The classical risk-neutral newsvendor problem is to decide the order quantity that maximizes the one-period expected profit. In this note, we consider a risk-averse newsvendor with stochastic price-dependent demand. We adopt Conditional Value-at-Risk (CVaR), a risk measure commonly used in finance, as the decision criterion. The aim of our study is to investigate the optimal pricing and ordering decisions in such a setting. For both additive and multiplicative demand models, we provide sufficient conditions for the uniqueness and existence of the optimal policy. Comparative statics show the monotonicity properties and other characteristics of the optimal pricing and ordering decisions. We also compare our results with those of the newsvendor with a risk-neutral attitude and a general utility function.

We consider a manufacturer-retailer supply chain for a seasonal product whose demand is weather sensitive. The retailer orders from the manufacturer (supplier) prior to the selling season and then sells to the market. We examine how a manufacturer can structure a weather-linked rebate to improve his expected profit. The proposed class of rebate contracts offers several advantages over many other contract structures, including no required verification of leftover inventory and/or markdown amounts, and no adverse effect on sales effort by the retailer. We provide a thorough analysis of the manufacturer's and retailer's decisions in this context. We show that the weather-linked rebate can take many different forms, and this flexibility allows the supplier to design contracts that are Pareto improving and/or limit his risk in offering the contract and the retailer's risk in accepting it. For weather rebates with certain characteristics, the manufacturer can fully hedge his risks of offering a weather rebate by paying a risk premium; we show how this can be accomplished. We also show that the basic structural results extend to settings in which the two parties would like to limit their risk.