More than 3.049 billion monthly active social media (Facebook) users are engaging in sharing content, views, surfing, and bridging their friends and family. Web 3.0 is a buzzword now That is going to ensure the decentralization of information, blockchain technology, data security, data privacy, and individual control over private data. The world’s scenery has been changed through the invention of the internet and social media has changed the landscape in the same way in this century. Social media has revolutionized the way companies convey their assortment of products and services to prospective customers. It has become a catalyst for changing the decisions of social media users. It has enabled every little firm to become a large conglomerate to pinpoint their niche customer segment and reach them effectively with various techniques. It has been observed that influencers in social media have a noteworthy and robust correlation (i.e., 73%) and contribute the most to travelers’ travel decision-making, indicating the least reliability (28% correlation). The study shows that the R square value is 0.88 and the adjusted R square value is 0.88, indicating that travelers’ decision-making is 88% shaped by social media influencers. Therefore, the boom of social media has also facilitated the way people communicate with each other, especially when they seek recommendations for purchasing something or availing of a service. It provides a platform for both consumers and businesses to have two-way communication where both parties can interact effectively on a real-time basis without incurring much expense. Social media has also brought a lot of tourist destinations closer to tourists that are situated in a remote part of the country or in a place that is quite untouched by tourist groups. It allows destination organizations like sites, parks, hotels, and amusement centers to conveniently publish multimedia content involving blog posts, images, videos, and interactive games and attract visitors to these destinations. Social media marketing also provides real-time information on customer profiles, behaviors, and perceptions to the marketing manager. It also influences tourist groups in making travel decisions like choosing a destination, a time of travel, or a package that they might want to avail of. In this research paper, we have identified four social media stimuli and shown their correlation with tourists’ decision-making. In this paper, it has been identified that more than 80% of the time, social media has a positive influence on travelers’ decisions about their tour itinerary. Social media has opened the horizon of decentralized communications among people all over the world. People can easily find their content as they are looking to meet their demands. 

Exploring the Effectiveness of Social Media on Tourism Destination Marketing: An Empirical Study in a Developing Country

How folk music induces destination image: A synthesis between sensory marketing and cognitive balance theory

The projected image, created by destination marketing organizations, and the perceived image, formed by tourists’ perceptions, are crucial factors in destination selection. In this paper, machine learning models are used to construct projected image dimensions and perceptual dimensions for Chinese and English to analyze the similarities and differences between projected and perceptual images and their Chinese sustainability and cultural differences issues. We take Xiamen, a seaside tourist city in China, as an example, and analyze it by collecting 110,098 official promotional texts (both in Chinese and English) and tourist online review feedback as data sources using a latent Dirichlet allocation (LDA) model of natural language processing. The findings show that (1) the official projected image focuses on the overall image of the destination, while the tourists’ perceived image focuses on the specific image. (2) The official projected image covers the whole area of tourism, while the tourists’ perceived image focuses on Xiamen’s well-known attractions. The results of the above two points are the same for both the Chinese and English Topic models. (3) The official projected image focuses on three dimensions of destination: sustainability-economic, socio-cultural and environmental, while the tourist perception is more in the socio-cultural and environmental dimensions. (4) Both the projected and perceived images in Chinese and English differ in cross-cultural situations. The perceived images of Chinese and British tourists are influenced by their respective cultural backgrounds. Chinese tourists’ perceptions reflect cultural values associated with collectivism, long-term orientation, and uncertainty avoidance. On the other hand, British tourists’ perceptions align with cultural values of individualism, short-term orientation, and lower uncertainty avoidance. These differences can be explained using Hofstede’s cultural dimensions theory. The research in this paper can provide a reference for the promotion of tourism cities, and tourism destination organizations should not only focus on sustainable promotion, but also attract domestic and foreign tourists through differentiated promotion.

Exploring the Discrepancy between Projected and Perceived Destination Images: A Cross-Cultural and Sustainable Analysis Using LDA Modeling

The prevalence of ChatGPT (and generative artificial intelligence in general) has precipitated a paradigm shift in diverse industries, including tourism and hospitality. ChatGPT revolutionalises all business functions (from marketing to operations), empowering tourism and hospitality organisations to transform and innovate their business models. This study seeks to comprehensively examine the use and implications of ChatGPT in tourism and hospitality by discussing the current and future state of the technology, while also suggesting an agenda for future research. To that end, six areas, namely, business intelligence and tourism analytics, tourism marketing and experience, hospitality services, cultural and heritage tourism, travel services, and destination management, are elaborated on in depth. By compiling views solicited from international experts, this groundbreaking opinion piece unveils profound insights into the evolutionary journey of an emerging technology that is shaping tourism and hospitality. The paper provides useful implications for tourism scholars and professionals alike. 

Understanding the impact of ChatGPT on tourism and hospitality: Trends, prospects and research agenda


Purpose
As an important emerging topic in recent years, reviews on tourism and hospitality social entrepreneurship (THSE) by theme remain limited. This paper aims to map the current publication trends, reveal the formation path and identify the future research directions of THSE, providing comprehensive and in-depth insight.


Design/methodology/approach
This study presents a systematic review of 89 articles on THSE published in the Web of Science, ScienceDirect and EBSCOhost. It follows grounded theory to classify literature and an expert feedback process to ensure validity.


Findings
Research on THSE is mainly found in developing countries and regions. Qualitative methods have been the most popular for researchers. This paper classifies THSE research into four main themes: antecedents, processes, effects and challenges.


Practical implications
This review suggests that social enterprise managers should consider the inclusive business model and adopt empowerment, network construction, market approaches and bricolage to mobilize resources. Policymakers should disseminate relevant laws and regulations to provide a flexible and equal environment. Education and capacity building for people should be strengthened to train future social entrepreneurs.


Originality/value
This review provides an integrated process model by clustering articles to update the holistic picture of THSE. This work identifies research gaps that future research should address.


An integrated path framework of tourism and hospitality social entrepreneurship: a systematic literature review

Tourism destination research from 2000 to 2020: A systematic narrative review in conjunction with bibliographic mapping analysis

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Tourism destination research from 2000 to 2020: A systematic narrative review in conjunction with bibliographic mapping analysis