An Original Complexity Theory Perspective on Supply Chain Risk Propagation in Nigerian Manufacturing Networks

This dissertation applies complexity theory to advance understanding of supply chain risk propagation dynamics in Nigerian manufacturing networks, developing an original theoretical model and agent-based simulation framework that captures the emergent, non-linear, and path-dependent characteristics of risk propagation that deterministic supply chain risk management models cannot represent. Nigerian manufacturing supply chains exhibit the properties of complex adaptive systems, including tight inter-firm coupling, information asymmetry, institutional heterogeneity, and adaptive agent behaviour, characteristics that generate risk propagation dynamics qualitatively different from those in simpler, more formalised supply chain structures studied in the predominantly Euro-American supply chain risk literature. The theoretical model is developed through abductive reasoning informed by longitudinal fieldwork in manufacturing networks in the leather goods, electronics, and pharmaceutical sectors across Lagos, Aba, and Kano. An agent-based simulation model operationalises the theoretical model, with agent behavioural rules calibrated using empirically observed firm responses to supply disruption events documented during thirty months of network observation. Simulation experiments explore risk propagation under varying network topologies, risk event magnitudes, and information sharing regimes. Original findings reveal three previously untheorised propagation mechanisms: institutional void contagion, informal credit network collapse cascades, and adaptive supplier switching clustering. Policy simulation results identify targeted information sharing infrastructure investments as the highest-leverage intervention for reducing network-wide risk propagation velocity. Keywords: complexity theory, supply chain risk, agent-based modelling, risk propagation, Nigerian manufacturing