E‐government diffusion: a comparison of adoption constructs

Lemuria D. Carter

112 citations0/0 files storedTransforming Government People Process and Policy

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E-Government and Public Services Technology Adoption and User Behaviour Employer Branding and e-HRM

Abstract

Purpose E‐government adoption is the focus of many research studies. However, few studies have compared the adoption factors to identify the most salient predictors of e‐government use. The purpose of this paper is to compare popular adoption constructs to identify the most influential. Design/methodology/approach A survey was administered to elicit citizen perceptions of e‐government services. Findings The results of stepwise regression indicate perceived usefulness, trust of the internet, previous use of an e‐government service and perceived ease of use all have a significant impact on one's intention to use an e‐government service. Perceived usefulness emerges as the most important factor in predicting e‐government adoption. This factor alone explains 74.8 percent of the variance in intention to use. Research limitations/implications In light of these findings, researchers should still explore the role of adoption factors in e‐government diffusion. The proposed model is a robust, yet parsimonious way to explore the key factors that influence technology acceptance. This study includes the adoption perceptions of citizens from one state in the USA. Future studies should overcome this limitation by incorporating citizens from other regions and nations. Practical implications This study illustrates the elements of e‐government use that are most salient to citizens. Government agencies should focus on these factors when designing and promoting e‐services. Originality/value This study shows that the integration of a technology acceptance model, trust and previous e‐government experience work together to explain a large percentage of variance in intention to use e‐government. In particular, perceived usefulness (aka relative advantage, aka performance expectancy) is the most salient predictor.

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References

1989Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology 2003User Acceptance of Information Technology: Toward A Unified View1 1977Self-efficacy: Toward a unifying theory of behavioral change.1977Self-efficacy: Toward a unifying theory of behavioral change.1995An Integrative Model Of Organizational Trust 2020Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis 1991Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation 2003Trust and TAM in Online Shopping: An Integrated Model1

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