A various logistic analyzes to predict participation in volunteer activities after COVID-19: 891 residents aged 19 or older in Gyeongsangnam-do

Purpose of the study: This study provides basic data for building a platform against disasters by the private, regional and professional personnel by analyzing the predictive factors of volunteers' future volunteer intentions. Research Method: A hypothesis model was set for 891 residents aged 19 or older in Gyeongsangnam-do, and the volunteer predictive variables were analyzed in Chi square and logistic regression. Conclusions and suggestions: The research results show that the greatest willingness to volunteer in the future is volunteer experience (Exp (B) = 3.475, P =0.000). We suggest the activation of various recognition rewards such as specialized education and mileage accumulation for those with a lot of volunteer experience, and cooperative sharing platforms for schools, communities, and private experts to prepare for disasters. The significance of this study is meaningful in setting and verifying variables predicting the willingness to participate in volunteer work after COVID-19 using public data in Gyeongsangnam-do based on a hypothetical theoretical model.