Augmented reality adoption intention among travel and tour operators in Malaysia: mediation effect of value alignment

PurposeThis 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.Design/methodology/approachThe 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.FindingsThe 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.Originality/valueThis 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.

Machine learning models for predicting international tourist arrivals in Indonesia during the COVID-19 pandemic: a multisource Internet data approach

PurposeThis research presents machine learning models for predicting international tourist arrivals in Indonesia during the COVID-19 pandemic using multisource Internet data.Design/methodology/approachTo develop the prediction models, this research utilizes multisource Internet data from TripAdvisor travel forum and Google Trends. Temporal factors, posts and comments, search queries index and previous tourist arrivals records are set as predictors. Four sets of predictors and three distinct data compositions were utilized for training the machine learning models, namely artificial neural networks (ANNs), support vector regression (SVR) and random forest (RF). To evaluate the models, this research uses three accuracy metrics, namely root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE).FindingsPrediction models trained using multisource Internet data predictors have better accuracy than those trained using single-source Internet data or other predictors. In addition, using more training sets that cover the phenomenon of interest, such as COVID-19, will enhance the prediction model's learning process and accuracy. The experiments show that the RF models have better prediction accuracy than the ANN and SVR models.Originality/valueFirst, this study pioneers the practice of a multisource Internet data approach in predicting tourist arrivals amid the unprecedented COVID-19 pandemic. Second, the use of multisource Internet data to improve prediction performance is validated with real empirical data. Finally, this is one of the few papers to provide perspectives on the current dynamics of Indonesia's tourism demand.

The technology acceptance model revisited: empirical evidence from the tourism industry in Pakistan

PurposeThis 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.Design/methodology/approachA 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.FindingsThe 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.Originality/valueThis 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.

I'm afraid to travel! Investigating the effect of perceived health risk on Malaysian travellers' post-pandemic perception and future travel intention

PurposeThis study investigates the effect of COVID-19 pandemic perceived health risk on traveller's post-pandemic perception and future travel intention. The study aims to provide insight into the unprecedented COVID-19 pandemic and its potential influence on tourist behaviour.Design/methodology/approachTwo hundred and forty-four responses were gathered quantitatively through an online survey. The research hypotheses were analysed using the partial least square structural equation modelling (PLS-SEM).FindingsThis study found that COVID-19 affects tourists' travel behaviour. Key findings found that perceived health risk discourages travel attitudes and eventually lessens their future travel intentions. Results also suggest future strategies/directions for restarting the tourism industry.Practical implicationsThe study outcome assists tourism stakeholders in understanding the changes in tourist behaviour amid the heightened perceived health risk of COVID-19. Tourism policymakers and industry players should consider exploring how to mitigate similar health crises in the future.Originality/valueBy extending the theory of planned behaviour (TPB), this study establishes a theoretical framework in exploring the interrelationships between perceived risk, post-pandemic perception and future travel intention. This study sets a significant research agenda for future tourism research in understanding the mechanism behind health risk perceptions and tourist behaviour.

COVID-19 and tourist mobility at destinations: a literature review and emerging research agenda

PurposeThis paper aims to review conceptual and empirical studies that analyse the impact of the pandemic on mobility and tourism behaviour at destinations in order to identify proposals, forecasts and recommendations to guide the future research agenda on the subject.Design/methodology/approachThis study used a systematic literature review to synthesise information from scientific articles published in journals indexed in the Web of Science database related to tourism mobility at destinations during the COVID-19 pandemic.FindingsThis article found that, according to the existing literature, the COVID-19 pandemic is acting as a catalyst for the sustainable transition of tourism. Although the findings reveal a lack of empirical research on the impact of the pandemic on tourism mobility at destinations, the article synthesizes the short- and long-term impacts of the pandemic and sets out the future research agenda on tourist mobility at destinations.Originality/valueTo the best of the authors' knowledge, this is the first systematic review of the impact of the pandemic on mobility and tourism behaviour at destinations that attempts to describe the emerging challenges and the agenda for future research.

Regenerative tourism in Aotearoa New Zealand – A new paradigm for the VUCA world

PurposeThe paper provides a summary of the findings from GOOD Awaits – The Regenerative Tourism New Zealand (NZ) Podcast and envisions a regenerative future for tourism in Aotearoa.Design/methodology/approachThis paper is based on the findings from the GOOD Awaits Podcast, a series of interviews with pioneers and practitioners of regenerative tourism. The podcast was created as a platform for the collective discovery of a new way forward for tourism in the wake of COVID-19, and the series provides a detailed summary of the regenerative tourism movement in NZ.FindingsThrough these interviews, a vision for a regenerative visitor economy in Aotearoa emerged. This new model is rooted in indigenous knowledge and living systems theory. It is a paradigm shift that allows us to see tourism as a living ecosystem and requires innovative economic models, such as social entrepreneurship, systems level changes to the way tourism operates and is governed, local tourism solutions with community thriving as the primary aim and much more collaboration both within tourism and across sectors.Originality/valueRegenerative tourism is an emerging model and one that is rapidly gaining traction in NZ and globally. The GOOD Awaits podcast is a unique, thoughtful and practical demonstration of what this model could look like in Aotearoa. It demonstrates the potential and feasibility of regenerative tourism practice, and the response has shown the desire for these conversations at a national and international scale. This paper is an accessible summary of the podcast's first season and has value for anyone interested in the regenerative tourism movement in Aotearoa.

Optimization model: the innovation and future of e-ecotourism for sustainability

PurposeThis study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in geographic areas and the application of ecotourism elements that are integrated with big data innovation through artificial intelligence technology.Design/methodology/approachData analysis is performed through dynamic system modeling. Simulations are carried out in three models: First, existing simulation models. Second, Scenario 1 is carried out by utilizing a causal loop through innovation of big data-based artificial intelligence technology to ecotourism elements. Third, Scenario 2 is carried out by utilizing a causal loop through big data-based artificial intelligence technology on aspects of ecotourism elements and destination competitiveness.FindingsThis study provides empirical insight into the competitiveness performance of destinations and the performance of implementing ecotourism elements if integrated with big data innovations that will be able to massively demonstrate the growth of sustainable tourism performance.Research limitations/implicationsThis study does not use a primary database, but uses secondary data from official sources that can be accessed by the public.Practical implicationsThe paper includes implications for the development of intelligent technology based on big data and also requires policy innovation.Social implicationsSustainable tourism development.Originality/valueThis study finds the expansion of new theory competitiveness of ecotourism destinations.

Prioritizing motivators influencing intentions to visit spiritual destinations in India: an application of analytical hierarchical process (AHP) approach

PurposeSpiritual tourism is becoming a significant growth area of the Indian travel market, with more Indians opting to go on pilgrimage to popular religious cities. There are many spiritual destinations where some of this life's essences can be sought to enjoy harmony and peace. The study aims to prioritize motivators driving the intentions of the tourists to visit the spiritual destination.Design/methodology/approachThe current study applied the analytical hierarchical process, a multi-criteria decision-making technique, on the sample of visitors from all the six spiritual destinations to rank the motivational factors that drive the intentions of the tourist to visit a spiritual destination.FindingsThe study's results postulated that spiritual fulfillment motives and destination atmosphere are the top prioritized motivations, while destination attributes and secular motives emerged as the least prioritized.Practical implicationsThe research study provides valuable insights to the spiritual tourism industry stakeholders to target the tourists' highly prioritized motivations to augment the visits to a particular spiritual destination.Originality/valuePrevious research has explored the motivations and modeled their relationships with tourists' satisfaction and intentions. But, the present study has applied a multi-criteria decision-making technique to add value to the existing knowledge base.

Fashioning tourism future for visiting large cities

PurposeLarge cities are and will continue to become important tourism destinations in foreseeable future. Tourists' motives of the present is the prognosis for their future tourists' behavior. In respond to the longstanding critics in city tourism study, the present research aims to examine the underlying motives of tourists visiting large cities and offer insights into fashioning tourism future for visiting large cities. The identified motives inform three distinct implications fashioning tourism future of large cities.Design/methodology/approachA quantitative investigation was performed by surveying city tourists. Measurements on the survey form were derived from both scholarly and grey literature in relation to tourists' motivations. 326 valid questionnaires were netted to attain the study aim. Three-quarters of respondents were from Europe, Australia and Pacific. Descriptive analysis and exploratory factor analysis were conducted to achieve the research aims.FindingsFive underlying motives of tourists visiting large cities were revealed: shopping indulgence, urban commons, city icons, cultural and lifestyle and personal advancement. Mapping the findings with a conceptual scheme depicting tourism product in destination, the author revealed a new dimension, urbanity and offered critical reflection on three implications for the tourism future of large cities.Originality/valueLiterature examining city tourists' motives neglect the context-specific measurements while administering the investigation. The research design embraces the urban-specific measurements in the data collection tool, contributing to deeper understanding on how tourism functions in cities. A new dimension, urbanity, which illustrates tourists' motives exclusive in large cities, was identified. Furthermore, three implications fashioning tourism future of large cities are revealed with the support of empirical evidence.

Global tourism in crisis: conceptual frameworks for research and practice

Purpose The aims of this Editorial are twofold: (i) synthesise emergent themes from the special issue (ii) tender four theoretical frameworks toward examination of crises in tourism. Design/methodology/approach The thematic analysis of papers highlights a diversity of COVID-19 related crises contexts and research approaches. The need for robust theoretical interventions is highlighted through the four proposed conceptual frameworks. Findings Crises provides a valuable seam from which to draw new empirical and theoretical insights. Papers in this special issue address the unfolding of crises in tourism and demonstrate how its theorization demands multi and cross-disciplinary entreaties. This special issue is an invitation to examine how global crises in tourism can be more clearly appraised and theorised. The nature of crisis, and the extent to which the global tourism community can continue to adapt remains in question, as dialogues juxtapose the contradictions between tourism growth and tourism sustainability, and between building back better and returning to normal. Originality/value The appraisal of four conceptual frameworks, little used in tourism research provides markers of the theoretical rigour and novelty so often sought. Beck’s risk society reconceptualises risk and the extent to which risk is manmade. Biopolitics refers to the power over the production and reproduction of life itself, where the political stake corresponds to power over society. The political ecology of crisis denaturalises “natural” disasters and their subsequent crises. Justice complements an ethic of care and values like conative empathy to advance social justice and well-being.