Insights into Flood‐Coping Appraisals of Protection Motivation Theory: Empirical Evidence from Germany and France

Philip Bubeck, Wouter Botzen, Jonas Laudan, Jeroen C.J.H. Aerts and Annegret H. Thieken

Risk Analysis, 2018, vol. 38, issue 6, 1239-1257

Abstract: Protection motivation theory (PMT) has become a popular theory to explain the risk‐reducing behavior of residents against natural hazards. PMT captures the two main cognitive processes that individuals undergo when faced with a threat, namely, threat appraisal and coping appraisal. The latter describes the evaluation of possible response measures that may reduce or avert the perceived threat. Although the coping appraisal component of PMT was found to be a better predictor of protective intentions and behavior, little is known about the factors that influence individuals’ coping appraisals of natural hazards. More insight into flood‐coping appraisals of PMT, therefore, are needed to better understand the decision‐making process of individuals and to develop effective risk communication strategies. This study presents the results of two surveys among more than 1,600 flood‐prone households in Germany and France. Five hypotheses were tested using multivariate statistics regarding factors related to flood‐coping appraisals, which were derived from the PMT framework, related literature, and the literature on social vulnerability. We found that socioeconomic characteristics alone are not sufficient to explain flood‐coping appraisals. Particularly, observational learning from the social environment, such as friends and neighbors, is positively related to flood‐coping appraisals. This suggests that social norms and networks play an important role in flood‐preparedness decisions. Providing risk and coping information can also have a positive effect. Given the strong positive influence of the social environment on flood‐coping appraisals, future research should investigate how risk communication can be enhanced by making use of the observed social norms and network effects.

Date: 2018
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