Uncapacitated Pricing Optimization for Mobile Broadband Services

Abstract

This research seeks to determine the optimal price for mobile broadband services of a particular service provider. The case study is mobile broadband services in the Indonesian market. We made a plausible assumption that there is no capacity constraint. We used choice-based conjoint with hierarchical Bayes estimation method to derive individual part-worth utilities, based on which market simulation was run to obtain the share-of-preference function. By combining this with information about market size, we came up with data points representing the demand function. Instead of fitting the data points with some theoretical demand functions, we used monotonic cubic splines to interpolate the demand function. Accordingly, we did not use explicit demand functions in the optimization, but a numerical interpolation function to estimate demand for any particular price level. Using enumeration, we then came up with a recommended contribution-maximizing prices under one, two, and three fare-classes segmentation. We assumed a perfect segmentation where cannibalization and arbitrage were not present. Single-segment pricing optimization came up with an optimal price of Rp135,200 with a total contribution of Rp1,106,902,315,961. Increasing the number of fare-class to two has improved the total contribution by 21,23%, while the three fare-class resulted in a further 50% increase in total contribution compared to that of the two fare-class. Further, we discussed a generalized optimal segmentation problem under the same assumption. We also investigated the impact of changes in competitors’ service attributes on the optimal prices.