EconPapers    
Economics at your fingertips  
 

How to achieve carbon abatement in aviation with hybrid mechanism? A stochastic evolutionary game model

Peiwen Zhang and Rui Ding

Energy, 2023, vol. 285, issue C

Abstract: Aviation carbon emissions are growing as the volume of aviation traffic continues to increase, both exacerbating global greenhouse gas emissions and increasing the resistance to green aviation development. To effectively promote aviation carbon abatement, this paper, based on the hybrid mechanism composed of carbon trading and taxation, a tripartite Itô stochastic evolutionary game model is first constructed. The complex game interactions among the administration, major airlines, and minor airlines are analyzed. Second, we use Gaussian white noise as the ambient uncertainty and apply stochastic Taylor expansion to find the numerical approximation solution. Finally, through numerical simulations, the decision-making behavior of stakeholders and their sensitivity to key influencing factors are illustrated. The study shows that different variables have differential effects on stakeholders’ strategic choices in terms of convergence speed, change speed, and stability. Starting from three different regulatory paths, this study provides insights into the priority and direction of adjusting relevant variables, thereby offering guidance for policymakers and managers in effectively regulating aviation carbon abatement.

Keywords: Aviation carbon emissions; Hybrid mechanism; Stochastic evolutionary game; Carbon emission reduction (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544223027433
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:285:y:2023:i:c:s0360544223027433

DOI: 10.1016/j.energy.2023.129349

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:energy:v:285:y:2023:i:c:s0360544223027433