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Top1. Introduction
Adoption is a behavioral process that occurs over time. Karahanna, Straub, and Chervany (1999) discuss the two stages of the adoption process, including the pre-adoption stage, which is the stage before the system’s initial use, in our case, the e-Government system. The second stage is the post-adoption stage, which is the stage after the technology is implemented. This post-adoption stage is when the users include the e-Government technology in their routines. The adoption of e-Government systems has been of global importance in recent years (Kumar et al., 2021; Moreno-Enguix et al., 2019).
In the e-Government context, we propose that studies used in meta-analytic studies should consist only of those in a single adoption stage. Therefore, the pre-adoption stage and the post-adoption stage studies should be assessed separately. During analysis, the studies should be separated because of differences in behavior in each stage by citizens using e-Government systems. The pre-adoption phase involves the initial intention to use the technology and not use. In contrast, the post-adoption phase is when the system is being used. During use, citizens form actual use routines during the post-adoption phase. Because there are behavioral differences between the two phases, we propose that each of these models’ determinants be distinct (Karahanna et al., 1999). This paper identified significant differences between determinants of pre-adoption and post-adoption of e-Government systems using a meta-analysis. In contrast, prior studies combined the pre-adoption and post-adoption studies when examining e-Government, attempting to provide a meta-analysis of studies investigating two distinct behaviors.
Two key factors motivate this research. First, in prior studies, the two stages of adoption (pre-adoption and post-adoption) had been examined together in a meta-analysis (Rana et al., 2011; Rana et al., 2012). Typically, the studies used well-established theories using model measures that are invariant over different conditions (Kang et al., 2017); such as the Technology Acceptance Model (TAM), Diffusion of Innovation theory (DOI), DeLone and McLean IS success model, Unified theory of acceptance and use of technology (UTAUT), and theory of planned behavior (TPB). TAM has been the most studied model (Rana et al., 2015b), with many of its constructs used in other models. When the meta-analytic approach combines both pre- and post-adoption studies, the analysis provides inconsistent determinants of both stage behaviors. For example, while perceived usefulness and perceived ease are significant in pre-adoption studies (e.g., Alomari, Woods, and Sandu, 2012 and Lu, Huang, and Lo, 2010), they are weaker in post-adoption studies (Almahamid et al., 2010). The technology acceptance model (TAM) is related to the pre-adoption stage, providing explanatory power for the intention to adopt a system through the variable of behavioral intention to use. Also, trust is demonstrated as an important antecedent that is present in pre-adoption but not in post-adoption studies. Actual use can only be present in post-adoption studies.