Dynamic Pricing Predicting For Online Customers Using Machine Learning
Keywords:
Machine Learning, Dynamic Pricing, Predictive Modelling, Consumer BehaviorAbstract
The goal of dynamic pricing, which is common in the business, is to maximise a company's long-term profitability by continuously adjusting the prices of its products and services. It functions adequately in an environment where pricing can be changed often, like online shopping.Understanding the connection between price and market reaction is crucial to dynamic pricing, which primarily aims to optimise prices.In this research, we use Improved XGBoost methods based on machine learning to solve the dynamic pricing problem. Classification and regression are handled by this supervised machine-learning approach. The true worth of algorithms for machine learning lies in their ability to be applied to new situations through trial and error. Using a dataset of online sales history data and statistical estimating approaches, we test how well the suggested strategy performs. Based on the results of the experiments, we can conclude that the proposed model and algorithms are suitable for dealing with the dynamic pricing problem, and that they give higher prediction performance
Downloads
Metrics
References
Shpanya, A. (2013) "5 Trends To Anticipate In Dynamic Pricing". Retail Touch Points. Accessed on April 1, 2014.
Garbarino, E., & Lee, O. F. (2003). Dynamic pricing in internet retail: effects on consumer trust. Psychology & Marketing, 20(6), pp. 495-513.
McAfee, R. P., & Te Velde, V. (2006). Dynamic pricing in the airline industry.forthcoming in Handbook on Economics and Information Systems, Ed: TJ Hendershott, Elsevier.
Reinartz, W. (2002). Customizing prices in online markets. Management (www. unimib. it/symphonya), (1), pp. 55-65.
Strauss, J., Frost, R., & Ansary, A. I. (2009). E-marketing. Pearson Prentice Hall.
Cummings, T. (2013). Csmonitor.com, Everything you need to know about dynamic pricing, accessed from http://www.csmonitor.com/Business/Saving-Money/2013/1104/Everything-you-need-to-know-about-dynamic-pricing on 19th June, 2014.
Elmaghraby, W., & Keskinocak, P. (2003). Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions. Management Science, 49(10), pp. 1287-1309.
Fitkov-Norris, E. D., & Khanifar, A. H. M. A. D. (2000). Dynamic pricing in mobile communication systems.
Biller, S., Chan, L. M. A., Simchi-Levi, D., & Swann, J. (2005). Dynamic pricing and the direct-to-customer model in the automotive industry. Electronic Commerce Research, 5(2), pp. 309-334.
Weiss, R. M., & Mehrotra, A. K. (2001). Online dynamic pricing: efficiency, equity and the future of e-commerce. Va. JL & Tech., 6, pp. 11-17.
Dolan, R. J., & Moon, Y. (2000). Pricing and market making on the Internet.Journal of Interactive Marketing, 14(2), pp. 56-73.
Narahari, Y., & Dayama, P. (2005). Combinatorial auctions for electronic business. In Sadhana Academy Proceedings in Engineering Sciences, 30(2-3), pp. 179-211. Indian Academy of Sciences.
Rutherford, D. (1995). Routledge dictionary of economics. Taylor & Francis.
Randel, S. (2009). Dynamic Pricing: An old practice is making a comeback online, iProspect.com accessed from http://www.iprospect.com/blog/featured/dynamic-pricing-an-old-practice-is-making-a-comeback-online.html on 12th May, 2014.
Varian, H. R., & Shapiro, C. (1999). Information rules: a strategic guide to the network economy. Harvard Business School Press, Cambridge
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
