Pricing and carbon reduction decisions for a new uncertain dual-channel supply chain under cap-and-trade regulation

Naiqi Liu, Wansheng Tang (), Yanfei Lan and Huili Pei ()
Additional contact information
Naiqi Liu: Tianjin University
Wansheng Tang: Tianjin University
Yanfei Lan: Tianjin University
Huili Pei: Hebei University

Fuzzy Optimization and Decision Making, 2024, vol. 23, issue 3, No 5, 415-448

Abstract: Abstract This study concentrates on the pricing issue in a low-carbon dual-channel (DC) supply chain, where the upper-level manufacturer is regulated by the cap-and-trade (CAT) mechanisms. Market demand is a key factor affecting pricing decision and demand uncertainty complicates the pricing problem. To deal with the challenge that only partial demand distribution information is available, this paper proposes a novel ambiguity distribution set to depict the uncertain demand. Under the proposed ambiguity distribution set, a robust fuzzy bi-level optimization pricing model is developed for the low-carbon DC supply chain. Three CAT regulation mechanisms, no CAT regulation, grandfathering (GF) mechanism and benchmarking (BM) mechanism, are considered to address the manufacturer’s CAT regulation. The analytically tractable counterpart of the proposed model is derived and the corresponding robust equilibrium solutions are obtained under three CAT mechanisms. Numerical analyses are carried out to explore the impact of the demand uncertainty on the manufacturer’s selection of the CAT regulation mechanism. The numerical results indicate that the uncertainty degree can change the manufacturer’s selection of the regulated mechanisms. Specifically, when the uncertainty degree is smaller, the BM mechanism is beneficial for the manufacturer comparing with the GF mechanism; when the uncertainty degree is bigger, the manufacturer prefers to GF mechanism rather than BM mechanism.

Keywords: Pricing decision making; Dual-channel supply chain; Cap-and-trade; Ambiguity set; Robust fuzzy optimization (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10700-024-09427-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:fuzodm:v:23:y:2024:i:3:d:10.1007_s10700-024-09427-9

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10700

DOI: 10.1007/s10700-024-09427-9

Access Statistics for this article

Fuzzy Optimization and Decision Making is currently edited by Shu-Cherng Fang and Boading Liu

More articles in Fuzzy Optimization and Decision Making from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().