Understanding is continuance an IS commitment perspective

The adoption of information systems (IS) by individuals has been a focus of IS research for years. Although initial adoption has been extensively studied by many researchers, less is known concerning users psychological relationship with adopted information systems, especially when alternative systems are available. Along with the growing interest in understanding effective use of IS beyond adoption, continued use of IS attracted increasing attention in the IS field indicating a need for in depth understanding of user s loyalty to adopted systems. To date, researchers have reported few attempts to identify an effective while parsimonious model of user loyalty and switching determinants. This research is carried out with a goal to fill this research gap by providing a theoretical framework along with empirical evidence that may contribute to both academic research and management practice. This dissertation incorporates commitment theories, which originated in social psychology, to the study of IS continuance and system switching intention. Integrating existing models of IS continuance, this dissertation proposes an IS commitment model that can help explain why some information systems enjoy sustained use while others diminish soon after initial adoption. Specifically, this dissertation suggests that IS continuance may be best understood by investigating user commitment towards specific information systems. Three dimensions of IS commitment, i.e., affective commitment, calculative commitment, and normative commitment are identified to formulate a research model. The antecedents to each dimension of IS commitment are investigated and included in the research model. Two longitudinal studies were conducted to empirically test the research model in the context of Web-mail services and group collaboration platforms. The comparisons of this research model with other prevalent IS adoption and continuance models, such as Technology Acceptance Model (TAM) (Davis 1989) and Expectation-Confirmation Model (ECM) (Bhattacherjee 2001) suggest improved variance explained by the proposed model. The implications, limitations, and future research directions are also addressed in this dissertation