Nowadays, with more and more WEEE (Waste Electrical and Electronic Equipment) being abandoned, WEEE recycling activities are increasingly popular. In this paper, we build a closed-loop supply chain model and focus on the recycling behaviors of the members in this supply chain, which contains two manufacturers, the retailer and the consumer. In the reverse chain, we set up dual channels and design two recycling methods: sell-back method and trade-in method. We use classical backward induction to run the model. And then we analyze the stability of the system and the impacts of some essential parameters by numerical simulation. The speed of control method and the decision-making method to control chaos, and they both have a good control effect.
Nowadays, with a great number of household electrical appliances being discarded in every corner of the world every day, household electrical appliances recycling is attracting more attention. In this paper, we build a closed-loop supply chain that consists of a manufacturer and a third-party recycler based on the development of “Internet Plus” recovery platform. We thoroughly analyze the model and its evolution by chaos theory, complex dynamics theory, and numerical simulation and introduce the adaptive method to control the chaos of the system. We find that as the manufacturer increases the retail price, the stable area of the market becomes smaller. At the same time, when the manufacturers direct recycle price or the price adjustment range of the products recycled from the third party exceeds a certain threshold, all the recycle prices in the whole market will fluctuate, thus causing market chaos. Among them, as an adjustment decision method, delay strategy reduces the volatility of recycle price and makes it return to a stable state, which is an effective method to control system disorder. In addition, the third-party recycler will change the optimal subsidy model according to the government’s price subsidy level, while the manufacturer always prefers the price subsidy model.
We establish in this paper a new two-stage supply chain with one manufacturer and two retailers which have a fixed market share in the mature and stable market with specific reference to consumer electronics industry. This paper offers insights into how the three forecasting methods affect the bullwhip effect considering the market share under the ARMA(1, 1) demand process and the orderup-to inventory policy. We also discuss the stability of the order with the theory of entropy. In particular, we derive the expressions of bullwhip effect measure under the MMSE, MA, and ES methods and compare them by numerical simulations. Results show that the MA is always better in contrast to the ES for reducing the bullwhip effect in our supply chain model. When moving average coefficient is lower than a certain value, the MMSE method is the best for reducing the bullwhip effect; otherwise, the MA method is the best. Moreover, the larger the market share of the retailer with a long lead time is, the greater the bullwhip effect is, no matter what the forecasting method is.
This article intends to use China State Grid Corp's business performance evaluation system to study the Shandong Electric Power Group Corp's power grid operation efficiency. And through analyzing the operational efficiency of each decision unit by DEA, we analyze the adjustment direction of the input and output on the angle of horizontal, vertical and internal analysis, find the investment shortage, and put forward some improvement measures. From the changes of the input and output efficiency in the last 15 years, the changing trends of the total factor productivities is found, and the successful experience of the high efficiency is obtained with the specific background.
With the purpose of researching the bullwhip effect when there is a callback center in the supply chain system, this paper establishes a new supply chain model with callback structure, which has a material supplier, a manufacture, and two retailers. The manufacture and retailers all employ AR(1) demand processes and use order-up-to inventory policy when they make order decisions. Moving average forecasting method is used to measure the bullwhip effect of each retailer and manufacture. We investigate the impact of lead-times of retailers and manufacture, forecasting precision, callback index, and marketing share on the bullwhip effect of both retailers and manufacture. Then we use the method of numerical simulation to indicate the different parameters in this supply chain. Furthermore, this paper puts forward some suggestions to help the enterprises to control the bullwhip effect in the supply chain with callback structure.
Nowadays, with more and more WEEE (Waste Electrical and Electronic Equipment) being abandoned, WEEE recycling activities are increasingly popular. In this paper, we build a closed-loop supply chain model and focus on the recycling behaviors of the members in this supply chain, which contains two manufacturers, the retailer and the consumer. In the reverse chain, we set up dual channels and design two recycling methods: sell-back method and trade-in method. We use classical backward induction to run the model. And then we analyze the stability of the system and the impacts of some essential parameters by numerical simulation. The speed of the manufacture’s decision adjustment has a significant effect on the stability of the model. When the decision variables of manufacturers go into instability, the profits of both manufacturers and the retailer have a profit loss in multiple cycles on average. The lower production cost of manufacturer 1 will increase the retailer's profit and self-profit, while manufacturer 2's profit will decrease. And the smaller price coefficient of the retailer can bring higher profits but aggravate the chaotic condition, and the stability of the whole system will decrease. In the end, we adopt the parameter control method and the decision-making method to control chaos, and they both have a good control effect.
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