A meta-analysis of empirical e-government research and its future research implications

Abstract

The desired e-government potentials and its shortcomings in reality are key reasons why e-government has become a major topic of interest to academics and practitioners, leading to an extensive body of knowledge. However, the literature still demands further quantitative empirical research to substantiate theory development. This situation calls for a specific review of the literature that arranges relevant knowledge and provides a solid foundation for future research. However, available meta-analyses do not deliver the particular insights to appropriately address the shortage of quantitative empirical e-government research. Therefore, this study explicitly focuses on this specific field to systematically uncover areas requiring further exploration, and defines promising research directions for a solid foundation for future investigations. Key findings of the meta-analysis are: the existence of a systematic divide of existing quantitative empirical e-government studies into 12 research subtopics, which are assessed according to different classification criteria for scientific research gap-spotting; the identification of emerging subtopics that carry innovative research potential; and that e-government is expected to be an ongoing, open-ended research environment that still provides manifold investigative opportunities. Based on these findings, straightforward suggestions for future research are provided. Points for practitioners Beyond providing insights into the current state of quantitative empirical research for scientific researchers, this article also delivers value for professionals working in public management and administration. First, the study provides a comprehensive overview of e-government-related meta-analyses, which allows us to quickly identify the literature in order to tackle particular e-government management issues. Second, the article classifies existing quantitative empirical studies, defines specific subject areas and arranges relevant knowledge, which eases the processes of confining and labelling e-government activities. Last, since these deliverables are based on empirical studies that draw their conclusions from perceptions of reality, the summaries and classifications are thus regarded to be of special importance for public managers.