Awareness and Usage of Mobile Healthcare Applications: A Comparative Study of Tata 1mg, Netmeds, Pharmeasy, Apollo, and Flipkart Health+

Abstract

This article aimed to analyse awareness level, frequency of usage, ease of usage about the selected Mobile Healthcare Apps and examined impact of Service Quality of mHealthcare Apps, Satisfaction level of mHealthcare Apps, and Price level on Trustworthiness of mHealthcare Apps. This comparative research has surveyed 111 users of mobile Healthcare Apps, in Kengeri, Bengaluru, India during the period of 30 days using structured questionnaire which included closed ended questions and likert scale. The sampling techniques adopted is snowball sampling technique. The collected data analysed using Percentage Analysis, Descriptive Analysis, Weighted Rank Method, Comparative Analysis, Correlation and Simple Linear Regression Analysis. Key findings reveal Apollo 24/7 as the frontrunner in terms of brand awareness and perceived ease of use. Service quality emerged as a primary determinant of trustworthiness, surpassing price value. The developed regression model effectively explains a significant portion of the variance in trustworthiness. These insights are particularly relevant for managers and developers of mHealth apps, as they emphasize the importance of maintaining high service quality to build and sustain trust among users. These findings underscore the importance of service quality in fostering trust among users of mobile healthcare apps. While the study provides valuable insights into consumer perceptions and behaviors, its reliance on snowball sampling necessitates cautious interpretation of results. However, the study is not without limitations. The use of snowball sampling introduces potential selection bias, and the relatively small sample size restricts the generalizability of the findings. Furthermore, the research is geographically and demographically limited to Kengeri, Bengaluru. Future research could expand on this study by conducting comparative analyses across different regions to explore how cultural differences influence trust in mHealth apps. Additionally, qualitative studies could provide deeper insights into user experiences and the underlying factors that drive trust or distrust in these applications.