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Evolutionary Analysis Of Social Responsibility Behavior Of Megaproject Based On Computational Experiments

Posted on:2021-03-25Degree:MasterType:Thesis
Country:ChinaCandidate:D HeFull Text:PDF
GTID:2439330611465281Subject:Architecture and civil engineering
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In contemporary China,the construction upsurge of megaprojects is in the ascendant.As an important value factor to measure the success of megaproject,megaproject social responsibility(MSR)has been paid more and more attention.The megaproject social responsibility behavior has a dynamic evolution.In the process of evolution,the lack and misconduct of any party's social responsibility behavior will promote the alienation of social responsibility behavior,induce corruption,community conflict,ecological pollution and other problems,and further damage the investment benefit and social image.Although MSR has attracted the attention of the academia and industry,most of the researches ignore the dynamic evolution of MSR behavior,or the research results may not be fully applicable to the megaprojects in China.At present,the factors influencing the evolution of MSR behavior in have not been identified effectively and the evolution law has not been analyzed exactly.In order to guide all participants to perform social responsibility in an orderly and coordinated manner and promote the positive evolution of social responsibility behavior,this paper conducts a research on the process and mechanism of social responsibility behavior evolution of megaproject along the line of concept definition-theoretical model-computational model-case simulation.Firstly,the concept of social responsibility behavior evolution of megaprojects is defined.Secondly,based on the uniqueness of social responsibility behavior of megaproject in China,the evolution theoretical model of social responsibility behavior of megaproject was constructed by combining the complexity theory and organizational behavior theory,and the PLS-SEM method was used to verify the model.Thirdly,a computational model is constructed and implemented according to the theoretical model,which is verified to explore the evolution results of social responsibility behavior in the Shen Zhen–Zhong Shan Bridge project.Finally,the sensitivity analysis of single situation and multiple situations is carried out,and the evolution law of social responsibility behavior in megaprojects is summarized.The research mainly finds that the evolution process of social responsibility behavior in megaproject is as follows: Institutional environment,relationship interaction and values of Top Management Team(TMT)constitute the interaction process,which leads to the MSR behavior change and the emergence of evolution phenomenon.The evolution law of social responsibility behavior of megaproject is as follows: The institutional environment and relationship interaction play a strong role in promoting the evolution of social behavior,while the values of TMT play a weak role in promoting the evolution of social behavior.Even if each participant does not have a high degree of pure altruism values,under the promotion of the institutional environment and the process of relationship interaction,each participant will still be closely integrated into a whole,and the social responsibility behavior will evolve positively.Evolution patterns can be divided into three types: stagnation,gradual change and diffusion.Different patterns emerge according to different combinations of institutional environment,relationship tendency and relationship interaction length in relationship interaction.On this basis,the paper proposes that China's megaprojects should create a moderate institutional environment,strong relationship interaction as well as good values,and gives specific countermeasures.These findings are helpful to identify the key factors that guide the positive evolution of MSR behavior and are of certain significance to the practice of social responsibility management in megaprojects.
Keywords/Search Tags:Megaproject Social Responsibility, Behavior Evolution, Calculation Experiment, Agent-Based Modeling and Simulation
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