In recent years, the e-bike has become increasingly popular in many European countries. With higher speeds and less effort needed, the e-bike is a promising mode of transport to many, and it is considered a good alternative for certain car trips by policy-makers and planners. A major limitation of many studies that investigate such substitution effects of the e-bike, is their reliance on cross-sectional data which do not allow an assessment of within-person travel mode changes. As a consequence, there is currently no consensus about the e-bike’s potential to replace car trips. Furthermore, there has been little research focusing on heterogeneity among e-bike users. In this respect, it is likely that different groups exist that use the e-bike for different reasons (e.g. leisure vs commute travel), something which will also influence possible substitution patterns. This paper contributes to the literature in two ways: (1) it presents a statistical analysis to assess the extent to which e-bike trips are substituting trips by other travel modes based on longitudinal data; (2) it reveals different user groups among the e-bike population. A Random Intercept Cross-Lagged Panel Model is estimated using five waves of data from the Netherlands Mobility Panel. Furthermore, a Latent Class Analysis is performed using data from the Dutch national travel survey. Results show that, when using longitudinal data, the substitution effects between e-bike and the competing travel modes of car and public transport are not as significant as reported in earlier research. In general, e-bike trips only significantly reduce conventional bicycle trips in the Netherlands, which can be regarded an unwanted effect from a policy-viewpoint. For commuting, the e-bike also substitutes car trips. Furthermore, results show that there are five different user groups with their own distinct behaviour patterns and socio-demographic characteristics. They also show that groups that use the e-bike primarily for commuting or education are growing at a much higher rate than groups that mainly use the e-bike for leisure and shopping purposes.

近年来，电动自行车在许多欧洲国家变得越来越流行。电动自行车具有更高的速度和更少的精力，是一种向许多人推广的有前途的交通工具，并且被决策者和计划者认为是某些乘车旅行的理想选择。许多研究电动自行车替代效果的研究的主要局限性在于它们对横截面数据的依赖，而这种横截面数据无法评估人内出行方式的变化。结果，对于电动自行车替代乘车旅行的潜力，目前尚无共识。此外，很少有研究关注电动自行车用户之间的异质性。在这方面，可能存在出于不同原因（例如休闲与通勤旅行）使用电动自行车的不同群体，这也会影响可能的替代模式。本文通过两种方式为文献做出了贡献：（1）进行了统计分析，以基于纵向数据评估电动自行车出行被其他出行方式替代出行的程度；（2）它揭示了电动自行车人群中的不同用户群。随机拦截交叉滞后面板模型是使用来自荷兰机动性专家小组的五波数据估算得出的。此外，使用来自荷兰国家旅行调查的数据执行潜在类别分析。结果表明，当使用纵向数据时，电动自行车与汽车和公共交通工具的竞争性出行方式之间的替代作用并不像早期研究中所报告的那样重要。一般来说，在荷兰，电动自行车出行仅会大大减少传统的自行车出行，从政策角度来看，这可被视为不利的影响。对于通勤，电动自行车还可以代替乘车旅行。此外，结果表明，有五个不同的用户组具有各自不同的行为模式和社会人口统计学特征。他们还表明，主要将电动自行车用于通勤或教育的群体的增长速度大大高于主要将电动自行车用于休闲和购物目的的群体。