by Ellie Barker
The technological environment is forever changing, especially in relation to accessibility. As a result, technological advancements have attracted new users throughout all generation classifications. ‘Banking on the go’ illustrates the increasing availability of accessing mobile banking services whilst on the move and away from physical banking institutions.
Adoption of mobile technology has reached 4.77 billion consumers globally and around 68% of consumers in the UK (Statista 2017). The mobile app market accounts for approximately 44 million UK users (Statista 2017). Mobile apps represent a unique business industry specialising in production and maintenance of mobile app product and services. Input, however, comes from other sector and industry players. Heading towards post-Brexit, financial services need to provide far more interesting customer solutions (Severn 2016). Technological elements are, today, part of this immersive and engaging service solution. For financial services in the UK, firms are required to provide threshold services and engage customers with commonly used touchpoints. Although banks are increasingly providing customers with mobile apps, consumers’ readiness and adoption levels vary (Bolton 2017). Therefore, understanding mobile app adoption is relevant in society today due to the convenient and useful features it can provide consumers, such as controlling finances instantly.
Literature on e-banking and mobile banking adoption is existing and well developed already, although some factors are still to be considered. Hedonic motivations and various constructs which stimulate both adoption and use of mobile banking have not been discussed in detail. Hedonic motivations include factors such as enjoyment of the online service and the technological design. Utilitarian motivations such as convenience, practicality and efficiency have also been ignored. This research project will focus on mobile technology, specifically the mobile banking industry and mobile banking apps. The research will investigate the adoption of mobile banking by assessing the relationships between mobile technology-specific factors and their effects on Generation Z, Millennials, Generation X and Baby Boomers. The aim of this project is to clearly examine the motivations and technology-specific factors of mobile banking adoption.
Despite impressive adoption figures worldwide many consumers remain unwilling to adopt mobile technology or the benefits of mobile banking. Around 19% of people are accessing their bank on a daily basis through one of three channels; mobile app, physical location or website access via a desktop (Bolton 2017). Previous research looked into task-fit and usefulness of mobile banking as triggering or preventing adoption. However, studies on hedonic motivations are fragmented and do not capture values of mobile technology applications (Bolat 2015). Technology-specific factors are currently not recognised throughout the mobile technology industry; therefore, consumers continue to refrain from adopting mobile banking and mobile banking apps. Academics tend to treat mobile app settings similarly to those of electronic service settings. There are qualitative in nature studies but the outcome of these have not been input for quantitative studies, which this study intends to address.
This research investigates mobile technology alongside how motivations and generational differences impact adoption of mobile banking services. The model below was tested.
A quantitative research approach was used in order to evaluate why users adopt mobile banking services, and to what extent motivations and generational differences impact their intention and actual use. A quantitate survey was generated on Qualtrics which was later distributed throughout various online platforms, such as Facebook, LinkedIn, WhatsApp and E-mail. The survey was used to measure user profiles, motivations and feelings towards mobile banking services.
The survey received 213 responses with 31 responses missing. Hence, 182 responses are used for further analysis. Table 3 shows the majority of the sample, 40.88%, were aged 22-38 (Millennials) followed by 38.12% of the sample who were aged 39-59 (Generation X). A lower amount of responses was recorded from Generation Z and Baby Boomers. Further testing of the impact that generation gap, as a control variable (moderating factor).
The majority of respondents take part in internet banking, mobile app banking and face-to-face banking. Interestingly, although traditional methods of banking, face-to-face and telephone are used, more and more technology-enabled banking services are in use (238 mentions across the same with Internet banking being used by almost 81% of respondents). It is also surprising to see the uptake of mobile apps (almost 70% of respondents are using mobile apps).
Interestingly, across the younger generational group (18-21 and 22- 38) m-banking is one of the most popular platforms versus the older generational group (39-59) who prefer internet banking and finally 60+ opting for face-to-face approach. This light touch analysis already demonstrates differences in generational profiles.
The findings supported most of the given hypotheses, suggesting that varying motivations and generational differences do influence adoption and use of mobile banking. Moreover, research found that younger generations are concerned with hedonic features, whereas older generations are focused on utilitarian features. Further research is required for expansion on generational profile motivations together with research on additional factors combined with the proposed motivations of this study.
H3A, H3B, H3C and H3D tested the impact of generational profiles on relationships surrounding attitudes, adoption, use and motivations towards m-banking services. H3A was rejected and H3B and H3D were only partially accepted as they presented insignificant results. The relationship between attitudes and adoption of m-banking had the lowest impact from generational profile. From this it is clear age difference does not have an impact on the relationship between attitudes towards m-banking and adoption of m-banking. This result contradicts the study of Foon and Fah (2011) which suggests age acts as a major influence on ITA m-banking. Nevertheless, results show generational profile has a slight impact on the relationship between adoption and use of m-banking, suggesting age is a determinant of continued m-banking use which is in line with part of Foon and Fah (2011) study which suggests younger generations who acquire technology experience are more likely to use m-banking services and apps than older generations. Results show generational profile also has an impact on relationships between UM and use of m-banking, suggesting UM, such as convenience, practicality and efficiency are more of a concern for older generations when using m-banking services compared to younger generations. This supports the study of Munoz-Leiva et al (2017) suggesting the key advantage of m-banking is the ability to manage finances any time in any location, proving a thoroughly convenient tool (Jun and Palacios 2016).
Furthermore, the research is in line with the study of Surendran (2012) which suggests PU and PEU are key determinants of adoption and use, especially amongst older generations. Additionally, mobility and portability have been proved the most valued features of m-banking services (Cruz et al 2010; Liang et al 2007), supporting the requirement of convenience for Generation X and Baby Boomers. New research findings suggest that generational profile has the strongest impact on the relationships between HM and attitudes towards m-banking. Results show 49.5% of variance in attitudes towards m-banking are explained by hedonic motivations when age is the moderating factor. This is substantial and suggests younger generations are predominantly concerned with HM, such as enjoyment, excitement and interaction, which determines their overall attitude towards m-banking services. This supports existing research from academics, as attitude is deemed a key determinant of technology acceptance (Chuttur 2009). Additionally, the study of Hew et al (2015) suggests consumers are more inclined to use m-banking services and apps if they are user-friendly with interactive features, which in turn develop positive attitudes and a customisable experience (Chaffey 2017).
Remaining hypotheses (H1A, H1B, H1C, H2A, H2B, H4A, H4B) tested the link between attitudes, adoption, use and trust towards m-banking, as well as differences in motivations. Firstly, results show that 81.7% of variance in use of m-banking is explained by positive attitudes towards m-banking. This is significant and financial institutions should implement trials or extensive marketing to encourage positive attitudes which should support uptake and use. Furthermore, 67.9% of variance in ITA m-banking is explained by positive attitudes which, as stated above, is in line with the study of Chuttur (2009) who found attitudes to be a key determinant of technology adoption. Positive adoption of m-banking has also shown a positive impact on use of m-banking which builds on the study of Oliveira et al (2014), focusing on adoption of technology and suggesting consumer performance can be explained through TTF.
New findings from the research also suggest HM have a slight positive impact on attitudes towards m-banking. This supports the study of Bolat (2015) on mobile technology distinctiveness, in which a new hedonic motive perspective derives from as emotional and creative value is developed from personalisation features and consumers also obtain social value from immediate access to communication channels. Additionally, 66.8% of variance in use is explained by a positive impact from UM which is extensive, hence financial institutions should install practical, convenient and efficient features within their m-banking services and apps to encourage continued use. This new finding supports the study of Ewing et al (2013) which suggests one of the highest-scoring features of consumer usage is integrated payments, therefore providing convenience for m-banking customers.
The last hypotheses were based on trust of m-banking services. Results show nearly 50% of variance in adoption of m-banking is explained by trust which is in line with the study of McNiesh (2015) which suggests consumers lack trust towards m-banking as they have to release personal information through a technological device. Additionally, results show nearly 60% of variance in discouraged use of m-banking is explained by distrust, building on the study of Lee (2009) which suggests consumers are discouraged from adopting and using technology if they obtain a level of PR, such as performance or financial.
The infographic below presents an infographic concluding the study. As shown, the younger generation, Generation Z and Millennials, are predominantly concerned with hedonic motivations in relation to adoption and use of m-banking services.
Hedonic motivations, including fun, interactivity and enjoyment, have been found to generate positive feelings amongst a younger demographic, which in turn encourages their attitude towards m-banking, but most importantly the use. In contrast, the older generation, Generation X and Baby Boomers, are concerned with hedonic motivations, including convenience, practicality and efficiency. These aspects have been found to generate positive feelings amongst the demographic, which in turn encourages use of m-banking as well as positive attitudes towards the service.