A finite multi-period markdown pricing and transshipment model for single cycle product in a retail network

• Main Authors: Chua, Arthur Brian S., Javier, Emmanuel Francis E, Santos, Louie Leandro J.
• Format: text
• Language: English
• Published: Animo Repository 2010
• Subjects: Pricing; Inventory control > Effect of prices on > Econometric models; Markdowns; Industrial Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/11246
• Institution: De La Salle University

Past Researchers on Yield or Revenue Management has focused more on the Airline Industry where Pricing Decisions have been pointed out as main revenue drivers. Recent Researchers, on the other hand argued that Pricing Decisions could also be used in the Retailing Industry, specifically those that handle single cycle products wherein they have unique sets of products portfolios each selling season and that their objective is to yield the highest possible profit given a finite selling horizon. Single Cycle Products differ from other items that have replenishment options and even items with the characteristics of perish ability. The handling of Single Cycle products becomes more complicated since they experience a sense of obsolescence meaning they lose value over time. Recent Literatures on handling single cycle products present pricing strategies as solutions to improve revenue given the complex characteristics of this kind of product. In Research literature, pricing strategies can basically refer to inventory management. Other inventory management strategies involve dynamic allocation of products in the retail network. However present researchers have limitations such that they do not explore combinations of these inventory management strategies, and they delve into generalized systems which roots out complexities. Therefore, there is a need to formulate a mathematical model that includes both dynamic markdown pricing and transshipment strategy for single cycle product portfolios with finite selling horizons in a retail network that will maximize profit for the system. The mathematical model formulated is a mixed integer nonlinear programming problem. The model was simulated using GAMS software to obtain near-optimal solution. Validation of the model consisted of iterative of model logic given different scales of the model. Basic Sensitivity Analyses were done in order to figure out the effects of different system parameters on optimal decision variables. The results of the research include a set of policies that can be used to improve system performance of retail networks handling single cycle product portfolios when subjected to different system parameters.