Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61385
Title: Dilemma of introducing a green product: Impacts of cost learning and environmental regulation
Contributor(s): Zhu, Xiaoxi (author); Chiong, Raymond  (author)orcid ; Liu, Kai (author); Ren, Minglun (author)
Publication Date: 2021
DOI: 10.1016/j.apm.2020.11.026
Handle Link: https://hdl.handle.net/1959.11/61385
Abstract: 

External factors, such as the increasing environmental awareness among consumers and introduction of environmental regulations by governments, have stimulated manufacturers to produce new green products. Cost factors, on the other hand, encourage the continuation of older generation products and hinder the launch of new green products. To study this dilemma, we consider a single manufacturer with the ability of cost learning from the production of an older generation product, and it intends to launch a new green product. We first derive the optimal pricing and production strategies of the manufacturer based on accumulated cost learning using dynamic programming techniques. Then, we identify the threshold conditions for producing the new green product and the Pareto area that can increase both the profit of the manufacturer and surplus of consumers. For comparison purposes, we also study the impact of external regulations such as environmental taxes on the introduction of a new green product – with results suggesting that the implementation of environmental taxes promotes the accessibility of green products and reduces the Pareto area of profit and consumer surplus. We also find that, under the influence of cost learning, the introduction of new greener products and the implementation of environmental taxes serve to reduce the total environmental damage done by the manufacturer. Results of our models should provide instructive managerial insights for the introduction of new greener products.

Publication Type: Journal Article
Source of Publication: Applied Mathematical Modelling, v.92, p. 829-847
Publisher: Elsevier Inc
Place of Publication: United States of America
ISSN: 1872-8480
0307-904X
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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