Purpose This study aims to identify factors affecting tourists’ intention of using travel apps installed in their smartphones. Design/methodology/approach A questionnaire was developed largely based on the available scales in the published literature. A total of 389 participants responded to the survey, out of which 343 valid responses were obtained for statistical analysis. Findings Significant predictors of smartphone app usage intention included performance expectancy, social influence, price saving, perceived risk, perceived trust and prior usage habits. Usage behavior was largely mediated by usage intention, except in the case of habits. Contrary to the expectation, factors such as hedonistic motivation, facilitating conditions or effort expectancy did not impact usage intention or behavior. Practical implications The study gives app developers vital cues on tourist expectations from the apps. Oftentimes, developers tend to focus entirely on the material utility of their apps, neglecting every other factor influencing use. One particular implication is that despite tourism being a hedonistic activity, travel app usage behavior is not a hedonistic activity. Originality/value This is one of the few studies to examine adoption of smartphone travel apps in an emerging economy context by using extended unified theory of acceptance and use of technology framework with additional constructs.

Purpose -Mapping apps are location based travel apps used for navigation and routing. These apps are gaining worldwide popularity because of its enormous potential. Despite of the growing popularity and utility of the mapping apps, the published literature in this area is scarce, leaving an unexplored area of research. Thus, the current study aims to identify factors affecting tourist's intentions to use mapping apps while travelling. Design -The Extended Unified theory of acceptance and use of technology (UTAUT2) was applied as the basis of the present study Methodology -The data was collected from 284 travellers in India using a structured questionnaire. The data was analyzed using Partial Least Square approach. Findings -The results indicated that the most significant antecedents of behavioral intentions are habit, facilitating conditions, performance expectancy and hedonic motivation. It was observed that the actual usage behavior was influenced by traveler's intentions and habit to use the technology (mapping apps). However it was noted that effort expectancy, social influence and price value had no significant effects on the tourist's intentions to use mapping apps while travelling. Originality of the research -Till date limited empirical studies have explored the adoption of mapping apps by travelers. This study is unique as it explores the adoption intentions using a relevant theoretical framework in the developing economy context wherein the use of mapping apps is still in the nascent stage. This research contributes to the literature of innovation adoption and provides an interesting perspective to companies developing location based travel mobile apps.

Purpose The purpose of this paper is to examine the determinants of user adoption of smartphone fitness apps in context of an emerging economy. Design/methodology/approach The present study uses the extended unified theory of acceptance and use of technology (UTAUT2) as the base model along with two additional constructs, i.e. self-efficacy and personal innovativeness. The data collection was done through an online survey, wherein a total of 324 valid responses were obtained for the statistical analysis. All the hypothesized relationships were tested through partial least square structural equation modelling (PLS-SEM) using an open source programming language and software environment, i.e. R Software along with plspm-package. Findings Significant predictors of smartphone fitness app adoption intention include effort expectancy, social influence, perceived value, habit and personal innovativeness. Further, this study confirms significant relationship between personal innovativeness and habit, self-efficacy and effort expectancy and effort expectancy and performance expectation. This study reveals that personal innovativeness is the strongest predictor of behavioural intention. Contrary to the expectations, factors like performance expectancy, facilitating conditions and hedonic motivation did not influence behavioural intention. Practical implications This study gives significant clues to app developers that can drastically influence the adoption of fitness apps. The findings suggest that marketers should focus on users with high personal innovativeness that can further act as role models and significantly influence their social circle. Interestingly, the findings suggest that fitness apps, as compared to other apps, should not emphasize much on the hedonic value of their offerings. Originality/value This study is one of the few studies to examine the adoption of smartphone fitness apps in an emerging economy context by using extended version of UTAUT2 model. Further, this study shows how new endogenous and exogenous variables (i.e. self-efficacy and personal innovativeness) contribute to better explanatory power of the UTAUT2 framework.

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Purpose Technology has revolutionized the delivery of health-care services, with e-consultations becoming popular mode of service delivery, especially during the pandemic. Extant research has examined the adoption of e-health consultation services, with little attention paid to examine the switching behavior. This study aims to identify factors affecting patients’ intentions to switch from conventional mode i.e. visiting hospitals/clinics to e-health consultations. Design/methodology/approach To understand this we use the push–pull–mooring (PPM) framework and integrate variables from status quo bias framework to the model. A cross-section research design was used, which rendered 413 valid responses which were obtained from the patients visiting a traditional hospital setup. The data was analyzed using partial least square – structural equation modeling using SmartPLS 3.0. Findings Findings suggest that push effects (inconvenience and perceived risk), pull effects (opportunity for alternatives and ubiquitous care), mooring effects (trust) and inertia significantly influence patients’ switching intentions from visiting hospitals/clinics to e-health consultations. Further, habit and switching cost positively influence inertia. Practical implications This study shall enable online health-care service providers and practitioners to understand patients’ intentions to switch to online health platforms and accordingly develop related marketing strategies, services and policies to encourage them to switch to the new offerings. Originality/value The current study enriches the previous research on e-health services by applying and extending PPM framework as the base model and showing its efficiency in predicting individuals switching intentions in the context of emerging economies. This study bridges the gap by focusing on switching behavior in context of health services.