Research data - Business model implications of privacy-preserving technologies in data marketplaces: The case of multi-party computation

DOI:10.4121/19995101.v2
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/19995101
Datacite citation style:
Agahari, Wirawan; Dolci, R.; de Reuver, Mark (2023): Research data - Business model implications of privacy-preserving technologies in data marketplaces: The case of multi-party computation. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/19995101.v2
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

choose version:
version 2 - 2023-04-24 (latest)
version 1 - 2023-04-19

This dataset is a supplementary document to the article entitled "Business model implications of privacy-preserving technologies in data marketplaces: The case of multi-party computation." It is also a supplementary document for Chapter 3 of the dissertation entitled "The impact of Multi-Party Computation on data sharing decisions in data marketplaces: insights from businesses and consumers". 

The supplementary document consists of a grounded table (in an excel format) and a short presentation (in a powerpoint format).

The data was collected through semi-structured interviews conducted in March-June 2020. Further details are provided in the article and in the methodology section in Chapter 3 of the dissertation.

History

  • 2023-04-19 first online
  • 2023-04-24 published, posted

Publisher

4TU.ResearchData

Format

.xlsx (grounded table), .pptx (powerpoint presentation)

Funding

  • Safe Data Enabled Economic Development (grant code 825225) [more info...] European Commission

Organizations

TU Delft, Faculty of Technology, Policy, and Management, Department of Engineering Systems and Services, Section Information and Communication Technology

DATA

Files (3)