Optimal Choice of Enterprise’s Production Strategy under Constraints of Carbon Quota
Open accessAbstract
After analyzing the enterprise's production strategy under the constraints of carbon quota, this paper proposes new mathematical models aiming for the optimal choice of enterprise's production strategy under the monopoly and competitive environments respectively.Combining the neural network optimization theory, then the methods of Nonlinear Programming and Nash Equilibrium in Static Games are used to solve the models to obtain the enterprise's equilibrium quantity, the optimal carbon emission, and the profit of unit product in the low carbon technology.The study found that: under a monopoly environment, enterprises choose technology innovation strategy; under a competitive environment, enterprises use carbon trading strategies whenever carbon trading prices are low or high; however, there is no pure strategy Nash equilibrium when carbon trading prices are in the middle, in this case enterprises prefer to use the production strategies different from the competitor.
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Self-organizing maps have been used to analyze how R&D investment in green technologies changes in response to fuel prices, while a game theoretical framework using neural networks has been used to study optimal production strategies for companies under carbon quotas.
“For example, self-organizing maps have been used to analyze how R&D investment in green technologies changes in response to fuel prices [55], while a game theoretical framework using neural networks has been used to study the optimal production strategies for companies under carbon quotas [884].”
From Tackling climate change with machine learning (2023) · cites this paper as [884]
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Cited by
Sorted by citations
Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works
- Authors
- Zheng, X., Guo, Q., Li, Z., & Zhang, T.
- Affiliations
- Chengdu University of Technology (CN)
- Southwest Jiaotong University (CN)
- ORCID
- Zhang, Ting
- Venue
- International Journal of Computational Intelligence Systems
- Published
- 2018
- Volume
- 11
- Issue
- 1
- Pages
- 1268
- ISSN
- 1875-6883 (ISSN-L)
- OpenAlex
- W2897311777
- Cited by
- 5
- References
- 26
- Citations by year
- 2024: 1 · 2023: 2 · 2022: 2
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- International Journal of Computational Intelligence Systems (publishedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
- Social Sciences › Business, Management and Accounting › Marketing › Environmental Sustainability in Business
- Social Sciences › Business, Management and Accounting › Strategy and Management › Sustainable Supply Chain Management
- Keywords
- carbon quotas, CO2 emissions, manufacturing strategy, emissions trading, monopoly, competitive markets, Nash equilibrium, low-carbon technologies, technological innovation, neural network optimization, nonlinear programming, carbon trading price, equilibrium quantity
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