A Theoretical Framework for Resilience in Complex System Governance (CSG)

This dissertation addresses a critical gap in resilience research within complex systems by developing a theoretical framework for governance resilience—an underexplored area despite governance's crucial role in maintaining system resilience. Using the Complex System Governance (CSG) framework (Keating, Katina, Chesterman, et al., 2022; Keating & Katina, 2019), resilience is conceptualized as a system's ability to absorb disturbances while sustaining performance and enabling adaptive transformation. This involves three main capabilities: persistence, adaptability, and transformation in response to both internal and external pressures. Through a constructivist grounded theory approach involving iterative coding, memoing, and theory development, this study inductively constructs a governance resilience framework within the CSG context. It addresses two key research questions: 1. What theoretical framework can be developed for governance resilience in complex systems? 2. What are the outcomes when this framework is applied in an operational setting? The research identifies persistence, adaptability, and transformation as core components of governance resilience. Persistence relates to the system's restorative capacity and resource sufficiency, adaptability balances flexibility with stability, and transformation emphasizes proactive, forward-looking governance. The theoretical model proposes that governance resilience requires a holistic perspective that integrates internal and external contexts with future-oriented anticipation. This aligns with the viability axiom, which states that a system must handle internal and external variability to remain viable. System theory principles like circular causality and requisite variety support this approach, emphasizing that governance must mirror the resilience capabilities of the system it oversees. This study highlights the importance of metasystem functions—such as feedback, experience, and learning—in shaping governance resilience. It contributes a novel framework for governance resilience in complex systems, offering insights for policymakers, practitioners, and scholars aiming to strengthen resilience through governance strategies. By advancing a holistic approach, this work challenges existing resilience literature, expanding systems analysis to include governance resilience and broadening our understanding of resilience across complex systems.

Institutions

Publication Details

Journal
ODU Digital Commons (Old Dominion University)
Published
2025-02-10
DOI
https://doi.org/10.25777/ganm-fs79
Primary Topic
Sustainability and Climate Change Governance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Theoretical Framework for Resilience in Complex System Governance (CSG)

ODU Digital Commons (Old Dominion University)
Sustainability and Climate Change Governance
article

A Theoretical Framework for Resilience in Complex System Governance (CSG)

article en

Abstract

This dissertation addresses a critical gap in resilience research within complex systems by developing a theoretical framework for governance resilience—an underexplored area despite governance's crucial role in maintaining system resilience. Using the Complex System Governance (CSG) framework (Keating, Katina, Chesterman, et al., 2022; Keating & Katina, 2019), resilience is conceptualized as a system's ability to absorb disturbances while sustaining performance and enabling adaptive transformation. This involves three main capabilities: persistence, adaptability, and transformation in response to both internal and external pressures. Through a constructivist grounded theory approach involving iterative coding, memoing, and theory development, this study inductively constructs a governance resilience framework within the CSG context. It addresses two key research questions: 1. What theoretical framework can be developed for governance resilience in complex systems? 2. What are the outcomes when this framework is applied in an operational setting? The research identifies persistence, adaptability, and transformation as core components of governance resilience. Persistence relates to the system's restorative capacity and resource sufficiency, adaptability balances flexibility with stability, and transformation emphasizes proactive, forward-looking governance. The theoretical model proposes that governance resilience requires a holistic perspective that integrates internal and external contexts with future-oriented anticipation. This aligns with the viability axiom, which states that a system must handle internal and external variability to remain viable. System theory principles like circular causality and requisite variety support this approach, emphasizing that governance must mirror the resilience capabilities of the system it oversees. This study highlights the importance of metasystem functions—such as feedback, experience, and learning—in shaping governance resilience. It contributes a novel framework for governance resilience in complex systems, offering insights for policymakers, practitioners, and scholars aiming to strengthen resilience through governance strategies. By advancing a holistic approach, this work challenges existing resilience literature, expanding systems analysis to include governance resilience and broadening our understanding of resilience across complex systems.

ODU Digital Commons (Old Dominion University)
Dominion University College (GH), Old Dominion University (US)
Openalex Percentile: Top 57%
Sustainability and Climate Change Governance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.