An evolutionary game theory analysis linking manufacturing, logistics, and the government in low-carbon development

Haojun Wang, Lianghua Chen and Jun Liu

Journal of the Operational Research Society, 2022, vol. 73, issue 5, 1014-1032

Abstract: Cooperating in low-carbon linkage development is an inevitable choice for manufacturing and logistics enterprises in emerging economies and government plays an important role in the cooperation. This paper constructs a three-party evolutionary game theory model to study the behavior of the government, manufacturing, and logistics enterprises in such cooperation. Based on the game income matrix of strategy combinations, replicated dynamic equations are established and used to investigate the equilibrium state of the game; the local stability of the equilibrium state in various scenarios is analyzed using Jacobian matrix and stability theory, 3 D spatial replicated phase diagrams are used to show the strategy choice trends of participants. This paper also summarises the rules of game behavior under different income parameters. We found that additional developmental cost in low-carbon linkage is a key factors that directly affects the game results, and government plays an important role in the development: in the early stage of development when the investment is high, the government can promote cooperation by regulations or financial incentives. The findings are corroborated in numerical simulations. This paper enriches the literature on factors that affect decision-making in low-carbon linkage development, and provides useful insights to improve government intervention to promote a low-carbon economy.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/01605682.2021.1880294 (text/html)
Access to full text is restricted to subscribers.

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:taf:tjorxx:v:73:y:2022:i:5:p:1014-1032

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjor20

DOI: 10.1080/01605682.2021.1880294

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald

More articles in Journal of the Operational Research Society from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().