Factors Associated With the Adoption of Health Apps: Evidence From Emerging Economies

Introduction

The usage of mobile applications (apps) has provided huge benefits to consumers, including helping search for information on online purchases (Taylor & Levin, 2014; Chakraborty, 2019a). A smartphone device’s operating system is capable of installing applications with various functions (Garavand et al., 2019; Chakraborty, 2020; Chakraborty, 2018). According to data from India, smartphone users make up about 19% of the Indian population. Mobile apps have become of vital importance due to advancement of technology (Materia et al., 2020; Chakraborty, 2019b; Chakraborty, 2019e). The increased usage of Internet and mobile phones has resulted in a growth in the usage of health apps by consumers (Chakraborty, 2019c). Healthcare apps offer an effective platform for information exchange and updates (Apidi et al., 2017; Chakraborty, 2019d). Despite being established as an expedient, effective tool for supporting a variety of health-related aspects, the adoption and acceptance of technology by consumers remain a challenge. The firms engaged in marketing of health apps as well as policy makers and government agencies are increasingly finding the adoption of health apps challenging. It is therefore imperative to define what factors can help in adoption of the healthcare apps by the users. Determining the factors that can lead to enhanced adoption of healthcare apps will help develop marketing strategies and targeted communications by the firms and agencies. The previous studies in this area have explored the health apps usage intention and its relationship with diet, weight loss and exercising (Carroll et al., 2017). UTAUT model was used previously to assess the adoption intention of health apps (Wei et al., 2020) in Chinese context. The perceived intentions of patients to adopt the health apps given by clinics has also been studied for identifying the influencing factors of health apps adoption (Balapour et al., 2019). Using UTAUT2 model in combination with personal innovativeness and self-efficacy, health apps adoption has been studied (Dhiman et al., 2019) in the past. Yet there is gap in the studies on this subject in the context of emerging economies. This lack of information in this area has been indicated in a more recent study (Yang et al., 2020). Based on this justification, this study aims to provide the relevant information, which the current studies on the subject do not provide.

This study uses four established theories to determine the factors that contribute to the adoption of mobile health applications. The Diffusion of Innovation (Agarwal & Prasad, 1999; Rogers, 1983); (2) Technology Adoption Model (Davis, 1989; Davis et al., 1989; Moore & Benbasat, 1991; Ndubisi et al., 2003); (3) Theory of Planned behaviour (Ajzen, 1991); and (4) Unified theory of acceptance and use of technology (Venkatesh et al., 2013). This study makes a unique contribution by combining these four theories in the context of health apps. Hence the research aims to answer the following two research questions

• RQ1.What is the association between the identified constructs and the behavioural intention?

• RQ2. Does behavioural intention influence the adoption intention?