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.