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The purpose of this paper is to examine the relative influence of “reasons for” and “reasons against” adoption of mobile banking (m-banking) among Indian consumers.

Using the framework of behavioral reasoning theory (BRT), hypothesized relationships between values, reasoning constructs, attitude and intentions were developed. The hypotheses were tested using a representative sample of data obtained from Indian banking consumers (n=379). Confirmatory factor analysis and structural equation modeling were used to analyze the data.

The findings indicate that both “reasons for” and “reasons against” have an influence on m-banking adoption. Among the “reasons for” m-banking adoption, ubiquitous is the major determinant, and among the “reasons against” m-banking adoption, tradition barrier is the major determinant. The findings also confirm that value of “openness to change” significantly influences reasons for adoption and has no impact on reasons against and attitude toward m-banking.

This study examines customers in only one context (i.e. India). Future research can examine samples in other countries so that the results can be generalized. Also the mediating role of demographic factors can be studied in future studies to predict m-banking adoption.

The findings of this study emphasize the importance of examining both the pro-adoption and anti-adoption factors while developing marketing strategy. This study confirms that m-banking adoption can be increased if managers attempt to minimize the effect of barriers of m-banking adoption.

This is the first study to examine m-banking adoption using BRT, which investigates the reasons for and reasons against m-banking adoption in a single framework.

The purpose of this paper is to examine the determinants of user adoption of smartphone fitness apps in context of an emerging economy.

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.

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.

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.

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.

With the usage of social media and Web 2. 0, YouTube channels currently play a pivotal role in supporting a traveler’s destination visit. Travelers create their YouTube channels and share their past experiences in the form of videos, which helps other potential travelers to support their destination visit. The purpose of this paper is to understand how travelers adopt information through YouTube channels and how it influences the traveler’s intention to visit a destination.

A research model was constructed and empirically tested by using a sample of 486 respondents who watch YouTube channels before visiting a destination. Further, the hypotheses of this study were validated with the help of structural equation modeling using partial least squares. The respondents in this study were from Delhi.

This paper found comprehensiveness, relevance, timeliness, source expertise and attitude as the most significant predictors of a traveler’s destination visit intention through YouTube channel adoption. Further, source trustworthiness and accuracy were not found to be statistically significant.

The findings of this paper were based on data taken from the local respondents in Delhi. Further, it analyzed the influence of only seven dimensions on destination visit intention, which could have excluded some important factors that influence tourists’ destination visit intention.

This paper has provided implications for YouTube vloggers and tourists. The result proves that while making decisions regarding destination visit, tourists thinks critically and scrutinize the content of YouTube channels prior to deciding a destination. So, vloggers should provide relevant, comprehensive and accurate destination information through their videos to tourists.

To the best of authors’ knowledge, this paper is the first in the Indian context to examine the adoption of YouTube channels before visiting destinations through information adoption models with additional constructs.

The purpose of this paper is to utilize the novel approach of applying the behavioral reasoning theory (BRT) to examine the adoption of internet of things (IoT) based wearables for the healthcare of older adults and it aims to understand the relative effect of “reasons for” and “reasons against” adoption of IoT-based wearables for health care among older adults.

The hypothesized relationships were established using the BRT and empirically tested using a representative sample of 815 respondents. The data were analyzed using the PLS-SEM method.

The findings of this study demonstrate that adoption intention of IoT-based wearables for the health care of older adults is influenced by “reason for” and “reason against” adoption. The finding shows that “reasons for” adoption are ubiquitous, relative advantage, compatibility and convenience and “reasons against” adoption are usage barrier, traditional barrier and risk barrier. Value of “openness to change” significantly influences the “reasons for” and “reasons against” adoption of IoT-based wearables.

This cross-sectional study is conducted only in the Indian context and future research can be conducted in other countries to generalize the results.

This research highlighted both the adoption factors—“for” and “against,” which should be considered while developing marketing strategies for IoT-based wearables for health care of older adults. Adoption of IoT-based wearables for healthcare of older adults will increase when marketers endeavor to minimize the effects of the anti-adoption factors.

This is a unique study that examines the adoption of IoT-based wearables for healthcare among older people using the BRT, by probing the “reasons for” and “reasons against” adoption in a single framework.