Bikesharing, equity, and disadvantaged communities: A case study in Chicago

An exploratory analysis of the trend in the demand for the London bike-sharing system: From London Olympics to Covid-19 pandemic

“…Further, unemployed people are less likely to become a member of bike-share systems and thus the increase in unemployment rate should result in a decrease in the system usage, which is properly highlighted by our estimated parameter for unemployment rate variable. This result is also in agreement with cross-sectional studies that found bike-sharing stations in neighbourhoods with higher unemployment rates observe fewer ridership (Hyland et al 2018;Qian and Jaller 2020). Relative risk (and consequently relative change) is convenient in understanding the impact of categorical variables, representing different seasons and types of days on the daily demand for bicycles in the scheme.…”

“…Studies that look at supply-side of the system such as identifying problematic stations, finding the optimal size of stations or proposing methods to improve the efficiency of operator rebalancing program (Forma, Raviv, and Studies that analyse the demand and usage of the system (Eren and Uz 2020;Faghih-Imani et al 2014;Hyland et al 2018;Kaviti et al 2020) Faghih-Imani and Eluru 2020; Hyland et al 2018). In fact, a recent study of Chicago bikesharing system highlighted that employment rate is one of the most important factors to increase system demand in disadvantageous communities (Qian and Jaller 2020).…”

“…The mean daily temperature data for the period 2018 to 2020 was obtained from the NW3 Weather website together with data for wind speed, average humidity, and atmospheric pressure. and usage(Qian and Jaller 2020;Ricci 2015). To this end, monthly unemployment rate for the population aged sixteen and over was obtained from the UK Office for National Statistics (Office for National statistics, 2020).…”

Spatiotemporal Polyrhythm Characteristics of Public Bicycle Mobility in Urban Chronotopes Context

“…For example, bike sharing, as a stand-alone system or in conjunction with public transport, is less suited to be used by women and older age groups in Oslo, Norway [29]. Low-income populations, people of color, and transit-dependent households are not highly representative of the riders' profile [30]. Members who reside in minority-concentrated neighborhoods with low socioeconomic status use shared bicycles more frequently [31].…”

“…The three paths are superimposed in Figure 4b. The set of road nodes for path ab (R ab ) is (7,8,9,12,13,20,25,30,34). Every two consecutive nodes represent a road segment; thus, R ab has eight segments.…”