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Stochastic Analysis And Applied Research Of Game Theory And Principal-agent Theory On The Safety Accidents

Posted on:2012-07-30Degree:MasterType:Thesis
Country:ChinaCandidate:Y HaoFull Text:PDF
GTID:2249330371995964Subject:Industrial Economics
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In recent years, the coal mine accidents happen frequently in China. Although the Party and government pay a high attention to the issue and adopt some counter-measures to solve the problem, the prospect of the coal mine safety production situation is still not optimistic. So, the research on the issue of coal mine safety production in China is of significant theoretical and practical value. This thesis comprehensively applies Markov process of stochastic process theory, classical game theory, multi-task principal-agent theory under the probability constraint conditions and multidimensional game theory and other related disciplines’theories and methods, deeply study the essential reasons and counter-measures of the frequently happened coal mine accidents in China. The main research results of the thesis are as follows:Firstly, the thesis builds the Markov process model on the forecasting of the coal production industry in China, thus, provides a reference for the safety managers of the coal production industry and the coal mine safety supervision organization setting up the coal production safety warning strategy.Secondly, facing policy game on the governance of the local coal mine safety between central government and local government, the thesis applies the static game of complete information, static game of incomplete information and dynamic game of complete information to the analysis, and obtains the equilibrium solution between central government and local government and puts forward some relevant results and policy suggestions.Thirdly, the thesis adopts the multi-task principal-agent model under the probability constraint conditions to analyse the optimal incentive mechanism on the township coal mine enterprises managers" three working efforts" level of coal mine enterprises business performance, safety production, expansion of local government revenues and promotion of local employment rates, and puts forward some relevant results and policy suggestions.Fourthly, the thesis builds a two-dimensional static game model with complete information between coal mine enterprises group and coal mine supervision department. Based on the analysis of two-dimensional Nash equilibrium, the thesis explains the causes of the coal mine accidents of affiliated enterprises of the coal mine enterprises group and the problems existed in coal mine safety supervision in China. The thesis also puts forward some relevant results and policy suggestions.Fifthly, the thesis builds a three-dimensional dynamic game model with complete information between duopoly affiliated enterprises of the coal mine enterprises group about the decision on the three safety inputs:safety facilities inputs, workers’welfare inputs and technology R&D inputs, and obtains the sub-game perfect three-dimensional Nash equilibrium and the three-dimensional Nash equilibrium results on the three safety inputs of the two coal mine enterprises. Through the analyses of the equilibrium solution and two calculation examples, we can acquire that when the two coal mine enterprises adopt a game action on the three safety inputs, the coal mine enterprise should jointly consider the three safety inputs strategy, adopt an optimal strategic vector and scientifically and rationally allocate the limited safety inputs in order to maximize its safety benefits. Meanwhile, the coal mine enterprise should strive for a "first-mover advantage", take the initiative in safety inputs and move firstly in order to obtain more safety benefits than the rival coal mine enterprise.The research results of this thesis have some reference value on the research and study related about the issue of coal mine safety production in China.
Keywords/Search Tags:coal mine accidents, Markov process, game theory, multi-task principal-agentmodel, safety supervision, safety inputs
PDF Full Text Request
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