Reliability value of In Northern Finland, the study of Koivumäki in 2008 investigated the perception of 243 customers toward new mobile service by UTAUT. Its findings showed that the familiarity of the users to the service has a significant impact on the intention to adopt this service while the time spent to use does not affect it.

For Chinese banking industry, based on the integration of UTAUT and test technology fit model (TTF), Zhou (2010) also supported that performance expectancy, task technology fit, social influence and facilitating conditions causes a significant effect on customers’ intention to adopt mobile banking. It also found that task technology has a significant influence on performance expectancy of mobile banking.  This study was conducted from 250 respondents.

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!


order now

In Thailand, by using extended UTAUT and adding other dimensions: perceived cost perceived convenience and perceived credibility, Bhatiasevi (2015) concluded that there are significantly positive relationships between performance expectancy, effort expectancy, social influence, perceived credibility, perceived convenience and customers’ adoption

Hanafizadeh et al. (2014) also studied various factors effect on banking adoption intention in Iran. Built on SEM approach and the sample size of 361 bank customers, the study found that perceived usefulness, compatibility, need for interaction, perceived ease of use, perceived risk, perceived cost, trust and perceived credibility significantly in effect m-banking adoption.

In Taiwan, by drawing from UTAT theory, Yu (2012) found major factors effecting m-banking acceptance of the region on sample size of 441 respondents are social influence, perceived financial cost, performance expectancy, and perceived risk.

Altilising from TAM and IDT, Koenig-Lewis et al. (2010) conducted a study from 155 participants aged 18-35 in Germany. This study revealed that while perceived usefulness, compatibility, and risk are salient factors in effecting consumer intention to adopt mobile banking. Similarly, built on TAM and TPB research structure, Sripalawat et al. (2011) concluded that subject norms to be the most influential factor, perceived usefulness to be the second influential factor, and self-efficacy to be the third influential factor in mobile banking adoption.

Sohail and Al-Jabri (2014) examined the dimensions of the adoption of mobile banking among 128 users and 338 non-users in Saudi Arabia. Relative advantage, complexity, compatibility, perceived risk and trial-ability are found to be critical factors to influence m-banking adoption. Moreover, other major contributions in effecting to customers’ intention are perceived risk, compatibility and trial-ability. Similarly, perceived risk is also found to negatively impact on performance expectancy and behavioral intention of m-banking in Pakistan (Anus et al. 2011).  Likewise, the study of Yang (2009) and Cruz et al. (2010) supported that perceived risk were top two barriers for adopting mobile banking services.Items