Work

Collectively resolving information asymmetries through data sharing clubs: agritech case study

Year: 2025

Type: conference-paper

Abstract: There is a symbiotic relationship between the developers of AI services and the communities seeking to harness the benefits of AI. Some form of ecosystem governance is required if such relationships are to become mutually beneficial rather than parasitic, with one side deriving benefits at the expense of the other. This paper examines how a data trust framework can provide data sharing ecosystem governance to facilitate data flows and resolve information asymmetries between competitive entities. The EU Horizon-funded SPADE project case is discussed as an application scenario featuring agricultural drones, digital twins, and other data sharing challenges to explore this concept. We also examine how a club theory approach can help implement a sound business model with a data trust framework as a governance model.

Source: IET conference proceedings.

DOI: 10.1049/icp.2025.2987

Authors: Steve Brewer, Nikolai Kazantsev, Kyle Alves, Phil Godsiff, Michelle Pauli, Andrew McMillan, Simon Pearson

Institutions: University of Lincoln, University of Cambridge, University of the West of England

Language: English

Topic: Digital Platforms and Economics

Subfield: Strategy and Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Peace, justice, and strong institutions, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W4414854875

FWCI:

Cites:

Cited by:

Related to: