Sustainable production strategies of loss-averse competitive manufacturers with reference dependence under cap-and-trade policy

被引:0
|
作者
Zhang, Yu [1 ]
Yi, Yuyin [1 ]
机构
[1] School of Management, Jinan University, Guangdong, Guangzhou
关键词
Cap-and-trade; Competition; Emission reduction investment; Loss aversion; Reference dependence; Stockout conversion;
D O I
10.1016/j.tre.2024.103809
中图分类号
学科分类号
摘要
This study examines the joint optimization decisions on production quantity and sustainable investment of two competing low-carbon manufacturers with loss aversion and reference dependence under the cap-and-trade policy. We focus on exploring the impacts of manufacturers’ risk attitude, encompassing factors like the degree of loss aversion and reference dependence, the cap-and-trade policy, and heterogeneous characteristics on optimal decisions and their expected utilities. The main findings are as follows. First, loss aversion and reference dependence have completely opposite effects on manufacturers’ production and emission reduction decisions. Specifically, production quantity will become more conservative. Interestingly, the investment to reduce emissions may actually become more aggressive. In addition, setting a lower reference level presents an opportunity for firms to generate greater profits compared to the risk-neutral scenario. Second, affected by loss aversion and reference dependence, manufacturers’ sustainable investment may decrease with carbon trading price, which is different from the conclusion of the existing research. Third, the total expected utility of heterogeneous manufacturers decreases with the difference of loss aversion and reference dependence. Finally, we extend our analysis to the impacts of sustainable investment, initial carbon emissions associated with emission reduction and heterogeneous market prices. This paper enriches the research on carbon emission reduction and loss aversion with reference dependence, and provides some managerial insights for practice from the perspective of government and enterprise operation. © 2024 Elsevier Ltd
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