Regulatory Risk Propagation Models for Systemic Vulnerability Analysis in Public Sector Supply Chains

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@article{1714883,
      author = {Adewale Adelanwa, Uchechukwu Nkechinyere Anene},
      title = {Regulatory Risk Propagation Models for Systemic Vulnerability Analysis in Public Sector Supply Chains},
      journal = {Iconic Research And Engineering Journals},
      year = {2018},
      volume = {2},
      number = {5},
      pages = {367-390},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1714883.pdf},
      abstract = {Public sector supply chains operate within highly regulated environments where policy shifts, compliance failures, procurement irregularities, and geopolitical pressures can trigger cascading disruptions across interconnected agencies and service providers. Despite extensive governance frameworks, there remains limited analytical integration between regulatory risk assessment and systemic vulnerability modeling. This study develops a Regulatory Risk Propagation Model (RRPM) designed to analyze how regulatory shocks diffuse across multi-tier public sector supply networks and amplify systemic vulnerability. The model conceptualizes regulatory risk as a dynamic node-level disturbance capable of spreading through contractual, financial, informational, and operational linkages. Drawing on network theory, system dynamics, and probabilistic risk modeling, the proposed framework integrates regulatory exposure indices with interdependency matrices to simulate propagation pathways. Regulatory triggers including policy amendments, compliance audits, sanctions, budgetary controls, and legal disputes are modeled as initiating events with varying intensity and latency effects. The framework incorporates Bayesian updating mechanisms to adjust vulnerability scores as new compliance or enforcement data emerge. By mapping centrality, connectivity density, and dependency concentration, the model identifies critical nodes whose regulatory disruption would generate disproportionate systemic consequences. Empirical validation is conducted using structured secondary data from selected public procurement systems, applying Monte Carlo simulation to estimate shock transmission probabilities and threshold conditions for systemic breakdown. Results demonstrate that regulatory risk does not propagate linearly; instead, feedback loops, bureaucratic bottlenecks, and funding rigidities accelerate vulnerability clustering in highly centralized procurement structures. The model further reveals that diversified supplier portfolios, decentralized approval authority, and adaptive compliance monitoring significantly dampen propagation intensity. The study contributes to public administration and supply chain risk literature by advancing a quantitative approach that moves beyond static compliance checklists toward predictive vulnerability analytics. Policymakers can employ the RRPM to stress-test regulatory reforms, evaluate institutional resilience, and design early-warning dashboards for systemic risk containment. Ultimately, the framework enhances transparency, accountability, and operational continuity within public sector supply ecosystems by embedding regulatory foresight into strategic risk governance architectures.},
      keywords = {Regulatory Risk, Systemic Vulnerability, Public Sector Supply Chains, Risk Propagation Modeling, Network Theory, Compliance Analytics, Procurement Governance, Bayesian Simulation.},
      month = {November},
  }