Adding Technology Acceptance to E-learning Information Systems Success within an Organizational Setting. Improving the prediction of use

Because of the speed in which the world is changing, businesses are in need of a fast and cost-effective way to train their employees. E-learning systems can provide this and therefore many business organisations are adopting these systems. Consequently, there is a need to measure the success of these systems to justify investments in them. However, current models that measure the success of an e-learning system cannot accurately predict the use of the system and are not tailored to e-learning within a business environment. Therefore, this study focusses on making improvements on predicting the use of the system and on verifying the model within business organisations. It does this by developing a conceptual model that consist of the D&M model, which focusses on measuring the success of an e-learning system, added with elements of the TAM, which is entirely focused on predicting the use of a technology system. This study uses a specific case, namely an e-learning system used by the Dutch Police Academy, and mixed research methods including surveys, interviews and usage data to find if the added TAM elements improve the predictability of the use of the system. Simultaneously, this data was used to verify the conceptual model within a business organisation. Multiple regression analyses were conducted with the quantitative data to test the relationship between the variables of the two models. The qualitative data was analysed thematically and was used to find explanations for the linkages among variables in the two models within a business organisation setting. The qualitative results rendered it possible to propose alterations on the model to make it more suitable for measuring the effectiveness within a business organisation setting. The results show that the TAM can be added to the D&M model and improve the variance explained in both user satisfaction and intention to use, two critical elements of the D&M model. When exploring the best fit of combining both models, it becomes clear that overall the TAM variables are more predictive over intention to use than the D&M model variables. This shows that it is more important how e-learning participants in a business organisation setting perceive the use of the system than how they perceive the quality of the system.