Digital Communication of Public Service Information and its Effect on Citizens’ Perception of Received Information

ABSTRACT

This paper explores how the development of digital solutions for communication and daily interaction between government and its citizens influences citizens’ satisfaction, trust and perceived importance of the information received from government. It illuminates this effect by drawing on a survey-experimental design in a Danish research setting. With digitization of public services happening so quickly, it leaves the question of how this transformation is actually viewed by the citizens. The change in medium from traditional communication by standard mail to digital communication can be argued to have both positive and negative effects. Some citizens might find it easy to rely on digital communication, others might perceive digital solutions as a challenge and an obstacle when receiving essential information, which again might foster greater dissatisfaction. Results of Bayesian statistical analysis suggest that the digitization of communication form has little effect on citizens’ trust and satisfaction with the information received. Further, results do indicate that the perceived importance of the information received is lower for information received digitally.

KEYWORDS:

• Digitization
• government - citizen interaction
• Bayesian data analysis
• survey experiment

Acknowledgments

I thank the Interdisciplinary Center for Organizational Architecture (ICOA) at Aarhus University for supporting the data collection for this project.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. https://en.digst.dk/policy-and-strategy/mandatory-digitisation/self-service/wave-3-on-mandatory-self-service/official-press-release/(04-01-2019).

2. https://en.digst.dk/policy-and-strategy/mandatory-digitisation/digital-post/(04-01-2019).

3. https://www.borger.dk/internet-og-sikkerhed/Digital-Post/Oftest-stillede-spoergsmaal (04-01-2019).

4. Some citizens are exempt from this requirement (citizens with; disabilities, living in remote areas, language difficulties or homeless): https://www.borger.dk/internet-og-sikkerhed/Digital-Post/Hjaelp-og-fritagelse (04-01-2019).

5. Results were run on the full sample as well; however, this did not change the overall results.

6. Models are estimated using brms and STAN, which draw on MCMC as sampling algorithm. All models showed high convergence with an R-hat equal to 1.

7. Borger.dk.

8. Borger.dk.