Demand estimation and assortment planning in wireless communications

This paper provides an efficient and useful approach for demand estimation and assortment planning of cell phone cards in wireless communication industry. We use maximum likelihood estimation to estimate the primary demand and substitution probability of each cell phone card based on historical sales data. This estimation model is nonlinear, so we transform it to a mixed integer linear programming model by logarithmic transformations and piecewise linear approximation. On the basis of the estimation results, we can make assortment planning. Considering the resource of cell phone cards is limited, we jointly optimize the assortment and quantity planning of cell phone cards. In numerical study, we apply our approach to a large mobile service provider in China and find our approach can increase the revenue of this mobile service provider by 23.69%. Sensitivity analysis shows the mobile service provider should provide more assortments to increase revenue when the types of cell phone cards that can be assigned to each store are limited.