| Popis: |
As primary users of a socially, economically, and environmentally significant yet increasingly stressed resource like water, the corporate and financial sectors have an important role in sustainable water management. However, extant literature reveals a gap in the empirical assessment of water risk perception and its influence on water risk evaluation and decision-making in the corporate and financial sectors. Our explanatory sequential mixed methods study examined the relationship between water risk perception and risk evaluation (risk ratings), addressing these gaps. We employed a cross-sectional survey (N = 25) followed by semi-structured interviews (N = 22), with a purposive expert sample of analysts, practitioners, and decision-makers in the corporate and financial sector in Ontario, Canada. Our study finds multi-dimensional risk perception factors, including knowledge, professional experience, perceived controllability, values, trust, location, and gender, that influence water risk ratings and vary with the type of risk. Moreover, the in-depth follow-up interviews reveal multiple drivers of different risk ratings, such as proximity bias, sector differences, trust in various institutions, as well as the influence of tacit knowledge, exposure, the role of regulations, media, and financial materiality. Our study empirically concludes that the water risk perception of analysts, practitioners, and decision-makers in the corporate and financial sectors is highly nuanced and impacts the evaluation of different water risks, and should be systematically integrated into risk assessment and decision-making frameworks. Our study advances knowledge in the fields of risk analysis and sustainable water management and contributes by empirically examining and explaining the complex and underexplored relationship between water risk perception factors and evaluation using novel interdisciplinary Risk Theory and mixed methods approaches. Finally, the study’s findings can help integrate sector and location-specific preferences and priorities with analytical data to design contextually-attuned decision support tools for sustainable water management strategies, policies, and practices. |
