Economic Dynamics and Human Resource Cohesiveness in Post-Disaster Recovery : A Quantitative Analysis of Indonesian Communities
DOI:
https://doi.org/10.55606/ijemr.v4i3.559Keywords:
Community Resilience, Economic Dynamics, Human Resource Cohesiveness, Post-Dosaster Recovery, Social CapitalAbstract
This study examines the influence of economic dynamics and human resource cohesion on the success and speed of post-disaster economic recovery in Indonesian communities. Using a cross-sectional quantitative survey design, data were collected through structured questionnaires from 120 respondents consisting of community members and recovery team members in disaster-affected areas across Indonesia during the period 2020-2024. This study used descriptive statistics, Pearson correlation analysis, and multiple linear regression using IBM SPSS Statistics 26 to analyze the relationship between these variables. The results showed that both economic dynamics (β = 0.30, p < 0.001) and human resource cohesion (β = 0.48, p < 0.001) had a significant positive effect on post-disaster economic recovery. The model used in this study was able to explain 72.7% of the variance in economic recovery (R² = 0.727, F = 155.39, p < 0.001). Human resource cohesion emerged as a stronger predictor, with a correlation of r = 0.804 with economic recovery, while economic dynamism correlated at r = 0.694. These findings emphasize that communities with strong economic activity and high levels of social cohesion tend to recover more quickly and effectively in maintaining business continuity and income stability. This study highlights the importance of integrating economic strengthening initiatives with increasing social cohesion as a key strategy to accelerate and sustain post-disaster community recovery efforts. The implication of these findings is that economic recovery programs must include social components that strengthen relationships between individuals, groups, and institutions within the community to create sustainability in the recovery process.
References
Behera, J. K. (2023). Role of social capital in disaster risk management: A theoretical perspective in special reference to Odisha, India. International Journal of Environmental Science and Technology, 20(3), 3385–3394. https://doi.org/10.1007/s13762-021-03735-y
Beyer, R. C. M., Narayanan, A., & Thakur, G. M. (2022). Natural disasters and economic dynamics: Evidence from the Kerala floods. [Online]. Available at: https://www.emdat.be/cred-crunch-53-flash-floods-sharing-field-experience-kerala. https://doi.org/10.1596/1813-9450-10084
Botzen, W. J. W., Deschenes, O., & Sanders, M. (2019). The economic impacts of natural disasters: A review of models and empirical studies. Review of Environmental Economics and Policy, 13(2), 167–188. https://doi.org/10.1093/reep/rez004
Cénat, J. M., et al. (2021). The Transcultural Community Resilience Scale: Psychometric properties and multinational va-lidity in the context of the COVID-19 pandemic. Frontiers in Psychology, 12, 1–10. https://doi.org/10.3389/fpsyg.2021.713477
Chang, S. E., & Rose, A. Z. (2012). Towards a theory of economic recovery from disasters. International Journal of Mass Emergencies & Disasters, 30(2), 171–181. https://doi.org/10.1177/028072701203000202
Da Silva, S. M., Nata, G., Silva, A. M., & Faria, S. (2022). Development and validation of a Community Resilience Scale for Youth (CRS-Y). PLoS ONE, 17(8), 1–21. https://doi.org/10.1371/journal.pone.0269027
Dikmenli, Y., Yakar, H., & Konca, A. S. (2018). Development of disaster awareness scale: A validity and reliability study. Review of International Geographical Education Online, 8(2), 206–220.
Dwyer, C., & Horney, J. (2014). Validating indicators of disaster recovery with qualitative research. PLoS Currents. https://doi.org/10.1371/currents.dis.ec60859ff436919e096d51ef7d50736f
Eisenman, D. P., Adams, R. M., & Rivard, H. (2016). Measuring outcomes in a community resilience program: A new metric for evaluating results at the household level. PLoS Currents, 8. https://doi.org/10.1371/currents.dis.15b2d3cbce4e248309082ba1e67b95e1
Geddam, S. M., & Raj Kiran, C. A. (2024). Enhancing disaster management effectiveness: An integrated analysis of key factors and practical strategies through Structural Equation Modeling (SEM) and Scopus data text mining. Geohazard Mechanics, 2(2), 95–107. https://doi.org/10.1016/j.ghm.2024.03.001
Guha-Sapir, D., & Hoyois, P. (2012). Measuring the human and economic impact of disasters. Report Produced for the Government Office of Science, Foresight Project 'Reducing Risks of Future Disasters: Priorities for Decision Makers, 1–40. Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/286966/12-1295-measuring-human-economic-impact-disasters.pdf
Hallegatte, S., Jooste, C., & McIsaac, F. (2024). Modeling the macroeconomic consequences of natural disasters: Capital stock, recovery dynamics, and monetary policy. Economic Modelling, 139, 106787. https://doi.org/10.1016/j.econmod.2024.106787
Hariyono, H., Purwono, R., Sukartini, N. M., & Madyawati, S. P. (2025). Post-eruption economic recovery: Strengthening livelihoods in Lumajang, Indonesia after Mount Semeru disaster. CCDJ, 5(1), 1–13. https://doi.org/10.55942/ccdj.v5i1.351
Henchion, M., et al. (2019). Big issues for a small technology: Consumer trade-offs in acceptance of nanotechnology in food. Innovative Food Science and Emerging Technologies, 58, 102210. https://doi.org/10.1016/j.ifset.2019.102210
Henderson, T. L., et al. (2009). After a disaster: Lessons in survey methodology from Hurricane Katrina. Population Research and Policy Review, 28(1), 67–92. https://doi.org/10.1007/s11113-008-9114-5
Hettige, S., Haigh, R., & Amaratunga, D. (2018). Community level indicators of long term disaster recovery. Procedia En-gineering, 212, 1287–1294. https://doi.org/10.1016/j.proeng.2018.01.166
Jakupcak, J. (2007). Prevalence and psychological correlates of complicated. Journal of Traumatic Stress, 20(3), 251–262. https://doi.org/10.1002/jts.20223
Keyvanfar, A., Shafaghat, A., Ya'Acob, N., & Roslan, A. (2021). Sustainable post-disaster settlement (SPS) assessment model for evaluating performance of construction management in post-flood risk-reduction and recovery. Journal of Sustainability Science and Management, 16(5), 174–199. https://doi.org/10.46754/jssm.2021.07.013
Khatri, R. B., et al. (2023). Preparedness, impacts, and responses of public health emergencies towards health security: Qualitative synthesis of evidence. Archives of Public Health, 81(1), 1–15. https://doi.org/10.1186/s13690-023-01223-y
King, D., & James, Y. G. (2021). Focusing post-disaster research methodology: Reflecting on 50 years of post-disaster research. Australian Journal of Emergency Management, 36(4), 32–39.
Kukeli, A. (2025). The effects and the macroeconomic dynamics of natural disaster damages: Investigation of local evi-dence. Regional Studies, Regional Science, 12(1), 5–22. https://doi.org/10.1080/21681376.2025.2452524
Marutschke, D. M., Nurdin, M. R., & Hirono, M. (2024). Quantifying social capital creation in post-disaster recovery aid in Indonesia: Methodological innovation by an AI-based language model. Disasters, 48(S1), 1–24. https://doi.org/10.1111/disa.12631
Nakagawa, Y., & Shaw, R. (2004). Social capital: A missing link to disaster recovery. International Journal of Mass Emergencies & Disasters, 22(1), 5–34. https://doi.org/10.1177/028072700402200101
Nilakant, V., Walker, B., & Rochford, K. (2013). Post-disaster management of human resources: Learning from an ex-tended crisis. Resilient Organisations Research Report 2013/03, 1–27. Available at: http://hdl.handle.net/10092/7840
Nurdin, M. R. (2022). Examining the effectiveness of government agencies in disaster recovery: Evidence from Indonesia. Journal of the Asia-Japan Research Institute of Ritsumeikan University, 4, 146–157.
Nurimansjah, R. A. (2023). Dynamics of human resource management: Integrating technology, sustainability, and adaptability in the modern organizational landscape. Golden Ratio of Mapping Idea and Literature Format, 3(2), 104–123. https://doi.org/10.52970/grmilf.v3i2.324
Panday, S., Rushton, S., Karki, J., Balen, J., & Barnes, A. (2021). The role of social capital in disaster resilience in remote communities after the 2015 Nepal earthquake. International Journal of Disaster Risk Reduction, 55, 102112. https://doi.org/10.1016/j.ijdrr.2021.102112
Patrascu, F. I., & Mostafavi, A. (2024). Spatial model for predictive recovery monitoring based on hazard, built envi-ronment, and population features and their spillover effects. Environment and Planning B: Urban Analytics and City Science, 51(1), 39–56. https://doi.org/10.1177/23998083231167433
PDNA Guidelines Volume B - Macroeconomic impact of disasters. (2017). [Online]. Available at: https://reliefweb.int/report/world/pdna-guidelines-volume-b-macro-economic-impact-disasters
Peluso, A., et al. (2023). Spatial analysis of social capital and community heterogeneity at the United States county level. Applied Geography, 162, 103168. https://doi.org/10.1016/j.apgeog.2023.103168
Pescaroli, G., et al. (2020). A Likert scale-based model for benchmarking operational capacity, organizational resilience, and disaster risk reduction. International Journal of Disaster Risk Science, 11(3), 404–409. https://doi.org/10.1007/s13753-020-00276-9
Qadriina, H. I., Herdiansyah, H., & Aryo, B. (2023). The role of social capital in the response and recovery process of post-disaster affected communities. International Journal of Science and Society, 5(4), 797–812. https://doi.org/10.54783/ijsoc.v5i4.849
Ramachandran, M., Ramu, K., & Sivaji, C. (2024). An emergency management building resilience using IBM SPSS Sta-tistics. Building Materials and Engineering Structures, 1(1), 41–50. https://doi.org/10.46632/bmes/1/1/5
Rouping, G., Sekuler, A. B., & Murray, R. F. (2001). A modal completion: A case study in. Neurocomputing, 38(1–4), 265–294. https://doi.org/10.1016/S0166-4115(01)80029-7
Stratton, S. J. (2018). Likert data. Prehospital and Disaster Medicine, 33(2), 117–118. https://doi.org/10.1017/S1049023X18000237
Suriastini, N. W., et al. (2023). Measuring disaster recovery: Lessons learned from early recovery in post-tsunami area of Aceh, Indonesia. Sustainability (Switzerland), 15(24), 16870. https://doi.org/10.3390/su152416870
Teng-Calleja, A. M., Presbitero, A., & de Guzman, M. M. (2024). Dissecting HR's role in disaster preparedness and re-sponse: A phenomenological approach. Personnel Review, 53(2), 455–472. https://doi.org/10.1108/PR-12-2021-0867
Teng-Calleja, M., Presbitero, A., & de Guzman, M. M. (2023). Dissecting HR's role in disaster preparedness and response: A phenomenological approach. Personnel Review, 53(2), 455–472. https://doi.org/10.1108/pr-12-2021-0867
Ulubasoglu, M., et al. (2024). The hidden power of community: Unveiling social capital's role in Australia's disaster re-silience. Centre for Disaster Resilience and Recovery, Deakin Business School for Australian Red Cross. Available at: https://www.redcross.org.au/globalassets/cms/publications/2024-social-capital-report.pdf
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