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Improving the transport system to enhance women's access to social opportunities and services has been a key initiative in mitigating gender inequality. Studies have examined women's different travel demands and experiences from men, and the mismatch between women's demands and transport services. However, little attention has been given to the gender gap in ride-hailing usage in the context of the fast development of platform economy-based new transportation services. Thus, this paper examines the nexus between gender and inequalities in ride-hailing from the demand side. Two key questions are explored: if ride-hailing serves women more/less, how does this gender difference in using ride-hailing occur? Does the emergence of ride-hailing mitigate or deteriorate the existing gender gap in capability to move? An innovative integration of big data and time-space geography approaches is developed to examine the multi-source data collected from Chengdu, China. The modelling results indicate that ride-hailing emerges as an affordable travel mode addressing women's demand for long-distance travel in the Chinese context of women's high labour participation and thus the existence of a considerable number of employed women with a sizeable daily activity space and a considerable income. The gender gap in capability to move is thus mitigated by ride-hailing at an aggregate level. This paper calls for a more nuanced and context-specific understanding of how ride-hailing may provide challenges and opportunities to gender equity in daily travel. [ABSTRACT FROM AUTHOR]

The explosive growth of ridesourcing services has stimulated a debate on whether they represent a net substitute for or a complement to public transit. Among the empirical evidence that supports discussion of the net effect at the city level, analysis at the disaggregated level from a geospatial perspective is lacking. Besides, it remains unexplored the spatiotemporal pattern of ridesourcing's effect on public transit, and the factors that impact the effect. Using DiDi Chuxing data in Chengdu, China, this paper develops a three-level structure to recognize the potential substitution or complementary effects of ridesourcing on public transit. Furthermore, this paper investigates the effects through exploratory spatiotemporal data analysis, and examines the factors influencing the degree of substitution via linear, spatial autoregressive, and zero-inflated beta regression models. The results show that 33.1% of DiDi trips have the potential to substitute for public transit. The substitution rate is higher during the day (8:00–18:00), and the trend follows changes in public transit coverage. The substitution effect is more exhibited in the city center and the areas covered by the subway, while the complementary effect is more exhibited in suburban areas as public transit has poor coverage. Further examination of the factors impacting the relationship indicates that housing price is positively associated with the substitution rate, and distance to the nearest subway station has a negative association with it, while the effects of most built environment factors become insignificant in zero-inflated beta regression. Based on these findings, policy implications are drawn regarding the partnership between transit agencies and ridesourcing companies, the spatial-differentiated policies in the central and suburban areas, and the potential problems in providing ridesourcing service to the economically disadvantaged population. [ABSTRACT FROM AUTHOR]

Reducing car use is commonly considered as a potential strategy to reduce transport-related problems such as traffic congestion and air pollution. The increasing use of online shopping may potentially replace shopping trips, thus possibly reducing car use. However, car owners – compared to non-car owners – can more easily visit physical stores and transport goods. Therefore, it can be assumed that online shopping is less likely to reduce shopping trips for car owners. Using 653 structured face-to-face interviews in Chengdu (China) in 2016, an empirical study is conducted. The results show that 44.0% of respondents indicated a decrease in shopping trip frequency after they started to purchase online, while only 14.4% indicated an increase in the frequency. This confirms that online shopping tends to be a substitute for shopping trips. Applying a propensity score matching approach, this paper further compares the likelihoods of changes in shopping trips caused by online buying between car owners and non-car owners, while considering sociodemographic factors, internet experiences, spatial attributes, and online shopping attitudes as covariates. The results indicate that – due to online buying – shopping trip frequency is less likely to decrease for car owners compared to non-car owners, while there is no significant difference in the likelihood of increasing shopping trip frequency between owners and non-owners. These findings imply that online shopping may not effectively reduce driving, thus unlikely being a valid solution for transportation problems resulting from the increasing use of cars. • Propensity score matching is applied to infer causality; • Shopping trips can be partly replaced by e-shopping; • E-shopping is less likely to replace shopping trips for car owners; • E-shopping may not effectively reduce driving. [ABSTRACT FROM AUTHOR]