Predictors of E-Government Use in Poland: A Post-COVID-19 Clients’ View

This exploratory study examines predictors of the use of e-government (UEG) in a post-COVID-19 landscape, focusing on attitude toward e-services (AES), trust in e-government (TEG), and trust in e-documents (TED). While prior research emphasized general trust in e-government as a central predictor, COVID-19 reshaped digital behaviors, necessitating an updated perspective. Using survey data from 130 Polish clients and conducting Structural Equation Modeling (SEM), our findings indicate that TED is the strongest predictor of e-government use. Moreover, contrary to expectations, AEG and TEG show no significant predictive power, suggesting that attitude and trust in institutions alone do not predict use. This study contributes to the growing literature on e-government by offering a post-COVID-19 perspective and emphasizing the importance of further research on trust in e-documents. These findings point to practical implications for policymakers, urging a shift toward a more client-oriented focus and public awareness campaigns to foster public trust.

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Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-08-15
Primary Topic
E-Government and Public Services
Type
article
Field-Weighted Citation Impact
0.00

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article

Predictors of E-Government Use in Poland: A Post-COVID-19 Clients’ View

Journal of the Association for Information Systems
E-Government and Public Services
article

Predictors of E-Government Use in Poland: A Post-COVID-19 Clients’ View

article en

Abstract

This exploratory study examines predictors of the use of e-government (UEG) in a post-COVID-19 landscape, focusing on attitude toward e-services (AES), trust in e-government (TEG), and trust in e-documents (TED). While prior research emphasized general trust in e-government as a central predictor, COVID-19 reshaped digital behaviors, necessitating an updated perspective. Using survey data from 130 Polish clients and conducting Structural Equation Modeling (SEM), our findings indicate that TED is the strongest predictor of e-government use. Moreover, contrary to expectations, AEG and TEG show no significant predictive power, suggesting that attitude and trust in institutions alone do not predict use. This study contributes to the growing literature on e-government by offering a post-COVID-19 perspective and emphasizing the importance of further research on trust in e-documents. These findings point to practical implications for policymakers, urging a shift toward a more client-oriented focus and public awareness campaigns to foster public trust.

Journal of the Association for Information Systems
Kozminski University (PL)
Narodowym Centrum Nauki
Peace, Justice and strong institutions
Openalex Percentile: Top 43%
E-Government and Public Services
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Predictors of E-Government Use in Poland: A Post-COVID-19 Clients’ View · Journal of the Association for Information Systems (2025) | TGRS Research Map | TGRS