2217. Dynamic nonlinear pricing in the presence of multiunit demand and two-dimensional customer heterogeneity
Invited abstract in session TC-11: Theory & Methods, stream Pricing and Revenue Management.
Thursday, 11:45-13:15Room: U2-200
Authors (first author is the speaker)
| 1. | Rouven Schur
|
| University of Duisburg-Essen |
Abstract
In many industries, such as retail, firms often face customers who buy multiple units at once and have traditionally relied on nonlinear pricing to influence purchase quantities. While this approach can be effective, it does not offer the flexibility of dynamic pricing – an increasingly important strategy due to advances in technology. Conversely, ignoring multiunit demand in a dynamic pricing context can lead to suboptimal prices and missed revenue opportunities. To address this, we present a multiunit dynamic pricing framework that integrates the strengths of nonlinear and dynamic pricing, allowing firms to quote distinct prices for different batch sizes over time.
Our approach to customer choice diverges from traditional models by accounting for two-dimensional customer heterogeneity – product attraction and consumption – both private information. These characteristics are modeled via separate random variables in the willingness-to-pay formulation, resulting in more complex purchase probability expressions than in conventional one-dimensional settings. We formulate a state-wise optimization problem from a monopolistic firm’s perspective, exploring scenarios in which the firm observes neither, one, or both characteristics at customer arrival. For each, we derive optimality conditions and, in certain cases, present closed-form solutions.
When no customer-specific information is observable, the model’s complexity can be mitigated by a refined formulation that serves as an upper bound and, under specific conditions, is optimal for the original problem. We also develop a heuristic that yields near-optimal solutions while substantially reducing computational requirements.
Keywords
- Revenue Management and Pricing
Status: accepted
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