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Multi-agent Collaborative Governance Mechanism And Operation Evolution Research Of Pneumoconiosis Problem In China

Posted on:2021-01-06Degree:DoctorType:Dissertation
Country:ChinaCandidate:X R HuangFull Text:PDF
GTID:1364330629981324Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
As the most serious occupational disease in China,pneumoconiosis accounts for about 90% of the total number of occupational diseases.In 2019,the number of pneumoconiosis patients in China has exceeded 975,000,of which 873,000 are occupational pneumoconiosis.In recent years,the overall incidence of pneumoconiosis is still on the rise,with an annual growth rate of 26,000 cases.In addition,the scope of pneumoconiosis-prone industries is gradually expanding,including not only metal mining and non-metal mining,but also machinery manufacturing,smelting,construction,road construction,hydropower and many other industries.As a serious occupational disease,pneumoconiosis exists the phenomenon of returning to poverty or causing poverty due to illness,which not only seriously damages the physiological function and mental health of patients,but also poses a threat to their marriage,family and social functions,and thereby bringing great negative effects to economic development and social stability.With the increasingly severe problem of pneumoconiosis in China,how to solve the problems of occupational health damage and overcome the current government’s single ineffective governance under the premise of achieving the management objectives of safe production and healthy labor has become a major issue to be solved urgently in the contemporary society.In terms of mode innovation,network structure upgrading and governance effectiveness improvement in the field of management behavior science research,collaborative governance presents great advantages.Therefore,the construction of pneumoconiosis multi-agent collaborative governance network structure of cross-departmental and cross-domain is the inevitable requirement and optional path to break through the current governance dilemma.Based on the concept definition of pneumoconiosis multi-agent collaborative governance,this study explores the components,coupling boundaries,and structural characteristics of the collaborative governance system of pneumoconiosis in China from the cognitive,coupled and evolutionary perspective.Based on the subject-relationship-structure,the five types of heterogeneous action collaborative governance model is systematically characterized,and the interaction mechanism of multiple subjects in collaborative governance is clearly defined.Through the combination of qualitative research,a pneumoconiosis multi-agent collaborative governance theoretical model in the context of collaborative co-governance of different network groups is constructed.On this basis,based on the questionnaire data and qualitative analysis results,statistical methods are applied to analyze the multi-agent interaction elements in the pneumoconiosis governance system and their influencing mechanism on the overall governance effectiveness.Further,through the multilayer neural network and social network modeling method,pneumoconiosis multi-agent collaborative governance network system network is constructed under the intervention of the multi-agent collaborative interactive elements and network mixed elements,and the system simulation method is applied to the nonlinear behavior modeling,so as to realize behavior selection under the influence of different situational elements.Finally,the pneumoconiosis multi-agent win-win policy system for collaborative governance is designed based on the empirical and simulation results.The specific research contents and conclusions are as follows:1.Theory construction of pneumoconiosis multi-subject collaborative governance from the perspective of multiple collaboratives.(1)The basic elements of the government,employing units,medical and health institutions,social organizations and pneumoconiosis patients are determined,and then the guidance-execution-benefit layer structure of the pneumoconiosis multi-agent collaborative governance network is clarified.(2)On this basis,according to the social preference theory,this research analyzes the pneumoconiosis multi-agent governance behavior from self-interest and reciprocity.(3)According to the expression of the multiple coupling order,the evolutionary path of “Strong aversion and mutual exclusion-Weak aversion and mutual exclusion-Weak reciprocity and collaboration-Strong reciprocity and collaboration-Reciprocity and all-winning” is proposed.2.Multi-agent interaction model construction and quantitative study of pneumoconiosis collaborative governance.(1)Through qualitative research,the interaction mechanism between multiple subjects for pneumoconiosis collaborative governance is identified.The current situation of interaction between subjects is analyzed from two levels: Work level(information,task,function,channel,development interaction)and Affection level(cognition,identity,trust,and dependency level).The research found that the same subject has certain bidirectional conflict in the interaction perception towards different subjects.In other words,pneumoconiosis patients have the lowest perception level of interaction quality with employing units,and they also have the lowest perception with pneumoconiosis patients.(2)The perceived quality of the overall relationship among the interacting subjects presents approaching trend,in which the Affection interaction perceptions of different subjects all show ranking consistency,that is,the dependency level < the trust level < the identity level < the cognition level.Therefore,the quality of the relationship between the interacting subjects is at the surface level of emotional cognition.(3)On the whole,the relationship perception level between different subjects and other subjects is relatively low,among which the “trapped type” patients with pneumoconiosis and employers accounts for the largest proportion,while the “dynamic type” participants of medical and health institutions accounts for a relatively large proportion and plays a positive role in the multi-subject interaction.3.Pneumoconiosis multi-agent collaborative governance model construction and its empirical analysis.According to the qualitative analysis,the governance structure framework of pneumoconiosis system including the subject factors,relation factors and structure factors is constructed.The empirical analysis results are as follows:(1)The collaborative governance of pneumoconiosis among different subjects is at low and middle level.Specifically,people with the following characteristics are less willing to participate in the pneumoconiosis collaborative governance: younger than 30 years old,unmarried,monthly family income within the range of 10,000-2,000 yuan,education level at or below primary school,number of family members at or above 6,working years less than 3 years,and at basic occupational level.(2)Subjective factors(value perception,benefit perception,and participation perception),relation factors(work and affection interactions)and structural factors(embeddedness perception,centrality perception,and systematicness perception)among the system endogenous factors have significant predictive effects on the multi-agent collaborative governance of pneumoconiosis.(3)Resource heterogeneity,capacity heterogeneity,ecological niche heterogeneity,policy and institutional risk,collaborative cost risk,and technical channel risks in the system exogenous factors have significant moderating effect paths on the relationship between subject,relation,structure factors and the partial behavioral tendency of multi-subject pneumoconiosis collaborative governance.4.Co-governance evolution and simulation analysis of the pneumoconiosis multi-agent collaborative governance system.Under the real multi-subject interaction,the linkage network group structure of government,employing units,medical and health institutions,social organizations and pneumoconiosis patients is constructed.Through the combination of Matlab,Python,Visual Studio and other platforms,the pneumoconiosis multi-agent collaborative governance evolution simulation system of is developed,which can replicate the evolution trend of pneumoconiosis multi-agent collaborative governance with time changes under the mixed intervention intensity of different elements.Simulation results show that:(1)In the initial state of the multiple governance system for pneumoconiosis,the interaction subjects showed the characteristic that the Strong aversion and mutual exclusion is the highest and the Weak aversion and mutual exclusion is the second,and the overall governance system fell into the “Antagonism State”.By further enhancing the network influence intensity,it can be found that outstanding members have a strong reversing effect,the level of pneumoconiosis collaborative governance rapidly increases,and the whole system continuously evolves to a better co-governance order,eventually reaching a “Symbiosis State”.(2)Based on the differences in subjects,the pneumoconiosis collaborative governance level among the five types of heterogeneous subjects shows a fluctuating trend under the intervention and influence of different degrees of interactive elements,among which the matching effect between pneumoconiosis patients and employing unit has the most significant impact on the evolution of the co-governance order.Specifically,in the two main body matching work and affection interactive intervention,under the same growth standard of pneumoconiosis patients and employing unit,pneumoconiosis patients and medical and health institutions,pneumoconiosis patients and social organizations,government and medical and health institutions,government and social organizations,medical and health institutions and social organizations in terms of changing multiple relation and order has a relatively strong ability of adjustment.However,pneumoconiosis patients and government,government and employing units,the employing units and medical and health institutions,employing units and social organizations have limited effectiveness in the intervention effect.In addition,the over-intensification of affection interaction will lead to the degradation of the co-governance efficiency of the whole system.(3)Under the intervention of interactive elements among the different levels of subject factors perception,the structure factors perception,heterogeneous characteristics,risk characteristics have relatively strong adjustments in changing the multiple co-governance relationship and order.When all the interaction factors and network influence intensity among different subjects are enhanced comprehensively,the whole network is promoted,jumping from the “Antagonism State” to “All-win State” at a relatively fast speed.Compared to promoting a single subject or element alone,it can enter a win-win situation at the time of initiation more quickly.Therefore,the comprehensive promotion of all network groups or all interactive elements can provide the strongest impetus for all-win cooperation,which can quickly promote the realization of pneumoconiosis multi-agent collaborative governance.5.Finally,based on the results of qualitative analysis and quantitative analysis,the pneumoconiosis multi-agent collaborative governance system and the design of PSBEN All-win and mutually beneficial policy system are constructed.Taking psychology(P),structure(S),behavior(B),efficiency(E),and network(N)as the promotion objects,the design of subjective psychological intervention,the design of network structure reconstruction,the design of prevention and control of subjective behavior,the design of multi-agent collaborative network efficiency improvement and the construction of social network diffusion are carried out respectively.In addition,the promotion strategy of pneumoconiosis collaborative governance is proposed,which can provide reference for the effective realization of collaborative governance among different subjects.This paper involves 61 figures,90 tables and 475 references.
Keywords/Search Tags:Pneumoconiosis governance, Multi-agent collaboration, Interactive structure, Symbiotic evolution, Intervention simulation
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