Importance-performance analysis in fitness apps. A study from the viewpoint of gender and age

Abstract

Background: We are currently undergoing a profound process of digital transformation that has favoured the development and use of apps in multiple facets of people's daily lives. In the fitness industry, this situation has facilitated the control of exercise and the maintenance of healthier lifestyles. However, it is not known how the perceived quality and importance of fitness apps vary for users based on gender and age, which is the objective of this study conducted among users of fitness centres.

Methods: By means of a convenience sample, 321 users from different centres of the boutique fitness chain Sano Centre (238 females and 83 males) took part in the study. They answered the 16 items of the MARS scale, distributed in four dimensions, in terms of importance and perceived quality. The existence of significant differences was analysed using non-parametrical statistics such as the U-Mann-Whitney (gender) and the H-Kruskal-Wallis (age). In addition, a cluster analysis, combining hierarchical and non-hierarchical methods, was analysed considering as a dependent variable the level of recommendation of fitness apps.

Results: Considering gender, in importance-performance analysis (IPA), credibility was the most important attribute for females and quality of information for males. In the case of age, credibility was the most important attribute in all the ranges. The cluster analysis established two groups (high and low recommendations of the fitness app). In importance, the first group scored better on all factors except entertainment and interest. In valuation, the scores were lower than on importance, especially in the low recommendation group.

Conclusion: Regarding usage behaviour, credibility is the factor to which users attach the highest importance and rating, regardless of gender and age. The main demand focuses on improving the gestural design and visual appeal, which will facilitate a better user experience.

Keywords: age; cluster analysis; digital platforms; fitness apps; gender.