Start with the purpose
A company may share data to meet a legal requirement, coordinate operations, earn revenue, or contribute to a societal goal. Those purposes can call for different relationships between the organizations involved.
What the study adds
We developed a taxonomy, a structured way to describe and compare data-sharing practices. It connects characteristics of the data with organizational choices and the wider network. The recurring patterns help explain why arrangements that look technically similar may serve different purposes.
The purpose shapes the sharing arrangement
Different goals call for different ways of organizing access, exchange, and use.
| Pattern | Typical arrangement | Example |
|---|---|---|
| Compliance | Sensitive customer data is exchanged for services under strong privacy, security, and legal requirements. | Medical records |
| Efficiency | Continuous, real-time data is exchanged for services that support better operations, requiring compatible systems and organizational processes. | Supply chain optimization |
| Revenue | Data is monetized through arrangements such as marketplaces, with organizational and technical compatibility. | IoT data marketplace |
| Society | Multiple sources support social or environmental goals, free of charge and under use-specific agreements. | Environmental applications |
These are descriptive patterns with overlapping characteristics. Compliance does not mean a duty to share; societal benefit does not mean unrestricted access.
The same data, a different arrangement
Illustrative example: a firm might sell equipment-use data to another business or share it with a partner to coordinate maintenance. Before choosing a platform, the firms need to clarify the purpose of the exchange and how each participant benefits.
Using the idea
The taxonomy provides a vocabulary for comparing a proposed arrangement with existing practices. A useful starting question is what the participants expect to gain from sharing. Technical choices can then be discussed in relation to that purpose.
About the study
Research approach
We developed a taxonomy, a shared set of characteristics for describing how organizations share data. Starting with existing classifications and a review of 44 research articles, we refined it against publicly documented practices across industries. This helped us connect decisions about the data with the organizations involved and the relationships between them.
Evidence and analysis
We classified 121 cases using the taxonomy, with independent researchers checking parts of the coding. Cluster analysis then grouped cases with similar characteristics. We interpreted those groups by returning to the case descriptions and examining which choices commonly occurred together. Separately, four experts involved in a chemical-industry data-sharing arrangement applied the taxonomy to their own case and assessed its usefulness.
How to use the findings
The patterns offer reference points for comparing a proposed arrangement with existing practices. The groups were only weakly separated, so they should be treated as broad patterns with overlap. The study captures publicly visible practices at a point in time. Confidential arrangements and detailed technical implementation may be missing, and the analysis does not establish which configuration causes better business results.
The paper
Data Sharing Practices: The Interplay of Data, Organizational Structures, and Network Dynamics
Electronic Markets · 2024
Paper preview · CC BY 4.0
© The authors 2024