Optimal decisions in a dual-channel competitive green supply chain management under promotional effort

Brojeswar Pal, Amit Sarkar, Biswajit Sarkar

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

The awareness of the environment has been extensively studied in the past decade. In this study, the production of eco-friendly and comparatively less harmful green innovative products is considered under an uncertain environment to reduce their detrimental effect on the environment under green supply chain management. Owing to the complexity of green innovation, the various pricing decisions of the players, green innovation level, and promotional effort under the centralized, manufacturer Stackelberg, and vertical Nash policies are studied. The relations among the parameters are analytically investigated such that the profits are optimized for various cases. The optimal level of green innovation, promotional effort, prices, and profits are achieved by varying the market potential and price parameters. It is also observed that the cost coefficients of green innovation and promotional effort have the highest effect on the optimal level. Green innovation is very effective in improving the players’ profit margin, and the manufacturer must decide the extent of green innovation to optimize the profits. The optimal level of the promotional effort for the various cases is determined such that the players can gain the most. It is found from the study that a dual-channel supply chain is more efficient than a single-channel supply chain for green products.

Original languageEnglish
Article number118315
JournalExpert Systems with Applications
Volume211
DOIs
Publication statusPublished - 2023 Jan

Bibliographical note

Funding Information:
The authors would like to express their gratitude to the editors and referees for their valuable suggestions and corrections to enhance the clarity of the present article. The second author also acknowledges the Council of Scientific & Industrial Research, Government of India for financial assistance. The work is supported by the National Research Foundation of Korea (NRF) grant, funded by the Korea Government (MSIT) ( NRF-2020R1F1A1064460 ).

Publisher Copyright:
© 2022

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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