Knowledge Assisted Dynamic Pricing for Large-Scale Retailers

Publication Type

Journal Article

Publication Date

6-2000

Abstract

It is very difficult for large-scale retailers to price thousands of items dynamically reflecting all constraints and policies. To solve this problem, we adopt a combined model approach that contingently selects appropriate pricing models and integrates them. The three proposed models are cost-plus, competitor-referenced, and demand-driven models. Since each model can be converted to a set of interval and point constraints, we have developed price point determination rules, which find a price point from the weighted interval and point constraints. A prototype system, Knowledge-Assisted Pricing Assistant (KAPA) is developed with this idea. According to our experiment involving 76 cases with 54 pricing experts, KAPA performed consistently, with human experts, about 89.5% accurate. This approach can be a very effective pricing scheme in the electronic marketing era.

Keywords

Retail pricing models, Expert systems, Price point determination rules

Discipline

Computer Sciences | Management Information Systems

Research Areas

Information Systems and Management

Publication

Decision Support Systems

Volume

28

Issue

4

First Page

347

Last Page

264

ISSN

0167-9236

Identifier

10.1016/S0167-9236(99)00095-0

Publisher

Elsevier

Additional URL

http://dx.doi.org/10.1016/S0167-9236(99)00095-0

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