4.7 Article

Collaboration in a low-carbon supply chain with reference emission and cost learning effects: Cost sharing versus revenue sharing strategies

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 250, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.119460

Keywords

Low-carbon supply chain; Reference emissions; Cost learning; Carbon tax; Pricing; Differential game

Funding

  1. Fujian Federation of Humanities and Social Sciences Research Program, China [FJ2019B108]
  2. Humanities and Social Sciences Research Programs of Ministry of Education, China [17YJC630097]

Ask authors/readers for more resources

The growing environmental awareness of consumers and the regulation of governments drive supply chain members to collaborate in emission reduction. Considering reference emission and cost learning effects, this study investigates a Stackelberg differential game, where a manufacturer acts as a leader and determines the wholesale price and emission reduction level and a retailer acts as a follower and sets the retail price. Equilibrium emission reduction and pricing strategies in cost- and revenue-sharing contracts are deduced from modelling these two collaboration modes. Results demonstrate that the manufacturer and the entire supply chain prefer the revenue-sharing contract rather than the cost-sharing one, whereas the retailer prefers only the wholesale price contract. High ratios in revenue-sharing contract lead to low emission levels and prices and hence benefit consumers. The environmental awareness of consumers and tax rates considerably affect the emission reduction, but learning effect does not. However, the high learning ability of the manufacturer can improve the performance of supply chain members. (C) 2019 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available