Fare evasion is currently a significant concern for public transport systems worldwide. Evasion causes huge economic losses to operators and cities, but also negatively influences the system’s security perceptions. Despite its importance, there are few efforts to understand which observable and non-observable factors motivate individuals to evade fares in a public transport system. Most studies dealing with fare evasion evaluate the effectiveness of several policies, quantify the amount of evasion, or correlate fare evasion with system satisfaction using aggregate data. This paper proposes a Hybrid Discrete Choice model to understand current evaders’ behavior considering sociodemographic, fare evasion records, trip characteristics, user satisfaction with the transport system, and perceptual indicators. The model was estimated using a unique stated preferences survey applied to 324 fare evaders of Transmilenio, the Bogotá (Colombia) Bus Rapid Transit system, in mid-2019. This is an interesting case study because, in 2018, the evasion rate was measured for the first time and it was discovered that evaders comprised approximately 15% of their users on weekdays.

The contribution of this research is twofold. First, results highlight the importance of considering observable and latent variables to understand individual behavior in examining fare evasion in similar public transport systems. Age and the evasion records resulted in being the most important observable variables in our case study. Latent variables suggest that the more the user is satisfied with the transport system, the less likely is to evade fares. However, we found that personality traits, such as individual rule-unconsciousness, moderate the effect of satisfaction on the evasion behavior. Second, our results provide evidence that the discussion between certainty and severity of punishment on fare evasion should not necessarily be centered on whether to exacerbate one of these factors. A combination of both, however, should reduce the recidivism rate.

逃票是目前全球公共交通系统的一个重要问题。规避会给运营商和城市带来巨大的经济损失，但也会对系统的安全感知产生负面影响。尽管它很重要，但很少有人努力了解哪些可观察和不可观察的因素促使个人在公共交通系统中逃避票价。大多数涉及逃票的研究都评估了多项政策的有效性，量化了逃票的数量，或者使用汇总数据将逃票与系统满意度相关联。本文提出了一种混合离散选择模型，以考虑社会人口统计、逃票记录、旅行特征、用户对交通系统的满意度和感知指标来了解当前逃税者的行为。该模型是使用 2019 年年中对波哥大（哥伦比亚）快速公交系统 Transmilenio 的 324 名逃票者进行的一项独特的陈述偏好调查来估计的。这是一个有趣的案例研究，因为在 2018 年，首次测量了逃避率，发现逃避者在工作日约占其用户的 15%。

这项研究的贡献是双重的。首先，结果强调了在检查类似公共交通系统中的逃票时考虑可观察变量和潜在变量以了解个人行为的重要性。在我们的案例研究中，年龄和逃避记录是最重要的可观察变量。潜在变量表明，用户对交通系统越满意，逃避票价的可能性就越小。然而，我们发现人格特质，如个体规则无意识，会调节满意度对逃避行为的影响。其次，我们的结果提供证据表明，关于逃票处罚的确定性和严重性之间的讨论不一定集中在是否加剧这些因素之一上。然而，两者的结合，