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CXC CSEC Social Studies exam guide - Section C3: Tourism

CXC CSEC Social Studies Exam Guide: OPTIONS: Section C3: Tourism

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In This Article Expand or collapse the "in this article" section Sociology of Tourism

Introduction, general overviews.

• Anthologies, Edited Collections, and Review Articles
• Evolutionary Sociology Perspectives in Tourism
• Neo-Durkheimian Perspectives in Tourism
• Marxist and Critical Theory Perspectives in Tourism
• Functionalist Perspectives in Tourism
• Weberian Perspectives
• Formalism and Phenomenological Perspectives in Tourism
• Symbolic Interactionist Perspectives in Tourism
• Bourdieusian and Practice-Based Theory Perspectives in Tourism
• Contemporary Sociology of Tourism in the Post-truth Era

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Sociology of Tourism by Erdinç Çakmak LAST MODIFIED: 23 August 2022 DOI: 10.1093/obo/9780199756384-0263

The sociology of tourism studies tourists’ relationships, roles, and motivations and the ongoing exchange among tourists, institutions, and host communities. Tourism cannot be treated in isolation since it embodies all tourism practices in a system they operate in. Thus, tourism is a complex sociocultural, economic, and political phenomenon and touches all levels of society. The investigation of tourism’s role in society, the tourism system’s effects on nature, tourism spaces, objects, practices, relationships, and the tourist typologies demand systematic sociological investigations. A researcher needs to consider the whole macro system through its members’ social, political, cultural, and economic interactions. In such a social context, both human and nonhuman actors continuously shape and reshape the tourism system, and the tourism system reshapes these actors’ values, attitudes, and behaviors. Researchers examining the sociology of tourism departed from several theoretical Perspectives , blended theory and method, and focused on sociological concepts to understand and explain the different aspects of tourism. This group of scholars has been working within the several cores of sociology (e.g., education, family, economy, development, religion, gender, language, migration, social inequalities, labor, art) and at the margins of emerging interdisciplinary formations, including those crossing many disciplines such as geography, anthropology, economics, political science, psychology, marketing, communication, women’s studies, history, and cultural studies. The sociology of tourism studies engendered transdisciplinary conversations both in academia and in practice, and the results of these studies have created pragmatic changes in tourism practices, habits, and governance.

Five scholars, judging from the Google Scholar citation counts of their critical works on the sociology of tourism, have contributed to the field in an original and pioneering way. These leading scholars’ abundant and consistent publications have provided the foundation for a sociological approach to tourism. They can be called the established leaders of the sociology of tourism, and are listed here alphabetically: Erik Cohen, Graham Dann, Marie-Françoise Lanfant, Dean MacCannell, and John Urry. Cohen 1972 opposed treating tourists as a homogenous mass and provided a heuristic tourist typology ranging from familiarity to strangeness. Later, Cohen 1984 classified tourism’s sociology into four main areas: tourist as a traveler, tourists’ relationships with hosts, the tourism system, and tourism impacts. MacCannell’s 1973 seminal article on staged authenticity spotlighted the relationship between tourism and (Western) modernity, which became an essential research agenda for the sociology of tourism in the last quarter of the twentieth century. MacCannell 1976 argued that alienated modern tourists are motivated by a quest for authenticity in their travels, but this quest is thwarted through a “staged authenticity” offered by host communities. Dann 1977 sought to answer the question “what makes tourists travel?” and employed the themes of anomie and collective representations in the sociology of tourism research. He combined anomie with status enhancement in a motivational study of tourists and provided the first empirical results of the presentation and profiles of anomic tourists. Besides this approach, Dann 1996 took a sociolinguistic approach and examined the promotional counterpart of tourist motivations in “the language of tourism” using semiotic analyses. Lanfant 1980 emphasized the international dimension of tourism. She argued that tourism is a “total social phenomenon” which challenges identity formation. Lanfant, et al. 1995 transcended the dichotomy between seeing tourism as either business or not business and suggested a novel approach reflecting the fundamental level of reality in tourism practice. Urry 1990 introduced Foucault’s concept of “gaze” into tourism discourse. Urry prioritized the visual sense of gaze and distinguished the tourist gaze as “romantic” and “collective” without concerning other Foucauldian issues of power and authority. By introducing the concept “gaze” into tourism, Urry made a crucial theoretical opening in the sociology of tourism, and other scholars followed him by focusing further on the body and other senses. Later in the decade, Urry 1999 proposed studying journeys, connections, and flows (both physical and virtual movements) as mobile theories and mobile methods and that this be placed at the top of the research agenda.

Cohen, E. 1972. Toward a sociology of international tourism. Social Research 39:64–82.

This article stresses the travel dimension of tourism and devises tourist typologies along a continuum from familiarity to strangeness. It emphasizes the differences among tourists and calls for further examination of their travel types’ attitudes, motivations, and behavior.

Cohen, E. 1984. The sociology of tourism: Approaches, issues, and findings. Annual Review of Sociology 10.1: 373–392.

DOI: 10.1146/annurev.so.10.080184.002105

This is a crucial academic text for understanding the classification of the sociology of tourism. Cohen classifies tourism into four main areas: tourists, their interaction with hosts, the tourism system, and tourism impacts. Following this article, scholars have given more attention to systematic empirical research in the field.

Dann, G. M. 1977. Anomie, ego-enhancement and tourism. Annals of Tourism Research 4.4: 184–194.

DOI: 10.1016/0160-7383(77)90037-8

This paper maintains that tourists’ anomie (i.e., absence of the general societal and ethical standards) needs to be investigated at the pre-travel level. This sociopsychological research is the first empirical research of tourists’ attitudes and behavior and it provides a firmer theoretical and empirical footing to the literature on tourist profiles.

Dann, G. M. 1996. The language of tourism: A sociolinguistic perspective . Wallingford, UK: CAB International.

This book analyzes the verbal framing of tourists’ experiences. Paradigms on social control, the tourist as a child, and the tourism media from the printed word to television screen have been brought together with semiotic analyses at a quality level.

Lanfant, M. F. 1980. Introduction: Tourism in the process of internationalisation. International Social Science Journal 32.1: 14–43.

This article captures the multipolarity of tourism as a particular form of consumption. The author provides insights into world tourism organizations and the role of international bodies and tour operators by using the methodological principles of systems analysis.

Lanfant, M. F., J. B. Allcock, and E. M. Bruner, eds. 1995. International tourism: Identity and change . London: SAGE.

This book offers a novel approach in examining how tourism transcends individual societies and has become an international fact. It emphasizes the necessity of understanding the local and global developments simultaneously. The volume argues that local social practices cannot be understood independently of the global, and that the global practices are never independent of the local setting in which they operate.

MacCannell, D. 1973. Staged authenticity: Arrangements of social space in tourist settings. American Journal of Sociology 79.3: 589–603.

DOI: 10.1086/225585

This academic article and the ensuing book have dominated the discussions in the sociology of tourism in the last quarter of the twentieth century. This study describes the alienation of Western tourists and their search for authentic experiences in other times and places while hosts modify a cultural practice for tourism.

MacCannell, D. 1976. The tourist: A new theory of the leisure class . New York: Schocken.

This is the most influential book in the sociology of tourism and it portrays the role of tourists in postindustrial society. Tourists seek meanings to their deepest longings and travel as pilgrims to the secular world, paying homage to various attractions that are symbols of modernity.

Urry, J. 1990. The tourist gaze: Leisure and travel in contemporary societies . London: SAGE.

This book takes a postmodernist perspective and describes the foundation of tourist behavior in the form of a tourist gaze. Here tourism becomes a performance and acts as a central element in the broad cultural changes in contemporary society.

Urry, J. 1999. Sociology beyond societies: Mobilities for the twenty-first century . London: Routledge.

In this book, Urry suggests the necessity of replacing the examination of society as the traditional basis of sociology from bounded clusters and objects of a region to networks and fluids in the borderless world. The book studies the physical and virtual movements of people, ideas, messages, money, and waste products across international borders.

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What Does Social Tourism Mean and How it is Redefining Travel? 

What does social tourism mean? 

How is it usually financed , what is the objective of social tourism , how can we help social tourism , real-life examples, final thoughts .

The tourism industry offers an abundance of benefits. It encourages economic growth, creates jobs, and brings massive amounts of revenue to some of the most popular tourism destinations. However, it’s not always beneficial directly to the local communities, and it’s not always accessible to all . 

On average, from every $100 spent by travelers in developing countries, only $5 stays in the local economy , resulting in significant tourism leakage . The widely-adopted traveling practices such as booking hotel accommodations, buying mass-produced souvenirs, or choosing international food chains rather than local restaurants often cause long-term harm to the community. 

Not to mention the issues of over-tourism that disrupts the daily life of the locals, increases pollution, and harms the environment. 

Fortunately, trends are changing in the tourism sector. Travelers are becoming increasingly aware of the consequences of over-tourism and how this issue is impacting the destinations they visit – which is why more and more people are starting to adopt social and sustainable tourism . 

Social tourism is a growing trend that prioritizes building positive relationships between visitors and host communities and developing “ programs, events, and activities that allow all population groups to enjoy tourism ”. 

Take a look below to learn what social tourism entails and how it’s redefining travel. 

Social tourism is a broad concept that encompasses countless events and activities. Different holiday types, such as working holidays , for instance, can fall under the category of social tourism. Activities you engage in at the destination, the type of destination you choose, and even the type of accommodation you book or some unique client group a tourism organization works with could all be labeled as social tourism. 

In a nutshell, social tourism focuses on providing economic, social, and cultural benefits to travelers and their host communities. 

On the one hand, travelers can participate in social tourism by contributing to their destinations – volunteering, participating in local projects, helping build homes for disadvantaged local groups, supporting local artists and crafters, donating, and more. 

On the other hand, some travelers can be the beneficiaries of social tourism . Countless government and private tourism organizations provide travel opportunities to those groups that wouldn’t otherwise be able to enjoy traveling – impoverished families, people with disabilities, children, and seniors, for instance. 

Moreover, some popular travel destinations are starting to invest in building a more accessible infrastructure that improves the traveling experience for all. You’ll find wheelchair-accessible beaches in Cyprus , braille-etched railings at Castel Sant’Elmo in Naples, and “ touchable paintings ” at museums worldwide. 

Considering that social tourism can take many forms, it’s not surprising that it’s known under many different names – sustainable tourism, accessible tourism, tourism for all, enlightening tourism, and responsible tourism , among others. 

Social tourism can be financed in one of several ways, depending on its particular type. If you want to contribute to the destination you’re visiting, you’d most commonly have to finance any activities and events you participate in out of pocket . 

You could join a charitable organization that covers expenses for certain activities, such as building homes for the locals, for instance, where it might cover the costs of the materials. However, you’d still likely have to pay for any other travel-related expenses yourself – accommodation, transportation, food, and more. 

Social tourism events and activities for children, impoverished families, people with disabilities, and others, on the other hand, are most commonly fully financed by local and federal governments , employers, non-profit organizations, and charities . On occasion, the participants could even receive a small spending allowance that enables them to fully enjoy their travels. 

The main objectives of social tourism include: 

• Supporting local communities – leaving a positive mark on the communities in your travel destinations; 
• Discovering new destinations – visiting places off the beaten path and going to less traveled-to countries; 
• Learning about new cultures – getting to know the locals, their languages, cultures, traditions, and history; 
• Providing economic benefits to host countries – shopping local, investing in arts and crafts from the local artists, improving the local economy; 
• Making travel accessible to all – allowing everyone to experience the wonders of traveling, regardless of their socio-economic group, age, health, or more. 

Ultimately, the main goal of social tourism is connecting travelers with their host countries, helping build international relationships, and making travel more enjoyable and more responsible. 

There are multiple ways to promote and support social tourism: 

• Support charities and non-profits – many social tourism charities rely on contributions from individuals to create immersive programs and activities that help tourists and host countries; 
• Make donations – donate to relevant organizations that support local communities in your favorite travel destinations or those that offer travel opportunities to underprivileged groups in your area; 
• Volunteer – join volunteer groups that connect you with locals; 
• Avoid popular destinations – go off the beaten path and travel to lesser-known destinations; 
• Talk to your local government representatives – as many social travel activities are government-funded, you can talk to the local representatives to find the best ways to support social tourism. 

You don’t have to go out of your way to support social tourism. Even minor changes to your typical traveling habits could help – booking accommodation with a host family instead of a hotel, buying souvenirs from local artists, eating at small local restaurants, recycling while traveling, and more. 

As evidenced so far, Social Tourist isn’t just a Charlie D’Amelio’s apparel brand. It’s an increasingly important concept that presents immeasurable benefits to travelers and their host communities. Therefore, it’s not surprising that we’re seeing more and more real-life examples of social tourism. 

Take a look at just a few organizations that are helping make social tourism mainstream. 

Make a Difference (MAD) Travels 

Make a Difference (MAD) Travels is a unique social entrepreneurship based in the Philippines. It offers sustainable, one-of-a-kind travel experiences to international tourists who want to make a difference. It focuses on building relationships between travelers and their destinations of choice , leading exciting off-the-beaten-path tours, introducing travelers to the local cultures, and offering educational courses and experiences. 

What’s more, MAD Travels enables you to support local communities even from a distance. You can support communities in Zambales or Rizal by gifting a tree planted on your behalf or shopping for local Filipino products like organic honey or bamboo straws directly from the Mad Travels site. 

Awaken 

Awaken is all about traveling with a purpose. Based in Ecuador, it started as an at-risk youth foundation and has evolved into a social tourism organization that helps you support the communities you visit while enjoying immersive travel experiences. 

The organization’s main aim is to support children and their parents who come from juvenile detention centers and immerse them back into society. By joining one of Awaken’s programs, you can travel to some of Ecuador’s most mesmerizing destinations, join volunteer groups, go on active tours, and learn all about the local people, culture, and history. 

Invisible Cities 

Invisible Cities is a UK-based social enterprise that supports homeless people through travel. Currently available only in some of the biggest cities in the UK, including Glasgow, Manchester, Edinburgh, Cardiff, and York, it helps teach homeless people how to become walking tour guides in their cities. 

Invisible Cities offers comprehensive skill-building training and encourages its guides to deliver authentic tours focusing on the monuments and locations they have chosen. 

The organization aims to dispel myths and stereotypes regarding homelessness and improve the lives of those impacted by it. 

Operation Groundswell 

Operation Groundswell offers immersive programs across Central and South America, East Africa, and Asia, redefining backpacking experiences and allowing you to get truly immersed in the cultures you’re exploring. 

Started by a group of backpacking enthusiasts, it’s grown to be one of the largest organizations of its kind. You can join open, pre-planned programs or even design your own custom experiences. Choose the regions you want to visit, select the theme you’d like to learn more about (such as human rights, health, environment, or education), and design an active holiday you’ll never forget. 

Good Travel 

Good Travel promotes travel experiences that lead to a positive social, economic, and environmental impact. To that end, the organization collaborates with local businesses that give back to their communities, partners with international non-profit organizations, and donates to countless global charities. 

Each trip is designed to fit the Good Travels ethos, offset our carbon footprint, support marginalized groups, boost the local economy, and deliver memorable travel experiences. 

Although there are many pre-planned trips to countries like Peru, New Zealand, Fiji, and others, you can also develop a personalized itinerary that suits your traveling preferences. 

Okavango Craft Brewery 

Okavango Craft Brewery in Northern Botswana is a unique addition to the list. Not specifically created as a social tourism organization but rather a great local brewery with a cause, it enables you to support Okavango’s people and elephants and enjoy good beer made from locally-sourced ingredients. 

As you enjoy your dinner and drinks, you’ll help the brewery support the NGO EcoExist non-profit organization that helps promote a sustainable existence between farmers and elephants in areas with high elephant-human conflict. If you’re traveling in the area, pay the brewery a visit to help support the farmers that allow you to enjoy local beers. 

Have Fun Do Good 

Have Fun Do Good (HFDG) is an organization developed for adventure-seekers who want to do good on their travels. Whether staying close to home or traveling to far-off destinations, HFDG helps you create immersive travel experiences and join volunteer programs that enable you to make a difference. 

You’ll get to meet new people, explore beautiful locations, learn about new cultures, and support international charities. 

HFDG offers small group travel experiences and corporate events that can improve your team-building and help your business support good causes. 

International Social Tourism Organisation (ISTO)

International Social Tourism Organisation (ISTO) is one of the largest (and oldest) social tourism non-profits, established in 1963. It promotes responsible, accessible tourism for all that benefits individuals and communities across the globe. 

The organization has five primary goals to improve: 

• Accessibility; 
• Fair business; 
• Environment; 
• Solidarity; 
• Quality of life. 

ISTO aims to make leisure, holidays, and tourism accessible to all – the youth, seniors, people with disabilities, and others. It partners with local businesses and governments to create opportunities for everyone to enjoy tourism without limitations while simultaneously supporting and benefiting the local populations, their cultural heritage, and their environment. 

Elevate Destinations 

Elevate Destinations operates under the belief that travel is sacred, and as such, it should always have a positive social and environmental impact. Therefore, it offers memorable travel experiences that help you find greater meaning in the world while connecting with coglobal communities, supporting the environment, and preserving our natural surroundings. 

Elevate Destinations offers immersive, family-friendly trips, adventurous travels for adrenaline-seekers, learning journeys, charity challenges, donor travel experiences, and more for individuals and organizations alike. 

Moreover, it’s developed a new travel program, “Buy a Trip, Give a Trip”, that allows you to support local youths. The program gives local children an opportunity to visit some of the most popular tourist sites in their own countries. 

Responsible Travel 

Last but certainly not least is Responsible Travel , an organization that focuses on nature preservation and empowering local communities. It prioritizes responsible travel, reducing carbon emissions, developing accessible travel opportunities, and organizing volunteer events that allow you to give back to the communities you’re visiting. 

It also has a “Trip for Trip” program that allows you to send a disadvantaged child on a day trip when you book your own holiday, all at no additional cost. 

Social tourism is quickly taking off, becoming one of the biggest tourism trends of the decade. Allowing you to visit some of the most astonishing destinations, support your host communities, preserve nature, and make travel accessible to all, social tourism is making a world of difference one trip at a time. 

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Marc Truyols has a degree in Tourism from the University of the Balearic Islands. Marc has extensive experience in the leisure, travel and tourism industry. His skills in negotiation, hotel management, customer service, sales and hotel management make him a strong business development professional in the travel industry.

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UN Tourism | Bringing the world closer

Ethics, Culture and Social Responsibility

• Global Code of Ethics for Tourism
• Accessible Tourism

Tourism and Culture

• Women’s Empowerment and Tourism

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The convergence between tourism and culture, and the increasing interest of visitors in cultural experiences, bring unique opportunities but also complex challenges for the tourism sector.

“Tourism policies and activities should be conducted with respect for the artistic, archaeological and cultural heritage, which they should protect and pass on to future generations; particular care should be devoted to preserving monuments, worship sites, archaeological and historic sites as well as upgrading museums which must be widely open and accessible to tourism visits”

UN Tourism Framework Convention on Tourism Ethics

Article 7, paragraph 2

This webpage provides UN Tourism resources aimed at strengthening the dialogue between tourism and culture and an informed decision-making in the sphere of cultural tourism. It also promotes the exchange of good practices showcasing inclusive management systems and innovative cultural tourism experiences .  

About Cultural Tourism

According to the definition adopted by the UN Tourism General Assembly, at its 22nd session (2017), Cultural Tourism implies “A type of tourism activity in which the visitor’s essential motivation is to learn, discover, experience and consume the tangible and intangible cultural attractions/products in a tourism destination. These attractions/products relate to a set of distinctive material, intellectual, spiritual and emotional features of a society that encompasses arts and architecture, historical and cultural heritage, culinary heritage, literature, music, creative industries and the living cultures with their lifestyles, value systems, beliefs and traditions”. UN Tourism provides support to its members in strengthening cultural tourism policy frameworks, strategies and product development . It also provides guidelines for the tourism sector in adopting policies and governance models that benefit all stakeholders, while promoting and preserving cultural elements.

Recommendations for Cultural Tourism Key Players on Accessibility 

UN Tourism , Fundación ONCE and UNE issued in September 2023, a set of guidelines targeting key players of the cultural tourism ecosystem, who wish to make their offerings more accessible.

The key partners in the drafting and expert review process were the ICOMOS International Cultural Tourism Committee and the European Network for Accessible Tourism (ENAT) . The ICOMOS experts’ input was key in covering crucial action areas where accessibility needs to be put in the spotlight, in order to make cultural experiences more inclusive for all people.

This guidance tool is also framed within the promotion of the ISO Standard ISO 21902 , in whose development UN Tourism had one of the leading roles.

Download here the English and Spanish version of the Recommendations.

Compendium of Good Practices in Indigenous Tourism

The report is primarily meant to showcase good practices championed by indigenous leaders and associations from the Region. However, it also includes a conceptual introduction to different aspects of planning, management and promotion of a responsible and sustainable indigenous tourism development.

The compendium also sets forward a series of recommendations targeting public administrations, as well as a list of tips promoting a responsible conduct of tourists who decide to visit indigenous communities.

For downloads, please visit the UN Tourism E-library page: Download in English - Download in Spanish .

Weaving the Recovery - Indigenous Women in Tourism

This initiative, which gathers UN Tourism , t he World Indigenous Tourism Alliance (WINTA) , Centro de las Artes Indígenas (CAI) and the NGO IMPACTO , was selected as one of the ten most promising projects amoung 850+ initiatives to address the most pressing global challenges. The project will test different methodologies in pilot communities, starting with Mexico , to enable indigenous women access markets and demonstrate their leadership in the post-COVID recovery.

This empowerment model , based on promoting a responsible tourism development, cultural transmission and fair-trade principles, will represent a novel community approach with a high global replication potential.

Visit the Weaving the Recovery - Indigenous Women in Tourism project webpage.

Inclusive Recovery of Cultural Tourism

The release of the guidelines comes within the context of the International Year of Creative Economy for Sustainable Development 2021 , a UN initiative designed to recognize how culture and creativity, including cultural tourism, can contribute to advancing the SDGs.  

UN Tourism Inclusive Recovery Guide, Issue 4: Indigenous Communities

Sustainable Development of Indigenous Tourism

The Recommendations on Sustainable Development of Indigenous Tourism provide guidance to tourism stakeholders to develop their operations in a responsible and sustainable manner within those indigenous communities that wish to:

• Open up to tourism development, or
• Improve the management of the existing tourism experiences within their communities.

They were prepared by the UN Tourism Ethics, Culture and Social Responsibility Department in close consultation with indigenous tourism associations, indigenous entrepreneurs and advocates. The Recommendations were endorsed by the World Committee on Tourism Ethics and finally adopted by the UN Tourism General Assembly in 2019, as a landmark document of the Organization in this sphere.

Who are these Recommendations targeting?

• Tour operators and travel agencies
• Tour guides
• Indigenous communities
• Other stakeholders such as governments, policy makers and destinations

The Recommendations address some of the key questions regarding indigenous tourism:

Download PDF:

• Recommendations on Sustainable Development of Indigenous Tourism
• Recomendaciones sobre el desarrollo sostenible del turismo indígena, ESP

UN Tourism/UNESCO World Conferences on Tourism and Culture

The UN Tourism/UNESCO World Conferences on Tourism and Culture bring together Ministers of Tourism and Ministers of Culture with the objective to identify key opportunities and challenges for a stronger cooperation between these highly interlinked fields. Gathering tourism and culture stakeholders from all world regions the conferences which have been hosted by Cambodia, Oman, Türkiye and Japan have addressed a wide range of topics, including governance models, the promotion, protection and safeguarding of culture, innovation, the role of creative industries and urban regeneration as a vehicle for sustainable development in destinations worldwide.

Fourth UN Tourism/UNESCO World Conference on Tourism and Culture: Investing in future generations. Kyoto, Japan. 12-13 December 2019 Kyoto Declaration on Tourism and Culture: Investing in future generations ( English, French, Spanish, Arabic, Russian and Japanese )

Third UN Tourism/UNESCO World Conference on Tourism and Culture : For the Benefit of All. Istanbul, Türkiye. 3 -5 December 2018 Istanbul Declaration on Tourism and Culture: For the Benefit of All ( English , French , Spanish , Arabic , Russian )

Second UN Tourism/UNESCO World Conference’s on Tourism and Culture: Fostering Sustainable Development. Muscat, Sultanate of Oman. 11-12 December 2017 Muscat Declaration on Tourism and Culture: Fostering Sustainable Development ( English , French , Spanish , Arabic , Russian )

First UN Tourism/UNESCO World Conference’s on Tourism and Culture: Building a new partnership. Siem Reap, Cambodia. 4-6 February 2015 Siem Reap Declaration on Tourism and Culture – Building a New Partnership Model ( English )

UN Tourism Study on Tourism and Intangible Cultural Heritage  

The first UN Tourism Study on Tourism and Intangible Cultural Heritage provides comprehensive baseline research on the interlinkages between tourism and the expressions and skills that make up humanity’s intangible cultural heritage (ICH). 

Through a compendium of case studies drawn from across five continents, the report offers in-depth information on, and analysis of, government-led actions, public-private partnerships and community initiatives.

These practical examples feature tourism development projects related to six pivotal areas of ICH: handicrafts and the visual arts; gastronomy; social practices, rituals and festive events; music and the performing arts; oral traditions and expressions; and, knowledge and practices concerning nature and the universe.

Highlighting innovative forms of policy-making, the UN Tourism Study on Tourism and Intangible Cultural Heritage recommends specific actions for stakeholders to foster the sustainable and responsible development of tourism by incorporating and safeguarding intangible cultural assets.

UN Tourism Study on Tourism and Intangible Cultural Heritage

• UN Tourism Study
• Summary of the Study

Studies and research on tourism and culture commissioned by UN Tourism

• Tourism and Culture Synergies, 2018
• UN Tourism Study on Tourism and Intangible Cultural Heritage, 2012
• Big Data in Cultural Tourism – Building Sustainability and Enhancing Competitiveness (e-unwto.org)

Outcomes from the UN Tourism Affiliate Members World Expert Meeting on Cultural Tourism, Madrid, Spain, 1–2 December 2022

UN Tourism and the Region of Madrid – through the Regional Ministry of Culture, Tourism, and Sports – held the World Expert Meeting on Cultural Tourism in Madrid on 1 and 2 December 2022. The initiative reflects the alliance and common commitment of the two partners to further explore the bond between tourism and culture. This publication is the result of the collaboration and discussion between the experts at the meeting, and subsequent contributions.

Relevant Links

• 3RD UN Tourism/UNESCO WORLD CONFERENCE ON TOURISM AND CULTURE ‘FOR THE BENEFIT OF ALL’

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Sustainable Growth of Social Tourism: A Growth Mixture Modeling Approach Using Heterogeneous Travel Frequency Trajectories

Jaeseok lee.

1 Faculty of Hospitality and Tourism Management, Macau University of Science and Technology, Macao, China; om.ude.tsum@eelkoeseaj

2 Doctor of Business Administration Program, Goldey-Beacom College, Wilmington, DE 19808, USA

Associated Data

Publicly available datasets were analyzed in this study. This data can be found here: [ https://www.tour.go.kr , accessed on 7 May 2021].

As travel activity has gained attention as one of the essential ways of understanding the sustainable growth of social tourism, a growing number of research projects have been conducted to elucidate the relationship between residents’ travel quantity (frequency) and quality (experience) in both macro and micro perspectives. Yet, very little research has highlighted that travel opportunities are not equally available to residents, especially a longitudinal perspective. The current study classified domestic travelers into four distinct classes using four years of longitudinal data from 5054 Korean residents. Latent growth curve modeling (LGCM) and growth mixture modeling (GMM) were employed to find out (1) the optimal number of classes, (2) the longitudinal travel frequency trajectory of each class, and (3) the distinctive demographic and travel characteristics of the four classes. This study provides some practical implications for policymakers when optimizing available resources for sustainable travel opportunities to relevant target sub-populations. Furthermore, detailed step-by-step analytic tutorials are also introduced for the extended application of longitudinal latent variable analysis in the tourism and hospitality fields, providing additional insights for relevant stakeholders.

1. Introduction

Tourism experience enriches individuals and society as a whole. Chen and Petrick [ 1 ] summarized the health and wellness benefits of travel experiences from previous studies and concluded that positive tourism experiences make travelers feel relaxed, healthier, less stressful, and, eventually, happier. Similarly, McCabe and Qiao [ 2 ] assert that tourism should be considered from a welfare perspective due to its positive effects on sustainability, mental health, quality of life, responsible tourism, and care-giving. Thus, these positive effects contribute to overall well-being and life satisfaction in general [ 3 , 4 ]. Social tourism, a form of social welfare provided by the government, is a clear example of a related tourism policy. Social tourism enhances the quality of life of all residents by providing additional opportunities to enjoy travel experiences, including those with a limited ability (e.g., money, time, and health) [ 5 , 6 , 7 , 8 , 9 , 10 ]. The World Tourism Organization adopted the Global Code of Ethics for Tourism in 1999, where the right to tourism is noted to address the importance of social tourism [ 11 ]. Similarly, the International Social Tourism Organisation emphasizes the importance of “Tourism for all” in an attempt to expand social tourism across the continents [ 8 ]. Alvarez-Sousa [ 10 ] and Griffin and Stacey [ 9 ] echoed the importance of a tourism-for-all policy in Europe and asserted that more research should be conducted globally.

Accordingly, many governments have put considerable effort into promoting leisure, recreation, and tourism activities. The increasing public consensus on social tourism started in the 1970s in South Korea, resulting in the establishment of the Tourism Basic Act in 1975 and the long-term Korean tourism development and promotion plan in 1979 [ 12 ]. Since then, the Korean government has developed various tourism-related laws, projects, and policies that aim to promote tourism activities for domestic tourists (e.g., Travel Week and TourDure project) [ 13 ]. More recently, private sectors have been actively engaged in social tourism offerings (e.g., cultural, recreational, and art activities) as part of their corporate social responsibility [ 14 ]. Although various efforts made by the Korean government and private sectors have ultimately promoted the growth of domestic tourism and the local economies of tourist destinations, the unique collaboration between public and private sectors in social tourism raises the question of whether tourism-for-all is implemented in Korea as it intended.

Meanwhile, the majority of social tourism studies have focused largely on cross-sectional outcomes, such as the overall impact on national tourism at a given time [ 10 , 15 ]. To the best of our knowledge, the year-on-year trends in travel patterns in terms of the individual-level travel frequency have been neglected in hospitality and tourism journals. Therefore, a longitudinal analysis at the individual level may provide additional insights into the tourism policy and its effect on individual behaviors. For example, the individual-level travel frequency pattern and their length of stay could help policymakers determine tourism demand at the national level [ 16 , 17 ], which eventually connects to nationwide tourism policy and/or strategy. More importantly, the understanding of travel frequency at the individual level and its determining factors are directly linked to the fluctuation and profitability of the domestic tourism market.

Recently, Xu and Martinez [ 18 ] called for further research based on LGCM to analyze repeated measures of longitudinal data in the hospitality and tourism fields. Besides, researchers usually adopt a family of longitudinal analysis (e.g., repeated measures analysis of variance, latent curve model, and panel data analysis) as their research design when exploring the changes in the outcome variable over time. These methods allow scholars to understand the overall trend over time based on the assumption of a homogenous population. Nevertheless, numerous hospitality and tourism studies have exclusively utilized cross-sectional research design to understand complex social phenomena and possibly neglect within-subject variations over time [ 18 , 19 ].

Furthermore, research recently published in hospitality and tourism fields strongly emphasized the importance of heterogeneity within the sample to get a clearer understanding of research questions [ 20 , 21 ]. To respond to these calls, researchers may need to incorporate person-centered (differences among unobserved subpopulations) and variable-centered (differences in outcome change) approaches into the analytic framework. Therefore, we suggest growth mixture modeling (GMM) as one of the possible analytic tools for solving the research question. GMM is “a method for identifying multiple unobserved sub-populations, describing longitudinal change within each unobserved sub-population, and examining differences in change among unobserved sub-populations” [ 22 ] (p. 565). In contrast to traditional longitudinal analytic techniques, GMM, as part of the family of latent variable modeling techniques, can identify unobserved heterogeneous subgroups among the population, thereby helping researchers understand heterogeneity in trajectories over time [ 23 ]. Notably, segmentation with cross-sectional data ignores the nonindependence of within-subject variations and the dynamic nature of between-subject variations over time [ 19 ]. However, GMM enables researchers to identify different sets of heterogeneous subpopulations (often called latent classes), where homogeneous trajectories (i.e., intercept and slope factors) are shared by within-class individuals. In other words, GMM can simultaneously cluster and describe changes in the outcome variable over time. Furthermore, it flexibly adds the predictors and distal outcomes to the trajectory, as well as the class membership variable. In a similar way to multinomial logistic and ordinary regression analysis, GMM analyzes the relationship between predictors and latent class membership, and between the membership and distal outcomes depending on the scale of the distal outcome variable(s).

Therefore, the current study aims ( 1 ) to examine the sustainable growth of social tourism in each heterogeneous social stratum with a focus on the Korean domestic travel market from a longitudinal perspective, and ( 2 ) to illustrate a step-by-step guide on the application of GMM. To do so, this study first explains the basic foundation of the GMM analytic framework in easy-to-understand language to facilitate the use of the statistical method in future studies for researchers with minimal statistical knowledge. This study uses nationwide panel survey data to illustrate the analytic procedure and the interpretation of the findings. Using the South Korean domestic travel frequency data, the present study identifies the trajectories of travel frequency among Korean tourists over time and further investigates the differences in demographic characteristics across distinct groups. In addition, we recommend further research topics that can utilize GMM in the hospitality and tourism fields.

2. Literature Review

2.1. social tourism.

The history of social tourism can be traced back to the nineteenth century, mostly in Europe, and the definition has changed throughout global historic events such as World War II and The Great Depression [ 2 ]. The recent definition of social tourism, “all activities, relationships and phenomena in the field of tourism resulting from the inclusion of otherwise disadvantaged and excluded groups in participation in tourism. The inclusion of these groups in tourism is made possible through financial or other interventions of a well-defined and social nature [ 24 ] (p. 29)” shows that social tourism is a civil right as a type of social welfare [ 11 ]. The co-word analysis of McCabe and Qiao [ 2 ] shows that social tourism is closely related to the keywords of the physical status of tourist (e.g., disabled and health) and age (e.g., senior and children), followed by potential positive consequences of social tourism (e.g., sustainable, quality of life, well-being, and happiness). Social tourism research, in this vein, has attempted to determine what groups have (and do not have) enough accessibility to tourism activity, and why and how (social exclusion and inclusion) [ 2 , 8 ].

Another stream of social tourism research has been conducted with a focus on sustainable tourism and community-based tourism as well [ 13 , 15 , 25 ]. Destination-focused social tourism research examines the sustainable economic growth of local tourism industries and destinations [ 2 ], and the collective well-being of local residents from the public health perspective [ 26 ]. Hartwell et al. [ 26 ] assert that there is a need for multidisciplinary research collaboration, including destination management, policy, capital, and activities, because excessive tourism activities (i.e., over-tourism) often cause a conflict between the local residents and tourism.

2.2. Overview of Growth Mixture Modeling (GMM)

GMM has been developed from the concept of a generalized latent variable modeling framework. Muthén and Muthén [ 23 ] proposed the need to integrate person-centered and variable-centered analysis in the context of longitudinal studies; their framework suggests that researchers could simultaneously identify relationships between individuals (e.g., distinct subpopulation—homogenous within categories but heterogeneous across categories)—and between variables (e.g., trends over time, typical structural equation modeling [SEM]) by including the continuous and categorical latent variables. Muthén [ 27 ] presented a generalized framework, where traditional SEM is expanded by incorporating categorical latent variables. Similar to the continuous latent variable, the categorical latent variable considers measurement error and multi-item scales. The generalized latent variable modeling framework enables further developments and applications, such as growth curve modeling, multilevel modeling, latent class analysis, missing data modeling, and growth mixture modeling (see Muthén [ 27 ] for a further review).

As part of the second generation of SEM [ 28 ], GMM can handle measurement errors in the collected data; more importantly, it can be incorporated into a more general latent variable framework by including antecedents and consequences of the changes in the temporal trend. GMM has many advantages over previous analytic methods. Hence, it has been widely adopted in developmental psychology, educational psychology, education, clinical research, and criminology (e.g., Ram and Grimm [ 22 ]; Bauer [ 29 ]; Harring and Hodis [ 30 ]; Jung and Wickrama [ 31 ]). For instance, a study on educational psychology investigated heterogeneity in the changes in self-concept in mathematics and its predictive relation to their choice of major [ 30 ]. Moreover, in clinical research, Muthén and Muthén [ 23 ] revealed the longitudinal classification of heavy drinking measured across ages 18–30 and its relation to alcohol dependence at the age of 30. Thus, GMM allows researchers to identify the trajectories of individual behaviors over time and their connections with the desired target behaviors or status.

GMM has traced its origins back to conventional latent growth curve modeling (LGCM) [ 23 ]. LGCM researchers are mainly interested in estimating the average initial status (i.e., intercept in a regression line), the average growth rate (i.e., slope in a regression line), and the variation across individuals’ initial status and growth rate (i.e., variance of intercept and slope) [ 32 ]. LGCM also focuses on individual variation in growth trajectory (i.e., intercept and slope) captured by random coefficients. Thus, the continuous latent variables for intercept and slope can vary across individuals to capture individual variability [ 23 ]. Furthermore, LGCM can examine individual differences in growth development with respect to the differences in the external situation and individual characteristics [ 32 ]. Specifically, it enables researchers to understand individual growth variations by analyzing the relationship of an observed outcome variable to growth pattern and/or to external influence [ 23 ]. LGCM application allows researchers to quantify individual differences in their growth and distal outcomes in relation to time-invariant and/or time-variant characteristics (e.g., grade or age).

GMM goes beyond LGCM by considering unobserved heterogeneity in modeling growth differences between samples, while the fundamental assumption of LGCM suggests that all individuals are drawn from a single population [ 22 , 23 ]. In reality, samples are often obtained from multiple populations, regardless of our prior knowledge of group characteristics. An assumption that a single population is unrealistic in many cases may lead to misunderstanding the resulting growth [ 19 ]. Everyone may exhibit different characteristics such as personality, educational background, and previous experience, and the differences in individual characteristics may influence the trajectory or the development patterns. This assumption allows different parameter values for mixture components relating to each unobserved subgroup of individuals and captures various trajectory classes based on the differences in growth curve shapes [ 33 ]. Substantively, GMM allows researchers to identify multiple unobserved subpopulations to examine the differences in change between unobserved heterogeneity subgroups [ 22 ]. Accounting for heterogeneity between samples, GMM is based on a model-based clustering technique called finite mixture modeling to identify latent classes among variables of interest [ 30 ]. Guided by theory, GMM empirically estimates the unobserved heterogeneity of the growth trajectory and supports the theoretical argument.

GMM is one of the most generalized forms of the latent variable modeling framework family. It incorporates continuous and categorical latent variables with applications of time-variant and time-invariant predictors and distal outcomes. Other types of latent variable modeling, such as latent class analysis, latent transition analysis, and latent class growth modeling, are special cases of the generalized latent variable modeling [ 23 ]. This generalized framework will yield an improved understanding of complex and comprehensive hospitality and tourism phenomena.

In comparison with other methodologies, GMM poses numerous advantages that have been used repeatedly for the same purpose in the hospitality and tourism field. First, GMM takes advantage of all conventional latent modeling techniques (e.g., SEM) like multi-item measurements for the latent variable and the consideration of measurement error. Second, unlike a traditional latent modeling framework, GMM takes the person-centered and variable-centered approaches together. Thus, the model can allow researchers to investigate the changes in the effect over time depending on individual characteristics. Similarly, the third advantage implies that GMM can handle missing data by applying the same methodological treatment with latent variable modeling. Fourth, GMM can be incorporated into a general framework of latent variable modeling. Specifically, the relationships between covariates, class memberships, and distal outcomes are derived from the model specification, rather than post hoc calculation. This simultaneous estimation provides more accurate estimates compared with several separate steps of parameter estimations. Fifth, in comparison with ad hoc segmenting techniques, GMM employs a model-based segmentation approach, which allows the falsifying of suboptimal models. Last, GMM can assume the heterogeneity of samples in the process of estimating the changes in the growth rate. Consequently, GMM helps researchers identify several heterogeneous groups of people who exhibit different levels of growth rate and initial status.

2.3. Estimation and Analytic Procedures of GMM

This section briefly introduces a graphical representation of GMM to provide the underlying analytic background of the current research. Figure 1 depicts a graphical representation of the GMM approach allowing researchers to identify empirically testable hypotheses and brief ideas about modeling strategies. Figure 1 shows that GMM has two major interconnected structural models [ 34 , 35 ], namely, (1) the classification model and (2) the prediction model. In the classification model, there are two notable associations between three components: (1a) observed variables (e.g., travel frequency in each year) are related to continuous latent variables (e.g., intercept, linear slope, and quadratic slope), and (1b) a categorical latent variable (e.g., latent class—potential heterogeneity groups) is estimated from the continuous latent variables. In the prediction model, (2a) travel frequencies regressed on time-variant predictors (e.g., annual income), which help/control model classification. We can identify (2b) who is more likely to belong to a specific latent class by using time-invariant predictors (e.g., gender), and (2c) can also estimate any possible differences in the distal outcomes of respondents (e.g., subjective happiness, quality of life, and/or well-being, which we do not have in our study but would be useful for any follow-up study) by the latent class. The relationships between observed variables, continuous latent variables (trajectory), categorical latent variable (class), time-invariant predictors, and/or time-variant predictors in the diagram can have different parameters in each latent class. The direction of the arrow from the time-invariant predictors to the latent class variable represents the time-invariant characteristics of variables x, namely, socio-economic status or individual enduring personality. Certainly, several properties of the multinomial logistic regression model can be used to explain the relationship between time-invariant predictors and the latent class variable. Moreover, time-invariant predictors and latent class can predict future distal outcomes (change in the outcome), such as academic achievement, subjective happiness, and behavioral intention. The distal outcome can be used to verify the predictive validity of the class memberships based on growth factors, as well as individual characteristics [ 36 ]. Lastly, Figure 1 includes a quadratic slope in the model, while only a single linear or non-linear slope variable can also be specified with the changes in the path coefficient for the relationships between latent (i.e., intercept, linear slope, and quadratic slope) and observed variables. Figure 1 also shows that the initial year (i.e., 2012) needs to be set as 0 for both linear and quadratic slopes. The remaining path coefficients for a linear slope latent variable would be fixed at natural numbers (i.e., 1, 2, and 3) starting from 1 to the last number (t − 1), whereas the path coefficients for quadratic slopes would be fixed at the quadratic form of the path coefficient of a linear slope. For the nonlinear model, the first and any other year (usually the second year) are set to be 0 and 1, respectively, while the other years need to be freely estimated.

A graphical representation for GMM research. Note(s): Covariance and variance paths are depicted in dotted lines. The numbers on the one-arrow lines are fixed path coefficients.

This study proposes several procedures based on earlier studies [ 22 , 34 ] as a guideline for using GMM in our field. The application of GMM requires researchers to follow a multistep process for the accurate estimates of parameters and to ensure the validity of the model/results. The suggested procedures for GMM are outlined and explained in Figure 2 . A further explanation of the empirical analysis is presented in the latter part of this paper. However, we emphasize the need for guiding theories or reasonable hypotheses regarding trajectories before designing a study using GMM. Although no single theory can guide the heterogeneity of growth factors and longitudinal development process, researchers require highly different theoretical evidence and/or supplementary information to prove the plausibility and interpretability of the results [ 37 ]. Specifically, GMM aims to explore the change over time and confirm those identified longitudinal changes in the theory. The initial hypotheses formulated for GMM must be based on guiding theories and substantial evidence, but the actual results would be the foundation for further enrichment of existing theories.

Analytic procedure for GMM research.

3. Research Design

3.1. research framework.

The research framework (see Figure 1 ) has been developed based on previous studies. At the individual level, travel behaviors may vary from time to time based on circumstances [ 17 , 38 ]. Although the destination choice and subsequent behaviors can change over time in response to changes in circumstance, the general patterns of travel behaviors (e.g., travel frequency) could be related to previous travel patterns, e.g., vacation season, travel frequency, and destination choice. For instance, consistently traveling at a similar time of the year but to another destination(s). In the tourism literature, it is suggested that inertia and traditions regarding vacation throughout the year eventually cause the seasonality of the origin and the destination [ 39 , 40 ]. For example, school holidays, vacations from work, and public holidays substantially impact tourism demand and are generally used for leisure behavior. Therefore, the present study claims that an individual’s travel patterns (i.e., travel frequency in each year) could follow a certain pattern depending on the situation and previous experience. Personal characteristics (socio-demographics, personality, and value) and situation needs/constraints (purpose, party, and travel distance) are inextricably intertwined together, and thus influence travel-related decisions differently [ 38 , 41 ]. Therefore, we assume the heterogeneity of travel patterns and their changes over time in our sample.

3.2. Data Preparation

We used the data from the Korea National Tourism Survey for the empirical analysis. The Ministry of Culture, Sports, and Tourism of the Republic of Korea has conducted a recurring longitudinal panel survey of representatives of the South Korean population each year for decades. The survey provides detailed information on travel behaviors and the socio-demographics of Korean households annually. A diary-type survey questionnaire was utilized during data collection to identify the detailed information on each trip that survey respondents took throughout the year, e.g., purpose, destination, length of trip, time of the year, or information sources. Furthermore, this survey collected the data repeatedly from the same respondents over time. These rich and unique characteristics of the data allow for the investigation of the heterogeneity of travel frequency patterns over time. The data can be openly accessed through the Korean Tourism Knowledge and Information System ( www.tour.go.kr , accessed on 7 May 2021) [ 42 ].

Of the 7588 total survey respondents over a four-year period, the current study only involved those who participated in at least one overnight trip and those who did not miss any survey during the four years. Based on these qualifications, a total of 5054 individual respondents were used for further analysis. This restriction was imperative to the study design because the travel frequency of the first year (i.e., the year 2012 in this study) was the starting point of a trajectory of longitudinal travel frequency. The model cannot be properly estimated without this information. For estimation purposes, all travel-related information (travel frequency, trip purpose, and trip type) were aggregated to the year level from the individual trip level. This transformation allows the incorporation of time-variant and time-invariant variables (demographic characteristics, i.e., age, gender, and income) into the model specification.

3.3. Data Analytics

This study follows the analytic procedure described in the previous section (See Figure 2 ). First, LGCM is employed to identify the overall trajectories of travel frequencies for domestic travel among South Korean tourists. Using four years of longitudinal tourist data, the latent intercept and slopes are estimated from the frequencies of annual domestic travel. This step mainly aims to estimate the overall growth trajectory and the within-subject variation. Second, GMM is employed to explore the heterogeneous subsets of travel trajectory. In this step, a class-specific trajectory for each class is identified independently from the overall level. Third, among several alternative models with different numbers of latent classes tested in the second phase, the optimal model is selected based on the information criteria. The interpretability and the feasibility of the identified solution should also be considered in this process. Lastly, this study would provide empirical justification for the selected model and identify the differences in the characteristics among classes for managerial implications.

4. Study Findings

4.1. step 1: application of lgcm.

The first step of the analytic procedure attempted to build a series of models that analyze the trajectories of travel frequencies over time. In doing so, this study first analyzed the descriptive statistics of travel frequencies in our data (see Table 1 ). The overall trend generally shows an inverted U shape over the four-year period. The average travel frequency in the year 2012 was 2.17. It gradually increased until 2014 (2013: 2.34; 2014: 2.45) and slowly decreased in 2015 (travel frequency: 2.41). This result clearly proves that the overall pattern is not linear but rather quadratic or nonlinear unless it has heterogeneous subgroups. Specifically, this study employed three different LGCMs (i.e., linear, quadratic with centering, and nonlinear models) to choose the best fitting model for the subsequent step. Table 2 provides the model fit indices of three LGCM models. Among them, LGCM02, which is a quadratic model with mean centering, shows the best fit indices (CFI = 1.000, TLI = 1.000, RMSEA = 0.000 [90% CI: 0.000–0.034], and SRMR = 0.002). In addition, we conducted a series of χ 2 difference tests based on the Satorra–Bentler scaled chi-square between the three models. Results showed that LGCM02 is the best model (LGCM01 vs. LGCM02: S-B χ 2 = 85.168, p < 0.001; LGCM03 vs. LGCM02: S-B χ 2 = 46.348, p < 0.001). Therefore, LGCM02 (i.e., quadratic with mean centering) is the best fitting model for our data. The results indicate statistically significant variations in the intercept, linear, and quadratic slopes of the trajectories in LGCM02 model. This finding implies that the data is not homogeneous with respect to the travel frequency trajectory pattern, thus implying the need for further analysis using GMM.

Descriptive statistics of annual domestic travel figures.

LGCM models.

Note(s): RMSEA = Root mean square error of approximation; CI = Confidence interval; CFI = Comparative fit index; TLI = Tucker-Lewis index; SRMR = Standardized root mean square residual. a The Quadratic model was estimated with centering. *** p < 0.001, ** p < 0.01, * p < 0.05.

4.2. Step 2: Identification of the Optimal GMM Model

The LCGM results in the first step clearly proving the possibility of several classes based on the growth trajectories for annual travel frequencies over time. To determine the optimal number of classes, the GMM for 1-, 2-, 3-, 4-, 5-, and 6-classes were analyzed. The GMM for more than 6-class was not examined because it does not show any difference in its sample size per class and yields inadmissible solutions for the mean values of intercept, linear, and quadratic variables. Among them, the optimal model was selected based on several criteria proposed by the seminal studies in this area [ 23 , 43 , 44 ]. The values of Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample size adjusted BIC (SABIC) for a model with k class should be lower than that for a model with the k-1 class, thus implying that the k class model fits the data better [ 43 , 44 ]. In addition, entropy, which is an indicator representing the quality of the classification, was also used. Entropy ranges from 0 to 1, where the higher entropy value represents the better model [ 45 ]. The value of entropy is a standardized measure of classification accuracy based on the posterior probabilities from the corresponding model [ 46 ]. Therefore, each sample was assigned to the most likely latent class based on posterior probabilities during the classification. The entropy empirically proves if each individual in the model is classified into the “one and only one category” [ 37 ]. However, not only the model fit indices must be considered but also all other empirical evidence, such as the theoretical justification, membership distributions, and the actual pattern of the data [ 47 ].

Table 3 indicates the fit indices for six candidate GMM models. Among the six candidates, the 4-class model showed the lowest AIC, BIC, and SABIC values. Moreover, the value of entropy for model 4 was adequate (0.735). In addition to the information criterion values, the sample size per class was also considered to justify the optimal number of classes. Nylund et al. [ 44 ] suggest not to use a class with a prevalence of less than 5% due to its low coverage estimates. In reality, the small size of classes could create potential interpretation and generalizability issues. For example, one class in the 5-class model was a relatively smaller size group (2.36%) than the others, and it must be excluded for further empirical analysis. The class membership for the 4-class model was reasonably spread across the classes (8.07%, 14.90%, 32.83%, and 44.20%). Based on this evidence, we selected the 4-class model as the best fitting model that reflects the trajectory of travel frequencies over time. Therefore, this study concluded that the 4-class model had a better fit than the 3- or the 5-class model.

Fit indices for GMM models.

Note(s): LL = Log-likelihood; AIC = Akaike information criterion; BIC = Bayesian information criterion; SABIC = Sample size adjusted BIC; ALMR LRT = Adjusted Vuong-Lo-Mendell-Rubin likelihood ratio test; BLRT = Bootstrap likelihood ratio test. ★ indicates the optimal solution based on the model fit indices. a The number in parenthesis indicates the percentage of the corresponding class. *** p < 0.001, ** p < 0.01, * p < 0.05.

4.3. Step 3: Identification of Trajectory

Table 4 provides the parameter estimation of latent growth factors based on the best solution for our data, i.e., the 4-class GMM. Our best solution is a quadratic model with mean centering. Thus, the model includes intercept (i.e., initial state), linear, and quadratic terms (i.e., slope). The visual illustration of travel frequency trajectories is presented for an intuitive distinction between the models (see Figure 3 ). LGCM shows the blurred thick line in the middle, which indicates a weak concave trajectory ( n = 5054, 100%). By contrast, the 4-class GMM model shows distinctive trajectories across the classes. For instance, class 1, named the ‘high-increasing class [HI]’, shows the highest domestic travel frequency in 2012 (i.e., intercept) and an increasing pattern over time, although the quadratic term is in the negative (class 1: n = 408, 8.1%). Classes 2 [medium-decreasing class; MD] and 4 [low-increasing class; LI] illustrate concave trajectories and lower travel frequency than the average in 2015. However, class 4 [LI] starts from almost zero in 2012 (class 2: n = 753, 14.9%; class 4: n = 2234, 44.2%). While all the three other classes show concave trajectories, class 3 [medium-recovering class; MR] shows a slight convex trajectory above the overall trajectory (class 3: n = 1659, 32.8%). The findings of this study confirmed a significant heterogeneity of the travel frequencies that existed among Korean domestic tourists.

GMM results. Note(s): HI = High-Increasing class; MD = Medium-Decreasing class; MR = Medium-Recovering class; LI = Low-Increasing class; LGCM = Overall latent growth curve model.

Parameter estimation of latent growth factors for the 4-class GMM.

Note(s): a Due to the inadmissible solution, the corresponding variance was fixed at zero in the model, assuming no variance of the corresponding factor. *** p < 0.001, ** p < 0.01, * p < 0.05.

4.4. Step 4: Understanding of the Characteristics of Each Trajectory Pattern

This study subsequently conducted chi-square and ANOVA tests to investigate and better understand the differences in demographic characteristics between each trajectory. Table 5 illustrates that the four trajectory patterns are independent with regard to the city where they reside in ( χ 2 = 95.132, p < 0.001), their highest education level ( χ 2 = 276.099, p < 0.001), and their marital status ( χ 2 = 106.622, p < 0.001). Furthermore, age ( F = 44.592, p < 0.001) and annual income ( F = 59.527, p < 0.001) are statistically different across four trajectories. In general, the results show that the majority of residents in the HI class (i.e., class 1) live in small- to medium-sized cities, obtain a higher-level education, comprise a relatively higher proportion of the married population, and have the youngest [age] but the highest monthly income. People in MD class (i.e., class 2) reside in big cities, obtain less education, show a slightly lower proportion of married people, are slightly younger, and have above-average income levels. MR class (i.e., Class 3) has similar characteristics to the overall population, i.e., half of them are from big cities, two-thirds obtain lower education level (but are more educated people than the overall population), three-fourths of the population are married, are relatively young, and have higher income level than other groups. The last group, the LI class (i.e., class 4), is more likely to come from a town, shows a relatively high proportion of a lower educated population, has slightly more of a widowed population, and has the oldest age and lowest income in comparison with other groups.

Differences in demographic characteristics between trajectories.

Note(s): HI = High-Increasing class; MD = Medium-Decreasing class; MR = Medium-Recovering class; and LI = Low-Increasing class. a Duncan Post Hoc Test was performed for Age and Annual Income. Distinct subgroups were labeled with a superscription of (a) , (b) , and (c) . *** p < 0.001, ** p < 0.01, * p < 0.05.

5. Discussion and Conclusions

5.1. discussion.

The current research explores the heterogeneous latent class with respect to the longitudinal trajectory of annual travel frequency in the Korean domestic travel market so as to examine the sustainable growth of social tourism in Korea. While the overall trend of travel frequency between 2012 and 2015 increased slowly from 2.17 to 2.41, the findings from GMM revealed the four distinct trajectories of travel frequencies among the Korean populations in the meantime. In addition, the findings also note that each group has unique demographic characteristics. Therefore, discovering the four distinctive travel trajectories would help tourism policymakers identify the more- and less-traveling population and thus optimize their available resources (funding, government support, and other subsidies from nonprofit organizations) for the relevant target population.

Although the finding of this study showed that a considerable number of Korean citizens still traveled approximately once per year, the annual travel frequency is not balanced across the classes. One class (HI, class 1) showed overwhelmingly higher figures compared to the frequencies seen in other classes. The HI class covering 8.1% of the population enjoyed the most travel opportunities during the research period. On the other hand, two classes (MD, class 2, and LI, class 4) need more attention from the social tourism perspective. The MD class shows decreasing travel frequency and the LI class still shows the lowest travel frequency over the research period. Compared to the other classes, the members of these two classes received education for a shorter period of time, tend to reside in big cities, are older, and had less income. Furthermore, they have a more complicated marital status structure—with a higher percentage of widowed and divorced.

The findings of the current study demonstrate the inequality of the travel opportunities in the research population, and identifies their demographic characteristics (age, income, and residential area). Therefore, policymakers could utilize this study’s findings as fundamental information for developing an effective tourism policy that promotes public welfare by providing additional travel opportunities and encouraging tourism and leisure activities to those with limited travel experience. Social tourism, as a form of social welfare, could be designed effectively using this study’s findings, thereby enhancing quality of life in general [ 6 , 7 ]. Moreover, this study discovers important insights into public policy decision-making in South Korea by utilizing publicly available national statistical data. Future research could consider including time-variant and time-invariant predictors in the research framework. This step will provide possible solutions for boosting tourism demand at the individual and national levels. Furthermore, the association between domestic and international travel trajectories is a research topic that could provide practical implications for governments to improve national tourism policies.

5.2. Potential Application of the GMM Approach in Hospitality and Tourism Research

This study highlights the applicability of the proposed GMM method and the longitudinal study design for future hospitality and tourism research. In general, GMM is applicable to research questions focusing on changes in a certain outcome over time, while interest in the heterogeneity among samples can be added to its utilization. Furthermore, the ability to recognize the heterogeneity within the proposed model would provide more diverse insights and substantial contributions to the fields of hospitality and tourism [ 20 , 21 ]. In this section, we would suggest several possible applications in hospitality and tourism research.

Numerous hospitality and tourism studies have repeatedly confirmed that many people often repurchase the same tourism products or hospitality services over time due to favorable service quality; however, repeated behavior may cause a change in the satiation of affective responses [ 48 , 49 ]. This type of research problem can be solved by using GMM in a longitudinal manner. In this case, the level of satisfaction (or revisit intention) for each repurchase experience is the main interest variable. Applying GMM to this case allows us to capture the pattern of satiation over time, the heterogeneity within the sample, and potential determinants or outcomes.

GMM can also be useful for data at the firm level because the performance of hospitality firms is often dynamic in nature depending on the seasonality and/or economic situation [ 50 , 51 ]. The desired outcomes (or variables of interest) can be the annual performance of the hospitality company, the number of service failure incidents in each year, and any periodical information that describes the firms’ performance. Other possible examples of longitudinal analysis in hospitality and tourism fields would be identifying how the hospitality firms’ revenue eventually changes after launching a new advertisement, the relationship between consumers’ levels of satisfaction and repeated purchases, how emotional labor employees manage stress after completing an emotional intelligence training program, or how tourists use social media differently before, during, and after travel [ 52 , 53 ]. By employing the GMM approach to the longitudinal data, researchers can identify the dominant patterns of changes in the variable of interest among samples and the possible influencing factors from the research findings. For example, restaurant owners or policymakers could identify the underlying patterns of food risk (e.g., food poisoning incidents) in the city and subsequently identify the potential area that needs special care or the potential policy that needs to be revised.

Lastly, GMM is widely adopted by developmental psychologists. In reality, hospitality companies have put effort into their employees’ education and focused on retaining successfully educated employees [ 54 , 55 ]. Similarly, a hospitality company can use GMM to determine the influencing factors during the training/education programs and identify possible solutions for the previous question, which require an improved understanding of the development pattern and the characteristics of employees in each trajectory. In this example, the variable of interest would be the level of expertise, the number of the task completed, and job satisfaction. The findings from these studies would help human resource managers improve their understanding of their employees and design an effective education and training program for them.

5.3. Challenges in GMM for Hospitality and Tourism Research

While GMM evidently possesses a great potential to contribute theoretically and practically to hospitality and tourism research, future studies should incorporate several important considerations to actually implement the GMM approach in the framework. First, GMM, as a longitudinal research method per se, requires data collection from the participants at multiple times (e.g., more than three times due to the model identification condition) without any intervention or with very limited intervention. GMM often requires a heavy computational analytic process especially as the number of classes increases, which recommends a large sample size for practical application [ 22 ]. Therefore, researchers must exert substantial time, effort, and money to simply obtain the primary data for their research. However, sample attrition problem often arises during the data collection process. Possible solutions include collaboration between hospitality companies, use of publicly available data, or survey of panel members over time [ 18 ]. Second, while using the GMM approach, researchers often fall into a trap, i.e., focusing on the empirical evidence rather than the theory itself. As part of the SEM family, the research framework/model should be based on theory and theoretical discussion (i.e., a confirmatory approach), rather than the exploration of the possible outcome from the data (i.e., an exploratory approach) [ 23 , 37 , 43 ]. Regardless of these challenges for the method application, GMM could address many important research questions in our field via an advanced and rigorous research design. Researchers should revisit their own research questions again using GMM to address unanswered or inaccurately answered questions.

5.4. General Conclusion

This study explored and identified certain subpopulation clusters with unequal travel experiences from the social tourism perspective. To this end, the study applied the GMM technique with four-year-long longitudinal travel frequency data in the Korean domestic travel market. The study found four distinctive longitudinal clusters concerning the annual travel frequency. Policymakers are expected to make the best use of the current study findings when working on policies regarding social tourism. The present paper also benefits academic researchers by providing practical guidelines on how to apply GMM. GMM allows researchers to describe changes in the key outcome variables over time and subsequently cluster samples into several groups simultaneously depending on the trajectories. This advantage could provide fruitful insights and discussions for academia and practitioners in our field.

Acknowledgments

The authors wish to thank reviewers and the special issue editor, Heesup Han, for their insightful comments and suggestions on revising the manuscript. We also would like to extend our sincere thanks to Yeongbae Choe for his supportive comments.

Author Contributions

Conceptualization, J.L.; formal analysis, J.L.; investigation, J.L.; methodology, J.L.; project administration, J.B.; supervision, J.B.; visualization, J.B.; writing—original draft, J.L.; writing—review and editing, J.B. Both authors have read and agreed to the published version of the manuscript.

This research was funded by Macau University of Science and Technology, grant number FRG-19-046-FHTM.

Institutional Review Board Statement

Ethical review and approval were waived for this study because the present study used not-individually-identifiable public data (45 CFR § 46.102).

Informed Consent Statement

Not applicable.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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2. Defining Social Tourism and its Historical Context

From the book social tourism in europe.

• Lynn Minnaert , Anya Diekmann and Scott McCabe
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Psychology in Tourism

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• First Online: 24 November 2023
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• Aman Kumar 2  

Part of the book series: Springer International Handbooks of Education ((SIHE))

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This comprehensive literature review explores the intricate relationship between psychological factors and tourism development, with a focus on the mediating role of community interaction. The tourism industry stands as a global economic powerhouse, influencing employment, revenue generation, and GDP contributions. While existing research delves into various psychological aspects such as destination image, online purchase intention, and memorable experiences, there remains a notable gap regarding the theoretical and empirical exploration of psychological elements in destination image formation.

This study seeks to address this gap by investigating how psychological factors contribute to tourism development, with a special emphasis on the mediating influence of community interaction. The conceptual model highlights the interconnectedness of these elements, shedding light on the dynamics at play in this multifaceted industry. Furthermore, this review encompasses a diverse array of psychological theories, including the Theory of Reasoned Action, Motivational Model, Theory of Planned Behavior, and Socio Cognitive Theory, all of which offer valuable insights into tourist behavior and decision-making processes. Additionally, the study delves into the impact of the COVID-19 pandemic on travel behavior, emphasizing the vital role of psychological factors in shaping the industry’s recovery and future trajectory.

In conclusion, this literature review offers a robust foundation for further empirical research on the psychological dimensions of tourism development, with a specific focus on the mediating impact of community interaction. By synthesizing existing knowledge and identifying gaps in the literature, this study provides a valuable roadmap for future investigations in this dynamic and critical field.

• Tourism development
• Psychological factors
• Community interaction
• Memorable experiences
• GDP contribution

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Adams, S. J. (1963). Towards an understanding of inequity. Journal of Abnormal and Social Psychology, 67 (5), 422–436.

Article   Google Scholar  

Ajzen, I. (1991). The theory of planned behaviour. Organizational Behavior and Human Decision Processes, 50 , 179–211.

Alba, J. W., & Williams, E. F. (2013). Pleasure principles: a review of research on hedonic consumption. Journal of Consumer Psychology, 23 (1), 2–18.

Andereck, K. L., Valentine, K. M., Knopf, R. C., & Vogt, C. A. (2005). Residents’ perceptions of community tourism impacts. Annals of Tourism Research, 32 (4), 1056–1076.

Andriotis, K., & Vaughan, D. R. (2003). Urban residents’ attitudes towards tourism development: the case of Crete. Journal of Travel Research, 42 (2), 172–185.

Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. Journal MIS Quarterly, 33 (2), 339–370.

Ap, J. (1990). Residents’ perceptions research on the social impacts of tourism. Annals of Tourism Research, 17 (4), 610–616. https://doi.org/10.1016/0160-7383(90)90032-M

Assaf, A., & Scuderi, R. (2020). COVID-19 and the recovery of the tourism industry. Tourism Economics, 26 (5), 731–733. https://doi.org/10.1177/1354816620933712

Babin, B., Darden, W., & Griffin, M. (1994). Work and/or fun: measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20 (4), 644–656.

Baloglu, S., & Brinberg, D. (1997). Affective images of tourism destinations. Journal of Travel Research, 35 (4), 11–15.

Basil, D. Z., & Herr, P. M. (2006). Attitudinal balance and cause-related marketing: An empirical application of balance theory. Journal of Consumer Psychology, 16 (4), 391–403.

Batra, R., & Ahtola, O. T. (1991). Measuring the hedonic and utilitarian sources of consumer attitudes. Marketing Letters, 2 (2), 159–170.

Bigné, J. E., Sánchez, M. I., & Sánchez, J. (2001). Tourism image, evaluation variables and after purchase behaviour: Inter-relationship. Tourism Management, 22 (6), 607–616.

Brehm, J. W. (1966). A theory of psychological reactance . Academic Press.

Google Scholar  

Brida, J. G., Disegna, M., & Osti, L. (2014). Residents’ perceptions of tourism impacts and attitudes toward tourism policies in a small mountain community. Toursimos, 9 , 37–71.

Caldwell, L. (2005). Leisure and health: Why is leisure therapeutic? British Journal of Guidance and Counselling, 33 (1), 726.

Carstensen, L. L. (1992). Social and emotional patterns in adulthood: Support for socioemotional selectivity theory. Psychology and Aging, 7 (3), 331–338.

Carstensen, L. L., Fung, H. H., & Charles, S. T. (2003). Socioemotional selectivity theory and the regulation of emotion in the second half of life. Motivation and Emotion, 27 (2), 103–123.

Chadee, D. (2011). Theories in social psychology . Wiley-Blackwell Press.

Chiu, C., Wang, E., Shih, F., & Fan, Y. (2011). Understanding knowledge sharing in virtual communities: an integration of expectancy disconfirmation and justice theories. Online Information Review, 35 (1), 134–153.

Coghlan, A. (2015). Tourism and health: using positive psychology principles to maximise participants’ wellbeing outcomes – a design concept for charity challenge tourism. Journal of Sustainable Tourism, 23 (3), 382–400. https://doi.org/10.1080/09669582.2014.986489

Cohen, S. A., Prayag, G., & Moital, M. (2013). Consumer behaviour in tourism: Concepts, influences and opportunities. Current Issues in Tourism, 17 (10), 872–909.

Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19 (2), 189–211.

Cook, K. S., & Rice, E. (2003). Social exchange theory. In J. Delamater (Ed.), Handbook of social psychology (pp. 53–76). Kluwer.

Crouch, G. I., Perdue, R. R., Timmermans, H., & Uysal, M. (2004). Building foundations for understanding the consumer psychology of tourism, hospitality and leisure. In G. I. Crouch, R. R. Perdue, & H. Timmermans (Eds.), Consumer psychology of tourism, hospitality and leisure (pp. 1–10). CABi.

Chapter   Google Scholar  

Cusumano, M. A., Gawer, A., & Yoffie, D. B. (2019). The business of platforms: Strategy in the age of digital competition, innovation, and power . HarperCollins.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13 (3), 319–339.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35 (8), 982–1003.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22 (14), 1111–1132.

Decrop, A., & Snelders, D. (2004). Planning the summer vacation – an adaptable process. Annals of Tourism Research, 31 (4), 1008–1030.

Dillon, A., & Morris, M. (1996). User acceptance of new information technology: theories and models. In M. Williams (Ed.), Annual review of information science and technology (Vol. 31, p. 3e32). Information Today.

Domjan, M. (2009). The principles of learning and behavior . Cengage Learning.

Doxey, G. V. (1975). A causation theory of visitor-resident irritants, methodology, and research inferences. In Presented at the 6th Annual Travel and Tourism Research Association Conference (pp. 195–198). Travel and Tourism Research Associate.

Dutt, C. S., Ninov, I., & Haas, D. (2015). The effect of visiting friends and relatives on Expatriates’ destination knowledge: Abstract. In V. Katsoni (Ed.). Cultural tourism in a digital era: First International Conference IACuDiT, Athens, 2014 (pp. 325–327). : Springer International Publishing. Retrieved from: https://doi.org/10.1007/978-3-319-15859-4_27 .

Elliot, A. J., & Devine, P. G. (1994). On the motivational nature of cognitive dissonance: dissonance as psychological discomfort. Journal of Personality & Social Psychology, 67 (3), 383–394.

Filep, S., & Deery, M. (2010). Towards a picture of tourists’ happiness. Tourism Analysis, 15 , 399410.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research . Addison-Wesley.

Fiske, S. T., & Taylor, S. E. (1984). Social cognition . Addison-Wesley.

Floyd, M. F. (1997). Pleasure, arousal, and dominance: exploring affective determinants of recreation satisfaction. Leisure Sciences, 19 (2), 83–96.

Fullagar, S. (2008). Leisure practices as counter-depressants: Emotion-work and emotion-play within women’s recovery from depression. Leisure Sciences, 30 , 3552.

Gallarza, M. G., Gil, I., & Caldero´ n, H. (2002). Destination image: Towards a conceptual framework. Annals of Tourism Research, 29 (1), 56–78.

Gallese, V., Keysers, C., & Rizzolatti, G. (2004). A unifying view of the basis of social cognition. Trends in Cognitive Sciences, 8 (9), 396–403.

Gartner, W. C. (1993). Image formation process. Journal of Travel and Tourism Marketing, 2 (2/3), 191–215.

Gawronski, B., & Strack, F. (2004). On the propositional nature of cognitive consistency: dissonance changes explicit, but not implicit attitudes. Journal of Experimental Social Psychology, 40 (4), 535–542.

Goossens, C. (2000). Tourism information and pleasure motivation. Annals of Tourism Research, 27 (2), 301–321.

Gössling, S. (2021). Tourism, technology and ICT: A critical review of affordances and concessions. Journal of Sustainable Tourism, 29 (5), 733–750. https://doi.org/10.1080/09669582.2021.1873353

Gretzel, U., Fesenmaier, D. R., Formica, S., & O’Leary, J. T. (2006). Searching for the future: challenges faced by destination marketing organizations. Journal of Travel Research, 45 (2), 116–126.

Hall, D., & Brown, F. (2006). Tourism and welfare: Ethics, responsibility and sustained wellbeing . CAB International.

Book   Google Scholar  

Heider, F. (1920). Zur Subjektivitat der Sinnesqualitaten (On the subjectivity of sense qualities). University of Graz, Austria (Unpublished doctoral dissertation).

Heider, F. (1958). The psychology of interpersonal relations . Wiley-Blackwell Press.

Holbrook, M. B. (2006). Consumption experience, customer value, and subjective personal introspection: an illustrative photographic essay. Journal of Business Research, 59 (6), 714–725.

Holmes, J. G. (2002). Interpersonal expectations as the building blocks of social cognition: an interdependence theory perspective. Personal Relationships, 9 (1), 1–26.

Homans, G. C. (1964). Commentary. Sociological Inquiry, 34 (2), 221–234.

Johnson, D. W., & Johnson, R. T. (2002). Cooperative learning and social interdependence theory. Theory and Research on Small Group, 4 (1), 9–35.

Joppe, M., Martin, D. W., & Waalen, J. (2001). Toronto’s image as destination: A comparative importance-satisfaction analysis by origin of visitor. Journal of Travel Research, 39 (3), 252–260.

Kandampully, J. (2000). The impact of demand fluctuation on the quality of service: A tourism industry example. Managing Service Quality, 10 (1), 10–18.

Keyes, C. L. M. (2005). Mental illness and/or mental health? Investigating axioms of the complete state model of health. Journal of Consulting and Clinical Psychology, 73 (3), 539548.

Keyes, C. L. M. (2007). Promoting and protecting mental health as flourishing: A complementary strategy for improving national mental health. American Psychologist, 62 (2), 95108.

Kim, J. (2014). The antecedents of memorable tourism experiences: The development of a scale to measure the destination attributes associated with memorable experiences. Tourism Management, 44 , 34–45.

Kim, H., & Richardson, S. L. (2003). Motion picture impacts on destination images. Annals of Tourism Research, 30 (1), 216–237.

Kim, J., Ritchie, J. R. B., & McCormick, B. (2012). Development of a scale to measure memorable tourism experiences. Journal of Travel Research, 51 (1), 12–25.

Koc, E., & Boz, H. (2014). Psychoneurobiochemistry of tourism marketing. Tourism Management, 44 (1), 140–148.

Koc, E., & Boz, H. (2022). Psychoneurobiochemistry of tourism marketing. Retrieved 19 August 2022, from.

Korstanje, M. (2015). A portrait of Jost Krippendorf. Anatolia, 26 (1), 158–164.

Krippendorf, J. (1986). Tourism in the system of industrial society. Annals of Tourism Research, 13 (4), 517–532.

Kuvan, Y., & Akan, P. (2005). Residents’ attitudes toward general and forest-related impacts of tourism: The case of Belek, Antalya. Tourism Management, 26 , 691–706.

Kwon, S., & Jang, S. (2012). Effects of compensation for service recovery: From the equity theory perspective. International Journal of Hospitality Management, 31 (4), 1235–1243.

Laczniak, R. N., DeCarlo, T. E., & Ramaswami, S. N. (2001). Consumers’ responses to negative word-of-mouth communication: an attribution theory perspective. Journal of Consumer Psychology, 11 (1), 57–73.

Lawson, F., & Baud-Bovy, M. (1977). Tourism and recreational development . Architectural Press.

Leisen, B. (2001). Image segmentation: The case of a tourism destination. Journal of Services Marketing, 15 (1), 49–66.

Lenzen, M., Sun, Y. Y., Faturay, F., Ting, Y. P., Geschke, A., & Malik, A. (2018). The carbon footprint of global tourism. Nature Climate Change, 8 (6), 522–528. https://doi.org/10.1038/s41558-018-0141-x

Li, S., Scott, N., & Walters, G. (2014). Potential methods for measuring emotion in Chinese tourism advertising, G20 First East-West Dialogue on Tourism and the Chinese Dream, Griffith University, Gold Coast, 13–15 Nov.

Lieberman, M., Gauvin, L., Bukowski, W. M., & White, D. R. (2001). Interpersonal influence and disordered eating behaviors in adolescent girls: the role of peer modeling, social reinforcement, and body-related teasing. Eating Behaviors, 2 (3), 215–236.

Ma, J., Gao, J., Scott, N., & Ding, P. (2013). Customer delight derived from theme park experiences: the antecedents of delight based on cognitive appraisal theory. Annals of Tourism Research, 42 (1), 359–381.

Manceau, D., & Tissier-Desbordes, E. (2006). Are sex and death taboos in advertising? An analysis of taboos in advertising and a survey of French consumer perceptions. International Journal of Advertising, 25 (1), 9–34.

Mannell, R., & Iso-Ahola, S. (1987). Psychological nature of leisure and tourism experience. Annals of Tourism Research, 14 (3), 314–331. https://doi.org/10.1016/0160-7383(87)90105-8

Munhurrun, P. R., & Naidoo, P. (2011). Residents' attitudes toward perceived tourism benefits. International Journal of Market Research, 4 , 45–56.

Nunkoo, R., & Ramkissoon, H. (2011). Developing a community support model for tourism. Annals of Tourism Research, 38 , 964–988.

Nunkoo, R., Gursoy, D., & Juwaheer, T. (2010). Island residents’ identities and their support for tourism: an integration of two theories. Journal of Sustainable Tourism, 18 (5), 675–693.

Okun, M. A., & Schultz, A. (2003). Age and motives for volunteering: testing hypotheses derived from socioemotional selectivity theory. Psychology Aging, 18 (2), 231–239.

Orîndaru, A., Popescu, M., Alexoaei, A., Căescu, Ș., Florescu, M., & Orzan, A. (2021). Tourism in a post-COVID-19 era: Sustainable strategies for industry’s recovery. Sustainability, 13 (12), 6781. https://doi.org/10.3390/su13126781

Panchal, J., & Pearce, P. (2011). Health motives and the Travel Career Pattern (TCP) model. Asian Journal of Tourism and Hospitality Research, 5 (1), 32–44.

Pearce, P. L. (1982a). The social psychology of tourism . Pergamon.

Pearce, P. L. (1982b). The social psychology of tourist behavior . Pergamon.

Pearce, P. (2009). The relationship between positive psychology and tourist behaviour studies. Tourism Analysis, 14 , 3748.

Pearce, P. L., & Packer, J. (2013). Minds on the move: New links from psychology to tourism. Annals of Tourism Research, 40 (1), 386–411.

Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and persuasions: Classic and contemporary approaches . W.C. Brown.

Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion: Central and peripheral routes of attitude change . Springer-Verlag.

Pham, M. T. (1998). Representativeness, relevance, and the use of feelings in decision making. Journal of Consumer Research, 25 (2), 144–159.

Pritchard, M. P. (1998). Responses to destination advertising: Differentiating inquiries to a short, getaway vacation campaign. Journal of Travel and Tourism Marketing, 7 (2), 31–51.

Ramires, A., Brandão, F., & Sousa, A. C. (2018). Motivation-based cluster analysis of international tourists visiting a world heritagecity: The case of Porto. Portugal. Journal of Destination Marketing & Management, 8 , 49–60.

Rubenstein, C. (1980). Report on how Americans view vacations. Psychology Today, May, pp. 62–76.

Ryglová, K., Burian, M., & Vajčnerová, I. (2011). Tourism – business principles and opportunities in practice . Grada Publishing. isbn:978-80-247-4039-3.

Ryzin, G. (2006). Testing the expectancy disconfirmation model of citizen satisfaction with local government. Journal of Public Administration Research and Theory, 16 (4), 599–611.

San Martín, H., & Herrero, Á. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341–350. https://doi.org/10.1016/j.tourman.2011.04.003 .

San Martín, H., & Rodríguez del Bosque, I. (2008). Exploring the cognitive–affective nature of destination image and the role of psychological factors in its formation. Tourism Management, 29 (2), 263–277. https://doi.org/10.1016/j.tourman.2007.03.012

Sanjay, K., & Kumar, S. S. (2017). A theoretical framework for wellness tourism motivation factors. In P. S. Sibi, R. Mathew, P. Mohanty, & Y. V. Rao (Eds.), Contemporary research and practices in tourism and hospitality- with special focus on accessibility (pp. 214–223). Himalaya Publishing House.

Schifter, D. B., & Ajzen, I. (1985). Intention, perceived control, and weight loss: an application of the theory of planned behaviour. Journal of Personality and Social Psychology, 49 , 842–851.

Schwartz, J. (2003). Cassandra’s Daughter: A history of psychoanalysis . Karnac Books.

Scott, N., Gao, J., & Ma, J. (2017). Tourism experience design . CABI.

Seligman, M. (1998). Learned optimism (2nd ed.). Pocket Books.

Sharpley, R. (2014). Host perceptions of tourism: A review of the research. Tourism Management, 42 , 37–49. https://doi.org/10.1016/j.tourman.2013.10.007

Eva Šimková. Procedia – Social and Behavioral Sciences 114 (2014) 317–321.

Skavronskaya, L., Scott, N., Moyle, B., Le, D., Hadinejad, A., Zhang, R., Gardiner, S., Coghlan, A., & Shakeela, A. (2017). Cognitive psychology and tourism research: state of the art. Tourism Review, 72 (2), 221–237. https://doi.org/10.1108/TR-03-2017-0041

Slade, M. (2010). Mental illness and wellbeing: The central importance of positive psychology and recovery approaches. British Medical Council Health Services Research, 10 , 2640.

Stringer, P. F., & Pearce, P. L. (1984). Toward a symbiosis of social psychology and tourism studies. Annals of Tourism Research, 11 (1), 5–17.

Swarbrooke, J., & Horner, S. (2007). Consumer behaviour in tourism (2nd ed.). Butterworth-Heinemann. isbn:978-0-7506-6735-7.

Tang, L., & (Rebecca). (2014). The application of Social Psychology Theories and concepts in hospitality and tourism studies: A review and research agenda. International Journal of Hospitality Management, 36 , 188–196. https://doi.org/10.1016/j.ijhm.2013.09.003

Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6 (2), 144–176.

Tung, V. W. S., & Ritchie, J. R. B. (2011). Exploring the essence of memorable tourism experiences. Annals of Tourism Research, 38 (4), 1367–1386.

Turkle, S. (2015). Reclaiming conversation: The power of talk in a digital age . Penguin Random House.

Turner, R. A., Fitzsimmons, C., Forster, J., Mahon, R., Peterson, A., & Stead, S. M. (2014). Measuring good governance for complex ecosystems: perceptions of coral-reef dependent communities in the Caribbean. Global Environmental Change, 27 , 22–30.

Usakli, A., & Baloglu, S. (2011). Brand personality of tourist destinations: an application of self-congruity theory. Tourism Management, 32 (1), 114–127.

Van Dyne, L., & Ellis, J. B. (2004). Job creep: A reactance theory perspective on organizational citizenship behavior as over-fulfillment of obligations. In J. A. M. Coyle-Shapiro, L. M. Shore, M. S. Taylor, & L. E. Tetrick (Eds.), The employment relationship: Examining psychological and contextual perspectives (pp. 181–205). Oxford University Press.

Villamira, M. A. (2001). Psicologia del viaggio e del turismo . UTET.

Virdi, R., & Traini, A. (1990). Psicologia del turismo. Turismo, salute, cultura . Armando Mondadori. ISBN 9788871441573.

Walmsley, D. J., & Young, M. (1998). Evaluative images and tourism: the use of personal constructs to describe the structure of destinations images. Journal of Travel Research, 36 (3), 65–69.

Wei, C., Zhao, W., Zhang, C., & Huang, K. (2019). Psychological factors affecting memorable tourism experiences. Asia Pacific Journal of Tourism Research, 24 (7), 619–632. https://doi.org/10.1080/10941665.2019.1611611

Williams, A. (2006). Tourism and hospitality marketing: fantasy, feeling and fun. International Journal of Contemporary Hospitality Management, 18 (6), 482–495.

World Health Organization (WHO). (2013). Mental health: A state of wellbeing. Accessed 14 Mar 2014, http://www.who.int/features/factfiles/mental_health/en/

World Tourism Organisation. (2012). UNWTO tourism highlights 2012. http://mkt.unwto.org/sites/all/files/docpdf/unwtohighlights12enlr_1.pdf

Zhang, H., Wu, Y., & Buhalis, D. (2018). A model of perceived image, memorable tourism experiences and revisit intention. Journal of Destination Marketing & Management, 8 , 326–336. https://hpkangra.nic.in/ , https://www.google.com/search?q=fliker.com

Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power . Public Affairs.

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Kumar, A. (2024). Psychology in Tourism. In: Sharma, A. (eds) International Handbook of Skill, Education, Learning, and Research Development in Tourism and Hospitality. Springer International Handbooks of Education. Springer, Singapore. https://doi.org/10.1007/978-981-99-3895-7_12-1

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DOI : https://doi.org/10.1007/978-981-99-3895-7_12-1

Received : 13 September 2023

Accepted : 18 September 2023

Published : 24 November 2023

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