W e study a novel newsvendor-type problem where the information on demand quantity is not exogenously given. The customer needs to make the booking decision based on her estimation on demand, which is affected by the value of shortage penalty cost. The problem is motivated by low-cost airline service practices where passengers need to book baggage allowance for their travel. The baggage overweight price affects the accuracy of passengers' baggage weight estimation and thus their booking quantities. Through stochastic decision models, we analytically characterize the impact of shortage penalty cost on passengers' booking decisions as well as airline's profit. We consider various modeling settings, including a system with multiple passengers and a system where passengers have stochastic inconvenience costs on not-carrying overweight baggage. The results and insights from our study provide guidelines for firms to set their optimal penalty prices.
We study a two-stage resource pooling problem with multiple resources and customers. The central decision-maker decides the capacity level of the resources within a total budget before the realization of uncertain demand. Then, the fulfillment policy is determined by individual service-level requirements. We use a robust satisficing framework to formulate the problem and allow ambiguity in the distribution of demand. Moreover, we introduce a new utility-based probability distance allowing the model to be solved exactly using a column and constraint generation algorithm. We also provide a more efficient solution method for some special cases. Finally, we conduct experiments for a process flexibility problem, which is an example of the resource pooling problem. We show the advantage of our model over some benchmark approaches, and show the impact of the flexibility structure and correlation between demands.
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