Tourism Consumers Research Articles

A felelősségteljes magatartás erősödése a turisták körében = Strengthening Responsible Behavior among Tourists

Examining today’s tourism, it should be noted that undesirable side effects have appeared and intensified, both from a social and environmental perspective. Maintaining the popularity of tourism and its further development requires change. This change must occur in both supply and consumer demand. In our study, we examine the extent to which the Hungarian population is open to exhibiting environmentally conscious and responsible consumer behavior during their travels. We analyze the results of key manifestations of responsible tourism and the attitude of the domestic population towards environmental awareness. Our study is particularly relevant as many host areas are already struggling with the negative effects of overtourism. Therefore, it is important to understand whether there is a willingness among tourism consumers to adopt more environmentally conscious and responsible consumer behavior.

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.

Relationship between tourism consumers’ experience, flow, satisfaction, and subjective well-beingregarding LAN tour

Relationship between tourism consumers’ experience, flow, satisfaction, and subjective well-beingregarding LAN tour

A Study on the Interaction between Product Types and Collectable Experiences Depending on the Uniqueness Needs of Tourism Consumers

A Study on the Interaction between Product Types and Collectable Experiences Depending on the Uniqueness Needs of Tourism Consumers

Optimized Decisions for Smart Tourism Destinations: A Cross-Generational Perspective Using an Improved Importance–Performance Analysis

Our study introduces an enhanced version of the Importance–Performance Analysis (IPA) method, a powerful tool that can be applied across various domains. This method plays a crucial role in our research, aiding in making well-informed decisions about smart tourism destination attributes. We achieved this by evaluating how 911 consumers from four different generations (Baby Boomers, Generation X, Millennials, and Generation Z) rated these attributes based on their most recent tourist destination visit. Unlike traditional methods that often rely on subjective opinions or complex statistical models, the Improved IPA (IIPA) method offers a clear approach to decision-making. It enables decision-makers to focus on the most crucial attributes that drive consumer interest, thereby optimizing resource allocation and marketing efforts. Specifically, to remain competitive, decision-makers for smart tourist destinations should focus on queuing-time forecast and applications, websites, and content accessible for travelers with disabilities for Baby Boomers; e-complaint handling for Generation X; smart emergency response system for Millennials; and tourist-flow forecast, real-time traffic broadcast, electronic-entrance guard systems, and accessible data about physical design features of accommodation, restaurants, and tourist attractions for Generation Z. Theoretically, this study advances the research on managerial decision-making by demonstrating the effectiveness of the IIPA as a clear and straightforward method for making optimal decisions about product or service attributes. In practice, the study provides decision-makers with valuable insights into the importance of different categories of smart attributes in shaping the overall holiday experience at a tourist destination for Baby Boomers, Generation X, Millennials, and Generation Z tourism consumers.

What theories can be used to study hospitality and tourism consumers in the post-pandemic era?

PurposeThis paper aims to highlight unconventional or underused theories that can be considered for the study of hospitality and tourism consumers. The authors discuss how these theories can be applied.Design/methodology/approachThis research paper is conceptual and descriptive in nature. The authors address the proposed theories by applying the Delphi method.FindingsTheories such as dramaturgical theory, persuasion theory, script theory, customer inspiration theory and segmented assimilation theory are underused but can be applied to studies of hospitality and tourism consumers’ behavior. They can be helpful for understanding various aspects of consumer behavior, such as their decision-making, motivations, attitudes and perceptions, in hospitality and tourism.Originality/valueConsumer behavior is more diverse and complex in the post-pandemic era. The authors draw attention to theories that are underused but have explanatory power with regards to hospitality and tourism consumers’ behaviors. These non-conventional theories can provide new theoretical perspectives and offer new insights.

Analysis of Emotional Tendency of Tourism Consumers Based on LSTM and Fuzzy Control Algorithm

Learning the emotional tendency of travelers improves their interests and provide optimal traveling recommendations. This, however, requires large volumes of data such as travel plans, visit sites, personal interests, value for money, etc. for a detailed analysis. For ease of such analysis, in this article, an organized combinational control method (OC2M) is proposed. This method relies on conventional long short-term memory (LSTM) and fuzzy control (FC) to support such analysis. The first is responsible for filtering non-repeated data from the previous travel/ tour history reducing the data discreteness. This is organized non-recurrently to prevent outdated/ trivial data from influencing the consumer’s emotional learning. The FC process filters the adaptable data with the future tour/ travel plan for providing optimal recommendations that are liable to the consumer’s emotional tendency. This is identified based on the user's interest, preferences, and emotional connectivity with the place or plan from previous histories. Therefore, the proposed method improves the recommendation and validation tendencies of the consumer’s travel plan accordingly.

Research on the Design Method of Rural Lodging Based on the Integration of Architecture and Environment

The concept of modern tourism intelligent application in China is to fully meet the information needs of tourists and customer experience, and the development of intelligent tourism relying on Internet of Things (IoT) is its most basic guarantee condition. With the rise of ethnic village tourism and the change of new consumer lifestyle, B&B shows an explosive development. Tourism consumers are also shifting from hotels to home stays in the process of tourism. Therefore, based on IOT application as the starting point, this paper firstly, gives a more detailed description of the development process and marketing status of home stays, and discusses its various problems. Then, based on the TP theory of ethnic villages, Porter's five forces analysis model and the SWOT analysis method of ethnic villages, the marketing environment of homestays is studied in depth to discover their advantages.The HTOE model develops a marketing mix strategy for B&Bs that meets the actual situation of ethnic village development

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".

Marketing Strategy of Rural Home Stay Industry Based on Intelligent IOT

The concept of modern tourism intelligent application in China is to fully meet the information needs of tourists and customer experience, and the development of intelligent tourism relying on Internet of Things (IoT) is its most basic guarantee condition. With the rise of ethnic village tourism and the change of new consumer lifestyle, B&B shows an explosive development. Tourism consumers are also shifting from hotels to home stays in the process of tourism. Therefore, based on IOT application as the starting point, this paper firstly, gives a more detailed description of the development process and marketing status of home stays, and discusses its various problems. Then, based on the TP theory of ethnic villages, Porter's five forces analysis model and the SWOT analysis method of ethnic villages, the marketing environment of homestays is studied in depth to discover their advantages.The HTOE model develops a marketing mix strategy for B&Bs that meets the actual situation of ethnic village development.

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

DETERMINAN PERMINTAAN PARIWISATA INTERNASIONAL: STUDI WISATAWAN MANCANEGARA DI INDONESIA TAHUN 2013-2020

The tourism sector is one of the sectors that contributes the most to national foreign exchange earnings. However, trade in tourism services is still faced with a number of problems and challenges going forward. This can be seen from the comparison of the number of foreign tourist arrivals in Indonesia which shows that Indonesia's tourism market share is still limited and has not been able to compete in the international market. The purpose of this study is to determine and analyze the influence of the Tourism Consumer Price Index (TCPI), GDP per capita of the country of origin of foreign tourists, the Rupiah Exchange Rate against the currency of the country of origin of foreign tourists, and the Visit Visa Free Policy in Indonesia on international tourism demand in Indonesia in the 2013-2013 period. 2020. The variables used are variables that can influence international tourism demand according to previous researchers.The data used in this study is secondary data combining cross sections from 28 countries of tourist visitors and time series from 2013 to 2020. The data collection method was carried out through documentation sourced from the World Development Indicators, Bank Indonesia, and the Central Statistics Agency (BPS). The analytical method used is panel data with the help of Stata 17. The results of this study show that the GDP per capita of the country of origin of foreign tourists has a positive and significant effect on the demand for international tourism in Indonesia in 2013-2020. The rupiah exchange rate has a negative and significant effect on the demand for international tourism in Indonesia in 2013-2020, while the TCPI and Visit Visa Free Policy in Indonesia have no significant effect on demand for international tourism in Indonesia in 2013-2020.

AI Think with Me, Or Think for Me?

This research aims to study and analyze strategies for the strategic application of artificial intelligence in marketing by developing a framework that guides artificial intelligence planning strategies in marketing systematically and can be followed up by making decisions about service strategies at the J&T Company. The research locus is the object and source of data from the place being researched so that the information obtained can provide accurate data and truth in research. J&T Cargo is a technologically innovative express company under the auspices of the J&T Group. The locus of this research was carried out at: Marketing manager, HR manager and marketing expert team. The qualitative approach carried out through the data analysis technique used is the Manual Data Analysis Procedure (MDAP) by Rofiah, (2022), from the results of interviews accompanied by triangulation of sources, methods and theories it can be concluded that artificial intelligence for marketing strategies at J&T Cargo is used to determine preferences. Various Consumer Segments; Micro Segment Customers; Target Cause Marketing Outreach; Identify the Best Target; Refining Customer Based Perception Maps; Positioning Slogan; Psychographic Consumer Segmentation; Tourism Consumer Segment; New Customer Promotion Target; Target Digital Consumers; Target Customers Based on Brand with the aim of monitoring local market developments, so that in this business J&T Cargo is not left behind compared to other competitors. This paper also contributes to strategic marketing research by providing a systematic and rigorous approach to identifying research gaps that bridge strategic marketing practice research and artificial intelligence.

The Technology Acceptance Model and Hospitality and Tourism Consumers’ Intention to Use Mobile Technologies: Meta-Analysis and Structural Equation Modeling

What drives consumers to adopt mobile technologies has been a significant research topic in hospitality and tourism literature. The Technology Acceptance Model (TAM) has been widely adopted to examine this topic. Meta-analytic structural equation modeling (MASEM) was conducted to assess the efficacy of the TAM in estimating consumers’ intention to adopt these technologies in hospitality and tourism contexts. The moderating effects of cultural differences (Eastern vs. Western) and research contexts (hospitality vs. tourism) were also examined. Based on 33 individual samples ( N = 13,635), the results indicated that: “perceived usefulness” (PU) has the strongest impact, “perceived ease of use” (PEOU) has stronger effects on PU and attitude in the context of Eastern culture compared to Western culture, and the relationship between “attitude” and “intention” was stronger in the context of hospitality than in the context of tourism. Implications for hospitality and tourism researchers and practitioners are discussed based on these findings.

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.

The influence of motivators on responsible consumption in tourism

Responsible consumption in tourism is a crucial prerequisite for its sustainable development. Tourists' attitudes are an essential topic in the issue of waste generation and management in both academic and practical environments. Raising awareness of waste issues, education, media influence, and influencers? support can positively or negatively shape tourists' attitudes toward environmentally conscious behavior. The paper examines the attitudes of Slovak tourism consumers toward sustainable consumption and waste generation. The study objective is to evaluate the effectiveness of motivators for responsible consumption in Slovakia's tourism industry. Four motivators and two attitudes that determine responsible consumption in tourism were determined. The results are based on data from primary research through a questionnaire conducted on a sample of 284 respondents. The intensity of perception of individual motivators was monitored through a 5-point Likert scale. The study defines one research question and four hypotheses. Spearman's correlation coefficient and logistic regression were used to verify the relationship between the selected motivators and consumers? attitudes. The results confirm that the motivators ?Family? and ?Media?, by providing information about waste and its effects on tourism destinations, are strong motivators for responsible consumption in tourism. ?Education? and ?Influencer? are less effective motivators. Based on this, the contribution presents possible measures to strengthen the education of consumers in the tourism industry on responsible consumption in waste generation.

Research on Intelligent Analysis Model of Tourism Consumers’ Purchase Intention and Its Application Practice in E-commerce Platforms

Abstract Tourism consumption, as a special type of daily consumption, has significant features that distinguish it from other types of consumption. The purpose of this paper is to summarize and extract the feature engineering in tourism consumption, encode the feature engineering in tourism consumption behaviors using the Transformer model, and predict consumer purchase intention. After the performance evaluation of the Transformer-based consumer purchase intention analysis model constructed in this paper, it is applied to the e-commerce platform, taking the dynamic pricing strategy of the e-commerce platform as the entry point and analyzing the application effect of the model in the optimal inventory time path, the optimal price of the platform, and the expected revenue. The transformer-based consumer purchase intention analysis model in this paper is significantly better than other prediction models in AUC, accuracy, precision, recall, and F1. When applied to e-commerce platforms, this paper’s model helps to realize the inventory equilibrium state between inbound enterprises and e-commerce platforms, which improves the overall revenue of both parties. When time t=40 or inventory n=30, the optimal online store price of the platform after the model is lower than the price before the model is applied, and consumers can enjoy a better purchasing experience. t=40 or n=30, the total expected revenue of both parties after the model is higher than the total expected revenue before the model is applied. This paper shows that the Transformer-based consumer purchase intention analysis model can positively impact the dynamic pricing of e-commerce platforms.

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.

Research on optimization strategy of new media marketing of rural tourism under the background of “Internet+”

Abstract Under the background of the Internet, the effective use of new media means can improve the marketing level of rural tourism and adapt to the development needs of the new era. The construction of a new media marketing platform for rural tourism uses Hadoop, an extensive data framework system, to analyze the tourism preferences of various consumers. Based on the constructed platform, a rural tourism consumer portrait model is designed using the fuzzy-C mean clustering algorithm and the personalized recommendation algorithm considering the time effect to realize the precise marketing of rural tourism consumers. In the analysis of consumer precision marketing, consumers can be subdivided into three categories of growing, high-value and general consumers through clustering, and the marketing success rate of the recommendation algorithm in this paper reaches 0.765. The regression analysis further understands that the quality of the products and services of the rural tourism website (0.586) is the factor that has the most significant influence on the satisfaction of the consumers, followed by brand awareness (0.556), and that the different new rural tourism media marketing strategies have the most significant influence on the satisfaction of consumers. Consumer satisfaction is affected by media marketing strategies in other ways. Based on the study’s results, this paper proposes relevant optimization of new media marketing strategies for rural tourism to promote sustainable development.

Space tourism: Value-attitude-behavior theory, artificial intelligence, and sustainability

Despite concerns over its sustainability, space tourism is an emerging luxury consumer service which is promoted to participants as providing a new connection to Earth and humanity. However, little research examines the potential connectivity between sustainability and space tourism, especially given the strong technological dimensions of space tourism. The purpose of this study is to explore an extended value-attitude-behavior theory with AI awareness and social and personal norms to examine space tourism's alignment with the UN's 17 Sustainable Development Goals. Through 664 potential space tourism consumers and applying PLS-SEM, multi-group analysis, fsQCA, and deep learning methods, findings revealed the significant influence of value and AI awareness on attitude and social and personal norms leading to sustainable behaviors. Findings provide insights into space tourism's sustainability, emphasizing environmental considerations and AI awareness in shaping luxury travel consumer services.