In this subchapter, we will firstly introduce and explain the theoretical model developed for this thesis.
Afterwards, we will move to the specifics by elaborating on the hypothesised interrelationships between independent variables, the dependent variables, and moderators. Constructs will be explained in the order which they appear in the theoretical model, i.e., Performance Expectancy will be the first, Effort Expectancy second, and so forth. The proposed theoretical model (Figure 12). is based on Venkatesh's UTAUT2 model as the theoretical foundation but has been extended by integrating additional concepts grounded in literature. The framework takes the individual user as the unit of analysis, whilst the constructs represent factors that are hypothesised to influence the adoption and usage of mobile payment systems.
The theoretical model represents how we as researchers make logical sense of the relationships among the several factors that have been identified as important to the research problem. The framework flows logically from the documentation of previous research in the problem area (Uma Sekaran, 2016). In summary, the theoretical model depicts the interrelationships between the independent variables and the dependent variable, which are believed to be important for the dynamics of the situation being investigated. The framework helps the researchers to postulate or hypothesise and ascertain certain relationships, and to improve our understanding of the dynamics of the situation (ibid).
As it can be seen in the theoretical model, constructs listed on the vertical axis are categorised into two distinct groups: system-centric factors, and user-centric factors.
Constructs assigned to the former group all emphasise attributes of a mobile payment system. For example, Performance Expectancy refers to an individuals' belief that a mobile payment system will help him or her to perform and accomplish tasks (Venkatesh et al., 2012). Likewise, Perceived Security refers
the loss of personal and financial data when executing transactions and payments (Khalilzadeh et al., 2017). The latter group, user-centric factors, contains all the constructs that are of attitudinal nature. In contrast to system-specific factors, which emphasise the utilitarian value that mobile payment systems provide, the User-centric factors measure the users' internal subjective perception of accepting mobile payment systems. For example, Trust reflects a user's internal perception of the mobile payment system's trustworthiness and is measured as the extent to which an individual believes that using mobile payments is safe.
The categorisation of constructs into system and user-related factors has previously been used and verified by scholars researching not only mobile payment acceptance, but technology acceptance in general (Kim et al. 2009; Oliveira et al. 2016). For example, the study by Kim et al. (2009) examined the impact of factors that influence the adoption of mobile payments, and the authors categorised factors into two groups: individual differences, and mobile payment system characteristics (Kim et al., 2009).
Likewise, the study by Lwoga (2017) also studied user acceptance of mobile payment by using UTAUT as the theoretical base, however, in their research model constructs were categorised into user-centric factors, security factors, and mobile payment system characteristics (Lwoga, 2017). A similar approach was adopted by Keramati et al. (2016), who categorised factors affecting mobile payment adoption into behavioural and technical factors.
4.1 System-Centric factors
Firstly, Performance Expectancy is operationalised in the same way as in the original UTAUT2. This means that Performance Expectancy influences behavioural intention just as in UTAUT2, and its effect on behavioural intention is moderated by age and gender. Secondly, Effort Expectancy is also operationalised in the same way as in the original UTAUT2, meaning Effort Expectancy is hypothesised to influence behavioural intention, whilst its strength is moderated by age, gender and experience.
Thirdly, Facilitating Conditions is hypothesised to influence both behavioural intention and subsequent use behaviour, whilst its effect on both constructs is moderated by age, gender and experience. All these hypothesised relationships are the same as in the original UTAUT2.
Fourthly, Perceived Security is hypothesised to affect both behavioural intention and use behaviour, while the strength of its influence is hypothesised to be moderated by age and gender. Furthermore, the inclusion of Perceived Security as a new construct represents an extension of the original UTAUT2 framework. The strong relationship between Perceived Security, behavioural intention, and use behaviour has been verified extensively in prior mobile payment literature (Park et al., 2018; Shin, 2010;
Cobanoglu et al., 2015; Slade et al., 2013), thus providing justification for its inclusion in this thesis’
theoretical model. In this thesis, Perceived Security is a multi-dimensional construct that consists of related underlying concepts such as: Perceived Security and Risk.
Figure 9 - User-Centric Factors
4.2 User-Centric factors
Moving further down the vertical axis we see four constructs that have been grouped together under User-centric Factors.
Figure 10- System-Centric Factors
The first construct in the User-centric factors, Social Influence, is hypothesised to be a direct determinant of behavioural intention, whilst the strength of its effects is affected by age, gender, and experience.
The second construct, Trust, is a new additional construct that has not already been conceptualised in Venkatesh's UTAUT2. However, it has been argued that the most influential issue that consumers evaluate when contemplating online exchange is trustworthiness (Park et al., 2018). Moreover, Trust in technology has been linked to user technology adoption, signifying the role of Trust as a significant concept (Park et al., 2018; Shin, 2010). For these reasons, we believe that the higher level of Trust the consumers place in mobile payment services, the more likely they will form an intention to adopt mobile payments. Thus, Trust is hypothesised to positively correlate with both behavioural intention and use behaviour, whilst its effects are moderated by age and gender.
The third construct, Habit, is conceptualised in the same way as in UTAUT2, meaning Habit positively correlates with behavioural intention and use behaviour, and its effects are moderated by all three moderators: age, gender, and experience (Venkatesh et al., 2012). The fourth and final construct, Personal Innovativeness, is a new additional construct not previously captured in UTAUT2. However, previous research has verified that the higher the innovativeness level of a user, the greater the predisposition to feel comfortable with the technology and realise the benefits of the technology (Oliveira et al., 2016). In a mobile payment context, Personal Innovativeness is explained as the individuals' willingness to try new mobile technologies, i.e., mobile payments (Kim et al., 2010). Such willingness to try new technologies stems from the fact that innovative individuals are active information seekers, open to new ideas, and therefore, innovativeness will play a determining role in the intention to adopt new mobile technologies (ibid). Moreover, Personal Innovativeness is conceptualised as a personal trait, which is why it is placed under user-centric factors in the theoretical model. Based on the aforementioned accounts, we hypothesise that Personal Innovativeness will have a positive influence on behavioural intention to adopt mobile payments; whilst the strength of the relationship will be moderated by age and gender.
4.3 Theoretical Model
Figure 11- Theoretical Model