D Ennen

Bio: D Ennen is an academic researcher. The author has contributed to research in topics: Mode choice & Public transport. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.

Ride-hailing services in Germany: Potential impacts on public transport, motorized traffic, and social welfare

Abstract: In the policy debate on ride-hailing services such as Uber, the impacts on traffic, emissions, and public transport are hotly discussed. The regulatory framework in Germany has so far prevented a widespread entry of ride-hailing providers. In this paper, we use a mode choice model and trip data to determine the likely impacts of ride-hailing services for a representative region in Germany. We find that the significantly lower fares compared to taxis lead to strong substitution of public transport, cycling, and walking. As a consequence, motorized traffic increases, despite the pooling of individual rides by ride-hailing providers. However, the total impact on mode choice and traffic remains modest, and a widespread displacement of public transport is not to be expected. The final welfare analysis shows that the emergence of ride-hailing services is beneficial for society as a whole. In particular, the benefits from lower fares exceed the external costs arising from additional motorized traffic.

Is motorcycle e-hailing welfare improving?

Abstract: The proliferation of motorcycle e-hailing platforms in Indonesia is regarded by many as exerting myriads of benefits for the wider society as its consumers and its driver-partners. However, such online platforms have disrupted their traditional sector counterparts—the offline motorcycle ridesourcing. This paper gauges the impact of motorcycle e-hailing services using the difference-in-difference (DiD) framework using 422 respondents' data from 11 train stations in Jakarta. We provide welfare comparisons between the two groups of motorcycle ridesourcing (offline and online ridesourcing) at two distinct periods: before and after the advent of motorcycle e-hailing platforms. Our results suggest that, first, online drivers who enlisted themselves into the online platforms had come from the lower segments of the offline drivers' income distribution. Second, we also find that the online drivers exhibit higher levels of net income and hourly income than offline drivers, while the job satisfaction levels of these drivers remain unchanged. Third, we find strong indications that, after the proliferation of ridesourcing platforms, offline drivers' incomes have been well reduced even lower than the low performers of offline drivers before the treatment. Finally, while it is economically rational for offline drivers to join the online platforms, this paper has identified several barriers that potentially hamper them in doing so.