Predicting the acceptance of e-government: a systematic review
Abstract
Purpose
This study uses a systematic review to explore the potential causes of previous findings related to e-government acceptance research. By identifying the most frequently used, best, promising or worst factors that affect the acceptance of e-government, this research presents a research agenda for e-government researchers.
Design/methodology/approach
Through conducting a systematic review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) procedure, this research first selected 109 papers. Subsequently, this research analyzed the predictors and linkages of e-government acceptance by adopting a weight-analysis method proposed by Jeyaraj et al. (2006).
Findings
The results first revealed the five most frequently used predictors and five best predictors of e-government acceptance at a comprehensive level. Furthermore, this study summarized the best predictors affecting the acceptance of e-government from the perspectives of adopter types and e-government stages. The results also illustrated the promising and the worst predictors influencing e-government acceptance.
Originality/value
The contribution of this research is twofold. First, this study identified the linkages between e-government acceptance at the individual and organizational levels and between different e-government development stages. Second, this research provided a research direction that could offer useful insights for future e-government studies.
Keywords
Acknowledgements
An earlier, preliminary version of this research which contained less data, and less concise analysis was presented at the 2021 International Conference on Information Systems (ICIS), held from December 12–15 in Austin, Texas: Wu, X., and Chong, A.Y.L. (2021). A review of predictors in e-government adoption research.
The project is funded by the National Natural Science Foundation of China (42271267), the Key Project of Zhejiang Provincial Soft Science Research Plan (2023C25008) and the Humanities and Social Sciences Research and Planning Foundation of the Ministry of Education of China (22YJA630063).
Citation
Wu, X., Chong, A.Y.L., Peng, Y. and Bao, H. (2024), "Predicting the acceptance of e-government: a systematic review", Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-12-2022-0970
Publisher
:Emerald Publishing Limited
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