https://doi.org/10.61152/PLCR9111
Meaghan Kennedy1, Michaela Bonnett1, and Teri Garstka2
1Orange Sparkle Ball, 2Social Innovation Labs, The University of Kansas
Series: Sunbelt 2024
Original Publication Date: June 25th, 2024
Publisher: Orange Sparkle Ball
Abstract
A Model for Technology-Enabled Community Resilience
Introduction
Tech-Enabled Community Resilience is an innovative model designed to enhance resilience and optimize impact in complex systems such as communities and ecosystems. The model leverages social network analysis and technology to visualize network dynamics, measure interactions, and implement targeted interventions.
Model Structure
The approach consists of two key stages: a Startup Phase focused on assembling champions and co-creating a shared vision, and a Steady-state Phase involving iterative measurement and intervention. By utilizing technology platforms for data collection and visualization, the model provides near real-time understanding of network functioning.
Advantages Over Traditional Approaches
Traditional resource mapping approaches provide a limited understanding of the network based on a static understanding of resources and a lack of complexity about network function. The Tech-Enabled Community Resilience model provides for a more dynamic, systems-thinking perspective. The model allows for precision interventions based on network structure, potentially influencing community-level outcomes.
Case Studies and Research Findings
Case studies from social care networks and economic development initiatives demonstrate the model's applicability across various contexts. Research findings linking network cohesion to improved community outcomes during crises, and network structure to increased innovation in ecosystems, underscore the model's potential impact.
Future Directions
Further model refinement includes the development of a portfolio of network-based interventions, integration of real-time data sources, and strategies for adaptive governance structures. This model represents a significant advancement in how to understand and harness complex systems for community resilience and impact optimization.
Citation List
Bonnett, M., Ladetto, A., Kennedy, M., Fernandez, J., & Garstka, T. (2024, June 25). Network Analysis of a Mobility Ecosystem in Detroit, MI [Conference Talk]. Sunbelt, Edinburgh, Scotland. https://www.insna.org/events/sunbelt-2024---edinburgh##
Cantner, U., & Graf, H. (2006). The network of innovators in Jena: An application of social network analysis. Research Policy, 35(4), 463–480. https://doi.org/10.1016/j.respol.2006.01.002
Garstka, T. (2024, June 25). The Relationship Between Community Networks and Population-Level Outcomes [Conference Talk]. Sunbelt, Edinburgh, Scotland. https://www.insna.org/events/sunbelt-2024---edinburgh##
Garstka, T., & Kennedy, M. (2023, May). Tech-Enabled Community Resilience [Conference Presentation]. Good Tech Fest, Washington, DC. https://www.goodtechfest.com/
Gartska, T., Kennedy, M., & Bonnett, M. (2024, September). Tech-Enabled Community Resilience: Research on the Transformative Role of Inclusive Social Care Ecosystems. International Social Innovation Research Conference (ISIRC), Bern, Switzerland. https://www.nunify.com/events/isir1
Isada, F. (2021). The Partnership Network Structure of Automakers under Radical Technological Change. Business Systems Research Journal, 12(2), 95–113. https://doi.org/10.2478/bsrj-2021-0021
Norris, F. H., & Stevens, S. P. (2007). Community Resilience and the Principles of Mass Trauma Intervention. Psychiatry, 70(4), 320–328. https://doi.org/10.1521/psyc.2007.70.4.320
Norris, F. H., Stevens, S. P., Pfefferbaum, B., Wyche, K. F., & Pfefferbaum, R. L. (2008). Community Resilience as a Metaphor, Theory, Set of Capacities, and Strategy for Disaster Readiness. American Journal of Community Psychology, 41(1–2), 127–150. https://doi.org/10.1007/s10464-007-9156-6