists for traveling and to take into account the emergence of a new solvent young generation of consumers who have their own consumer preferences.

Study on Tourism Consumer Behavior and Countermeasures Based on Big Data.

In our study, through consulting, summarizing, and analyzing a large number of related literature studies on tourism consumer behavior, tourism big data, text data analysis, and so on, a framework of research ideas on tourism consumption was constructed. The train browser, NLPIR, and other software packages are used to crawl, preprocess, and mine the travel sample data, and the word frequency analysis, co-occurrence analysis, content analysis, sentiment analysis, network analysis, and other methods are used to analyze the characteristics and decision-making behavior of tourists. Based on the results of behavioral analysis, we proposed tourism development strategies from three aspects: reforming and promoting tourism marketing strategies, improving tourism product and service quality, and improving tourism destination management methods. The results show that (1) for the tourist characteristics, taking into account the factors of climate and geographical location, the domestic market is divided into four grades of markets, and different marketing strategies are adopted according to different market characteristics; (2) for the tourism decision-making behavior, a “push-pull resistance” tourism decision-making model was established through word frequency analysis, co-occurrence analysis, and content analysis; (3) for the tourism consumption preferences, through network analysis of scenic spots, it is found that there are three tourist routes preferred by tourists; and (4) for the tourism perception evaluation behavior, based on the “cognitive-emotional” model, this study describes the tourism image from the two dimensions of the cognitive image and emotional image. Generally speaking, tourists show a positive perception state. The research on tourism consumer behavior based on UGC (user-generated content) data can help scenic spots and other tourism companies to understand the characteristics and rules of tourists' behavior, understand the consumption preferences of different tourism groups, develop diversified tourism products, improve the quality of tourism services, and further cater to market segments. This research provides a new idea for tourist attractions and tourism management departments to monitor tourist behavior through big data analysis.

Characteristics of consumer behaviour in tourism, beauty and sports fields- female consumer

As women's socioeconomic status and disposable income have increased, many women also have a healthier and more fashionable lifestyle. More and more women have begun to pay attention to consumption in the fields of travel, beauty and sport, and now women have become an important consumption force in these fields. This article summarizes the consumption of women in the three fields of tourism, beauty and sports, and finally finds that in the field of tourism, women like shopping, relaxation activities, women's travel and other travel methods that can relieve stress; in the field of beauty, women They are more in pursuit of environmentally friendly and green cosmetics, and like to refer to other people’s experience, but they are prone to herd mentality and lead to impulsive consumption; in terms of sports, women hope to gain a sense of identity and personal value from the purchase of sports products and other consumer behaviors. The research significance of this paper is to help enterprises grasp the consumption behavior of women in the three fields of tourism, beauty and sports, grasp the demand motivation of women, and lay a good foundation for enterprises to formulate more appropriate marketing strategies and better serve female customers.

Study on Tourism Consumer Behavior Characteristics Based on Big Data Analysis.

In terms of scenic marketing, big data research also plays an important role in the precise marketing of scenic spots. This paper has focused on the big data related to scenic spots as the research object, explores the relationship between various subdivision big data and the number of tourists in scenic spots, and investigates the difference and influence of the consumption behavior of the secondary consumption items in the scenic area, to find the potential of the scenic area’s business growth and to promote the continuous and stable growth of the scenic area’s sales and tourism economy. Using the relevant theories and analysis methods, such as consumer behavior, big data, and tourism consumer behavior, the content mainly focuses on the establishment of the analysis model of the number of tourists in the scenic spot, the data collection, the estimation of the model parameters, the various types of big data, the calculation of the contribution rate of the data to the number of tourists in the scenic spot, and the difference analysis of the secondary consumption items of different types of tourists in the scenic spot. Results show that a multi-objective analysis model is established based on the relevant econometric theories, and an optimization plan is proposed after the multicollinearity diagnosis of the model; to establish a data envelopment analysis (DEA) model of the difference and influence of different types of tourists’ consumption behavior in scenic spots and study the consumption behavior characteristics of different types of tourists when they purchase secondary consumption items in scenic spots; the econometric model is used to analyze the big data, adjust the linear relationship of some variables, then adopt the method of gradually adding variables combined with the consumer theory, and finally determine the number of daily tourists as the explained variable, the number of internet protocol (IP), Baidu index, and the virtual value of the weekend, dummy variables for variables, bounce rate, and air pollution as explanatory variables.

Effect of Frugality and Cognition on Forest Health Tourism Intention-A Mediating Effect Analysis Based on Multigroup Comparison.

At present, the market demand for forest health tourism is weak. The main purpose of this study is to investigate whether frugality inhibits the intention of forest health tourism and whether the positive effect of cognition on the intention of forest health tourism can compensate for the inhibition of frugality. Based on mental account theory and planned behavior theory, this study constructs a structural equation model with intermediary variables—health consumption mental account and forest health consumption attitude. According to the results of the path analysis of the data, which was collected through the questionnaire survey of urban residents, the positive influence of cognition can compensate for the inhibitory effect of frugality. On this basis, mediating effect analysis based on multigroup comparison is further carried out. This study verifies for the first time the inhibitory effect of frugality on the intention for forest health tourism, enriches the theoretical system of tourism consumer behavior, and provides a scientific basis for the market positioning of forest health and the formulation of marketing strategies.

Effects of Social Media on Consumer Behaviour for Tourism Products

The study helps to investigate the relationship between social media and consumer behavior regarding tourism products. Every consumer is using social media and they are getting information from online media and social sites. Communication through online media and social applications is getting easy and less expensive. Social media affects customers’ purchasing behavior. Electronic word of mouth is also a part of social media that influences consumers’ decision process. This is a review paper that helps to understand information sharing in social media in the tourism industry. This paper helps to understand the effects of information-based social applications and online media on consumer behavior in tourism sector and also identify the most important variable which influences consumer behavior in tourism.