Pricing Internet Service Plans Considering Customer Choice Models and Stochastic Usage

Articles in Press

Document Type : Article

Authors

1 Department of Industrial Engineering , Sharif University of Technology, Tehran, Iran

2 Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran

10.24200/j65.2026.68389.2475

Abstract

Pricing internet service plans is a complex and strategically important problem due to their multi-part tariff structure, which requires detailed modeling and careful analysis. These pricing schemes typically consist of two key components: a fixed fee that grants customers access to a predetermined data allowance, and a variable charge imposed on each unit of consumption beyond that allowance. Designing such tariffs becomes even more challenging when customer usage patterns exhibit uncertainty, as is common in real-world internet consumption. In this study, we investigate the pricing of internet service plans under a multi-part tariff structure while explicitly incorporating the stochastic nature of users’ monthly data consumption. Recognizing that customers differ not only in their usage levels but also in how they evaluate and select plans, we integrate several customer choice models into the pricing framework. These models capture different behavioral patterns and decision-making strategies, enabling the service provider to account for heterogeneity in customer responses. Building on these behavioral insights, we develop four mathematical optimization models that jointly determine both the optimal data allowance and the corresponding price for each plan under each choice model. These models allow for a systematic investigation of how behavioral assumptions and consumption uncertainty shape optimal pricing strategies. Our numerical results reveal that when usage is stochastic, understanding customer choice behavior has a substantial impact on the provider’s revenue. In particular, customer uncertainty about their actual consumption increases the likelihood of purchasing higher-volume plans or incurring additional charges, both of which contribute to higher revenue for the provider. Furthermore, the results show that expanding the menu of available plans does not necessarily improve profitability. In fact, under stochastic usage, offering too many plans may reduce revenue by enabling customers to more precisely match their expected consumption with the available tariff options. These findings underscore the importance of jointly considering usage uncertainty and customer choice behavior in the design of internet pricing schemes.

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Sharif Journal of Industrial Engineering & Management

Articles in Press, Accepted Manuscript
Available Online from 28 July 2026

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