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Sustainability 2017, 9(12), 2168; doi:10.3390/su9122168

Indicators for Responsible Research and Innovation: A Methodological Proposal for Context-Based Weighting

INGENIO (CSIC-UPV) Universitat Politècnica de València, Cámino de Vera s/n, València 46022, Spain
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Received: 17 October 2017 / Revised: 12 November 2017 / Accepted: 20 November 2017 / Published: 24 November 2017
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Abstract

In the last decade, the term Responsible Research and Innovation (RRI) has rapidly attracted the attention of policy-makers and researchers of Europe, mainly due to its promotion by the European Commission (EC). The concretion of this framework of RRI has been articulated by the EC around six key areas: governance, public engagement, gender equality, science education, open access, and open science and ethics. The indicators to measure these dimensions have been proposed recently. In our opinion the set of indicators available so far has two weaknesses: a lack of context-based indicators and a need for hierarchical ordering. Our aim is to provide tools for policy- and decision-makers that might need to identify the more important indicators in a specific context. In this work, we explored how the multicriteria analysis technique Analytical Hierarchical Process (AHP) can be used to prioritize indicators for RRI by involving experts in the specific context. The AHP method allowed weighting indicators according to experts in the different areas and producing four different options to select indicators. The method of AHP can be an appropriated instrument to select the most suitable indicators for RRI policies and initiatives. View Full-Text
Keywords: multiple criteria decision-making (MCDM); Responsible Research and Innovation (RRI); science policy evaluation; sustainable science multiple criteria decision-making (MCDM); Responsible Research and Innovation (RRI); science policy evaluation; sustainable science
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MDPI and ACS Style

Monsonís-Payá, I.; García-Melón, M.; Lozano, J.-F. Indicators for Responsible Research and Innovation: A Methodological Proposal for Context-Based Weighting. Sustainability 2017, 9, 2168.

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