A Dynamic Analysis of Pricing and Investment in Circular Economy with Learning-By-doing
Ru Zhang
Issues in Economics and Business, 2025, vol. 11, issue 1, 1
Abstract:
In this paper, we explore the optimal control problem of a monopolist's pricing and recycling investment strategies under learning-by-doing within a circular economy. The model incorporates both virgin and recycled resources in production, and accounts for the accumulation of knowledge through recycling activities. We show that- (i) the monopolist's recycling investment and pricing strategies evolve over time as a result of learning-by-doing, leading to operational efficiency gains; (ii) the monopolist's private incentives for recycling are lower than the social optimum, resulting in an underinvestment problem; (iii) the gap between private and social incentives highlights the need for regulatory interventions to promote sustainable recycling practices. Our analysis identifies the existence of a steady-state equilibrium and examines how knowledge accumulation dynamically influences the firm's cost structure and pricing strategies. The findings offer valuable insights into the long-term interactions between pricing, recycling investments, and sustainability objectives in a monopolistic market, with broader implications for the promotion of a circular economy.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.macrothink.org/journal/index.php/ieb/article/download/22501/17317 (application/pdf)
https://www.macrothink.org/journal/index.php/ieb/article/view/22501 (text/html)
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:mth:ieb888:v:11:y:2025:i:1:p:1
Access Statistics for this article
Issues in Economics and Business is currently edited by Derrick Harden
More articles in Issues in Economics and Business from Macrothink Institute
Bibliographic data for series maintained by Technical Support Office ( this e-mail address is bad, please contact ).