“Data stickiness” in interagency government data sharing: a case study

Abstract

PurposeThe provision of high-quality e-Government services requires efficient and collaborative sharing of data across varied types of government agencies. However, interagency government data sharing (IDS) is not always spontaneous, active and unconditional. Adopting a stickiness theory, this paper reports on a research study, which explores the causes of data stickiness in IDS.Design/methodology/approachThis study employed an inductive case study approach. Twenty-three officials from the government of City M in Hubei Province, Central China, were approached and interviewed using a semi-structured question script.FindingsThe analysis of the interview data pointed to 27 causes of data stickiness in five main themes: data sharing willingness; data sharing ability; data articulatability; data residence; and data absorptive capacity. The analysis revealed that interagency tensions and lack of preparedness of individual agencies are the main causes of data stickiness in IDS.Originality/valueThe case setting is based on China's Government, but the findings offer useful insights and indications that can be shared across international borders.

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“…While these examples concern cross-border information exchange, Zhou et al (2021) also identified considerable challenges in data exchange between agencies at different levels of government within China, with inter-relationships between agencies proving to be paramount. This is an important consideration for internal border control systems in a federated country such as Australia where information exchange between federal immigration authorities and criminal justice agencies operated by states and territories is crucial.…”

“…Data sharing between government agencies often forms the 'bedrock' for digital government (Zhou et al, 2021(Zhou et al, , p. 1286. While the language used around technological developments often conveys an impression of unimpeded integration across electronic systems, the reality is often otherwise, and the smooth flow of data between agencies is far from straightforward or guaranteed.…”