“…Hence, studies on the predictors of MFS/m-banking user attitude and behavior have recently gained momentum in the academic and business community because such research can assist MFS marketers to devise and implement better strategic decisions required for customer acquisition and retention (Malik et al, 2013;Saleh and Mashhour, 2014;Slade et al, 2015;Abdinoor and Mbamba, 2017;Cui et al, 2020;Manchanda and Deb, 2020). Using technology acceptance model (TAM) (Davis et al, 1989) and other related behavioral theories, several past studies identified numerous crucial predictors, such as perceived usefulness (PU)/relative advantage/performance expectancy, perceived ease of use (PEOU)/complexity/ effort expectancy, subjective norms, perceived functional and emotional benefits, consumer innovativeness, demographics, perceived risk, facilitating conditions and many more that can influence users' attitude and intention to use m-commerce/m-payment/MFS (Yang, 2005;Hsu et al, 2011;Yen and Wu, 2016;Chi, 2018;Gupta and Manrai, 2019;Al-Saedi et al, 2020;Jung et al, 2020;Manrai and Gupta, 2020).…”