The purpose of this article is to show the effect of Risk Perception RP and Risk Definition RD on the Risk-Addressing Behaviour RB. To carry out this study secondary data was used from a semi-structured survey administered between February and June 2020, a period during the early stages of the COVID-19 pandemic. The study identified six dimensions of risk perception and thus tested six structural models. Risk perception (ξ RP) is defined as an external latent variable in the study. It is also assumed that the risk perception variable may affect the risk definition variable (η RD). The application software SmartPLS was used to analyse data through exploratory factor analysis and partial least squares structural equation modelling on our research model. To achieve Convergent validity of the structural equation model of partial least squares, three criteria were met. In the study, Discriminant Validity was examined using the Fornell-Larcker criterion and Heterotrain-Monotrait Ratio (HTMT) coefficients. Results reveal that there is no direct relationship between the RB and “religion and beliefs”, the “fear level, the experience”, the “peer influences level” and the “openness”. However, we found a positive relationship between the agreement on “knowledge” and on RB and statistically significant relationships between the agreement on the RD and the agreement on the “religion and beliefs”, the “fear level”, the “experience”, the “knowledge”, the “peer influences level” and the RB. Moreover, there is an indirect relationship when controlling for the agreement on the RD between the agreement on the RB and the agreement on the “fear level”, the “experience”, the “knowledge” and the “peer influences level”. However, there is no relationship between the agreement on the “openness” and the agreement on the RB and a statistically significant but moderate relationship between the agreement on the RD and the agreement on the RB. Although, there seems to be abundant research on RP, so far we have found only a few studies on the influencing factors of RP, as effected by RB and RD, especially in distressed times such as during this current pandemic period of COVID-19. This study adds to body of literature and sheds new light on the interaction between RP, RB and RD in a time of distress. It provides important and original information that may be useful for government agencies, businesses, individuals, and the media when setting policies, governance structures, regulations, procedures and determining how to communicate.
