Operational Optimization For Firms Considering Loss Aversion And Consumer Green Premium

The traditional researches on Operations Management (OM) usually help firms to make optimal decisions according to the classical rational decision theory.However, as time goes on and the development of knowledge, the researchers start to realize that some decision-making behaviors in real life are often inconsistent with the expected results of traditional theory. Hence, there are some limitations when assuming the "rational economic man" in real decisions. Because of the bounded rationality and the different behavior preferences in different circumstances, it is very important to take human behavior factors into account when studying the operations management. Though, there have been some topics in the field of operations management began to focus on behavioral factors, and made some achievements,there still are a lot of interesting and valuable issues worth to discuss. Therefore, in this context, our thesis focuses on two typical behavior factors, i.e., the loss aversion behavior preference and green premium behavior preference, and then analyze their effects on firms' decision-making.The main research contents and results of this thesis are:(1) From the perspective of loss aversion, in chapter 3, we consider a one-period two-echelon supply chain composed of a loss-averse supplier with yield randomness and a loss-averse retailer with demand uncertainty. At the beginning of the selling season, the retailer orders from the supplier via the wholesale price contract, and then the supplier makes his production decision.We derive the loss-averse retailer's optimal order policy and the loss-averse supplier's optimal production policy with a simple wholesale price contract. Our results indicate when, how, and why loss aversion occurs can cause decision bias in a supply chain. More specifically, we find that the loss-averse retailer will order more than, equal to, or less than the risk-neutral retailer, and the loss-averse supplier will produce more than, equal to, or less than the risk-neutral supplier. We find that the loss-averse retailer's optimal order quantity may increases in wholesale price and decrease in retail price which can never occur in the risk-neutral newsvendor model.Finally, we lend insights into how loss aversion and random yield risk contribute to supply chain inefficiency by numerical analysis.(2) From the perspective of green premium, in chapter 4, we build a consumer's utility model when a remanufacturer selling both new and remanufactured product.For demand, we try to structure the purchase behavior of both ordinary and green consumers on remanufactured and new product respectively. For supply, we analyze the manufacturer's optimal pricing strategy about the economic and the environmental consequences. For environmental policy, we evaluate the impacts of' the cap-and-trade mechanism and provide an effective interval of the carbon price.(3) From the perspective of green premium, in chapter 5, we discuss the difference between two carbon reduction way (End-of-Pipe and Clean Technology),and analyze the influences of green premium in cap and trade mechanism.The results are: for decision-making, compared with the End-of-Pipe Technology,the manufacturer must make one more decision about how many products for process reduction treatment when choose the Clean Technology. For profit, the benefit of End-of-Pipe Technology is only from the cost difference, while the Clean Technology is from both cost and output difference. When there are green premiums, the manufacturer who choose Clean Technology need to be careful. Only a foresighted manufacturer can make wise optimal decision and achieve maximum profit.The main innovative points of this thesis can be illustrated in three aspects:(1) The innovation from topic selection. We focus on the people's psychology and behavior influence when do OM researches, which can enrich the research situation and provide practical experience.(2) The innovation from model establishment. In chapter 3, we build a complex but more realistic model. In chapter 4, we construct a comprehensive model considering the behaviors from consumer, remanufacturer and government. In chapter 5, we build a comparison model analyzing two carbon reduction ways.(3) The innovation from research results. First, some decisions of loss aversion are surprisedly different from the risk-neutral case. Second, we provide the environmental policy from a new perspective about unifying the economic and environment goals. Finally, the manufacturer who choose Clean Technology must be far-sighted.