Newsvendor’s optimal decisions under stochastic demand and cap-and-trade regulation

Author(s):  
Shaojian Qu ◽  
Guoqing Jiang ◽  
Ying Ji ◽  
Guangming Zhang ◽  
Nabe Mohamed
Author(s):  
Hongxia Sun ◽  
Jie Yang ◽  
Yang Zhong

With the increasingly serious problem of environmental pollution, reducing carbon emissions has become an urgent task for all countries. The cap-and-trade (C&T) policy has gained international recognition and has been adopted by several countries. In this paper, considering the uncertainty of market demand, we discuss the carbon emission reduction and price policies of two risk-averse competitive manufacturers under the C&T policy. The two manufacturers have two competitive behaviors: simultaneous decision making and sequential decision making. Two models were constructed for these behaviors. The optimal decisions, carbon emission reduction rate, and price were obtained from these two models. Furthermore, in this paper the effects of some key parameters on the optimal decision are discussed, and some managerial insights are obtained. The results show that the lower the manufacturers’ risk aversion level is, the higher their carbon emission reduction rate and utilities. As the carbon quota increases, the manufacturers’ optimal carbon reduction rate and utilities increase. Considering consumers’ environmental awareness, it is more beneficial for the government to reduce the carbon quota and motivate manufacturers’ internal enthusiasm for emission reduction. The government can, through macro control of the market, make carbon trading prices increase appropriately and encourage manufacturers to reduce carbon emissions.


2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Bin Chen ◽  
Man Yu

In an uncertainty market, social learning plays a significant role in obtaining information to make better decisions. Under cap-and-trade regulation, this paper aims to investigate firms’ pricing and carbon emission abatement issues considering the impact of social learning. This paper establishes a two-period model in a market consisting of a manufacturer and heterogeneous consumers. The manufacturer produces two alternatives (ordinary product and low-carbon product) and makes decisions on sales prices and carbon emission abatement levels. Consumers make decisions on whether and which product to buy. Consumers are not sure about their valuations of products and have the opportunity to discover their true valuation by social learning. The results show that the emission abatement level on ordinary product is affected by the pricing strategy for both types of products. However, the emission abatement level on low-carbon product is only affected by its own pricing strategy. It also shows that social learning lowers the emission abatement level on ordinary product, whereas it improves the emission abatement level on low-carbon product when charging a high price for low-carbon product. Moreover, the price of ordinary product in period 1 is no less than that in period 2. In contrast, the price of low-carbon product in period 2 is higher than that in period 1.


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