Various theories and models were deployed in previous studies of user satisfaction and continuance usage intentions in different areas. Expectations Confirmation model deployed to find the satisfaction and continue intentions among Chinese consumers (Chong, 2013); User satisfaction regarding smartphones studied with the help of Bhattacherjee’s post acceptance model (Liang et al, 2018); continued intention in purchase of mobile phones used flow theory (Gao et al, 2015); Contingency and task technology theories employed to find the variables of consumer satisfaction in mobile tourism shopping (Kim et al.,2 015). Modified TAM extended with additional variable- perceived enjoyment to explore the user satisfaction and continuance intention to use smartphone for shopping by (Agrebi and jallais, 2015); TAM was also used to find the variables of user satisfaction of mobile App services in life insurance (Lee et al., 2015); (Shang and Wu., 2017) study used combination of TAM and ECM model in mobile shopping to find their influence on consumer satisfaction and continuance intention. (Cao et al., 2018) used Trust transfer theory to predict the trust construct in mobile payment and their effect on satisfaction and continued intentions. (Marinkovic et al., 2017) combined various models perceived usefulness (TAM), perceived enjoyment (flow theory), and social influence (UTAUT) to investigate the customer satisfaction.
UTAUT model was used to measure the behavioural intentions of users and UTAUT also used to identify the customers usage intentions in different technologies that include Mobile banking, Mobile commerce, and Internet banking etc. researchers deployed UTAUT in different domains such as Internet banking (Rahmath Safeena et al., 2017); education (Rinku Dulloo and M. M Puri, 2019; Setiani, N. et al., 2020; Jalal Sarabdani et al., 2017); government services (Faaeq M. A. et al, 2014; Saxena, S., 2018; Olabode Olatubosun and K.S. Madhavarao, 2012) and health care (Sreejesh, S et al., 2021; W.B. Arfi et al., 2021; Plotzky C et al., 2021) domains. In this paper, it is used to check the continuance intention and recommendation intentions to use UPI.UTAUT has been used in mobile technology studies related to Mobile banking (Zhou et al, 2010; Mohamad saparudin et al., 2020; OslyUsman et al., 2020); Mobile tourism shopping (Tan et al, 2018); Mobile commerce (Chong, 2013;Veljko Marinkovic et al., 2019); Mobile advertising (Wong et al., 2015); Mobile learning (Chao, 2019). UTAUT model was used to measure the behavioural intentions of users, in this paper it is used to check the continuance intention and recommendation intentions to use UPI. The research model was developed by modifying UTAUT with additional variables as shown in the figure 1.
Performance Expectancy (PE) - It is degree to which using a technology will provide benefits to its users in performing certain activities. Studies explored the impact of PE on consumer satisfaction in mobile shopping (Shang and Wu, 2017; Agrebi and Jallais, 2015); Mobile learning (Chao, 2019). PE has affected satisfaction positively in mobile learning (Chao, 2019); mobile Apps (Tam et al, 2018); mobile commerce (Chong, 2013; Marinkovic et al, 2017). In this study, it is defined as the extent to which consumers think utilising UPI will achieve a specific goal. PE will effect user satisfaction and have an impact on users' intentions to continue using UPI.
H1: Performance Expectancy is positively related to user satisfaction.
Effort Expectancy (EE) - The degree of easiness involved with using technology is a key variable in the UTAUT paradigm. A person's perception of how easy it would be to utilise a technology is referred to as perceived ease of use. Studies have conflicting results that: EE affects consumer satisfaction positively in mobile commerce (Yeh and Li, 2009); mobile insurance (Lee et al., 2015); mobile shopping (Agrebi and Jallais, 2015; Shang and Wu, 2017). It is suggested that EE will affect satisfaction with the usage of UPI in this study, where it is defined as the level of ease associated with using UPI.
H2: Effort Expectancy is positively related to user satisfaction
Social Influence (SI) - refers to degree that users perceive that family and friends believe they should use a particular technology. Social influence denotes the effect of important people’ believes on user behaviour, their reviews can be affecting the usage of mobile technologies (Tao Zhou, 2011). So that electronic payment providers should use Word of mouth to facilitate user’s intentions. A study found that social ties have significant impact on satisfaction and continued intention in mobile social apps (Hsiao et al, 2016); satisfaction had also affected significantly by Social Influence in mobile shopping (San-Martin et al., 2016). It is defined in this study as the extent to which a person believes that another significant person encourages him or her for using UPI.
H3: Social Influence is positively related to user satisfaction.
Facilitating Conditions (FC) - someone’ believes that available organisational and technical infrastructural support to use of a system. We can say that Facilitating conditions mean users have necessary resources and knowledge to operate UPI services. In this perspective, the availability of customer support, mobile devices, an internet connection, and QR codes are facilitating conditions for employing UPI services. The degree to which a person believes that an administrative and technological framework is in place to facilitate the usage of UPI is what it is referred to as in this study. In massive open online courses Facilitating conditions affected User satisfaction significantly (Liyong Wan et al., 2020). FC also found significant influence on consumer satisfaction in online services in South Korea. (Gholami et al,2012; Minki Park, 2020).
H4: Facilitating Conditions is positively related to user satisfaction.
Personal Innovativeness (PI): personal innovativeness can be referring as individual’s adoption of new things/ products as compare to others in the community of which they belong (Leavitt and Walton, 1975). Innovativeness has great role to know the users intentions to use new electronic technologies, but people have not so great experience about new mobile innovations (Kim et al., 2010).
The studies found that personal innovativeness has positive and significant effect on user’s satisfaction (Khan et al., 2019). Personal innovativeness affected satisfaction positively but personal innovativeness was not associated with continuance intention in IT (Chou and Chen, 2009). In m-commerce context personal innovativeness has positive influence on continuance intention (Lu June, 2014). Mobile tourism studies showed that more satisfied tourists with use of innovative technology likely to have usage intentions of it (T. Jung et al., 2015).
H5 and H6: personal innovativeness is positively related to user satisfaction and Continuance intention to use UPI.
Satisfaction (SAT)- Satisfaction means the fulfilment of expectations. It is one of the pillars in marketing and an important factor that affects trustworthiness of the consumer (Marinkovic et al., 2017). Satisfaction increases if after purchasing the consumer is experiencing improved product or service than his expectations (Yeh and Li 2009). Satisfied customers normally repurchase the products and take part in constructive spread of information (Wang and Liao, 2007).
Continuance Intention (CI) - refers to a person's long-term or continuing purpose to use a technology (Bhattacherjee,2001). The main factor affecting users' intention to continue using a service is their level of satisfaction. Users are more satisfied with the community when they have had positive experiences utilising it, when problems are successfully solved, or when they feel like they belong there (Han et al, 2018). In mobile commerce (Chong, 2013), (Luqman. A. et al., 2016), mobile shopping (Shang and Wu, 2017), mobile purchases (Gao et al., 2015), mobile banking (Liébana et al., 2017), mobile utilities (Kuo et al., 2009; Susanto et al., 2016), and mobile apps (Kuo et al., 2009), satisfaction was discovered to be a significant factor (Hsiao et al., 2016; Tam et al., 2018).
H7: User’s satisfaction is positively related to continuance intention.
Pace of Innovation (POI): It is the pace at which innovations in the technology are occurring at which pace. The digital payments technologies are moving forward at revolutionary speed; users are willing to use new digital payment systems (Cabanillas et al, 2017). In India, As compared to other technologies UPI is changing fast and innovations in UPI occurring frequent. (Camilleri, 2019) Study found that pace of technological innovation has no relationship with intention to use social media.
H8: the pace of innovation has positive and significant effect on their continuance intention to use UPI
Intention to recommend (IR): Word of Mouth (WOM) has a great influence on intention to recommend in firm performance (Keiningham et al., 2007; Morgan and Rego, 2006; Reichheld, 2003). Literature depicted that Continuance intention as well as intention to recommend were both influenced by satisfaction, moreover, various factors such as quality of system, perceived usefulness perceived enjoyment, confirmation, quality of information and satisfaction affected continuance intention and intention to recommend in information based mobile application (Setyawan et al., 2017). Higher satisfaction towards technology usually has more continuance intentions to use it and go in for positive word of mouth (Wang and Liao, 2007).
H9 Continuance intention of using UPI is positively associated with Intention to recommend.