DINFO
Financiado
Dynamic Information Acquisition Experimentation and Communication
Individuals, firms, and public organizations spend significant time and reIndividuals, firms, and public organizations spend significant time and resources to acquire, collect, and process information that guides and optimizes the...
Individuals, firms, and public organizations spend significant time and reIndividuals, firms, and public organizations spend significant time and resources to acquire, collect, and process information that guides and optimizes their decision making. Information is acquired directly by own research efforts, from academic publications that selectively publish scientific research, or from self-interested third parties that control the flow of information to influence decisions, and often information can also be learned through data-collection during day-to-day business.
How much and what information should be acquired? How can third parties be incentivised to provide information? What is the role of commitment and verifiability of evidence in communication between a self-interested information provider and a user of that information? How should data collected from day-to-day business be used to optimize decisions, if these decisions also affect and feed back into future data collection? How should results of scientific research be communicated if it affects both decision by practitioners as well as the choice of future research topics?
This research programme aims to shed light on these questions. Recognizing that information acquisition takes time, and happens gradually, often in multiple stages, it develops dynamic models of information acquisition and experimentation. The programme has four parts: (1) It develops a novel framework to analyse frictions in dynamic information acquisition and transmission that arise in communication and persuasion. (2) It develops new techniques to analyse robust dynamic information choice. (3) It develops a dynamic model of incentives for information production and communication in scientific research that contributes to the debate on publication standards. (4) It develops a theoretical framework to analyse the optimal use of data in the nascent field of predictive policing and other applications of data-driven resource allocation.
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Duración del proyecto: 67 meses
Fecha Inicio: 2021-01-27
Fecha Fin: 2026-08-31
Fecha Fin: 2026-08-31
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2021-01-27
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2020-COG:
ERC CONSOLIDATOR GRANTS
Cerrada
hace 4 años
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
UNIVERSITY COLLEGE LONDON
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
436.02K€ |
Participante