A multi-analytical model for mobile banking adoption: a developing country perspective

Purpose: Mobile banking (Mbanking) is one of the most widely used mobile technology applications in recent times. This research aims to develop and test a research model by integrating social influence, trust and compatibility along with demographic variables into the original technology acceptance model (TAM) for Mbanking adoption which can be useful for understanding individual behaviours from an international business perspective. Design/methodology/approach: Data were collected through a structured survey from 208 Omani Mbanking users and analysed using a two-staged regression and neural network (NN) model. Findings: The results showed that perceived ease of use and demographic variables were not statistically significant in the multiple linear regression model, whereas the importance of the aforementioned variables was relatively high in the results obtained from the NN model. Furthermore, other predictors, namely, trust, perceived usefulness, compatibility and social influence included in the proposed research model that were established as significant by the regression model were assigned high relative importance by the NN model as well. Practical implications: The study reflects the customer’s opinion from a developing country perspective. In addition, the research makes a significant theoretical contribution by using predictive modelling instead of causal or explanatory modelling for the development of a new and extended TAM model. The findings can be gainfully used by international business to understand Omani customer- and design-appropriate strategies for market penetration. Originality/value: This study offers deeper understanding about Mbanking adoption from a developing country perspective and identifies and integrates important variables that influence the adoption in the aforementioned context.