Markdown policies for optimizing revenue, towards optimal pricing in retail
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Due to inadequate initial allocation of supply, retail organizations are usually confronted with markdowns during a sales season. In this article the apparent paradox between the traditional Law of Demand and retailing pricing is solved. Through the use of Survival Analysis, as is commonly used in Biomedical Research, a framework is developed for determining optimal price paths in a retail context. When thought of in analogy to birth and death processes, sell through curves can be seen as life cycles of retail goods and can be applied in Revenue Optimization. We show that two significant events in calendar time exist: the moment a probable markdown occurs and the instance the underlying good is sold. Next, we apply convolution to define the markdown point in calendar time and estimate the price elasticity with an exhaustive search yielding the markdown moment that optimizes revenue
Article History
How to Cite
Meijer, R., Pieffers, M., & Bhulai, S.. (2014). Markdown policies for optimizing revenue, towards optimal pricing in retail. Journal of Business and Retail Management Research, Volume 08 Issue 1.
Citation Context
APA
Meijer, R., Pieffers, M., & Bhulai, S.. (2014). Markdown policies for optimizing revenue, towards optimal pricing in retail. Journal of Business and Retail Management Research, Volume 08 Issue 1.
MLA
Meijer, Rudi, et al.. "Markdown policies for optimizing revenue, towards optimal pricing in retail." Journal of Business and Retail Management Research, Volume 08 Issue 1, 2014.
Chicago
Rudi Meijer, Michael Pieffers, and Sandjai Bhulai. "Markdown policies for optimizing revenue, towards optimal pricing in retail." Journal of Business and Retail Management Research Volume 08 Issue 1 (02 Jun 2014).
Harvard
Meijer, R., Pieffers, M., & Bhulai, S. (2014) Markdown policies for optimizing revenue, towards optimal pricing in retail. Journal of Business and Retail Management Research, Volume 08 Issue 1
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