Predicting internet banking adoption in Oman: A neural network approach

The recent advancement in internet technologies are providing better business opportunities for banking sectors together with its customers. The purpose of this paper is to explore the main determinants such as service quality, trust, perceived usefulness, perceived ease of use and attitude of internet banking customers on the basis of existing literature of technology acceptance model. Statistical models were applied to understand and predict internet banking adoption. The data were collected using google docs from eighty Omani banking customers. The results obtained from multiple linear regression model were compared with the results obtained from neural network model to predict internet banking adoption. The performance of neural network model was superior to multiple linear regression model. The findings of this study shows that service quality was the most important predictor of internet banking adoption, followed by trust, attitude, perceived ease of use, and perceived usefulness. This study will help banking professionals, service providers, academicians, and information systems researchers.