Optimal decisions on price and inventory for a newsboy-type retailer with identifiable information and discount promotion.

Consider a retailer selling a seasonal item, new items are stocked at the beginning of sale season and no inventory replenishment is permitted. Assuming the initial price is exogenous and the information about demand becomes more accurate as the sales season progresses, the retailer is allowed to make an in-season price adjustment after conducting a review. After the review time, if the price is adjusted to be lower than the initial price, demand increases more quickly with price decreasing which reflects the promotional effect of discount. Given the initial inventory, an optimal price adjusting model is proposed to maximize the retailer's revenue. Taking decisions on inventory into account, the proposed model is extended to maximize the retailer's profit rather than revenue. Numerical examples are also illustrated to test the proposed model. The results show that the optimal in-season price mainly depends on the proportion of the remaining demand, the price sensitivity, and the effect of sales promotion. An important managerial implication is that the retailer should gather the demand information about the price and raise the in-season price as soon as possible to gain more revenue when the price elasticity is small enough. Otherwise, when the price elasticity is larger, the retailer should maintain or decrease the price to gain more revenue.

Competitive analysis of online revenue management with two hierarchical resources and multiple fare classes.

Resource allocation problem is one of key issues in the field of revenue management. The traditional models usually rely on some restrictive assumptions about demand information or arrival process, which is sometimes out of line with reality. To overcome this shortcoming, the method of competitive analysis of online algorithms, which eliminates the need for the assumptions on demand and arrivals, is adopted to deal with the quantity-based revenue management problem. The current model in this paper considers two downgrade compatible levels of resources. Given the capacities and fares of both levels of resources, the objective is to accept appropriate customers and assign them to appropriate resources so as to maximize revenues. Compared with the existing literature, this paper generalizes the concerned resource allocation problem by considering multiple fares for each level of resources. From the perspective of online algorithms and competitive analysis, both an upper bound and an optimal online strategy are derived in this paper.

A pricing model for group buying based on network effects.

Group buying (GB) is a popular business model in e-commerce. With the rise of online social media, the positive network effect of buying with others is more important than price discount for consumers to choose GB. However, the negative network effect of GB is also significant for some consumers. In this paper, we classify consumers into two segments considering both positive and negative network effects, and three possible sales strategies as well as their optimal decisions on price are presented. We find that GB strategy dominates individual buying (IB) strategy when the positive network effect is sufficiently high or the proportion of consumers with low valuation is relatively large. We also find that MIX strategy offering both IB and GB is always better than IB, while the relationship between MIX and GB is depending on actual market situations. Some other managerial insights are also discussed.