Business-to-Government Data Sharing for Public Interests in the European Union: Results of a Public Consultation

1Citations
Citations of this article
28Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Lately governments and companies began experimenting with voluntary data sharing of business data for addressing public problems (so-called Data Collaboratives). This early practice revealed a number of challenges impeding business-to-government (B2G) data sharing and thus limiting the potential of data to provide answers and guide policies and action. One of the key challenges is the lack of a clear regulatory framework for B2G data sharing. To tackle this issue, the European Commission is taking regulatory action and preparing the Data Act which aims to spell out the rules and conditions for B2G data sharing for public interest. These developments, however, are met with resistance. While there is a strong push from the public sector for more private sector data, the private sector is less enthusiastic about the prospective mandatory B2G data sharing. In our study we zoom in on this issue in more detail and pose the following research question: How do public and private sector actors in the European Union view the prospect of mandatory B2G data sharing for public interest? To answer this question, we analyze the open dataset of responses to the public consultation of the European Commission. We find statistically significant results of business opposition to regulatory action and to mandating B2G data sharing, particularly among telecom and finance sectors. We also conclude that opposition to mandatory data sharing varies depending on the public interest purpose and is lowest among businesses with regards to emergencies and highest with regard to education, inclusion, and statistics.

Cite

CITATION STYLE

APA

Susha, I., Schiele, J., & Frenken, K. (2022). Business-to-Government Data Sharing for Public Interests in the European Union: Results of a Public Consultation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13391 LNCS, pp. 515–529). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-15086-9_33

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free