Abstract
The paradigms of taxis and ride-hailing, the two major players in the personal mobility market, are compared systematically and empirically in a unified spatial–temporal context. Supported by real field data from Xiamen, China, this research proposes a three-fold analytical framework to compare their mobilities, including (1) the spatial distributions of departures and arrivals by rank–size and odds ratio analysis, (2) the statistical characteristics of trip distances by spatial statistics and considering distance-decay effect, and (3) the meta-patterns inherent in the mobility processes by nonnegative tensor factorization. Our findings suggest that taxis and ride-hailing services share similar spatial patterns in terms of travel demand, but taxi demand heterogenizes more quickly with changes in population density. Additionally, the relative balance between the taxi industry and ride-hailing services shows opposite trends inside and outside Xiamen Island. Although the trip distances have similar statistical properties, the spatial distribution of the median trip distances reflects different urban structures. The meta-patterns detected from the origin–destination-time system via tensor factorization suggest that taxi mobilities feature exclusive nighttime intensities, whereas ride-hailing exhibits more prominent morning peaks on weekdays. Although ride-hailing contributes significantly to cross–strait interactions during daytime, there is a lack of efficient services to maintain such interactions at night.
Highlights
The past decade has witnessed an increase in online ride-hailing as a predatory competitor to the traditional taxi industry
To gain an insight into the similarities and differences between taxi and ride-hailing, their mobility patterns were compared through three aspects: (1) the spatial differentiation of travel demands, (2) the spatial and statistical variation of trip distances, and (3) the context-dependent components that can be extracted from the origin–destination–time system of each
Considering the land-use patterns shown in Figure 1c, it is clear that urban built-up areas, followed by rural residential and industrial areas, contribute most to the generation of travel demands
Summary
The past decade has witnessed an increase in online ride-hailing as a predatory competitor to the traditional taxi industry. It is no exaggeration to suggest that taxis and ride-hailing services comprise two polarities of the commercial personal mobility market [2]. Despite certain heterogeneity, their common attributes (e.g., point-topoint delivery, pricing strategies, and flexible operation modules compared with public transit) should have generated extensive academic comparisons . Their common attributes (e.g., point-topoint delivery, pricing strategies, and flexible operation modules compared with public transit) should have generated extensive academic comparisons Such cases are not found in the literature. Ride-hailing comprises an emerging form of personal mobility, and its providers (e.g., Uber) are privately operated
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