Abstract
As a pricing method that adjusts the price in real-time according to market demand, competitive environment, and consumer behavior, dynamic pricing strategy has been widely used in the field of e-commerce. This study aims to explore the impact of dynamic pricing strategies on the operational efficiency of online retail companies and take Amazon and JD, two typical online retail companies, as examples. This study adopts a mixture of qualitative and quantitative methods. This study will conduct a case study on the impact of dynamic pricing strategies on the operational efficiency of Amazon and JD. In the quantitative aspect, this study conducted descriptive statistics and regression analysis according to the results of the questionnaire survey. The results show that although dynamic pricing strategy has a positive impact on customer buyback rate and customer satisfaction, regression analysis shows that there is no significant relationship between dynamic pricing strategy and company operating efficiency. The research results provide references for online retail companies to make pricing decisions in digital competition.
References
Amazon. (2023). Amazon.com, Inc. 2023 annual report. Amazon. Retrieved from
https://www.amazon.com/annualreport
Byrne, J., & Humble, Á. M. (2007). An introduction to mixed method research. Atlantic research centre for family-work issues, 1, 1-4.
Barnsbee, L. (2018). Target Population - an overview | ScienceDirect Topics. https://www.sciencedirect.com/topics/engineering/target-population
Bassey, M. (2002). Case study research. Research methods in educational leadership and management, 108-121.
Bakhshizadeh Borj, K., Binai Rad, M., & Salehian Fard, R. (2022). The Effect of Dynamic Pricing Strategy on Customer Satisfaction with Service Recovery Through Perceived Justice in Internet Taxi Platforms (Case Study: Snap Intelligent Transportation System). Commercial Strategies, 19(19), 107-128.
Check online store ratings and save money with deals at PriceGrabber.com. (n.d.). Www.pricegrabber.com. https://www.pricegrabber.com/
Fornell, C. (1992). A National Customer Satisfaction Barometer: The Swedish Experience. Journal of Marketing, 56(1), 6-21. https://doi.org/10.1177/002224299205600103
Jia, S., Peng, K., Zhang, X., Li, Y., & Xing, L. (2022). Dynamic pricing strategy and regional energy consumption optimization based on different stakeholders. International Journal of Electrical Power & Energy Systems, 141, 108199.
Jiang, T., Wu, X., & Yin, Y. (2023). Logistics Efficiency Evaluation and Empirical Research under the New Retailing Model: The Way toward Sustainable Development. Sustainability, 15(20), 15028.
JD.com Revenue 2011-2023. (n.d.). Stock Analysis. https://stockanalysis.com/stocks/jd/revenue/
JD.com. (2023). JD.com 2023 Annual Report. JD.com. Retrieved from https://ir.jd.com/
Kumar, V., & Reinartz, W. (2016). Creating Enduring Customer Value. Journal of Marketing, 80(6), 36-68. https://doi.org/10.1509/jm.15.0414
Kumar, V., & Shah, D. (2004). Building and Sustaining Profitable Customer Loyalty for the 21st Century. Journal of Retailing, 80(4), 317-330. https://doi.org/10.1016/j.jretai.2004.10.007.
Neubert, M. (2022). A systematic literature review of dynamic pricing strategies. International Business Research, 15(4), 1-17.
Nimalasena, A., & Getov, V. (2016). Context-aware Approach for Determining the Threshold Price in Name-Your-Own-Price Channels. In Context-Aware Systems and Applications: 4th International Conference, ICCASA 2015, Vung Tau, Vietnam, November 26-27, 2015, Revised Selected Papers 4 (pp. 83-93). Springer International Publishing.
Profit, B. (2024, September 23). Revology Analytics. Revology Analytics. https://www.revologyanalytics.com/articles-insights/dynamic-pricing-balancing-profit-and-customer-satisfaction
Patel, P. (2009, October). Introduction to quantitative methods. In Empirical Law Seminar (Vol. 14, pp. 1-14).
Riquelme, I. P., Román, S., Cuestas, P. J., & Iacobucci, D. (2019). The Dark Side of Good Reputation and Loyalty in Online Retailing: When Trust Leads to Retaliation through Price Unfairness. Journal of Interactive Marketing, 47, 35-52. https://doi.org/10.1016/j.intmar.2018.12.002
Roopa, S., & Rani, M. S. (2012). Questionnaire designing for a survey. Journal of Indian Orthodontic Society, 46(4_suppl1), 273-277.
Srinivasan, D., Rajgarhia, S., Radhakrishnan, B. M., Sharma, A., & Khincha, H. P. (2017). Game-Theory based dynamic pricing strategies for demand side management in smart grids. Energy, 126, 132-143.
Stock Analysis. (2023). Amazon Revenue 1995-2023. Stock Analysis. https://stockanalysis.com/stocks/amzn/revenue/
Sethuraman, S., Maheswari, G. U., Thombre, S., Kumar, S., Patel, V., & Ramanan, S. (2023, December). ENCODE: Ensemble Contextual Bandits in Big Data Settings-A Case Study in E-Commerce Dynamic Pricing. In 2023 IEEE International Conference on Big Data (BigData) (pp. 5372-5381). IEEE.
Technology-Enabled Dynamic Pricing Strategy and Its Role in Retail. (2021, April 29). ELEKS - Software Engineering, Enterprise Software Development, Consulting. https://eleks.com/blog/technology-enabled-dynamic-pricing-strategy/
The power—and pitfalls—of dynamic pricing for omnichannel retailers | McKinsey. (n.d.). Www.mckinsey.com. https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-power-and-pitfalls-of-dynamic-pricing-for-omnichannel-retailers

This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c) 2025 Yinuo Wang, Yuqi Zhou, Jiahe Ding, Xuanle Ye (Author)