research-article

Blockchain as a driving force for federalism: : A theory of cross-organizational task-technology fit

Authors:

Alexander Stohr,

Gilbert Fridgen,

Alexander RiegerAuthors Info & Claims

Volume 68, Issue C

https://doi.org/10.1016/j.ijinfomgt.2022.102476

Published: 01 February 2023 Publication History

Abstract

Digital technologies play an important role for the delivery of many public services. However, selecting and adopting the ‘right’ digital technologies is often challenging, especially for federally structured governments. Universal factors for successful adoption are hard to establish, and the particularities of federalism, such as the separation of competencies, complicate technology selection. Nevertheless, blockchain technology seems to flourish in these environments. Through a single-case study on the blockchain project of Germany’s Federal Office for Migration and Refugees, we unpack one essential factor for this success: the fit between (cross-)organizational task structure and technological properties. This fit earns the Federal Office’s project considerable credit and traction with stakeholders and partner authorities – not least because it supports the argument that the digitalization of federal systems is possible without ‘digital centralization’ and redistribution of competencies. Our task-technology fit analysis contributes to a better understanding of the adoption of blockchain in the public sector. It also provides the foundation for an extended task-technology fit theory for federally structured, cross-organizational contexts.

Highlights

•

We analyze the adoption of blockchain in federally structured government systems.

•

We conduct a single-case study on Germany’s blockchain project for national asylum procedures.

•

We find that the properties of private blockchain frameworks fit federal organizing principles.

•

We develop an extended task-technology fit theory for cross-organizational, federal contexts.

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International Journal of Information Management: The Journal for Information Professionals Volume 68, Issue C

Feb 2023

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https://dl.acm.org/doi/10.1016/j.jengtecman.2023.101761
Chi OChi CGursoy DNunkoo R(2023)Customers’ acceptance of artificially intelligent service robotsInternational Journal of Information Management: The Journal for Information Professionals10.1016/j.ijinfomgt.2023.10262370:COnline publication date: 1-Jun-2023
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