Contributors: Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision (LAMSADE); Université Paris Dauphine-PSL; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS); Gestion de l'Eau, Acteurs, Usages (UMR G-EAU); Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro); Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Environnement, territoires et infrastructures (UR ETBX); Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Australian National University (ANU); Fenner School of Environment and Society; Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM); Syndicat Mixte Rivière Drôme; The Bartlett London; University College of London London (UCL); Argumentation, Décision, Raisonnement, Incertitude et Apprentissage (IRIT-ADRIA); Institut de recherche en informatique de Toulouse (IRIT); Université Toulouse 1 Capitole (UT1); Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3); Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP); Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1); Université Fédérale Toulouse Midi-Pyrénées; ANU (Australian National University) Global Research Partnerships Scheme; EU Erasmus+ Jean Monnet project: Europa Policy Labs (EUPL); EU Erasmus+ Jean Monnet project: Water Policy Innovation Hub (WPIH)
نبذة مختصرة : International audience ; Our digital age is characterized by both a generalized access to data and an increased call for participation of the public and other stakeholders and communities in policy design and decision-making. This context raises new challenges for political decision-makers and analysts in providing these actors with new means and moral duties for decision support, including in the area of environmental policy. The concept of “policy analytics” was introduced in 2013 as an attempt to develop a framework, tools, and methods to address these challenges. This conceptual initiative prompted numerous research teams to develop empirical applications of this framework and to reflect on their own decision-support practice at the science-policy interface in various environmental domains around the world. During a workshop in Paris in 2018, participants shared and discussed their experiences of these applications and practices. In this paper, we present and analyze a set of applications to identify a series of key properties that underpin a policy analytics approach, in order to provide the conceptual foundation for policy analytics to address current policy design and decision-making challenges. The induced properties are demand-orientedness, performativity, normative transparency, and data meaningfulness. We show how these properties materialized through these six case studies, and we explain why we consider them key to effective policy analytics applications, particularly in environmental policy design and decision-making on environmental issues. This clarification of the policy analytics concept eventually enables us to highlight research frontiers to further improve the concept.
Processing Request
No Comments.