Information Systems Success and Technology Acceptance within Government Organization

Organizations are investing heavily in information technology. To reap the true benefits from the technology, managers want to ensure that employees are using the technology to complete their daily tasks. There is a compelling need to assess the success of IS and IS applications and this has been a very popular but challenging topic of IS research. Numerous models of IS success and their extensions have been proposed and applied in empirical studies to identify those factors that affect IS success. This study continues this tradition and will extend the body of knowledge on the topic of IS success by developing a more comprehensive model for measuring IS success and technology acceptance within a government organization. The proposed model builds upon existing models such as DeLone and McLean (2003), Venkatesh et al (2003) UTAUT, and Wixom and Todd (2005). Most of the research on information systems success has focused on the use of a single application. This study assesses an entire set of IS applications used by the employees of a local municipal government. Assessment of IS success cannot be fully and accurately accounted for without understanding the nature of the application. This is because the application is related to the functions and features it serves. Who (and how many) uses it; who sponsors, owns and manages it; and whether the use is mandatory or optional are just a few examples of application variables. An instrument is developed to assess all the constructs of IS success along with those variables that capture differences among applications. Data for this study are collected from the entire employee population of the municipal government. This dissertation makes two unique contributions. Firstly, it provides a new comprehensive IS success assessment model which will be tested for the entire set of IS applications used by employees of a local municipal government. Secondly, it fills a gap in the IS success literature by assessing whether and how the IS success models are influenced by application variables.