Business intelligence usage determinants: an assessment of factors influencing indivdual intentions to use a business intelligence system within a financial firm in South Africa
Although studies are conducted on economical gains due to BI system adoption, limited knowledge is available on factors which influence BI system usage. Identifying these factors is necessary for organisations because this may enable the design of effective BI systems, thus increasing the chance of firms adopting them to realise the actual value inherent in the exploitation of BI systems. The purpose of this study is, therefore, to investigate factors which influence BI system usage. The investigation employed constructs derived from three theoretical frameworks, namely technology acceptance model (TAM), task-technology fit (TTF) and social cognitive theory (SCT) as follows: intention to use, perceived usefulness, perceived ease use, task characteristics, technology characteristics, task-technology fit and computer self-efficacy. To test the hypotheses, data was collected by administering the study to 682 BI system users in a South African financial institution, SA-Bank, wherein 193 usable responses were received. The findings of the study with partial least squares (PLS) analysis indicated support for the joint use of constructs from the three theoretical frameworks, explaining 65% of BI system usage variance. Furthermore, the perceived usefulness of a BI system reflected a stronger influence as a factor of BI system usage over the beliefs that the system was easy to use, and the belief that it was aligned to the performance of business tasks. An unusual outcome in this study was the lack of influence of computer self-efficacy on BI system usage. Nonetheless, the study extended validation of the use of constructs derived from the three theoretical frameworks for a BI technology in the context of SA-Bank, thereby contributing to theory. Finally, the results of hypothesis testing suggested a starting point for practitioners towards designing BI systems, and recommendations and suggestions are included in this report.
Business Intelligence system characteristics, Decision task characteristics