Volume 57, Number 4, July-August 2023
|2025 - 2043
|01 August 2023
A comparative study on a firm’s optimal production decision considering risk aversion and carbon policies
School of Logistics, Beijing Wuzi University, Beijing 101149, P.R. China
2 School of Management, Qufu Normal University, Rizhao, Shandong 276826, P.R. China
3 School of Economics and Management, Beihang University, Beijing 100191, P.R. China
* Corresponding author: firstname.lastname@example.org
Accepted: 23 April 2023
To cope with global warming and achieve the goal of carbon emission reduction, various carbon policies have been implemented in many countries and regions. Some studies have indicated that with the popularity of low carbon, a small proportion of consumers show a green purchasing tendency. However, for firms, it is still difficult to predict the green purchase preferences of most consumers, and firms may face greater market demand uncertainty, which will bring profit risks. We assume that a firm’s decision is subject to its behavioral considerations, that is, its risk attitude. Considering the risk preferences of decision-makers and carbon emission policies, this paper addresses decision optimization in operations management. Our purpose is to analyze the optimal production decisions of risk-averse firms under carbon cap and carbon tax policies. Adopting the CVaR (conditional value-at-risk) criterion, we construct an optimization model with the constraints of carbon policies and obtain the analytic formula of optimal solutions. Then, we compare the optimal operational decisions for risk-averse firms and risk-neutral firms and further explore the impact of risk aversion on production and the parameters of carbon policy. Finally, some numerical studies are presented to analyze the carbon policies and risk aversion on firms’ operational decisions and give some managerial insights based on the analysis results.
Mathematics Subject Classification: 91A80
Key words: Risk aversion / Conditional value-at-risk / Carbon capacity / Carbon tax / Production decision
© The authors. Published by EDP Sciences, ROADEF, SMAI 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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