# Spatiotemporal Heterogeneous Effects of Built Environment and Taxi Demand on Ride-Hailing Ridership
## 3 Methodology
### Study Area and Data
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Order ID** & **Vehicle ID** & **Pick-Up Time** & **Pick-Off Time** & **Pick-Up** & **Pick-Off** \\  & & & **Location** & **Location** \\  & & & **(Longitude,** & **(Longitude,** \\  & & & **Latitude)** & **Latitude)** \\ \hline BZ220411011142013000 XXX & SAXXX072 & 2022/04/11 & 2022/04/11 & (118.732278, & (1118.895874, \\  & & 01:15:37 & 01:49:57 & 32.140057) & 32.053261) \\ TS120220411013200 XXX & SAXXX201 & 2022/04/11 & 2022/04/11 & (118.842107, & (1118.873526, \\  & & 01:36:01 & 01:47:08 & 32.122716) & 32.109904) \\
152 faeb379 cfe4732 XX & SAXXX1J & 2022/04/16 & 2022/04/16 & (118.786830, & (118.787778, \\  & & 15:51:01 & 15:56:02 & 32.019600) & 32.012594) \\
149 fd1150121e482 eXX & SAXXXX1V & 2022/04/11 & 2022/04/11 & (118.77490, & (118.762545, \\  & & 12:21:27 & 12:25:03 & 31.967450) & 31.971193) \\ TS120220416183404 XXX & SAXXXX282 & 2022/04/16 & 2022/04/16 & (118.921599, & (118.915473, \\  & & 18:38:20 & 18:45:30 & 32.101403) & 32.110716) \\ TS120220412123602 XXX & SAXXX300 & 2022/04/12 & 2022/04/12 & (118.759594, & (118.772129, \\  & & 12:40:13 & 12:48:15 & 32.079994) & 32.069341) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Examples of ride-hailing and taxi orders in the dataset. The built environment variables are selected in terms of the 5D principle [31], including density, diversity, design, distance to transit, and destination accessibility. To capture these variables, a variety of data sources have been utilized. Population density and housing price are employed as measures of the density dimension. Population density is extracted from the University of Southampton ([[https://www.worldpop.org/](https://www.worldpop.org/)]([https://www.worldpop.org/](https://www.worldpop.org/)) for detail, accessed on 28 June 2023), which provides the population size of global cities based on a 100 \(\times\) 100 m geographical grid. The housing price is extracted from the Anjuke website ([[http://anjuke.com/](http://anjuke.com/)]([http://anjuke.com/](http://anjuke.com/)) for details, accessed on 28 June 2023), which is one of the largest online housing brokers in China. The design dimension is measured with road density and bike lane density. Road density and bike lane density are calculated based on the ratios of road lengths and bike lane lengths to the grid area. The road and bike lane lengths are extracted from OpenStreetMap ([[https://www.openstreetmap.org/](https://www.openstreetmap.org/)]([https://www.openstreetmap.org/](https://www.openstreetmap.org/)) for detail, accessed on 28 June 2023). Destination accessibility is measured with the distance from the centroid of a grid to the Central Business District (CBD). Distance to transit is measured with four variables: bus stop density, metro station density, distance to the nearest bus stop, and distance to the nearest metro station. The bus stop and metro station locations are obtained from AMAP.com, which provides various categories of POIs. In addition to these facilities, thirteen categories of POIs (i.e., restaurants, malls, transport facilities, financial institutions, hotels, educational and cultural facilities, scenic spots, living service facilities, residences, leisure and entertainment facilities, medical facilities, sports facilities, government agencies, and social organizations) are used to obtain the land use mix, which is a common measurement of the diversity dimension. The land use mix is calculated as follows:  
\[Entropy=\frac{-\sum P_{i}\times\ln P_{i}}{\ln n} \tag{1}\]  
Figure 2: Spatiotemporal distributions of ride-hailing ridership and taxi ridership. where \(P_{i}\) represents the ratio of each category of POIs, and \(n\) is the number of categories of POIs. The statistical descriptions of the built environment variables are shown in Table 3.