Published April 28, 2023 | Version 1
Journal article Open

Social responsibility in research and innovation practice and policy across global regions, institutional types, and fields: Interview data and qualitative content analysis outputs revealing the perspectives and experiences of professionals

  • 1. Global Sustainability Institute, Anglia Ruskin University, Cambridge, UK
  • 2. Lucy Cavendish College, University of Cambridge, Cambridge, UK
  • 3. Thriving Natural Capital Challenge Centre, Scotland's Rural College (SRUC), Edinburgh, UK
  • 4. School of Management, Anglia Ruskin University, Cambridge, UK
  • 5. Policy Research Unit, International Consortium of Research Staff Associations, Cork, Ireland

Description

The European Commission-funded RRING (Responsible Research and Innovation Networked Globally) Horizon 2020 project aimed to deliver activities that promoted a global understanding of Socially Responsible Research and Innovation (RRI). A necessary first step in this process was to understand how researchers (working across Global North and Global South contexts) implicitly understand and operationalise ideas relating to social responsibility within their day-to-day work. Here, we describe an empirical dataset that was gathered as part of the RRING project to investigate this topic. This Data Note explains the design and implementation of 113 structured qualitative interviews with a geographically diverse set of researchers (across 17 countries) focusing on their perspectives and experiences. Sample selection was aimed at maximising diversity. As well as spanning all five UNESCO world regions, these interview participants were drawn from a range of research fields (including energy; waste management; ICT/digital; bioeconomy) and institutional contexts (including research performing organisations; research funding organisations; industry and business; civil society organisations; policy bodies). This Data Note also indicates how and why a qualitative content analysis was implemented with this interview dataset, resulting in category counts available with the anonymised interview transcripts for public access.

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