Investigating factors affecting villagers' participation in earthquake crisis management: A case study of Harris County

A B S T R A C T
Earthquakes are among the most destructive natural disasters, often resulting in extensive human and financial losses, especially in rural communities. Consequently, public management, community participation, cooperation, and effective coordination with governmental and relief organizations play a vital role in crisis control. This study aims to explore the key factors influencing public participation in earthquake-related crisis management. This research is applied in purpose and descriptive-analytical in nature. The statistical population consists of the heads of rural households in the villages of Baje Baj, Kivij, Chobanlar, Valilo, and Jighe in Harris County, which experienced the most severe damage during the 2012 Arasbaran earthquake. Out of a total of 485 households, a sample of 373 participants was selected using Cochran’s formula. Data were collected through both library research and field surveys. In the field study, questionnaires were administered directly to household heads. To assess the reliability of the instrument, a pilot survey was conducted with 30 respondents, and the resulting Cronbach’s alpha was 0.897, indicating high internal consistency. Exploratory factor analysis was employed to analyze the data. The findings revealed that the social factor had the highest explanatory power, accounting for 85.12% of the total variance, while the physical factor had the lowest contribution, at 12.6%. Moreover, all variables demonstrated factor loadings above 0.4, confirming their significance in the model.
Extended Abstract
Introduction
Earthquakes are among the most devastating natural disasters, posing a serious threat to sustainable community development. Beyond their immediate destruction, they bring about widespread social, physical, and economic losses across the globe. Rural settlements, often lacking robust infrastructure and economic resilience compared to urban areas, are particularly vulnerable to these impacts. This heightened vulnerability underscores the importance of identifying and assessing potential risks in order to reduce casualties and financial losses through effective crisis management and preparedness. This study focuses on exploring the factors that influence rural residents’ participation in earthquake crisis management in villages across East Azerbaijan Province. Various elements have been identified as contributing to either active involvement or lack of engagement in disaster response efforts. Given the significance of this issue, the research specifically aims to uncover the key drivers of rural community participation in crisis management related to earthquakes in Heris County.
 
Methodology
The present study is applied in terms of purpose and is descriptive-analytical in nature. The statistical population of the study consists of the heads of rural households in Harris County. Therefore, villages were selected as samples for the study that had the highest amount of damage in the 2012 Arasbaran earthquake and were the villages of Baje Baj, Kivij, Chobanlar, Velilo, and Jighe, which included 485 households. The sample size was estimated at 373 people based on the Cochran formula. In order to examine the theories of this community and to determine the factors affecting the participation of villagers in earthquake crisis management, two methods of library and field studies were used. The Cronbach's alpha coefficient for the entire questionnaire was calculated using SPSS software. In order to calculate reliability, 30 questionnaires were first distributed among the sample. The reliability of the entire questionnaire was estimated to be 0.897 based on Cronbach's alpha. Exploratory factor analysis was used to analyze the data obtained from the questionnaire.
 
Conclusion
The KMO index value was found to be greater than 0.60, indicating that the sample size was adequate for conducting factor analysis. Moreover, the significance level of Bartlett’s test was less than 0.05, confirming that the correlation matrix was not an identity matrix and that meaningful relationships existed among the variables. Through this analysis, seven key factors were identified—namely social, economic and environmental, institutional and ecological, cooperation and mutual aid, housing reinforcement, infrastructural, and physical factors—which together accounted for 67.59% of the total variance. Among these, the social factor explained the largest portion of the variance (12.85%), while the physical factor contributed the least (12.6%). The results also showed that all variables had factor loadings greater than 0.40, confirming their relevance within their respective components. Specifically, for the social factor, the variables with the highest loadings were “awareness of earthquake preparedness techniques provided by architects and local councils” (0.71) and “participation in providing emergency shelter for victims” (0.62). For the economic and environmental factor, the top variables were “accepting expert opinions regarding construction materials” (0.85) and “maintaining close, friendly relations with local authorities” (0.82). Within the institutional and ecological factor, the variables “residing in safe areas designated by local authorities” (0.65) and “cooperating with local councils in reinforcement initiatives” (0.62) had the highest impact. In the domain of cooperation and mutual aid, the variable “volunteering with relief teams during rescue operations” showed the strongest influence (0.78). As for the housing reinforcement factor, the use of “modern and durable construction materials” scored highest (0.76), while in the infrastructural factor, “collaboration with engineers in implementing new foundation techniques” had the highest loading (0.75). Lastly, in the physical factor, “manual labor in implementing development projects” (0.64) emerged as the most influential variable. These findings highlight the complex interplay of social, technical, and institutional dynamics in shaping rural participation in earthquake crisis management.
 
Results and discussion
The KMO index value was found to be greater than 0.60, indicating that the sample size was adequate for conducting factor analysis. Moreover, the significance level of Bartlett’s test was less than 0.05, confirming that the correlation matrix was not an identity matrix and that meaningful relationships existed among the variables. Through this analysis, seven key factors were identified—namely social, economic and environmental, institutional and ecological, cooperation and mutual aid, housing reinforcement, infrastructural, and physical factors—which together accounted for 67.59% of the total variance. Among these, the social factor explained the largest portion of the variance (12.85%), while the physical factor contributed the least (12.6%). The results also showed that all variables had factor loadings greater than 0.40, confirming their relevance within their respective components. Specifically, for the social factor, the variables with the highest loadings were “awareness of earthquake preparedness techniques provided by architects and local councils” (0.71) and “participation in providing emergency shelter for victims” (0.62). For the economic and environmental factor, the top variables were “accepting expert opinions regarding construction materials” (0.85) and “maintaining close, friendly relations with local authorities” (0.82). Within the institutional and ecological factor, the variables “residing in safe areas designated by local authorities” (0.65) and “cooperating with local councils in reinforcement initiatives” (0.62) had the highest impact. In the domain of cooperation and mutual aid, the variable “volunteering with relief teams during rescue operations” showed the strongest influence (0.78). As for the housing reinforcement factor, the use of “modern and durable construction materials” scored highest (0.76), while in the infrastructural factor, “collaboration with engineers in implementing new foundation techniques” had the highest loading (0.75). Lastly, in the physical factor, “manual labor in implementing development projects” (0.64) emerged as the most influential variable. These findings highlight the complex interplay of social, technical, and institutional dynamics in shaping rural participation in earthquake crisis management.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
 We are grateful to all the scientific consultants of this paper.