Study of Dynamic Pricing Model for Two - Sided Marketplace

Pushkar Mehendale, Pranitha Buddiga

Abstract: Dynamic pricing has revolutionized the way prices are set in online marketplaces, providing sellers with the ability to adapt to changing demand and market conditions. This paper delves into the theoretical underpinnings and practical applications of dynamic pricing models in two - sided marketplaces. It explores various dynamic pricing strategies, including those based on demand forecasting, competition tracking, and machine learning. The paper analyses the impact of these strategies on market efficiency, considering factors such as consumer surplus, producer surplus, and overall market welfare. Furthermore, it examines the role of machine learning in optimizing pricing decisions, discussing how algorithms can leverage data to predict demand, identify optimal prices, and automate pricing adjustments. By synthesizing past research and utilizing data - driven approaches, this paper provides valuable insights into the mechanisms that drive dynamic pricing and the benefits it offers in competitive online environments.

Keywords: Dynamic Pricing, Two - Sided Marketplace, Revenue Management, E - commerce, Sports Ticketing, Machine Learning, Market Efficiency

How to Cite?: Pushkar Mehendale, Pranitha Buddiga, "Study of Dynamic Pricing Model for Two - Sided Marketplace", Volume 10 Issue 9, September 2021, International Journal of Science and Research (IJSR), Pages: 1787-1793, https://www.ijsr.net/getabstract.php?paperid=ES24624171746, DOI: https://dx.doi.org/10.21275/ES24624171746