Pricing against supply disruption under duopolistic competition

Author(s):  
Xinping Wang ◽  
Shengnan Sun
2021 ◽  
Vol 13 (13) ◽  
pp. 7041
Author(s):  
Jingfu Huang ◽  
Gaoke Wu ◽  
Yiju Wang

Supply disruption is a common phenomenon in business activities. For the case where the supply disruption is predictable, the retailer should make an emergency procurement beforehand to decrease the inventory cost. For the scenario such that the happening time of the supply disruption obeys a certain common probability distribution but the ending time of the supply disruption is deterministic, based on minimizing the inventory cost and under two possible procurement strategies, we establish an emergency procurement optimization model. By considering the model solution in all cases, we establish a closed-form solution to the optimization model and provide an optimal emergency procurement policy to the retailer. Some numerical experiments are made to test the validity of the model and the effect of the involved parameters on the emergency procurement policy.


Author(s):  
A.O. Olasoji ◽  
K. O. Akpeji ◽  
C.T. Gaunt ◽  
D.T.O. Oyedokun ◽  
K.O. Awodele ◽  
...  

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Qiankai Qing ◽  
Wen Shi ◽  
Hai Li ◽  
Yuan Shao

This study investigates the dynamic performance and optimization of a typical discrete production control system under supply disruption and demand uncertainty. Two different types of uncertain demands, disrupted demand with a step change in demand and random demand, are considered. We find that, under demand disruption, the system’s dynamic performance indicators (the peak values of the order rate, production completion rate, and inventory) increase with the duration of supply disruption; however, they increase and decrease sequentially with the supply disruption start time. This change tendency differs from the finding that each kind of peak is independent of the supply disruption start time under no demand disruption. We also find that, under random demand, the dynamic performance indicators (Bullwhip and variance amplification of inventory relative to demand) increase with the disruption duration, but they have a decreasing tendency as demand variance increases. In order to design an adaptive system, we propose a genetic algorithm that minimizes the respective objective function on the system’s dynamic performance indicators via choosing appropriate system parameters. It is shown that the optimal parameter choices relate closely to the supply disruption start time and duration under disrupted demand and to the supply disruption duration under random demand.


2014 ◽  
Vol 236 (2) ◽  
pp. 643-656 ◽  
Author(s):  
Michail Chronopoulos ◽  
Bert De Reyck ◽  
Afzal Siddiqui

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