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Research On The Green Service Behavior Of Logistics Enterprises Under The Government Environmental Regulation

Posted on:2021-05-28Degree:MasterType:Thesis
Country:ChinaCandidate:J W ZhengFull Text:PDF
GTID:2491306119473024Subject:Regional management and public policy
Abstract/Summary:PDF Full Text Request
With the arrival of the era of green economy,the logistics industry,as a major energy consumer,has become one of the main objectives of pollution control in China.Facing the increasing government environmental regulation,the transformation of green service of logistics enterprises,the most important executive body of logistics industry,is urgent.However,there are still many difficulties and obstacles in the current green service transformation of logistics enterprises.Some logistics enterprises are actively practicing green services,while some logistics enterprises are still lack of motivation and negative attitude.So,how to solve these problems? What are the reasons for the obstacles of green service transformation of logistics enterprises? How to stimulate logistics enterprises to choose green service transformation spontaneously? Aiming at the problems existing in the current green transformation of logistics enterprises,this paper combines the prospect theory with the game theory and uses the system dynamics to study the behavior evolution of government departments,logistics enterprises and employees.This paper mainly includes the following research contents:(1)Based on the behavioral economics theory,this paper analyzes analyzes the main forms of obstacles in green service behavior of logistics enterprises,and points out that the imbalance of rational and intuitive thinking system between enterprise decision-makers and enterprise employees is the root cause of the obstacles,and the reasonable government control measures can quickly adjust their thinking mode and accelerate the implementation of the green service behavior of the logistics enterprises;This shows that in the study of implementing green service behavior of logistics enterprises,in addition to the impact of government regulation,the impact of enterprise employees on it can not be ignored.(2)Combining the prospect theory with the game theory,this paper constructs a tripartite game model of government department,logistics enterprise and enterprise employees,and analyzes the model from four aspects: unilateral strategy choice of government department,unilateral strategy choice of logistics enterprise,unilateral strategy choice of logistics enterprise employees and mixed strategy choice of three parties.(3)The evolution process is simulated by using the system dynamics model,and it is found through parameter regulation that:(1)The level of cost is one of the important factors that affect the choice of game players’ strategies;(2)The different perceived value of punishment and reward to logistics enterprises and employees will affect their strategic choice;(3)One of the subjective factors that affect the players is the cognitive level of their ability to avoid supervision;(4)The degree of loss aversion and the degree of risk preference of the players are the subjective factors that affect the players。(4)Finally,according to the results of the study,some policy suggestions are put forward:(1)Priority should be given to reducing the expenditure cost of the players;(2)In the process of government control over enterprises and enterprise control over employees,a variety of control measures should be implemented at the same time,and a combination of rewards and punishments should be adopted;(3)The anchoring effect can be used to guide the players to have a reasonable understanding of their ability to avoid supervision;(4)Introduce external opinions,increase the confidence of enterprises and employees in the transformation of green services,and reduce the degree of avoidance of transformation risks by enterprises and employees.
Keywords/Search Tags:Environmental Regulation, Logistics Enterprises, Green Service Behavior, Tripartite Evolutionary Game, System Dynamics
PDF Full Text Request
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