Measuring the Impact of Key Factors on Knowledge Co-Production Outcomes in Citizen Science

Abstract

The need to better understand the knowledge coproduction potential through citizen science is increasingly acknowledged. This perspective goes beyond merely viewing citizen science as a way of community-based monitoring or volunteer-based data collection. Based on a conceptual framework by Yu et al. (in press), this study validates and measures the impact of key factors on knowledge co-production outcomes through citizen science. Using exploratory (EFA) and confirmatory factor analysis (CFA), we develop a model that suggests causative relationships between three exogenous constructs-"volunteer trust", "researcher-volunteer connectedness", "openness and accessibility"-and two endogenous constructs-"scientific citizenship" and "technoscientific outputs". "Researcher-volunteer connectedness" and "volunteer trust" appear to be more impactful for "scientific citizenship" than "openness and accessibility", while "openness and accessibility" demonstrate the highest impact on "technoscientific outputs". "Scientific citizenship" and "technoscientific outputs" do not exhibit strong direct correlations. Our results provide valuable input for strengthening the potential of citizen science to coproduce knowledge.

Keywords: knowledge co-production, citizen science, explicit knowledge, tacit knowledge, impact assessment