Modeling and Analysis of Pricing and Innovation Strategies in Product Development with Heterogeneous Customers and Dual Policies

Document Type : Research Paper

Authors

1 M.Sc. Student, Department of Department of System Engineering, Faculity of of Industrial Engineering and Management Systems, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran

2 Associate Professor, Department of System Engineering, Faculity of of Industrial Engineering and Management Systems, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran

3 Assistant Professor, Department of Industrial Engineering & Management Systems, Faculity of Industrial Engineering, University of Tehran, Tehran, Iran

10.22084/ier.2025.30980.2205

Abstract

Pricing is a critical element in supply chain decisions across strategic, tactical, and operational levels. Rapid technological innovation accelerates product introductions while empowering consumers to anticipate prices and performance. This paper develops a two-period mathematical model for optimizing pricing and product innovation decisions in markets with heterogeneous customers (myopic and strategic). Key contributions include: (1) determining optimal new product innovation level considering R&D costs, (2) introducing a comprehensive, behaviorally-informed customer utility function, and (3) jointly analyzing the impact of both customer types. Modeled within a dynamic game framework, the solution determines optimal first- and second-period prices, trade-in discounts, reduced prices for old products, and new product innovation levels. To solve this nonlinear problem, we develop a customized algorithm based on the spatial branch and bound method. Sensitivity analyses reveal that innovation level, strategic customer behavior, and pricing policy significantly impact profitability. Key findings indicate: (1) pre-determined pricing generates higher profits in 70% of scenarios, (2) dynamic pricing becomes superior under high product development costs or high proportions of strategic customers, and (3) trade-in program effectiveness increases with higher recycled product value. The analysis quantifies the distinct impacts of strategic customers, myopic customers, and trade-in programs. These insights provide managers with actionable guidance for selecting pricing strategies based on specific customer compositions and market conditions.

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Main Subjects

References

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Journal of Industrial Engineering Research in Production Systems
Volume 13, Issue 26
September 2025
Pages 95-117

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