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During the pandemic, two types of fear were identified that occur significantly in all groups or profiles of people. The aim of this paper is to determine which of the two types of fears exist in certain psychological groups, and which of the fears strongly influence the decision to travel.

The VALS 2 method and standardized questionnaire were used for the segmentation of the tourist market or for the determination of the psychographic profiles of the consumers, and three additional questions were joined to it as they were vital for the research of the type of fear and its impact on the decision for traveling. When the reliability of the questionnaire and the validity of the sample were determined, the data were further processed using a computer program package IMB AMOS SPSS 21.00, and then, based on the theoretical suppositions and hypotheses, the SEM structural model was created.

The paper indicates the existence of established types of fears in humans, when it comes to pandemics and similar crisis situations. People are most afraid of infection during travel, and lack of funds and job loss during the critical period of the pandemic. The research conducted confirms that all groups of people, who are determined by the psychological technique VALS 2, react with a certain dose of fear and make decisions under the pressure of fears.

The research had limitations in terms of contact with people and conducting live surveys. The measures during the pandemic, which were carried out by the state, included social distance and limited movement of people.

The work can contribute to the community, along with similar research. The results of the research will be available, and it will be possible to see the behavior of people during crisis situations, and the impact of fears on making decisions, both travel decisions and decisions related to other areas of life.

The paper provides research results on a large sample of respondents, and can serve as a basis for further research in the field of tourism, psychology and similar fields. It is crucial to consider the type of fears, and the strength of the impact of these fears on the decision to travel, during crisis situations.

This paper aims to replicate a model already proven in previous research in this field. This will make it possible to explain the possible relationships that may occur among the motivations, perceived value, satisfaction and loyalty of the tourist towards the Alhambra and Generalife inscribed as World Heritage Site (WHS) in 1984.

From a dataset containing 1,612 surveys, a model a model based on structural equations has been carried out through SmartPLS software, focus the analysis on the model dependent variables’ predictive power, as well as the size of the effect and the statistical inference of the structural relationships.

The main conclusions include the influence of perceived value on satisfaction as well as the influence of the latter on loyalty. it is remarkable the effect that the perceived value has on satisfaction, and satisfaction on loyalty. This implies that a positive assessment of world heritage destinations leads a subsequent loyalty to them.

The results obtained in this research can be used as a starting point for the establishment of new strategies for the promotion of the destination in terms of tourism and heritage.

The inclusion in the list of WHS is recognition in terms of material and historical quality, as well as a stimulus for tourism because it increases the number of visits to the destination. Several studies carried out in these types of destinations have shown the existence of a relationship between motivations, perceived value, satisfaction and loyalty. However, there are no previous studies carried out in the Alhambra and the Generalife that sustain this relationship. This work makes a contribution that completes the academic literature on the study of the emotional bonds between the historical and monumental heritage and the tourist who visits it and its behaviour.

The purpose of this study is to analyse Peruvian cuisine in the context of visitors’ overall experience, focusing on the loyalty of tourists in terms of gastronomy, their satisfaction with the destination, and the overall image.

Data were obtained from tourists who visited Lima (Peru). Structural equation modeling was used to verify the hypothesized relationships.

The results obtained confirm that satisfaction and appreciation, such as quality, have a positive influence on tourists’ loyalty and, therefore, they recommend and express their desire to come back to this destination. The traditional gastronomy of Lima stands out as a prominent factor on overall experience.

This paper helps the managers of cities in their decisions to improve the satisfaction and seek loyalty of those who visit a city, emphasizes the role of gastronomy.

The results obtained in this research can be used for the establishment of new strategies for the promotion of the destination in terms of tourism and traditional food.

The gastronomy in Lima, (Peru) is recognized worldwide, as well as a stimulus for tourism because it increases the number of visits to the destination. Several studies carried out in these types of destinations have shown the existence of a relationship between gastronomy, overall experience, satisfaction and loyalty. However, there are no previous studies carried out in Lima that sustain this relationship. This work makes a contribution that completes the academic literature on the study of the emotional bonds between Peruvian gastronomy and the tourist who visits it and its behaviour.

The purpose of this study was to uncover representative emergent areas and to examine the research area of marketing, tourism and big data (BD) to assess how these thematic areas have developed over a 27-year time period from 1996 to 2022. This study analyzed 1,152 studies to identify the principal thematic areas and emergent topics, principal theories used, predominant forms of analysis and the most productive authors in terms of research.

The articles for this research were all selected from the Web of Science database. A systematic and quantitative literature review was performed. This study used SciMAT software to extract indicators. Specifically, this study analyzed productivity and produced a science map.

The findings suggest that interest in this area has increased gradually. The outputs also reveal the innovative effort of industry in new technologies for developing models for tourism marketing. Ten research areas were identified: “destination marketing,” “mobility patterns,” “co-creation,” “gastronomy,” “sustainability,” “tourist behavior,” “market segmentation,” “artificial neural networks,” “pricing” and “tourist satisfaction.”

This work is unique in proposing an agenda for future research into tourism marketing research with new technologies such as BD and artificial intelligence techniques. In addition, the results presented here fill the current gap in the research since while there have been literature reviews covering tourism with BD or marketing, these areas have not been studied as a whole.

El objetivo de esta investigación fue descubrir nichos representativos de áreas emergentes y examinar el área de Marketing, Turismo y Big Data, evaluando cómo han evolucionado estas áreas temáticas durante un período de 27 años desde 1996–2022. Analizamos 1.152 investigaciones para identificar las principales áreas temáticas y temas emergentes, las principales teorías utilizadas, las formas de análisis predominantes y los autores más productivos en términos de investigación.

Todos los artículos para esta investigación fueron seleccionados de la base de datos Web of Science. Realizamos una revisión sistemática y cuantitativa de la literatura. Utilizamos el software SciMAT para extraer indicadores. Específicamente, analizamos la productividad y elaboramos un mapeo científico.

Los hallazgos sugieren que el interés en esta área ha aumentado gradualmente. Los resultados también revelan el esfuerzo innovador de la industria en nuevas tecnologías para desarrollar modelos de marketing turístico. Se identificaron diez áreas de investigación (“marketing de destinos”, “patrones de movilidad”, “co-creación”, “gastronomía”, “sostenibilidad”, “comportamiento turístico”, “segmentación de mercado”, “redes neuronales artificiales”, “precios”, y “satisfacción del turista”).

Este trabajo es único al proponer una agenda para futuras investigaciones en investigación de Marketing Turístico con nuevas tecnologías como Big Data y técnicas de Inteligencia Artificial. Además, los resultados presentados aquí llenan el vacío actual en la investigación ya que si bien se han realizado revisiones de literatura que cubren Turismo con Big Data o Marketing, estas áreas no se han estudiado como un conjunto.

这一特定研究领域的目标是发现具有代表性的新兴领域, 并考察市场营销、旅游和大数据研究领域, 以评估这些主题领域在1996年至2022年的27年间是如何发展的。我们分析了1152项研究, 以确定主要专题领域和新兴主题、使用的主要理论、主要的分析形式以及在研究方面最有成效的作者。

本研究的文章都是从Web of Science数据库中选出的。我们进行了系统化的定量文献审查, 并使用SciMAT软件来提取指标。具体来说, 我们分析了生产力并制作了一个科学研究地图。

研究结果表明, 人们对这一领域的兴趣已经逐渐增加。本文也揭示了工业界在开发旅游营销模式的新技术方面的创新努力。研究确定了十个研究领域：“目的地营销”、“流动模式”、“共同创造”、“美食”、“可持续性”、“游客行为”、“市场细分”、“人工神经网络”、“定价 “和游客满意度”。

这项研究的独特之处在于提出了未来利用大数据和人工智能技术等新技术进行旅游营销研究的议程。此外, 本文的结果填补了目前的研究空白, 因为虽然有文献综述涉及旅游与大数据或市场营销, 但这些领域还没有被作为一个整体来研究。

This study examines how tourists’ buying behavior toward souvenirs plays a pivotal role and explores the moderating role of prominent souvenirs in the marketing context. This study aims to examine the importance and the current status of the souvenir purchase behavior in Raghurajpur and Pipili village of Puri district in Odisha.

Purchasing behaviors of tourists such as different variables and tourist demographics were examined. The current study used the structural equation model (SEM) and regression in analyzing unique data from 400 tourists visiting the villages.

The research findings indicate that all the variables taken into consideration for research are accurate and are positively associated with tourist engagement in souvenir buying. All the factors are taken into consideration also proved significant toward the dependent variable, i.e. buying behavior. It is argued that adequate attention to the purchase behavior of tourists was not given by academic scholars, professionals and officials in Odisha.

The current study was limited to the two prominent villages of Odisha famous for handicrafts. Future research might address behavioral studies in other states of India or the place of Odisha. In the present study, data were collected from the tourist sample while exiting the village after shopping. Methods could be developed to elicit responses from tourists after they reached their homes to determine if their responses toward souvenir buying differ. Souvenirs and souvenir buying behavior is an untapped field of research in India.

This study has enormous potential to contribute to the existing literature on souvenir purchase behavior of tourists in Indian context. The current study will use the identified variables to predict the behavior of tourists towards souvenirs so that craftsmen and policy makers can make an effective marketing mix to brand the souvenirs.

This study is intended to anchor on souvenir purchase patterns of tourists in Pipili and Raghurajpur. An investigation of tourist shopping orientations for souvenir product holds potential for retailers to better direct marketing efforts to a non-local clientele. Understanding and analyzing variables would give government, craftsmen and other stakeholders to properly make marketing strategies for the handicraft sector. Handicrafts of Odisha are rapidly becoming commercialized items, and the authenticity is dying. This study can make the stakeholders aware of the tourist’s needs and preferences.

The authors provide a holistic and grounded understanding of the souvenir buying behavior of tourists in two prominent villages of Odisha through SEM and other indicators of souvenir buying from tourist’s perspective.

The ongoing COVID-19 pandemic highlights the importance of destination marketing and media profiling to re-engage international tourists. However, potential crisis-induced nation brand (NB) deficits must be addressed to re-ignite tourism demand. The study examines the possible intervening effect of the contemporary NB in the international destination marketing and media-travel motives nexus.

A deductive quantitative study was undertaken with an online Amazon Mechanical Turk sample of n = 454 respondents. Hypotheses were tested using PROCESS Macro, Model 4.

The results show that the NB [people and negative events] had a practically significant partial mediating effect in the destination marketing – nature-cultural oriented travel motivation nexus.

New insights are provided via a practical model which facilitates the measurement of potential nuances in the influence of destination marketing and media profiling on leisure tourists' travel motives amid crises. The intervening effect implies that a better understanding of the NB as an indirect antecedent to travel motivation may result in more effective crisis communications and tourism recovery-oriented marketing.

The study is amongst the first to extend marketing and behavioural theory to explore the interplay between the marketing and media profile, a nation's brand and tourists' travel behaviour amid a crisis. The study addresses a discernible dearth of knowledge related to the influence of the NB on tourist behaviour from an emerging market perspective.

The theoretical framework of this study focuses on the trends towards experiential tourism and new communication channels in the tourist sector. The specific areas of action that are covered in this research work focus on: a definition of experiential tourism, an analysis of markets as a resource of experiential tourism and communication strategies and the use of social media by the markets of Madrid to interact with the new experiential consumer.

This paper is arranged as follows: first, a review of the documents on new tourist sector trends towards the demand of experiential tourism, on marketing 2.0 and on social media has been carried out; second, communication strategies of the food markets seen as tourist resources are described herein, including results of the research in the use of social media; and finally, conclusions of the study are developed.

According to the conceptual approach and after reviewing the documents cited in this paper, it is possible to conclude that food markets are tourist resources that shall be exploited as “experiential providers” for a market niche that is increasingly demanding and expects to have a “tourist experience”. The present paper contributes to the literature on experiential tourism, including new communication strategies as a tool to contact experiential tourists. Accordingly, an analysis is carried out of a specific product/resource, such as the food markets of Madrid as resources or experiential leisure centers, and a study on product strategies (offer of experiences) and communication strategies on their experiential tourism offer fundamentally based on social media and websites.

Although this work represents an in-depth study of the food markets analyzed, the research could be extended to other markets or to other cities that are also working with markets as experiential tourism resources, though not in a structured design as in Madrid.

This work is different from previous studies for several reasons. In the first place, food markets are integrated as elements for the study of experiential tourism as tourist resources, and second, commercial interaction and other types of productive activities in urban centers are considered. In particular, social relations and collaboration between small retailers in markets, their managers and the institutions responsible for tourism management in the city of Madrid are barely analyzed in the literature. This includes the collaboration between public (Madrid City Council), cultural and business institutions (Madrid Fusión and Gastrofestival), hospitality and other businesses (established in the food markets) to promote cultural experiences and historic tourism.

The performed study has several implications for employers and policymakers. As historical, cultural and experiential tourism are growing trends throughout the world, new tourist consumer profiles must be analyzed. There are new groups of tourists looking for unique experiences and “local” activities, eager to visit renovated urban historical centers with a developed experiential leisure offer. This tourist activity facilitates the rebirth of the traditional food markets and promotes the creation of jobs and new opportunities for traditional businesses as shown in the present case study focused on the markets of Madrid.

The present paper contributes to the literature on experiential tourism, including new communication strategies as a tool to contact experiential tourists. Accordingly, an analysis is carried out of a specific product/resource, such as the food markets of Madrid as resources or experiential leisure centers, and a study on product strategies (offer of experiences) and communication strategies on their experiential tourism offer fundamentally based on social media and websites. The role played by food markets in the creation of an experiential tourism offer in Madrid and the communication strategies generated by them is described in this research. This study not only sheds light on the changes undergone by the tourist demand, specifically urban tourism but also it helps understand some of the strategies that big tourist cities are implementing in historic centers to reduce the risks of mass tourism.

The purpose of this study is to unearth the factors that influence tourists’ revisit intention. The proposed model of the study is grounded on using the theory of planned behaviour (TPB) and extending it with additional variables, i.e. satisfaction, destination image, perceived risk, service quality and perceived value.

This study adopted a cross-sectional approach to collect data. The data were collected by conducting a field survey questionnaire on 330 respondents and were analysed using partial least squares version 3.2.9.

The results show that perceived behavioural control, perceived value, destination image and satisfaction significantly affect visitors’ revisit intention. The influence of perceived value, perceived service quality and destination image on satisfaction is also confirmed. On the other hand, satisfaction is found to be a significant mediator between perceived service quality, destination image and perceived value.

The extended TPB model that includes perceived service quality, perceived value, perceived risk and satisfaction provided a model with a theoretical basis to explain tourist revisit intentions to a tourist destination.

El objetivo principal del estudio es descubrir los factores que influyen en la intención de revisita de los turistas. El modelo propuesto para el estudio se basa en el uso de la teoría del comportamiento planificado y se amplía con variables como la satisfacción, la imagen del destino, el riesgo percibido, la calidad del servicio y el valor percibido.

Este estudio adoptó un enfoque transversal para la recogida de datos. Los datos se recopilaron mediante un cuestionario de campo en el que participaron 330 encuestados. Los datos se analizaron utilizando la versión 3.2.9 de PLS.

Los resultados muestran que el control conductual percibido, el valor percibido, la imagen del destino y la satisfacción afectan significativamente a la intención de revisita. También se confirma la influencia del valor percibido, la calidad de servicio percibida y la imagen del destino sobre la satisfacción. Por otra parte, la satisfacción resulta ser un mediador significativo entre la calidad de servicio percibida, la imagen del destino y el valor percibido.

El modelo TPB ampliado que incluye la calidad de servicio percibida, el valor percibido, el riesgo percibido y la satisfacción proporcionó un modelo con una base teórica para explicar las intenciones de revisita de los turistas a un destino turístico.

本研究的目的是揭示影响游客重访意向的因素。本研究提出的模型以计划行为理论（TPB）为基础, 并以额外的变量（即满意度、目的地形象、感知风险、服务质量和感知价值）进行扩展。

本研究采用了横断面的方法来收集数据。通过对330名受访者进行实地调查问卷来收集数据, 并使用偏最小二乘法3.2.9版进行分析。

结果显示, 感知行为控制、感知价值、目的地形象和满意度对游客的再访意向有显著影响。感知价值、感知服务质量和目的地形象对满意度的影响也被证实。另一方面, 满意度被发现是感知服务质量、目的地形象和感知价值之间的一个重要中介因素。

包括感知服务质量、感知价值、感知风险和满意度在内的扩展TPB模型为解释游客对旅游目的地的再访意向提供了理论基础。

关键词: 满意度; 旅游; 计划行为理论; PLS-SEM; 目的地形象

As the tourism industry becomes more vital for the success of many economies around the world, the importance of technology in tourism grows daily. Alongside increasing tourism importance and popularity, the amount of significant data grows, too. On daily basis, millions of people write their opinions, suggestions and views about accommodation, services, and much more on various websites. Well-processed and filtered data can provide a lot of useful information that can be used for making tourists' experiences much better and help us decide when selecting a hotel or a restaurant. Thus, the purpose of this study is to explore machine and deep learning models for predicting sentiment and rating from tourist reviews.

This paper used machine learning models such as Naïve Bayes, support vector machines (SVM), convolutional neural network (CNN), long short-term memory (LSTM) and bidirectional long short-term memory (BiLSTM) for extracting sentiment and ratings from tourist reviews. These models were trained to classify reviews into positive, negative, or neutral sentiment, and into one to five grades or stars. Data used for training the models were gathered from TripAdvisor, the world's largest travel platform. The models based on multinomial Naïve Bayes (MNB) and SVM were trained using the term frequency-inverse document frequency (TF-IDF) for word representations while deep learning models were trained using global vectors (GloVe) for word representation. The results from testing these models are presented, compared and discussed.

The performance of machine and learning models achieved high accuracy in predicting positive, negative, or neutral sentiments and ratings from tourist reviews. The optimal model architecture for both classification tasks was a deep learning model based on BiLSTM. The study’s results confirmed that deep learning models are more efficient and accurate than machine learning algorithms.

The proposed models allow for forecasting the number of tourist arrivals and expenditure, gaining insights into the tourists' profiles, improving overall customer experience, and upgrading marketing strategies. Different service sectors can use the implemented models to get insights into customer satisfaction with the products and services as well as to predict the opinions given a particular context.

This study developed and compared different machine learning models for classifying customer reviews as positive, negative, or neutral, as well as predicting ratings with one to five stars based on a TripAdvisor hotel reviews dataset that contains 20,491 unique hotel reviews.

The main objective of this research is to analyze satisfaction with tourist services linked to the concept of sustainability in the context of a visit to the so-called equestrian show. The equestrian show adds values from the cultures that passed through the city. Specifically, the study focuses on tourist loyalty based on satisfaction with tourist services, satisfaction with the equestrian show and its overall quality. The fieldwork has been conducted in Córdoba, Spain. There are few studies on the relationship between tourist services linked to the concepts of sustainability and loyalty from the perspective of equestrian show management, making this a novel contribution to research.

The methodology used is based on a partial least squares structural equation modeling (PLS-SEM) approach.

To achieve the proposed objective, a structured questionnaire was used, and the results obtained confirm that satisfaction with tourist services linked to the concept of sustainability and the assessment of quality positively influence tourist loyalty. Consequently, they recommend returning to the destination and repeating the visit.

Heritage in Córdoba, Spain, is internationally recognized. Its uniqueness, with four world inscriptions along with the cultures that inhabited it, left a material heritage legacy in the city. Over time, this legacy has made it a magnet for visitors, making it essential to delve into its management and how concepts such as satisfaction with tourist services, combined with sustainability, impact the improvement of the visit.