Modern travelers prefer an easy and enjoyable experience upon travelling. According to several surveys, over 25% of respondents have installed mobile travel apps on their smartphone. Basically, the travel app is used to search and book flights or accommodation, while download and install the app is mainly to receive notification on the updated trip status and also for accessing app offline. Therefore, it's essential for tourism organization to emphasize on traveler preferences and new innovated technology could offer for competitive advantages in tourism industry. Generation Y grew up with technology and it constitutes 44% of population in Malaysia. Therefore, this research is focus on Generation Y in Malaysia, based on the UTAUT2 (Consumer Acceptance and Use of Information Technology) model to explore and predict the factors influencing the intention to use mobile travel apps. A total of 245 questionnaires were distributed to all states in Malaysia. Quantitative data were analyzed using IBM SPSS 22.0 and Smart PLS 3.0 software. The results findings show that performance expectancy has the highest significant relationship on behavioral to use mobile travel apps. It was followed by facilitating conditions and habit. Factors of effort expectancy, social influence, hedonic motivation and price value don't have much effect on individual's behavioral intention to use mobile travel apps. The theoretical, managerial and practical implications of these results are discussed.

PurposeMobile travel apps (MTA) smart features were identified based on recent travel application (app) trends and a literature review of MTA smart features. Subsequently, the MTA features that could be prioritised to increase user interest in MTA were determined. The MTA smart feature development challenges that should be mitigated were also identified.Design/methodology/approachThe app identification and selection were based on the one-stop solution characteristics containing the common function of travel apps and eight MTA smart features. A total of 193 Apple apps and 250 Google apps were identified, where 36 apps that met the inclusion and exclusion criteria based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart were selected for evaluation.FindingsThe high user ratings for apps from both app stores revealed the acceptance of smart technology in the tourism industry. Geolocation tracking services, travel itinerary generators, and real-time personalisation and recommendation were the three major features available in the included MTA. The challenges of MTA with smart features were highlighted from the tourism organisation, app developer and user perspectives.Practical implicationsThe findings can guide tourism organisations and app developers on the smart features that MTA should offer for user engagement. Technological organisations could optimise their technology stack by considering the identified smart features. The findings are valuable for scholars in terms of MTA aesthetics and usability to gain acceptability. The development challenges included significant investment in technology, location accuracy and privacy concerns when implementing MTA smart features.Originality/valueThe previous literature mainly focused on evaluating app quality, assessing app functionality, and user ratings using the Mobile Application Rating Scale, and scoping reviews of MTA articles. Contrastingly, this study is among the first in which MTA smart features were examined from a developer-centric perspective. Moreover, it is suggested that MTA includes integrated smart features for better tourism services and market penetration in the tourism industry.

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Mobile travel apps are essential tools in trip planning; they provide local insights and recommendation on destinations. Smart tourism features the extensive use of information and communication technology (ICT) which is a new evolution of old-style tourism and e-tourism, emphasised on two approaches: augmented reality (AR) and big data (BD). Several tourism studies have discussed the positive and negative impacts of adopting smart mobile travel apps in the tourism industry. Different factors may affect the app's adoption and acceptance of new technology. However, the level of adoption of smart mobile travel apps depends on the traveller's characteristics as each generation has different characteristics in the adaptability of smart technology. Therefore, this research model is based on the integration of the DeLone and McLean IS success (IS) model and consumer acceptance and use of information technology (UTAUT2) model to determine the factors influencing behavioural intention to use mobile travel apps for smart tourism among Generations X, Y, and Z.

Purpose Considering the limited understanding of determinants influencing the adoption of smart mobile tourism app (SMTA) featuring augmented reality (AR) and big data analytics (BDA), privacy concern (PC) and the risk of privacy information disclosure (PI) have threatened SMTA adoption. This study aims to propose an expanded consumer acceptance and use of information technology (UTAUT2) model by including new contextual components, integrated with privacy calculus theory (PCT) model to examine the determinants influencing behavioural intention (BI) to use SMTA. Design/methodology/approach Personal innovativeness (IN) and privacy information disclosure (PI) are incorporated in UTAUT2 model to determine its effect on SMTA featuring AR and BDA technologies from smart perspective. Both privacy concern (PC) and privacy risk (PR) derived from PCT model are also included to determine its influences on an individual's willingness to disclose privacy information for better-personalised services. We collected responses from 392 targeted participants, resulting in a strong response rate of 84.66%. These responses were analysed statistically using structural equation modeling in both SPSS 22.0 and SmartPLS 3.0. Findings Findings showed that personal innovativeness (IN), habit (HT) and performance expectancy (PE) significantly affect behavioural intention (BI) while privacy concern (PC) significantly affect privacy information disclosure (PI) to use SMTA. In contrast, effort expectancy (EE), hedonic motivation (HM) and privacy information disclosure (PI) had no significant effects on behavioural intention (BI) while privacy risk (PR) had no significant effects on privacy information disclosure (PI) to use SMTA. Originality/value The study findings help tourism practitioners in better comprehending recent trends of SMTA adoption for establishing targeted marketing strategies on apps to improve service quality. In addition, it enables app development companies acquire app users’ preferences to enhance their app development for leading app usage.