Technology and the development of the Internet has led to greater awareness among organisations of the role the Internet can play in improving services through online channels. Banks, financial institutions and the relevant government authorities in the Kingdom of Saudi Arabia (KSA) have made great progress towards improving their e-services; however, these efforts came with a lack of theoretical background concerning the main challenge, which is to encourage customers to accept Online Banking (OB). This research has explored these concerns, with the aim of providing better understanding of the salient factors affecting people's acceptance and adoption of OB technology within the specific national cultural context of Saudi Arabia. The literature suggests numerous factors as determinants of people's technology adoption in general and OB in particular. This study employs a qualitative approach to narrow down and identify factors that did not emerge in the literature, to arrive at the most appropriate ones. The qualitative stage of the research involved a combination of two focus groups (14 participants) and eight semi-structured interviews. After accomplishing the first stage, a model was proposed to explain the factors affecting user acceptance of technology in the context of OB in Saudi Arabia comprising eight constructs (Perceived Usefulness, Resistance to Change, Perceived Trust, Perceived Usefulness, Social Influence, Perceived Quantity, Uncertainty Avoidance and Perceived Image). A cross-sectional survey was developed and distributed, resulting in 945 responses for use in the data analysis (using SPSS 20.0), for descriptive and exploratory factor analysis to extract constructs of the model. To finish, the proposed model and its hypotheses were examined by applying two-stage structural equation modelling. The conceptual model was found to be of value in explaining the role of the chosen factors that affect user acceptance of technology. The research found the seven direct predictors of BI to use OB explained 84.5 percent of BI variance. From the findings, it was found that the most significant predictor of BI was UA, followed by RC then PU. This research contributed to knowledge by providing a new e-service adoption model involving the impact of national culture. The newly proposed factors (PQ and UA as determinants) helped understand users‟ e-behaviours in KSA where research is seriously under-developed. The research limitations and recommended further efforts are finally presented.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:701928 |
| Date | January 2015 |
| Creators | Altwaijri, Ahmad Saleh |
| Contributors | Hone, K. ; Charles, D. |
| Publisher | Brunel University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://bura.brunel.ac.uk/handle/2438/13835 |
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