UTAUT2 Survey on Online Fitness Adoption in India (2026)

This dataset accompanies a study examining whether constructs of the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) predict behavioral intention (BI) to use online fitness services among Indian respondents. The data were collected in 2026 via a Google Forms survey and include two files: the raw responses and the cleaned dataset with pre-computed construct scores. Each of the eight UTAUT2 constructs (Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Price Value (PV), Habit (HAB), and Behavioral Intention (BI)) is measured by three Likert-scale items (1–5). The dataset also includes demographic variables: age, gender, state of residence, education level, monthly income, and prior experience with online fitness. Multiple linear regression (R² = 0.53, F = 25.1, p < 0.001) identified four significant predictors of BI: PU (β* = 0.415), HAB (β* = 0.307), HM (β* = 0.191), and PEOU (β* = 0.129). These results are broadly consistent with prior UTAUT2 research on fitness app adoption. The data can be used to replicate the analysis, test alternative models or compare findings across populations. The attached PDF contains screenshots of the interactive dashboard built in Yandex DataLens to visualize the survey results. The dashboard can be accessed via the Related links. This dataset was produced as part of a coursework project at the Faculty of Computer Science, HSE University (Moscow).