abstract
- © 2017 The Authors. Published by Elsevier B.V. This paper proposes a methodology to define an optimal pricing strategy for convenience stores based on dimension reduction methods and uncertainty of data. The solution approach involves a multiple linear regression (MLR) as well as a linear programming optimization model. Two strategies Principal Component Analysis (PCA) and Best subset Regression (BSR) methods for the selection of a set of variables among a large number of predictors is presented. A linear optimization model then is solved using diverse business rules. To show the value of the proposed methodology optimal prices calculation results are compared with previous results obtained in a pilot performed for selected stores. This strategy provides an alternative solution that shows how a decision maker can include proper business rules of their particular environment in order to define a pricing strategy that meets business goals.