Dynamic pricing

About: Dynamic pricing is a research topic. Over the lifetime, 4144 publications have been published within this topic receiving 91390 citations. The topic is also known as: surge pricing & demand pricing.

Dynamic pricing vs. acquiring information on consumers’ heterogeneous sensitivity to product freshness

Abstract: We propose a model of an inventory system in which a perishable product is periodically replenished, and the retailer is unaware of consumer heterogeneity in consumers’ sensitivity to freshness of a perishable product with a fixed shelf life (though it exists). Using an analytical approach, we optimally solve the problem and evaluate the extent to which unawareness is likely to detract from a retailer’s profit and the extent to which it is likely to affect the price that consumers pay. In addition, we evaluate the conditions in which a dynamic pricing policy is beneficial either to the retailer or to the consumer, as compared with a static pricing policy. It is proven that the retailer should assign products a lower price at the early stages of their shelf life and then raise the price as the products approach expiration. A numerical illustration combined with sensitivity analysis demonstrates the applicability of the modelling approach. Key parameters such as volatility of consumer sensitivity to freshne...

Counteracting Strategic Consumer Behavior in Dynamic Pricing Systems

Abstract: Dynamic pricing and revenue management practices are gaining increasing popularity in the retail industry, and have engendered a large body of academic research in recent decades. When applying dynamic pricing systems, retailers must account for the fact that, often, strategic customers may time their purchases in anticipation of future discounts. Such strategic consumer behavior might lead to severe consequences on the retailers’ revenues and profitability. Researchers have explored several approaches for mitigating the adverse impact of this phenomenon, such as rationing capacity, making price and capacity commitments, using internal price-matching policies, and limiting inventory information. In this chapter, we present and discuss some relevant theoretical contributions in the management science literature that help us understand the potential value of the above mitigating strategies.

easyJet® pricing strategy: Should low-fare airlines offer last-minute deals?

Abstract: easyJet, one of Europe’s most successful low-cost short-haul airlines, has a simple pricing structure. For a given flight, all prices are quoted one-way, a single price prevails at any point, and, in general, prices are low early on and increase as the departure date approaches. We observe from these policies and from the empirical section of this paper that easyJet employs three distinct strategies: 1) it does not offer last-minute deals, 2) it offers a single class and lets price be the sole variable that controls demand, and 3) it varies the time at which tickets are first offered for sale (duration of sale). The first two policies are in stark contrast to traditional airline pricing strategies. Many airlines offer last-minute deals, either directly or via resellers. Second, the current prevailing practice is to control demand via seat allocation to various classes rather than by offering a single class and letting price be the sole variable that controls demand. The main objective of this research is to study the conditions under which offering a last-minute deal is optimal under the single-price policy. We also learn how the duration of ticket sales is affected by consumer characteristics. We find that, for an intermediate capacity level, uncertainty with respect to the arrival of the business segment will cause the firm to offer last-minute deals and thus partially price-discriminate within the tourist segment. The same is true for uncertainty with respect to the actual behavior of the firm: if consumers are uncertain whether the firm will offer last-minute deals, then, in equilibrium, both in a one-shot game and in a repeated game, the firm will, with some probability, offer such deals. In addition, we found that for an intermediate capacity level, the larger the number of segments (that differ in price sensitivity), the longer the duration of the period in which tickets are offered for sale.

Dynamic Pricing, Production, and Channel Coordination with Stochastic Learning

Abstract: We consider a decentralized two-period supply chain in which a manufacturer produces a product with benefits of cost learning, and sells it through a retailer facing a price-dependent demand. The manufacturer's second-period production cost declines linearly in the first-period production, but with a random learning rate. The manufacturer may or may not have the inventory carryover option. We formulate the resulting problems as two-period Stackelberg games and obtain their feedback equilibrium solutions explicitly. We then examine the impact of mean learning rate and learning rate variability on the pricing strategies of the channel members, on the manufacturer's production decisions, and on the retailer's procurement decisions. We show that as the mean learning rate or the learning rate variability increases, the traditional double marginalization problem becomes more severe, leading to greater efficiency loss in the channel. We obtain revenue sharing contracts that can coordinate the dynamic supply chain. In particular, when the manufacturer may hold inventory, we identify two major drivers for inventory carryover: market growth and learning rate variability. Finally, we demonstrate the robustness of our results by examining a model in which cost learning takes place continuously

Pricing Promotional Products Under Upselling

Abstract: Upselling is offering an additional product to a customer who just made a purchase. Most catalogers and online sellers, in addition to some traditional retailers, use upselling often to clear inventories of slow-moving items. We investigate the pricing and discounting questions for such an item, which we call the promotional product. In our model, an arriving customer may purchase this promotional product or one of the other products that the firm sells. If the customer purchases one of the other products, the promotional product is offered to the customer, possibly with a discount. While deciding whether to offer a discount and, if so, how big a discount to offer, the firm uses the information that the customer has just bought a certain product with a certain price. We investigate how discounting decisions depend on the inventory levels, time, type of pricing policy in use, and the relationship between the customers' reservation prices for the promotional product and the other products (negatively or positively correlated). In particular, we find that if the firm sets prices and discounts dynamically and the customers' reservation prices for the promotional product are negatively correlated with their reservation prices for the product they purchased, then customers are always offered a discount regardless of the inventory levels and time. On the other hand, if the customers' reservation prices for the promotional product are positively correlated with their reservation prices for the product they purchased, then the customer may or may not be offered a discount, depending on the inventory levels and time. Our numerical study shows that the benefit to the firm from using customer purchase information is high when the firm uses a static price, but chooses discounts dynamically. We also find that although dynamic discounting decisions bring modest improvements, setting the price dynamically seems to have a more significant effect on the firm's profits.