A Comprehensive Overview of Deep Learning for Algorithmic Pricing in Ride-Sharing Platforms

Abstract

This study extends the current scholarship on algorithmic pricing within the sharing economy. By leveraging the capabilities of deep learning, we seek to generate valuable knowledge for stakeholders in the ride-sharing domain, including platform operators, users, and policymakers. This research contributes to the field of economic science by demonstrating the potential application of deep learning in algorithmic pricing models for sharing economy platforms. Through a comparative analysis of various methodologies, we aim to provide actionable insights that can inform platform design, regulatory frameworks, and ultimately lead to a more efficient, equitable, and sustainable transportation system.

Keywords

• dynamic pricing
• sharing economy
• demand-supply fluctuations
• algorithmic pricing
• ride-sharing platforms