Optimizing Dynamic Pricing Strategies for Ride-Hailing Services in Competitive Tourist Markets: A Case Study of Bolt in Málaga, Spain

Abstract

This study presents an innovative approach to optimizing dynamic pricing strategies for ride-hailing services, focusing on Bolt’s operations in Málaga, Spain. Leveraging mathematical modeling and real-time data analysis, the research evaluates Bolt's pricing strategies to enhance competitiveness, especially in tourist-dense regions. The proposed model integrates demand-supply dynamics, temporal factors, and location-based considerations to ensure balance between affordability for customers and profitability for drivers. Additionally, the study emphasizes the importance of accessible and reliable pricing, tailored to the expectations of international tourists accustomed to using ride-hailing platforms in their home countries. The findings highlight the interplay between pricing strategies and customer retention, highlighting how Bolt can leverage adaptive pricing models to outperform traditional taxis and competitors like Uber. The research underscores the significance of aligning pricing strategies with market conditions, tourist demands, and operational challenges unique to Málaga’s seasonal fluctuations. By implementing these strategies, Bolt can optimize its market performance, ensure sustainable growth, and reinforce customer loyalty in competitive urban mobility landscapes.