Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of Interest
The COVID-19 pandemic has increased the demand for online food delivery services (OFDS), leading to an increase in related crashes over the last few years. While recent studies have focused on nonmotorised vehicles (such as bicycles or e-bikes), few researchers have examined the role of motorcycles...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Hindawi-Wiley
2023-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2023/6643649 |
| _version_ | 1797366799218507776 |
|---|---|
| author | I Gede Brawiswa Putra Pei-Fen Kuo Dominique Lord |
| author_facet | I Gede Brawiswa Putra Pei-Fen Kuo Dominique Lord |
| author_sort | I Gede Brawiswa Putra |
| collection | DOAJ |
| description | The COVID-19 pandemic has increased the demand for online food delivery services (OFDS), leading to an increase in related crashes over the last few years. While recent studies have focused on nonmotorised vehicles (such as bicycles or e-bikes), few researchers have examined the role of motorcycles and the possible spatial relationships with various points of interest (POIs). In addition, most crash and POIs studies have utilized typical restaurant datasets instead of specific restaurants partnered with OFDS, which might bias the impact of traffic safety estimation. To address these gaps, a geographically weighted negative binomial model (GWNBR) was used to determine the factors contributing to OFDS-related motorcycle accidents and account for spatial heterogeneity. The results indicated that areas with more restaurants, intersections, and shopping malls (only significant on weekends) tended to have more OFDS motorcycle crashes. The results should inspire more effective policies for delivery drivers, given the increasing popularity of OFDS. |
| first_indexed | 2024-03-08T17:09:46Z |
| format | Article |
| id | doaj.art-67aa3f8a54464a68be26a0c3c3f55a60 |
| institution | Directory Open Access Journal |
| issn | 2042-3195 |
| language | English |
| last_indexed | 2024-03-08T17:09:46Z |
| publishDate | 2023-01-01 |
| publisher | Hindawi-Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj.art-67aa3f8a54464a68be26a0c3c3f55a602024-01-04T00:00:13ZengHindawi-WileyJournal of Advanced Transportation2042-31952023-01-01202310.1155/2023/6643649Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of InterestI Gede Brawiswa Putra0Pei-Fen Kuo1Dominique Lord2Department of GeomaticsDepartment of GeomaticsZachry Department of Civil and Environmental EngineeringThe COVID-19 pandemic has increased the demand for online food delivery services (OFDS), leading to an increase in related crashes over the last few years. While recent studies have focused on nonmotorised vehicles (such as bicycles or e-bikes), few researchers have examined the role of motorcycles and the possible spatial relationships with various points of interest (POIs). In addition, most crash and POIs studies have utilized typical restaurant datasets instead of specific restaurants partnered with OFDS, which might bias the impact of traffic safety estimation. To address these gaps, a geographically weighted negative binomial model (GWNBR) was used to determine the factors contributing to OFDS-related motorcycle accidents and account for spatial heterogeneity. The results indicated that areas with more restaurants, intersections, and shopping malls (only significant on weekends) tended to have more OFDS motorcycle crashes. The results should inspire more effective policies for delivery drivers, given the increasing popularity of OFDS.http://dx.doi.org/10.1155/2023/6643649 |
| spellingShingle | I Gede Brawiswa Putra Pei-Fen Kuo Dominique Lord Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of Interest Journal of Advanced Transportation |
| title | Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of Interest |
| title_full | Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of Interest |
| title_fullStr | Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of Interest |
| title_full_unstemmed | Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of Interest |
| title_short | Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of Interest |
| title_sort | local spatial analysis of the crash frequency of food delivery motorcyclists vs nondelivery motorcyclists in relation to points of interest |
| url | http://dx.doi.org/10.1155/2023/6643649 |
| work_keys_str_mv | AT igedebrawiswaputra localspatialanalysisofthecrashfrequencyoffooddeliverymotorcyclistsvsnondeliverymotorcyclistsinrelationtopointsofinterest AT peifenkuo localspatialanalysisofthecrashfrequencyoffooddeliverymotorcyclistsvsnondeliverymotorcyclistsinrelationtopointsofinterest AT dominiquelord localspatialanalysisofthecrashfrequencyoffooddeliverymotorcyclistsvsnondeliverymotorcyclistsinrelationtopointsofinterest |