Supply Chain Coordination with Dynamic Pricing Advertising and Consumer Welfare An Economic Application

Authors

  • Huijie Tang University of Michigan
  • Zhoufan Yu Cornell University
  • Huanyu Liu Johns Hopkins University Carey Business School

DOI:

https://doi.org/10.70393/6a69656173.333230

ARK:

https://n2t.net/ark:/40704/JIEAS.v3n5a01

Disciplines:

Applied Mathematics

Subjects:

Mathematical Modeling

References:

13

Keywords:

Supply Chain Coordination, Dynamic Pricing, Advertising Investment, Consumer Welfare, Game Theory, Econometrics

Abstract

In this paper, we construct a supply chain coordination model that considers the complex relationships among dynamic pricing, advertising investment, and consumer welfare. The model focuses on a supply chain consisting of a manufacturer and a retailer, where the manufacturer produces the product and the retailer sells it. We first analyze the equilibrium under decentralized decision-making, in which the retailer is the leader and the manufacturer the follower. By building a differential game model, we derive the optimal pricing and advertising strategies under decentralization. Then, we set a centralized optimal benchmark in which the supply chain acts as an integrated decision maker. Comparing decentralized and centralized decisions, we find a double-marginalization effect under decentralization that reduces the total profit of the supply chain. To address this, we design a series of coordinating contracts—including revenue sharing, price discount, and two-part tariff contracts—among which revenue sharing can effectively coordinate the chain and maximize total profit. We further analyze the effect of advertising on consumer welfare. Using a consumer welfare measurement model, we find that advertising increases consumer surplus and thus improves consumer welfare. Numerical simulations verify the effectiveness of the model and the superiority of the coordinating contracts.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Author Biographies

Huijie Tang, University of Michigan

Master of Supply Chain Management, 500 S. State St, Ann Arbor, MI 48109, USA.

Zhoufan Yu, Cornell University

Master's in Applied Economics and Management, Cornell University, Ithaca, New York, United States, 14850.

Huanyu Liu, Johns Hopkins University Carey Business School

Johns Hopkins University Carey Business School,Master of Science in Marketing,100 International Drive, Baltimore, MD 21202, USA.

References

[1] Si, Y., Meng, Q., Yang, W., Fu, Z., & Li, Z. (2023). Omnichannel pricing with consumer channel preference and e-coupon deployment. Journal of Systems & Management, 32(6), 1142–1163.

[2] Chen, C. (2021). Research on pricing, structure, and coordination in cloud service supply chains (Master’s thesis). Anhui University.

[3] Zhou, Y., & Zhang, Y. (n.d.). Advertising investment and pricing with user mobility across local markets on competing platforms. China Journal of Management Science.

[4] Lü, J. (2023). Guidance, application, and development of consumer-generated advertising. New Perspectives on Media Convergence, 2023(02), 45–48.

[5] Ye, J. (2023). Decisions and coordination in agricultural supply chains with CSR and advertising spillovers (Master’s thesis). Anhui Agricultural University.

[6] Wang, H., Tang, H., Leng, N., & Yu, Z. (2025). A Machine Learning-Based Study on the Synergistic Optimization of Supply Chain Management and Financial Supply Chains from an Economic Perspective. arXiv preprint arXiv:2509.03673.

[7] Cao, N., Guo, Y., Tang, H., Li, X., & Zhou, Z. (2025). Research on Optimization Model of Supply Chain Robot Task Allocation Based on Genetic Algorithm and Software Practice. Available at SSRN 5466194.

[8] Li, X., & Fang, L. (2025). Information Interaction Design and Evaluation of Cross-Cultural Art Collaborative Language Learning System Based on Computer Vision and Natural Language Processing. Available at SSRN 5436074.

[9] Guo, L., Hong, J., Yu, Z., Zhou, J., & Leng, N. (2025). Study on Exploring the Optimization Path of Financial Supply Chain and the Improvement of Enterprise Economic Benefits by Integrating Graph Neural Networks Driven by Big Data. Available at SSRN 5440098.

[10] Zhou, Z., & Ma, H. (2025). Research on Metro Transportation Flow Prediction Based on the STL-GRU Combined Model. arXiv preprint arXiv:2509.18130.

[11] Li, X., & Fang, L. (2025). The Impact of Culturally Adaptive Feedback in Information-Interaction Systems on Language-Learning Motivation and Outcomes. Journal of Educational Theory, 2(1), 1–7.

[12] Zhou, Z., Guo, Y., Guo, L., Hong, J., & Peng, J. (2025). Research on Robot Process Modeling and Software Engineering Integration Path in Automated Processing of Accounting Information Based on Artificial Intelligence and Big Data. Available at SSRN 5359072.

[13] Jiang, Y., Zhang, T., & Liu, H. (2025, June 6). Research and design of blockchain-based propagation algorithm for IP tags using local random walk in big data marketing. TechRxiv. https://doi.org/10.36227/techrxiv.174918179.99038154/v1

Downloads

Published

2025-10-02

How to Cite

[1]
H. Tang, Z. Yu, and H. Liu, “Supply Chain Coordination with Dynamic Pricing Advertising and Consumer Welfare An Economic Application”, Journal of Industrial Engineering & Applied Science, vol. 3, no. 5, pp. 1–6, Oct. 2025.

Issue

Section

Articles

ARK