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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) ; 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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