Ride-hailing (ridesourcing) companies such as Uber, Lyft, and Didi Chuxing have been a disruptive force in the urban mobility landscape around the world during the past decade. In this paper, we analyse the working conditions, earnings, and job satisfaction of ride-hailing drivers. We begin by discussing the regulatory, labour, financial, and urban mobility effects of ride-hailing companies. Then, we present the results of a self-administered survey to ride-hailing drivers in Chile, which is complemented with the use of online tools for the estimation of driving earnings. Our findings show that the flexibility to choose work times is the most appreciated attribute of this job, even though most drivers follow a somewhat fixed routine each week. By contrast, the level of transparency with which ride-hailing apps determine driver pay is the attribute with the lowest satisfaction score. A large number of respondents drive for long daily and weekly periods, which is a health and safety hazard. Current drivers are not concerned about the future deployment of driverless vehicles for on-demand mobility services. Ordered probit models for job satisfaction show that ride-hailing was better evaluated by drivers who use it as a complement to another part-time job, by those who earn more money per week, and by those who have not experienced undesirable situations while working, such as harassment or traffic crashes.

中文翻译：

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共享经济和就业市场：智利的网约车司机案例

在过去十年中，Uber、Lyft 和滴滴出行等叫车（ridesourcing）公司一直是全球城市交通领域的颠覆性力量。在本文中，我们分析了网约车司机的工作条件、收入和工作满意度。我们首先讨论网约车公司对监管、劳动力、金融和城市交通的影响。然后，我们向智利的网约车司机展示了一项自我管理调查的结果，并辅以使用在线工具来估算驾驶收入。我们的研究结果表明，选择工作时间的灵活性是这项工作最受赞赏的属性，尽管大多数司机每周都遵循某种固定的例行程序。相比之下，打车应用决定司机薪酬的透明度是满意度最低的属性。大量受访者每天和每周长时间驾驶，这对健康和安全造成危害。目前的司机并不关心未来无人驾驶汽车的按需移动服务部署。工作满意度的有序概率模型显示，将网约车用作另一份兼职工作的补充的司机、每周赚更多钱的人以及在工作时没有遇到不良情况的人对网约车的评价更高，例如骚扰或交通事故。目前的司机并不关心未来无人驾驶汽车的按需移动服务部署。工作满意度的有序概率模型显示，将网约车用作另一份兼职工作的补充的司机、每周赚更多钱的人以及在工作时没有遇到不良情况的人对网约车的评价更高，例如骚扰或交通事故。目前的司机并不关心未来无人驾驶汽车的按需移动服务部署。工作满意度的有序概率模型显示，将网约车用作另一份兼职工作的补充的司机、每周赚更多钱的人以及在工作时没有遇到不良情况的人，对网约车的评价更高，例如骚扰或交通事故。