Murphy’s law, Parkinson’s law, Pareto principle: collaborative management of forest fires based on risk analysis

The escalating frequency and scale of global forest fires, exacerbated by climate change and human activities, present a critical challenge to ecosystem stability and public safety. Traditional forest fire management often suffers from inefficient resource allocation and inadequate risk mitigation due to its failure to systematically address inherent systemic biases and uncertainties. The purpose of this study is to investigate how three fundamental principles—Murphy’s Law, Parkinson’s Law, and the Pareto Principle—influence the effectiveness of collaborative forest fire management from a risk analysis perspective. Methodologically, the study employs a differential game theory framework to model the strategic interactions between government agencies and environmental organizations, incorporating risk assessment parameters. The key findings reveal that the strategic approach of stakeholders is highly sensitive to the perceived benefits of collaboration. Specifically, government agencies tend to adopt strategies aligned with the Pareto Principle when collaboration benefits are low, focusing on critical priorities, but shift towards behaviors reflective of Parkinson’s Law when benefits are high, potentially leading to resource expansion and inefficiency. In contrast, environmental organizations consistently demonstrate management approaches that adhere to the Pareto Principle. The study concludes that explicitly accounting for these behavioral principles is crucial for designing robust collaborative mechanisms. The primary contribution and novelty of this research lie in the original integration of these well-known sociological and management principles into a formal analytical model for disaster management. This novel framework provides a valuable tool for policymakers to anticipate stakeholder behavior, optimize resource deployment, and enhance the overall resilience of forest fire management systems against unforeseen risks.