COMPLEXITY-BASED DISASTER GOVERNANCE: MULTI-ACTOR COORDINATION IN FLOOD RESILIENCE BUILDING IN MAKASSAR

Abstract

This study examines flood disaster management through the lens of Complexity Theory to understand multi-actor coordination dynamics in building urban resilience. Using a qualitative case study approach with in-depth interviews, observation, and document analysis, the research investigates five key dimensions of complex adaptive systems: actor interactions, policy processes, decision-making patterns, power distribution, and information/value systems. Findings reveal a governance system characterized by fundamental contradictions between formal institutional structures and adaptive requirements for managing complex urban disasters. While community-level actors demonstrate emergent self-organization and rapid adaptive responses, formal institutions remain constrained by bureaucratic rigidity, sectoral fragmentation, and hierarchical control mechanisms. The policy process lacks iterative learning cycles, with evaluations functioning as administrative requirements rather than genuine learning mechanisms. Decision-making remains centralized despite the need for distributed authority during emergencies, creating critical response delays. Power asymmetries marginalize community knowledge while informal political networks disproportionately influence policy directions. Information systems suffer from fragmentation and trust deficits, with communities relying more on informal networks than official channels. The study demonstrates that effective flood governance requires transformation from command-and-control approaches toward collaborative networks that recognize distributed intelligence, enable polycentric decision-making, and integrate diverse knowledge systems. These findings contribute to complexity applications in public administration by revealing how theoretical principles manifest in specific governance contexts while highlighting the critical importance of aligning institutional designs with inherent complexity of contemporary urban challenges.