This presentation was presented in the 24th Nordic Academy of Management Conference in Bodø in the 24th of August 2017. The presentation is based on a conference/working paper and on research done in Tekes funded Digital Health Revolution project in Finland.

1. Revenue models of personal data
platform operators
Laura Kemppainen, PhD Student, DHR project
Timo Koivumäki, Minna Pikkarainen and Antti Poikola
Martti Ahtisaari Institute of Global Business and Economics, Oulu Business
School, University of Oulu
24th Nordic Academy of Management Conference
In Bodø in the 24th of August 2017

2. Introduction
• Companies collect growing amount of personal data (Rehman et al.,
2016; Gandomi and Haider, 2015)
• Individuals have a free service and are part of the value
proposition for business customers like advertisers (Muzellec et al,.
2015).
• Increasing concerns about
• data privacy (Vescovi et al., 2015, Spiekermann and Novotny, 2015)
• proper use of data (Roeber et al., 2015)?
• limited interoperability of data (Kshetri, 2014)
• gaining a holistic view of the data (Vescovi et al., 2015)
• Human-centered approach to personal data management
has been proposed
• Personal data platforms and business models are emerging to facilitate
the data
• GDPR and the EU Payment Services Directive to increase the
data portability

3. Introduction
Personal data platform operator
Facilitates resources and interactions of interdependent
stakeholders
Revenue model
Monetary benefits the company generates in exchange of value
Personal data
Any information relating to an individual: name, a photo, an email
address, bank details, posts on social networking websites, medical
information, or a computer IP address
EU Data Protection Reform and Big Data report (European Commission’s
(2016)

4. Purpose and research gap
• The purpose is to describe how personal data platform
operators capture value in this context
• There is limited research on how digital platforms capture
value
• as a transaction platform
• when individuals are in control over the data
• We contribute to platform business model literature in
management and industrial marketing

5. Theoretical background
• Revenue model is a crucial part of a business model
• Literature review was conducted on revenue models in multi-
sided markets
• Revenue can be generated from all sides of the multi-sided market
• Two distinct sides: Money side and subsidy side (use the platform for
free/freemium e.g. sellers and buyers in ebay) (Wang et al., 2014)

6. • We identified 14
revenue models in
multi-sided
markets
• Advertising and
subscription are
the most
frequently
mentioned ones
• Usually one
primary source of
revenue exists
(Enders et al. 2008)

7. Research design
• Qualitative inquiry with open-ended questionnaire data
• 27 organizations from 12 different countries
• Forerunners in creating services in this context (start-ups, bm’s in
development)
• Designed in collaboration with the European Commission
• Unit of analysis is an organization that has identified a
revenue model for a personal data platform operator
• Data was analyzed using the coding method (c.f. Basit, 2003;
Saldaña, 2015)
• 70 codes  into 6 categories of multiple codes  into 4 higher
order themes describing the revenue models

8. Results
• Key stakeholders: Individual and service provider (data source or
user of data)
• Two context-specific propositions for the foundation of
revenue model creation
• ‘No advertising’ model (ads explicitly avoided)
• ‘Free for users’ model (individuals do not pay, data requesting
organizations do)
• May become more popular when the market of free personal
data flow matures
• Revenue could be generated (mainly from service providers) by
combining
• Transaction fees
• Service fees
• Connection fees and
• Membership fees
• Thus combining fixed and pay-per-use models

9. Results
• Service fee
• Service providers and individuals pay for
• Value adding services on the platform
• Membership fee
• Service providers and individuals pay for
• The membership of the platform either annually or one-time basis
• Transaction fee
• Service providers pay for
• The data transactions from a data source
• Or using revenue sharing: a service provider pays only when it pays an
individual for the data or charges an individual a fee for its own service
• Connection fee
• Service providers pay for connecting services to the platform and connecting
with individuals
• Service provides as a data source pays for the creation of APIs when
outsourcing personal data management to platform

10. Conclusions
• Advertising is explicitly avoided among the platforms
• --> the problem is not adds but how data has so long been
collected and used in the shadows
• Connection fee has not been recognized in previous bm
studies on multi-sided markets
• To support the creation of data sharing framework
• Context of human-centered personal data management
differs from other multi-sided markets on how value is
captured
• Value is captured mainly from the ‘business side’
• Need for business models for all actors in the ecosystem to
find mutually beneficial ways to integrate personal data
• Open business model: sharing the revenue from data
transactions?

11. Next steps
• The market of personal data and business models are
constantly developing
• Human-centered approach to personal data management
is relatively new
• Interviews could be conducted to complement the
questionnaire answers

12. Thank you! Any comments?
Laura Kemppainen
laura.kemppainen@oulu.fi

13. References in this presentation
Rehman, M. H., Chang, V., Batool, A. & Wah, T. Y. (2016). Big data reduction
framework for value creation in sustainable enterprises. International Journal of
Information Management, 36, 917–928.
Gandomi, A. & Haider, M. (2015). Beyond the hype: Big data concepts,
methods, and analytics. International Journal of Information Management, 35, 137–
144.
Muzellec, L., Ronteau, S. & Lambkin, M. (2015). Two-sided Internet platforms: A
business model lifecycle perspective. Industrial Marketing Management. 45, 139-
150.
Lumpkin, G. T. & Dess, G. G. (2004). E-business strategies and internet
business models: How the internet adds value. Organizational Dynamics, 33(2), 161–
173.
Wang, Y., Tang, J., Jin, Q. & Ma, J. (2014). On studying business models in
mobile social networks based on two-sided market (TSM). Journal of
Supercomputing, 70(3), 1297–1317.
Wirtz, B. W., Schilke, O. & Ullrich, S. (2010). Strategic Development of Business
Models: Implications of the Web 2.0 for Creating Value on the Internet. Long Range
Planning, 43, 272-290.
Enders, A., Hungenberg, H., Denker, H-P. & Mauch, S. (2008). The long tail of
social networking. Revenue models of social networking sites. European
Management Journal, 26, 199–211.