Informal and privatized transit services, such as minibuses and shared auto-rickshaws, are integral to daily travel in large urban metropolises, providing affordable commutes where formal public transport is inadequate and other options are unaffordable. A defining feature of these systems is their decentralized organization, with drivers providing service in response to rider demand and earning opportunities. While this structure helps fill critical mobility gaps, it can also generate inefficient service patterns when profit-driven driver route choices do not align with system-wide mobility goals. We develop an analytically tractable game-theoretic framework to study incentives underlying informal and privatized transit systems with a fixed menu of routes, quantify efficiency losses from decentralized driver route choice, and design incentive mechanisms to mitigate these inefficiencies. Here, profit-maximizing informal operators (drivers) decide where to provide service and cost-minimizing commuters (riders) decide whether to use these services. Within this framework, we establish tight price of anarchy bounds showing that decentralized, profit-maximizing driver behavior can lead to bounded yet substantial losses in cumulative driver profit and rider demand served and that these losses can be mitigated through targeted interventions: budget-balanced cross-subsidization, which uses route-specific tolls/subsidies to shape driver payoffs, and fare optimization, which changes rider demand and driver margins through centrally regulated route-level fares. Finally, numerical experiments based on a real-world informal transit system in Nalasopara, India, reinforce these findings.

翻译：非正式与私有化公共交通服务，例如小巴和共享自动人力车，是大型城市日常出行不可或缺的组成部分，它们在正规公共交通不足且其他选择难以负担的情况下提供了可承受的通勤方式。这些系统的一个显著特征是其分散化组织，司机会根据乘客需求和服务获利机会来提供服务。尽管这种结构有助于填补关键的出行缺口，但当追求利润的司机路线选择与系统层面的流动性目标不一致时，也可能产生低效的服务模式。我们开发了一个解析可处理的博弈论框架，以研究在固定路线菜单下非正式与私有化公共交通系统中的激励机制，量化因分散化司机路线选择导致的效率损失，并设计激励机制以减轻这些低效。在该框架中，追求利润最大化的非正式运营者（司机）决定在何处提供服务，而追求成本最小化的通勤者（乘客）则决定是否使用这些服务。我们建立了严格的无序竞争代价界限，表明分散化、追求利润最大化的司机行为可能导致有限的但显著的累计司机利润和乘客需求服务量的损失，并且这些损失可以通过有针对性的干预措施来缓解：预算平衡的交叉补贴（利用特定路线的通行费/补贴来塑造司机收益）和票价优化（通过集中监管的路线级票价改变乘客需求与司机利润空间）。最后，基于印度纳拉索帕拉市真实非正式交通系统的数值实验进一步证实了这些发现。