Markdown optimization for an apparel retailer under cross-price and initial inventory effects

A markdown optimization problem is considered faced by a retailing industry.Products have substitution and complementary effects among each other.We determine simultaneously optimal pricing and initial inventory levels.We use ADP to find optimal markdown policies approximately.When cross-price and initial inventory are considered, revenues increase. Apparel Retailers have been using markdowns as a means of revenue maximization with an increased frequency. Parallel to this increase, several authors have studied single product markdown optimization problem under various settings or assumed that the products are independent in case of multi-products.In this paper, we address the simultaneous determination of markdown prices and optimal initial inventory levels under the cross-price effects in a random demand setting for multi-product groups for an apparel retailer chain in Turkey. First, we formulate the problem as a Markov Decision Process that considers price-based substitution and complementary effects among products and maximizes the expected total profit over a finite horizon. Then, we find the approximate markdown policies of each product by using Approximate Dynamic Programming algorithm. We investigate how cross-price elasticity affects the markdown policies of each product by considering several relationships among them, such as the products are all substitute or all are complement or some are substitute and some are complement. In addition to this, we provide insights on how they affect the expected revenues when non-optimal and optimal initial inventory levels are considered. When cross-price effects are considered in case of non-optimal initial inventory levels, average revenue increases about 32% while it increases to 50% when optimal initial inventory levels are in case.

[1]  Xuanming Su,et al.  Intertemporal Pricing with Strategic Customer Behavior , 2007, Manag. Sci..

[2]  Guillermo Gallego,et al.  Mark-down pricing: An empirical analysis of policies and revenue potential at one apparel retailer , 2002 .

[3]  Susana V. Mondschein,et al.  Periodic Pricing of Seasonal Products in Retailing , 1997 .

[4]  Cengiz Kahraman,et al.  Markdown Optimization via Approximate Dynamic Programming , 2013, Int. J. Comput. Intell. Syst..

[5]  Marshall L. Fisher,et al.  Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application , 2007, Oper. Res..

[6]  Warren B. Powell,et al.  “Approximate dynamic programming: Solving the curses of dimensionality” by Warren B. Powell , 2007, Wiley Series in Probability and Statistics.

[7]  Yossi Aviv,et al.  Optimal Pricing of Seasonal Products in the Presence of Forward-Looking Consumers , 2008, Manuf. Serv. Oper. Manag..

[8]  Gérard P. Cachon,et al.  The Value of Fast Fashion: Quick Response, Enhanced Design, and Strategic Consumer Behavior , 2011, Manag. Sci..

[9]  Rakesh,et al.  Dynamic Pricing and Ordering Decisions by a Monopolist , 1992 .

[10]  Oz Shy,et al.  How to Price: A Guide to Pricing Techniques and Yield Management , 2008 .

[11]  Felipe Caro,et al.  Inventory Management of a Fast-Fashion Retail Network , 2007, Oper. Res..

[12]  G. Gallego,et al.  Optimal starting times for end-of-season sales and optimal stopping times for promotional fares , 1995 .

[13]  Theodore Valkov From theory to practice: Real-world applications of scientific pricing across different industries , 2006 .

[14]  Warren B. Powell,et al.  Approximate Dynamic Programming I: Modeling , 2011 .

[15]  Stephen A. Smith,et al.  Clearance Pricing and Inventory Policies for Retail Chains , 1998 .

[16]  Pinar Keskinocak,et al.  Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions , 2003, IEEE Engineering Management Review.

[17]  Warren B. Powell,et al.  Approximate Dynamic Programming—II: Algorithms , 2010 .

[18]  Warren B. Powell,et al.  Approximate Dynamic Programming: Solving the Curses of Dimensionality (Wiley Series in Probability and Statistics) , 2007 .

[19]  Murali K. Mantrala,et al.  A Decision-Support System that Helps Retailers Decide Order Quantities and Markdowns for Fashion Goods , 2001 .

[20]  Garrett J. van Ryzin,et al.  A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management , 1997, Oper. Res..

[21]  B. Pashigian,et al.  Demand Uncertainty and Sales: A Study of Fashion and Markdown Pricing , 1988 .

[22]  Warren B. Powell,et al.  Merging AI and OR to solve high-dimensional stochastic optimization problems using approximate dynamic programming , 2008 .

[23]  Martin Natter,et al.  An encompassing view on markdown pricing strategies: an analysis of the Austrian mobile phone market , 2006, OR Spectr..

[24]  G. Ryzin,et al.  Optimal dynamic pricing of inventories with stochastic demand over finite horizons , 1994 .

[25]  Cengiz Kahraman,et al.  Analysis of cross-price effects on markdown policies by using function approximation techniques , 2013, Knowl. Based Syst..

[26]  Gabriel R. Bitran,et al.  Coordinating Clearance Markdown Sales of Seasonal Products in Retail Chains , 1998, Oper. Res..

[27]  Warren B. Powell,et al.  Feature Article - Merging AI and OR to Solve High-Dimensional Stochastic Optimization Problems Using Approximate Dynamic Programming , 2010, INFORMS J. Comput..

[28]  Baichun Xiao,et al.  Integration of pricing and capacity allocation for perishable products , 2006, Eur. J. Oper. Res..

[29]  R. Phillips,et al.  Pricing and Revenue Optimization , 2005 .

[30]  Gil S. Epstein Retail pricing and clearance sales: the multiple product case , 1998 .