The purpose of this study is to measure the role of factors affecting E-loyalty of visitors to a Tourism Website in Iran. A sample of 384 users of a destination website was analysed by using LISREL software. The results show that, except E-trust and E-commitment variables, all variables such as E-satisfaction play influential roles in E-loyalty to a destination website.

Purpose This study aims to investigate the predictive technology acceptance models and their evolution in the tourism context. These predictive models make a knowledgeable decision about the possibility of future outcomes by analysing data. As futurists are interested in making a prediction about the likelihood of different behaviours over time, researchers of these predictive models have focussed on behaviour and predicting the intentions of users. This study proposes to demonstrate the revolution of these models and how are changed overtime. It also indicates the role of them in future studies. Design/methodology/approach By reviewing the predictive models and literature, this study looks in-depth in the process of alteration of these models. Findings This study explores the reasons of the evolution of predictive models and how they are changed. It shed light on the role of predictive models in future research and will suggest new directions for forthcoming studies. Research limitations/implications One of the main limitations of this study is that as the world is currently struggling with COVID-19 and predictability of these models will be changed. As the future is disruptive, it cannot be concluded that how these models will be altered in future. Practical implications Role of predictive behavioural models of tourists is fundamentally crucial in assessing the performance of planners and marketers of tourism services in the future. It will also vastly helps the successful development of tourism sectors, and it has practical value for all tourism stakeholders. Originality/value Few studies have focussed on the evaluation of these models and their role in future research.

Purpose – This study aims to investigate the effects of XR technologies on the behavioral intentions of disabled tourists using a modified Technology Acceptance Model (TAM). Design – The model includes perceived trust, perceived control, perceived efficacy, and perceived enjoyment as determinants of technology acceptance by disabled tourists. The hypotheses derived from the literature were empirically tested. Methodology/Approach – The proposed model was tested by collecting data from 640 disabled tourists in Iran over a six-month period. An online survey was answered after watching two videos, representing the application of VR and AR. A quantitative method was applied, the PLS-SEM method was conducted to analyze the data. Findings – The model was significantly supported by the results on the determinants of attitudes of people with disabilities toward XR technology. Other than the effect of perceived efficiency on PEOU, all the hypotheses were supported, demonstrating the positive effects of each of factors on the attitudes of disabled tourists and their behavioral intentions towards XR technology. Originality of the research – This study significantly expands the academic knowledge on the fundamental factors affecting behavioural intentions of disabled tourists, as 15% of the world’s population. This is the first study to investigate these factors in relation to the disabled tourists and XR technologies. This study will provide insight to marketers and stakeholders on the behavioral intentions of disabled tourists.

The purpose of this study is to measure the role of factors affecting E-loyalty of visitors to a Tourism Website in Iran. A sample of 384 users of a destination website was analysed by using LISREL software. The results show that, except E-trust and E-commitment variables, all variables such as E-satisfaction play influential roles in E-loyalty to a destination website.

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