Behavioral Intention Analysis on E-Money Services in Indonesia: Using the modified UTAUT model

Abstract

The level of use of e-money services in Indonesia is still relatively low. Low in trust and high risk are thought to be determinants of the level of community behavioral intention. On the other hand, other factors of age, gender and level of education also affect the relationship of behavioral intention with the determinants. The purpose of this study is to determine the effect of the dimensions of trust (multi dimensional trust) and perceived risk on the intention of people's behavior on e-money services in Indonesia. Purposive sampling conducted on this study to the population of big city in Indonesia. Data collection was carried out with online Likert scale questionnaire, with instruments distributed in 5 big cities in Indonesia. The results of this study indicate that the dimensions of trust (Multi Dimensional Trust) influence the intention of the community in adopting e-money services, while the perceived risk does not affect the intention of the community in adopting e-money services. Performance expectation variable (Performance Expectancy) is the biggest factor that influences people's intention to adopt e-money services. Education as a moderating variable is the only variable that has significant effect on the influence of determinant variables on behavioral intention.

E-Money Payment: Customers’ Adopting Factors and the Implication for Open Innovation

“…This indicates that one or several domains from an established and widely applied basic framework, in this case, TPB and UTAUT, still provide consistent results. Analysis in the context of the use of e-money as a means of payment transactions consistently supports previous research results, i.e., that social factors and effort expectancy are predictors of behavior [26,27,44,47,48,52]. This means that customers will continue to use e-money, make it the first choice of payment, and keep the installed e-money application on smart devices because of external persuasion such as shops that they visit and close friends or family as social factors.…”

“…For example, in the case of online shopping, it was stated that shopping behavior online or through the internet was influenced by a person's attitude towards the shopping system [44,45] in the context of mobile banking adoption [46], use of non-cash systems [27], and adoption of smart home technology [47]. More specifically, it supports research carried out in the context of the use of electronic payments, mobile payments, the use of e-money, and similar topics [48,49].…”

Factors Influencing the Intention to Use Mobile Payment In Indonesia

“…Previous studies from , Perceived trust has a positive relationship between attitude and as well as Perceived ease of use toward using on mobile payment and intensity of using mobile payment, this is also supported by another study (Islam et al, 2020). However, based on his finding, Perceived trust negatively influences the user's perceived risk, which this also supported in other studies (Cabanillas, Leiva, et al, 2016;Giri et al, 2019). The results offer support that trust affecting the intention to use e-payment services.…”

“…Perceived trust in mobile payment negatively influences the user's Perceived of risk towards it (p = 0,035; t =2,111). There is an empirical study to support this Hypothesis, as shown in the research of Santosa et al (2021), Cabanillas, Leiva, et al (2016), and Giri et al (2019.…”

Acceptance of clinical decision support systems in Saudi healthcare organisations

“…The results of this study indicate that all the moderating variables adopted for this research, which included gender, age and experience, did not affect any of the 13 factors identified as influencing factors for GPs’ acceptance of CDSS. Several studies have similarly indicated the minimal effect or non-impact of these variables on users’ acceptance of technological systems, while other studies have indicated more particularly that age does not affect acceptance of IT (Giri, Apriliani, and Sofia, 2019; Gusman and Ariyanti, 2019), and some have indicated that gender does not affect acceptance of IT (Giri et al, 2019; Gusman and Ariyanti, 2019). Some researchers have also asserted that experience does not affect technology acceptance (Alasmari and Zhang, 2019; Harmandaoglu Baz, Cephe, and Balçikanli, 2019).…”