Based on a critical review of the Unified Theory of Acceptance and Use of Technology (UTAUT), this study first formalized an alternative theoretical model for explaining the acceptance and use of information system (IS) and information technology (IT) innovations. The revised theoretical model was then empirically examined using a combination of meta-analysis and structural equation modelling (MASEM) techniques. The meta-analysis was based on 1600 observations on 21 relationships coded from 162 prior studies on IS/ IT acceptance and use. The SEM analysis showed that attitude: was central to behavioural intentions and usage behaviours, partially mediated the effects of exogenous constructs on behavioural intentions, and had a direct influence on usage behaviours. A number of implications for theory and practice are derived based on the findings.
Highlights Nine adoption models are reviewed 29 different adoption constructs are identified The UMEGA outperforms all other models for e-government Government context should be taken into account The UMEGA is simpler to use and has a better explanatory power than the UTAUT
Sluggish adoption of emerging electronic government (eGov) applications continues to be a problem across developed and developing countries. This research tested the nine alternative theoretical models of technology adoption in the context of an eGov system using data collected from citizens of four selected districts in the state of Bihar in India. Analysis of the models indicates that their performance is not up to the expected level in terms of path coefficients, variance in behavioural intention, or the fit indices of the models. In response to the underperformance of the alternative theoretical models to explain the adoption of an eGov system, this research develops a unified model of electronic government adoption and tests it using the same data. The results indicate that the proposed research model outperforms all alternative models of technology adoption by explaining 77 % of variance in behavioural intention, with acceptable values of fit indices and significant relationships between each pair of hypothesised factors.
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