Factors Affecting the Internet Banking Adoption

Abstract

Internet banking is a beneficial service; it is less costly, offers the flexibility of time and space, and have excellent customer service. The commercial banks of Mongolia are offering internet banking to its customers to capitalize on its advantages. However, these services remain underutilized by their customers. The factors affecting the use of internet banking in Mongolia remain unknown. This study has integrated the E-service-quality model with the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) to investigate the factors affecting the use of internet banking services offered by the commercial banks in Mongolia. The data was collected through the survey method. Structured Equation Modeling (SEM) was used for the analysis. The results indicate that the E-service quality model is effective and robust. The hypotheses were supported by the data. Attitude, subjective norm, perceived behavioral control, perceived usefulness, and E-service quality were found to be the factors that affect customer's intentions to use internet banking in Mongolia. In the end, the future recommendations, limitations, and implications of the research are discussed.

The Behavior of Households Using the Dynamic Stochastic General Equilibrium Model: Alternative Models

“…For the two variables, the impulse response functions are similar. The big and noticeable difference is given by the In general, despite the differences among Iran's economy and those of other countries, the results of the current study are in line with the results previously obtained in the context of real business cycle models by Obstfeld (1990), Schmitt-Grohe (1998), and Chang et al (2020). The difference in the dynamic effects of the models designed in this research was not significant compared to the existing studies in this field, and the behavior of the models has been almost similar.…”

“…Recent studies using this characteristic comprise Obstfeld (199 (1997), Schmitt-Grohe (1998), Neumeyer and Perri (2005), Abdullah Yusof et al (2015), Azlina al. (2019), Chang et al (2020), Santoso andSriyana (2020), andBaharudin et al (2021).…”

“…In the models for a smal and Heathcote (2004), and mo (2018), Izadi and Marzban (20 study and accurately forecast th in the structure and framework models. Hence, the main focu function and its variables will This paper compares the b discount factor (Uzawa 1968(Uzawa ) (1997, Schmitt-Grohe (1998, Chang et al (2020) In this model, the subjec become more impatient as the clear from inspection of the E means the world interest rate. I state level of consumption sol compare the business-cycle im present paper considers a brief of aggregate per capita consum…”

“…The first model assumes an endogenous discount factor (Uzawa 1968). Recent studies using this characteristic comprise Obstfeld (1990), Mendoza (1991), Uribe (1997), Schmitt-Grohe (1998), Neumeyer and Perri (2005), Abdullah Yusof et al (2015), Azlina et al (2018), Ngadiman et al (2019), Chang et al (2020), Santoso and Sriyana (2020), and Baharudin et al (2021).…”

The Adoption of AI-Enabled Adaptive e-Learning Environment in Palestinian Schools: Integrating Extended Technology Acceptance Model and System Success Model

“…Additionally, studies by Tung, Chang and Chou highlighted the significant effects of perceived usefulness and perceived ease of use on the behavioral intention to use e-learning environment (Tung et al, 2008). Research by Chang et al emphasized that individual experiences and cognitive factors influence technology adoption (Chang et al, 2020). This is especially pertinent in our context, where actual use may vary due to perceived difficulty and risks associated with new learning platforms.…”