Market-Oriented Perspectives on Dynamic Pricing Decisions under Limited Inventory Conditions
Keywords:
dynamic pricing, limited inventory, market orientation, consumer behavior, competitive dynamicsAbstract
Dynamic pricing under limited inventory conditions has attracted substantial scholarly attention, particularly within the fields of revenue management and operations research. Existing studies predominantly emphasize algorithmic optimization and short-term revenue maximization, often abstracting from market-facing considerations. This review adopts a market-oriented perspective to re-examine dynamic pricing decisions in inventory-constrained environments. By integrating insights from consumer behavior, competitive strategy, and inventory management, the study highlights how limited inventory fundamentally reshapes market responses to dynamic pricing. The review demonstrates that inventory scarcity amplifies consumer price perceptions, fairness concerns, and strategic learning, while simultaneously intensifying competitive reactions and pricing interdependence among firms. Building on these insights, the paper develops an integrative framework that links inventory conditions, market dynamics, and firm-level strategic objectives, illustrating key trade-offs between short-term revenue optimization and long-term market sustainability. The review further identifies critical boundary conditions under which dynamic pricing may generate market resistance or instability. Finally, directions for future research are outlined, with particular attention to behavioral pricing models, fairness and regulation, human–algorithm interaction, and ethical considerations. Overall, this study contributes to the literature by reframing dynamic pricing under limited inventory as a market-embedded strategic decision rather than a purely analytical optimization problem.
References
1. X. Li and Z. Zheng, "Dynamic pricing with external information and inventory constraint," Management Science, vol. 70, no. 9, pp. 5985–6001, 2024.
2. B. Chen, D. Simchi-Levi, Y. Wang, and Y. Zhou, "Dynamic pricing and inventory control with fixed ordering cost and incomplete demand information," Management Science, vol. 68, no. 8, pp. 5684–5703, 2022.
3. S. Yuan, “Data Flow Mechanisms and Model Applications in Intelligent Business Operation Platforms”, Financial Economics Insights, vol. 2, no. 1, pp. 144–151, 2025, doi: 10.70088/m66tbm53.
4. G. Wang, “Performance evaluation and optimization of photovoltaic systems in urban environments,” Int. J. New Dev. Eng. Soc., vol. 9, pp. 42–49, 2025, doi: 10.25236/IJNDES.2025.090106.
5. N. B. Keskin, Y. Li, and J. S. Song, "Data-driven dynamic pricing and ordering with perishable inventory in a changing environment," Management Science, vol. 68, no. 3, pp. 1938–1958, 2022.
6. W. Ma, D. Simchi-Levi, and J. Zhao, "Dynamic pricing (and assortment) under a static calendar," Management Science, vol. 67, no. 4, pp. 2292–2313, 2021.
7. J. Zhao, “‘To IPO or Not to IPO’ - Recent 2025 IPOs and AI Valuation Framework”, Financial Economics Insights, vol. 2, no. 1, pp. 131–143, Dec. 2025, doi: 10.70088/hhczb769.
8. H. Matsumoto, T. Gu, S. Yo, M. Sasahira, S. Monden, T. Ninomiya, M. Osawa, O. Handa, E. Umegaki, and A. Shiotani, “Fecal microbiota transplantation using donor stool obtained from exercised mice suppresses colonic tumor development induced by azoxymethane in high-fat diet-induced obese mice,” Microorganisms, vol. 13, no. 5, p. 1009, 2025.
9. X. Zhang, “The Enabling Path of Private Equity Funds in the Growth Process of Emerging Market Enterprises”, Econ. Manag. Innov., vol. 2, no. 5, pp. 94–102, Oct. 2025, doi: 10.71222/511cxp26.
10. P. K. Kopalle, K. Pauwels, L. Y. Akella, and M. Gangwar, "Dynamic pricing: Definition, implications for managers, and future research directions," Journal of Retailing, vol. 99, no. 4, pp. 580–593, 2023.
11. A. V. den Boer and N. B. Keskin, "Dynamic pricing with demand learning and reference effects," Management Science, vol. 68, no. 10, pp. 7112–7130, 2022.
12. C. Yang, Y. Feng, and A. Whinston, "Dynamic pricing and information disclosure for fresh produce: An artificial intelligence approach," Production and Operations Management, vol. 31, no. 1, pp. 155–171, 2022.
13. X. Hu, Z. Wan, and N. N. Murthy, “Dynamic pricing of limited inventories with product returns,” Manufacturing & Service Operations Management, vol. 21, no. 3, pp. 501–518, 2019, doi: 10.1287/msom.2017.0702
14. W. Sun, “Integration of Market-Oriented Development Models and Marketing Strategies in Real Estate,” European Journal of Business, Economics & Management, vol. 1, no. 3, pp. 45–52, 2025
15. C. Wu, W. Bi, and H. Liu, "Proximal policy optimization algorithm for dynamic pricing with online reviews," Expert Systems with Applications, vol. 213, p. 119191, 2023.
16. B. Wu, “Market research and product planning in e-commerce projects: A systematic analysis of strategies and methods,” Academic Journal of Business & Management, vol. 7, no. 3, pp. 45–53, 2025, doi: 10.25236/AJBM.2025.070307.
