***Business model implications of privacy-preserving technologies in data marketplaces: The case of multi-party computation***
Authors: W. Agahari (1), R. Dolci (1), M. de Reuver (1)
(1)Section Information and Communication Technology, Department of Engineering Systems and Services, Faculty of Technology, Policy, and Management, Delft University of Technology, Delft, the Netherlands 

Corresponding author: W. Agahari

Contact Information:
w.agahari@tudelft.nl

Delft University of Technology - Faculty of Technology, Policy and Management
P.O. Box 5015 
2600 GA Delft
The Netherlands

***General Introduction***
This dataset is a supplementary document of the article entitled "Business model implications of privacy-preserving technologies in data marketplaces: The case of multi-party computation."
This dataset is also a supplementary document to Chapter 3 of the dissertation entitled "The impact of Multi-Party Computation on data sharing decisions in data marketplaces: insights from businesses and consumers."
This dataset contains a synthesis of data collected through semi-structured interviews as described in the article and in the Chapter 3 of the dissertation.
The data collection process and work leading to the article and the dissertation have received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 825225.

It is being made public in order for other researchers to use this data in their own work.

The data in this data set was collected March-June 2020 by researchers at the ICT section, ESS Department, Faculty of Technology, Policy and Management, Delft University of Technology.

***Study objective***
The interview study has two purposes: (1) to refine and validate a short presentation explaining how MPC works and its potential use case in data marketplaces, and (2) to investigate how MPC can change the business model of data marketplaces.

***Procedure***
Interviewees were presented with (1) the concept of data sharing through data marketplaces, (2) how MPC works, and (3) how it might change the way businesses share data in data marketplaces.
Subsequently, interviewees were asked to provide feedback to ensure clarity and correctness of the presentation. 
Then, interviewees were asked confirmatory questions regarding conceptual foundations of MPC.
After that, interviwees were asked about (1) value propositions of MPC for relevant actors in data marketplaces, (2) how MPC might change the architecture of data marketplaces, and (3) new revenue sources and/or financial constraints resulting from MPC use in data marketplaces.
Please refer to the article, the methodology section in Chapter 3 of the dissertation, and sheet "interview protocol" in the dataset for more detail about the survey questions.

***Description of the data in this data set***
Please refer to the research approach section of the article and the methodology section in Chapter 3 of the dissertation.