Consumer adoption of smartphone fitness apps: an extended UTAUT2 perspective

Abstract

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.

Patients’ perceptions of teleconsultation during COVID-19: A cross-national study

“…Another positive relationship emphasizes the value of Habit in adopting medical teleconsultation. Other health-related technology researchers validated these results in previous studies ( Duarte and Pinho, 2019 ; Ravangard et al., 2017 ; Dhiman et al., 2019 ). Videoconferences became part of people's daily life, especially during the COVID-19 pandemic and the isolation period.…”

Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach

“…Another study conducted by Dhiman et al (2019) applying UTAUT2 model also explored that significant predictors of Smartphone health fitness apps adoption intention include effort expectancy, social influence, perceived value, habit and personal innovativeness.…”

The Intention to Use Fitness and Physical Activity Apps: A Systematic Review

“…Analyzing the sample used in the different studies, there is a total of 16,025 subjects with an average sample of 843.42 subjects per study, with the Ndayizigamiye; Kante, and Shingwenyana study [54] having the smallest sample (n = 139) and Wei, Vinnikova, Lu and Xu study [55] having the largest sample with a total of 8840 subjects. Approximately a half of the studies (n = 8) used university students as a sample, followed by studies that considered users of sports applications (n = 4) and other studies took as their general population [54][55][56], a population of sports consumers [45], employees of a sports organization [57] and members of a fitness community [44,58]. Most studies had a higher proportion of females than males (n = 9), followed by studies that had parity in the sample (n = 5), four studies had a higher proportion of males while one study did not indicate the gender distribution of the sample [34].…”

“…Li, Liu, Ma and Zhang [46] sampled subjects over 25 years of age, while Huang and Ren [60] and Mohammadi and Isanejad [57] were at least 30 years old. Regarding the type of App evaluated, six studies evaluated the intention to use diet and fitness applications [30,44,51,52,55,59], another five studies evaluated sports information Apps [42,43,53,57,62], two studies measured the intention of fans to use the sports team app [1,45], health and fitness app [56,61], or fitness [58,60] and one study evaluated a social fitness-tracking app [63] and mHealth related to promote physical activity [54]. The most widely used theory for the design and use of the mobile sports app intent of use assessment instrument was TAM (n = 10).…”