Transitioning from incentive-based user acquisition to loyal retention on the mobility-as-a-service platform: A large-scale social experiment

•A large-scale social experiment incorporated 10,000 incentive-based new MaaS users.•Compare incentive-based acquired users’ behavior dynamics with naturally acquired users.•Conduct ROI analysis on the incentive-based user acquisition policy. Mobility-as-a-Service (MaaS) platforms, which integrate v...

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Veröffentlicht in:Transportation research. Part E, Logistics and transportation review Jg. 203; S. 104363
Hauptverfasser: Yu, Chengcheng, Dong, Wentao, Ye, Nixuan, Yuan, Quan, Yang, Chao
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.11.2025
Schlagworte:
Behavioral dynamics
Incentive policies
Mobility-as-a-Service (MaaS)
Public policy
Social experiment
User retention
Mobility-as-a-Service (MaaS)
Social experiment
Public policy
User retention
Incentive policies
Behavioral dynamics
ISSN:1366-5545
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Zusammenfassung:•A large-scale social experiment incorporated 10,000 incentive-based new MaaS users.•Compare incentive-based acquired users’ behavior dynamics with naturally acquired users.•Conduct ROI analysis on the incentive-based user acquisition policy. Mobility-as-a-Service (MaaS) platforms, which integrate various transit modes into a unified, user-friendly system, offer a promising approach to revitalizing public transit. This study empirically evaluates the effectiveness of incentive-based user acquisition policies within MaaS platforms through a large-scale social experiment conducted in Shanghai, where 10,000 participants engaged in our social experiment, receiving and using discounted weekly passes, a three-week incentive period, and an additional month of observation to assess retention and engagement effects. The analysis revealed that incentive-based acquisition policies induce substantial behavioral changes. High-frequency and mode-balanced users demonstrated higher retention rates than occasional non-regular users, yet users in all behavior statuses showed heightened churn rates once incentives were withdrawn, highlighting a dependency on continuous incentives for sustained engagement. Comparative analysis with naturally acquired users indicated that incentive-based users exhibit significantly higher churn rates and greater behavioral status transition probability. Furthermore, the Return on Investment (ROI) analysis demonstrated that discount levels do not significantly influence retention rates across different user behavior statuses. Higher incentive costs failed to yield improvements in retention, presenting a Pareto optimization challenge and suggesting that financial incentives alone are insufficient for long-term user engagement. Based on these findings, strategic recommendations include prioritizing lower discounts for a broader user base to optimize budget utilization and targeting high-ROI segments with higher discounts to recover incentive costs rapidly. This study contributes to the existing MaaS research field by providing empirical evidence from real-world social experiments, offering valuable insights to enhance user acquisition and retention through optimized incentive structures.
ISSN:1366-5545
DOI:10.1016/j.tre.2025.104363