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.

中文翻译：

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预测电子政务的接受度：系统回顾

 目的

本研究采用系统回顾来探讨先前与电子政务接受度研究相关的发现的潜在原因。通过确定影响电子政务接受度的最常用、最好、最有希望或最差的因素，本研究为电子政务研究人员提出了一个研究议程。

设计/方法论/途径

本研究按照系统评价和荟萃分析（PRISMA）程序的首选报告项目进行系统评价，首先筛选出109篇论文。随后，本研究采用Jeyaraj等人提出的权重分析方法，分析了电子政务接受度的预测因素和联系。 （2006）。

 发现

结果首先揭示了综合层面上电子政务接受度的五个最常用预测因子和五个最佳预测因子。此外，本研究从采用者类型和电子政务阶段的角度总结了影响电子政务接受度的最佳预测因素。结果还说明了影响电子政务接受度的最有希望和最差的预测因素。

 原创性/价值

这项研究的贡献是双重的。首先，本研究确定了个人和组织层面的电子政务接受度之间以及不同电子政务发展阶段之间的联系。其次，本研究提供了一个研究方向，可以为未来的电子政务研究提供有益的见解。