Emerging Revenue Models for Personal Data Platform Operators: When Individuals are in Control of Their Data

Laura Kemppainen, Timo Koivumäki, Minna Pikkarainen and Antti Poikola

Keywords

revenue model, personal data, platform operator, value capture, human-centered personal data management, multi-sided market


Abstract

Purpose: This paper identifies emerging revenue models for personal data platform operators that facilitate the
exchange of resources between an individual and a service provider for their mutual benefit. Context of this study
is human-centered personal data management, which refers to individuals being able to control the use and access
of their personal data for third-party services.


Design: This research is conducted by analysing qualitative questionnaire data from 27 organizations from 12 different
countries that are considered as forerunners in creating services in this context.


Findings: Our study shows that personal data platform operators capture value with transaction-, service-, connection-
and membership fees from service providers, data sources and individuals using the platform. This study also
reveals two propositions as the foundation of revenue model creation in the context of human-centered personal
data management, namely a no-advertising and free-for-users model. Our research findings show that monetising
personal data with advertising is avoided by personal data platform operators.


Research Limitations/Implications: This study calls for further research about how does providing control over personal
data to individuals influence on business models of platform operators and other service providers in the market.
Practical implications: For practitioners, this research offers new insights on revenue models that are being developed
by the forerunners of human-centered personal data management approach in the European market.


Originality/Value: Revenue models for personal data platform operators when taking a human-centered approach
to personal data management. Propositions to consider when creating revenue models in this context.


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