| Quantitative predictive research methodology was used to examine the perceptions of U.S. banking customers regarding their usage of biometric automated teller machines (ATMs). The research relied on Ngugi, Kamis, and Tremaine's 2011 biometric intention to use model. Data were collected using the measurement scales of Ngugi et al.'s user perception survey. The participants' responses were collected using an online version of the survey. A total of 388 completed responses were analyzed to discover if a relationship exists between participants' gender and/or age with regard to the following biometric critical factors: perceived system security, perceived system false acceptance rate, perceived system false rejection rate, perceived system invasiveness, facilitating conditions, system trust, and intention to use. The research highlighted the impact of biometric ATMs in the banking industry with regard to large international banks and small U.S. regional banks and credit unions, as well as how customer demographics influence factors in different technology acceptance models. The findings indicated that banking customers' gender is a significant predictor of biometric system accuracy. The findings also indicated that banking customers' age is a significant predictor of feelings of system invasiveness, feelings of biometric system security, and biometric system trust. Based on the results of the research, inferences and conclusions are discussed. The study also presented the implications of the findings from a scholarly perspective related to technology acceptance. Furthermore, implications are discussed from a practitioner's perspective with regard to implementing biometric technologies in an organizational setting. Lastly, suggestions for further research are discussed. |
