極端な災害における対処メカニズムと集団行動を強化するための社会的支援とデジタル技術の統合
Ali Nawaz Khan1, Mohsin Ali Soomro2
1Faculty of Business Administration, Macau Millennium College, Macao, China.
Abstract:
Floods remain one of the most devastating climate-related disasters worldwide, and their increasing frequency in South Asia has posed severe challenges for community resilience and disaster management. In Pakistan's Indus River plains, recurrent flooding continues to displace millions, underscoring the urgent need to understand psychosocial and digital dimensions of disaster preparedness. This study examines how flood-prone individuals utilize risk awareness, social support, and social media to enhance their coping appraisal and engage in collective action. Grounded in protection motivation theory (PMT), we have built a three-way interaction research model to examine how social media apps influence social support to affect the relationship between risk awareness and coping appraisal in times of flood. We collected data from perennial flood-prone inhabitants of the Indus River plains. AMOS 24 and SPSS 23 were used to analyze the collected data. Results revealed that risk awareness significantly enhances coping appraisal, which in turn strengthens collective action tendencies. This study found that social support moderates the relationship between risk awareness and coping appraisal, with stronger effects at higher social support levels. The three-way interaction analysis revealed that social media information sharing amplifies the impact of social support on the relationship between risk awareness and coping appraisal, demonstrating the fostering role of digital communication in disaster resilience. These findings underscore the synergistic impact of social support and digital platforms in fostering adaptive behaviors, offering crucial insights for disaster risk management practitioners, policymakers, and humanitarian agencies working in flood-prone regions. Ultimately, this study provides a framework for integrating social resources and digital tools into localized flood risk reduction strategies.
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