Search results

The purpose of this paper is to analyse the metaverse platform in a social context to better understand the future of this tool in tourism cities and how this can help to improve the well-being of residents in both digital and physical scenarios.

In this paper, the current and probable developments in the metaverse, and its use in tourism cities and companies have been investigated. Moreover, this study develops, collects and examines the main metaverse definitions by expert authors and organizations as a methodology to ensure the transparency and credibility of the metaverse analysis.

Findings suggest that the fusion of the metaverse and tourism cities must create residents’ services and experiences in the new MetaTourPolis to help interact and connect citizens with the city’s institutions and companies, as well as make tourism cities more attractive, innovative, environmentally friendly and healthier places to live. Metaverse will bring new changes for residents and tourists, in fact, this virtual platform is already changing and improving the residents’ quality of life and people with disabilities in tourism cities. For instance, the metaverse platform has been implemented in Seoul, Santa Monica and Dubai MetaTourPolis to interact with their residents, including people with disabilities, to resolve bureaucratic and administrative problems, avoiding this group and the rest of the residents travelling by bus or car to the city’s institutions. In addition, several metaverse applications based on softbot tutors or metaverse virtual social centres have been developed to improve blind and impaired people, and elderly people’ quality of life, respectively.

A new concept called “MetaTourPolis” has been included to stage the relationship between tourism cities and the metaverse platform, where the fusion of metaverse and the new tourism polis of the 21st century will be at the service of citizens, tourists and companies, to create more sustainable, efficient, quantitative and environmental tourism cities.

This study evaluated the determinants of augmented reality (AR) adoption in Malaysia's travel and tour operator sectors through an integrated technology-organization-environmental (TOE) and diffusion of innovation (DOI) model.

The TOE and DOI were considered the primary theoretical models but are combined and extended by including few additional variables. Data were collected from 220 respondents of travel and tour operating businesses in Malaysia and analyzed by applying PLS structural equation model technique.

The empirical results established that perceived cost, relative advantages, complexity and compatibility, observability, competitor pressure, value alignment, customer pressure, and trialability are positively connected with the behavioral intention except for external support. The results reveal that value alignment partially mediates the association between relative advantages and behavioral intention, complexity and behavioral intention, compatibility and behavioral intention, perceived cost and behavioral intention except in between trialability and observability.

This research is unique as the value alignment construct is included in the model, and thus it fulfills the literature gap by adding the mediation construct. This study contributes to enhancing AR's understanding of the Malaysian travel and tour operator industry through the lenses of owners or managers. It offers an integrated model that combines the TOE and DOI models, rare in this sector, and can be replicated or extended with validated scales.

Amazon Explore is a new online experience product from Amazon, which offers live stream sightseeing of destinations around the world. This paper aims to provide a first insight into how exactly Amazon Explore enters the virtual experience (VE) industry, and discuss the possible implications of its business model for the future of virtual and offline travel experiences.

Qualitative and quantitative methods of content analysis methods were employed in this study. The sample of this research consisted of 175 Amazon Explore products. Firstly, the authors analysed the content of each product, and then quantitative method were used to present the data. With this analysis, the authors presented how Amazon Explore is testing the foundations for new business models, and discuss the possible implications for the future of tourism. One year later, those same Amazon Explore products were reviewed again to check development progress. The following were the main questions regarding VE: How interactive are Amazon Explore products? How does Amazon Explore aim to ensure the monetisation of these products in an economically sustainable way in order to go beyond the “freemium” business model, often associated with VE as just another destination marketing tool?

This article presents the discussions of VE and virtual reality (VR). The authors determined the level of interactivity of the diverse VE offered themes with a model of four levels of interactivity. The results show that the analysed products achieve mostly only low levels of interaction. Regarding monetisation, Amazon Explore shows three possible future directions in the development of VE: as a marketing tool, as an extension of the offline experience and as potentially someday replacing real travel as part of the future monetisation scenario.

The article offers the first insights into Amazon's extension into the realm of VE in two time periods in 2020 and 2021, and, based on these preliminary results, discusses four possible scenarios for the future development of VE monetisation.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

This paper aims to analyze the adoption of social media platforms by tourists in Pakistan. Based on an adaptation of the technology acceptance model (TAM), this study assesses the factors that lead users to adopt these platforms.

A survey was administered to a convenience sample of 399 travelers who use social media in Pakistan. A Confirmatory factor analysis was conducted using AMOS to evaluate convergent and discriminant validity as well as composite reliability. Structural equation modeling was applied to examine the causal relationship among all proposed constructs.

The findings reveal that the perceived usefulness (PU) and perceived ease of use (PEoU) of a social media platform positively impact the behavioral intention of its users. The proposed constructs of compatibility, enjoyment, user expertise and e-trust all demonstrated their crucial roles in the adoption of a social media platform for tourism-related activities by enhancing the platform's PEoU and usefulness.

This research validates the relationship between PEoU and PU of a social media platform in the hospitality industry. Interestingly, this study has expanded TAM by validating the addition of four more constructs, (1) compatibility, (2) enjoyment, (3) e-trust, and (4) expertise, to add worth to this model regarding the understanding of social media usage in this specific industry. The findings are valuable both for managers and policymakers in the tourism sector in Pakistan, as the latter can utilize the results to entice a larger segment of social media users to the tourism industry.

Human group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city interest points to construct urban security risk indicators. This paper combines traffic data and urban alarm data to analyze the safe travel characteristics of the urban population. The research results are helpful to explore the diversity of human group behavior, grasp the temporal and spatial laws and reveal regional security risks. It provides a reference for optimizing resource deployment and group intelligence analysis in emergency management.

Based on the dynamics index of group behavior, this paper mines the data of large shared bikes and ride-hailing in a big city of China. We integrate the urban interest points and travel dynamic characteristics, construct the urban traffic safety index based on alarm behavior and further calculate the urban safety index.

This study found significant differences in the travel power index among ride-sharing users. There is a positive correlation between user shared bike trips and the power-law bimodal phenomenon in the logarithmic coordinate system. It is closely related to the urban public security index.

Based on group-shared dynamic index integrated alarm, we innovatively constructed an urban public safety index and analyzed the correlation of travel alarm behavior. The research results fully reveal the internal mechanism of the group behavior safety index and provide a valuable supplement for the police intelligence analysis.

The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.

The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.

The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.

The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.

The main purpose of this paper is to explore telepresence robots are being used in libraries to facilitate library services and also to explain the future trend in the application of robots in libraries.

Through a review of the literature, this paper analyzes various library websites and consults literature relating to the use of telepresence robots in libraries; the current application of robots in libraries has been highlighted along with case studies of libraries currently adopting telepresence robots.

The uses of telepresence technology in libraries help to enhance library services, reach new users and provide a more inclusive and accessible library experience. Telepresence robots enhance the quality and accessibility of library services, expand library outreach and provide new opportunities for virtual engagement and programming. The application of telepresence robots in libraries can offer many benefits, but there are also several challenges that libraries must address to ensure successful implementation.

This paper highlights how the application of telepresence robots in libraries improves service productivity in libraries and creates a more engaging environment for the user group. The benefits and challenges of using robots in the library and the future trend in the application of telepresence robots in libraries are also discussed.

This study aims to investigate the technology usage behaviour of the tourists in line with the modified unified theory of acceptance and use of technology (UTAUT) model.

Data were collected from a survey of 265 tourists using the random sampling technique. Partial least squares-based structural equation modelling (PLS-SEM) technique was used to analyze the data.

The findings revealed that performance expectancy, hedonic motivation and habit significantly influence the behavioural intention of tourists to use information and communication technology (ICT), while effort expectancy, social influence, and facilitating conditions do not have a significant influence. However, actual ICT usage behaviour largely depends on the behavioural intention of the tourists, and their habits, while the facilitating conditions do not have any influence in this case.

The findings uncover the core factors influencing tourists' actual ICT use behaviour that can assist the concerned stakeholders in designing tourism planning and sales. The study results also offer pathways for the world's tourism industry for a healthy recovery from the COVID-19 pandemic.

The findings have made robust contributions by extending the existing UTAUT-based literature by adding two new moderators in the relationship between behavioural intention and actual ICT usage behaviour.

This paper investigates the usage and trust of Chinese social media in the travel planning process (pre-trip, during-trip and post-trip) of Chinese tourists.

Through a combination of structured online survey (n = 406) and follow-up interviews, the research identifies the diversification of the demand-and-supply patterns of social media users in China, as well as the allocation of functions of social media as tools before, during and after travel.

Social media users are diverse in terms of their adoption of social media, use behaviour and scope; the levels of trust and influence; and their ultimate travel decisions and actions. Correlations between the level of trust, influence of social media and the intended changes in travel decisions are observed. Destination marketers and tourism industries should observe and adapt to the needs of social media users and potential tourist markets by understanding more about user segmentation between platforms or apps and conducting marketing campaigns on social media platforms to attract a higher number of visitors.

This paper demonstrated the case of social media usage in mainland China, which has been regarded as one of the fastest growing and influential tourist-generating markets and social media expansions in the world. This study further addressed the knowledge gap by correlating social media usage and travel planning process of Chinese tourists. The research findings suggested diversification of the demand-and-supply pattern of social media users in China, as well as the use of social media as tools before, during and after travel. Users were diversified in terms of their adoption of social media, use behaviour, scope, the levels of trust, influence and the ultimate travel decisions.

Destination marketing organizations should note that some overseas social media platforms that are not accessible in China like TripAdvisor, Yelp, Facebook and Instagram are still valued by some Chinese tourists, especially during-trip period in journeys to Western countries. Some tactics for specific user segments should be carefully observed. When promoting specific tourism products to Chinese tourists, it is necessary to understand the user segmentation between platforms or apps.

Social media is a powerful tool for tourism development and sustainability in creating smart tourists and destinations worldwide. In China, the use of social media has stimulated the development of both information and communication technology and tourism.