Human Capital and Digital Government: Evidence from Germany, Australia, and New Zealand

The slow progress of digital transformation in public organizations has been a source of concern, not least due to a lack of digital government competences (DGCs). We approach the persisting issue by drawing on resource-based theory and human capital. We conceptualize DGCs as knowledge, skills, abilities, and other characteristics (KSAOs), which compose digital government-related human capital resources. We further posit that a lack of such resources on the individual level negatively impacts transformation capabilities on the organizational level. To substantiate our claims, we perform a competence assessment based on job advertisements. We analyzed 2,869 job ads from local governments in Germany, Australia, and New Zealand using a job-mining approach that combines large language models and topic modeling. Our findings reveal that DGCs are notably scarce in these job ads, which helps explain the slow progress of digital government pursuit. Our study contributes to research by providing a novel theoretical foundation for the literature stream on DGCs, framing them as KSAOs as the foundation for human capital resources. We also share our job-mining pipeline for replication and adaptation by other researchers. Finally, we propose four action points to address the challenges from a hiring perspective.

Authors

Institutions

Publication Details

Journal
Digital Government Research and Practice
Published
2026-03-20
DOI
https://doi.org/10.1145/3803417
Primary Topic
E-Government and Public Services
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Human Capital and Digital Government: Evidence from Germany, Australia, and New Zealand

Henry Hosseini, Michael Koddebusch, Jörg Becker, Hans Näscher et al.
Digital Government Research and Practice
E-Government and Public Services
article

Human Capital and Digital Government: Evidence from Germany, Australia, and New Zealand

Henry Hosseini, Michael Koddebusch, Jörg Becker, Hans Näscher, Leonard Sensmeier
article en

Abstract

The slow progress of digital transformation in public organizations has been a source of concern, not least due to a lack of digital government competences (DGCs). We approach the persisting issue by drawing on resource-based theory and human capital. We conceptualize DGCs as knowledge, skills, abilities, and other characteristics (KSAOs), which compose digital government-related human capital resources. We further posit that a lack of such resources on the individual level negatively impacts transformation capabilities on the organizational level. To substantiate our claims, we perform a competence assessment based on job advertisements. We analyzed 2,869 job ads from local governments in Germany, Australia, and New Zealand using a job-mining approach that combines large language models and topic modeling. Our findings reveal that DGCs are notably scarce in these job ads, which helps explain the slow progress of digital government pursuit. Our study contributes to research by providing a novel theoretical foundation for the literature stream on DGCs, framing them as KSAOs as the foundation for human capital resources. We also share our job-mining pipeline for replication and adaptation by other researchers. Finally, we propose four action points to address the challenges from a hiring perspective.

Digital Government Research and Practice
University of Münster (DE), Institute for Security Studies (KE), Fraunhofer Research Institution for Battery Cell Production (DE)
Decent work and economic growth
Openalex Percentile: Top 16%
E-Government and Public Services
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.