Analytics-driven cost recovery modeling for demand responsive transport: Integrating demand patterns and operational performance data

Key Points

• Cost recovery modeling improves operational performance in demand responsive transport, enhancing service efficiency.
• The analysis indicates a significant relationship between demand patterns and operational performance in transportation.
• Implementation of analytics-driven methods shows potential for optimizing cost efficiency across transport systems.
• Findings highlight the need for data integration to better address demand in public transport services.