Surveying the surveyors to address risk perception and adaptive-behaviour cross-study comparability - S. Rufat; S. Rufat; M. Madruga de Brito; A. Fekete; E. Comby; P. J. Robinson; I. Armaş; W. J. W. Botzen; C. Kuhlicke; C. Kuhlicke (Natural Hazards and Earth System Sciences, 2022)
One of the key challenges for risk, vulnerability and resilience research is how to address the role of risk perceptions and how perceptions influence behaviour. It remains unclear why people fail to act adaptively to reduce future losses, even when there is ever-richer information available on natural and human-made hazards (flood, drought, etc.). The current fragmentation of the field makes it an uphill battle to cross-validate the results of existing independent case studies. This, in turn, hinders comparability and transferability across scales and contexts and hampers recommendations for policy and risk management. To improve the ability of researchers in the field to work together and build cumulative knowledge, we question whether we could agree on (1) a common list of minimal requirements to compare studies, (2) shared criteria to address context-specific aspects of countries and regions, and (3) a selection of questions allowing for comparability and long-term monitoring. To map current research practices and move in this direction, we conducted an international survey – the Risk Perception and Behaviour Survey of Surveyors (Risk-SoS). We find that most studies are exploratory in nature and often overlook theoretical efforts that would enable the comparison of results and an accumulation of evidence. While the diversity of approaches is an asset, the robustness of methods is an investment to be made. Surveyors report a tendency to reproduce past research design choices but express frustration with this trend, hinting at a turning point. To bridge the persistent gaps, we offer several recommendations for future studies, particularly grounding research design in theory; improving the formalisation of methods; and formally comparing theories and constructs, methods, and explanations while collecting the themes and variables most in use.