Understanding the utilisation of executive information systems using an integrated technology acceptance model : theoretical base and empirical validation
Over the past decade, a growing number of organisations have been developing executive information systems (EIS) to enhance the performance of their executive managers and facilitate their work. Such systems cannot improve individual and organisational performance if they aren't used. Thus, understanding the key determinants of EIS utilisation is an essential step toward enhancing their impact on individual users and organisational performance. Numerous case studies and explorative surveys of EIS development and implementation have been conducted, but an extensive literature review has shown that theory-based systematic investigations of post implementation use of EIS are rare, especially in the UK. The study reported here developed and tested a model of EIS usage. The proposed model integrates key constructs from the information systems success factors research stream into the theoretical frame of the technology acceptance model and other theories from social psychology (the theory of reasoned action, the theory of planned behaviour, and the Triandis model of attitude and behaviour). According to the proposed model, EIS usage is determined by six independent variables, namely perceived usefulness, perceived ease of use, information quality, involvement, subjective norm and facilitating conditions. In turn, perceived usefulness is influenced by perceived ease of use, perceived information quality, user involvement, subjective norm, and facilitating conditions. User involvement, perceived information quality and perceived ease of use are determined by four external factors, namely, user participation, information systems maturity, computer training, and user experience. The model was tested against data from 216 EIS users across various organisations. The results provided considerable support to the research model. In order of importance, subjective norm, perceived usefulness, facilitating conditions, information quality, and ease of use were found to explain 47.1% of the variance in EIS use. User involvement, information quality, subjective norm, ease of use, and facilitating conditions were found to explain 47.6% of the variance in perceived usefulness. Length of EIS use and computer use skill were found to explain 9% of the variance in perceived ease of use. IS maturity and user participation were found to explain 11% of the variance in EIS information quality. Finally, user participation was found to explain 2.4% of the variance in involvement. Implications of the study findings for practitioners and researchers are outlined.