Mostafa Jafarzadehfadaki , Virginia P. Sisiopiku , Wencui Yang , Dimitra Michalaka , Kweku Tekyi Brown , William J. Davis , Jalal Khalil , Da Yan
{"title":"阿拉巴马州伯明翰市人口特征和土地使用模式的时空模式及其对微型交通工具乘客数量的影响","authors":"Mostafa Jafarzadehfadaki , Virginia P. Sisiopiku , Wencui Yang , Dimitra Michalaka , Kweku Tekyi Brown , William J. Davis , Jalal Khalil , Da Yan","doi":"10.1016/j.multra.2024.100140","DOIUrl":null,"url":null,"abstract":"<div><p>The rise of the sharing economy in recent years led to changes in transportation service delivery, including the introduction of micromobility services. Case studies are needed to better understand determinants of micromobility mode choice and its impacts on transportation operations. This study used data from a micromobility pilot program in Birmingham, Alabama to analyze spatiotemporal demand variations and explore correlations between micromobility ridership and demographic characteristics and land use patterns. Using space-time pattern mining techniques, temporal and spatial variations in micromobility usage were confirmed, with peak usage observed on Fridays, Saturdays and Sundays, during afternoon and evening hours, and during warmer months. Spatial analysis employed Kernel Density techniques and revealed concentrated micromobility trip origins in high-density areas such as Railroad Park, downtown, the University of Alabama at Birmingham (UAB) campus, and the Five Points South neighborhood. Correlations between Birmingham micromobility ridership and demographic characteristics and land use patterns were studied using clustering approaches and a multilevel negative binomial model. The model identified significant positive associations between micromobility ridership and the younger population (18–34 years of age), with a negative association in the 45–54 age group, signaling a decline in usage among older individuals. Regarding land uses, the model results showed significant positive correlations with the presence of park areas and commercial, residential, and industrial land uses, and the university campus. Furthermore, a positive correlation was observed with the National Walkability Index and parking facilities, whereas increased distance from the city center was associated with reduced micromobility ridership. The study offers valuable insights that can assist decision and policymakers in Birmingham as well as other medium-sized cities, in planning, and implementing micromobility programs that serve the local needs.</p></div>","PeriodicalId":100933,"journal":{"name":"Multimodal Transportation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772586324000212/pdfft?md5=3115ae4e352e0bba8fda1b65d887df2c&pid=1-s2.0-S2772586324000212-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Spatiotemporal patterns and influences of demographic characteristics and land use patterns on micromobility ridership in Birmingham, Alabama\",\"authors\":\"Mostafa Jafarzadehfadaki , Virginia P. Sisiopiku , Wencui Yang , Dimitra Michalaka , Kweku Tekyi Brown , William J. Davis , Jalal Khalil , Da Yan\",\"doi\":\"10.1016/j.multra.2024.100140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The rise of the sharing economy in recent years led to changes in transportation service delivery, including the introduction of micromobility services. Case studies are needed to better understand determinants of micromobility mode choice and its impacts on transportation operations. This study used data from a micromobility pilot program in Birmingham, Alabama to analyze spatiotemporal demand variations and explore correlations between micromobility ridership and demographic characteristics and land use patterns. Using space-time pattern mining techniques, temporal and spatial variations in micromobility usage were confirmed, with peak usage observed on Fridays, Saturdays and Sundays, during afternoon and evening hours, and during warmer months. Spatial analysis employed Kernel Density techniques and revealed concentrated micromobility trip origins in high-density areas such as Railroad Park, downtown, the University of Alabama at Birmingham (UAB) campus, and the Five Points South neighborhood. Correlations between Birmingham micromobility ridership and demographic characteristics and land use patterns were studied using clustering approaches and a multilevel negative binomial model. The model identified significant positive associations between micromobility ridership and the younger population (18–34 years of age), with a negative association in the 45–54 age group, signaling a decline in usage among older individuals. Regarding land uses, the model results showed significant positive correlations with the presence of park areas and commercial, residential, and industrial land uses, and the university campus. Furthermore, a positive correlation was observed with the National Walkability Index and parking facilities, whereas increased distance from the city center was associated with reduced micromobility ridership. The study offers valuable insights that can assist decision and policymakers in Birmingham as well as other medium-sized cities, in planning, and implementing micromobility programs that serve the local needs.</p></div>\",\"PeriodicalId\":100933,\"journal\":{\"name\":\"Multimodal Transportation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772586324000212/pdfft?md5=3115ae4e352e0bba8fda1b65d887df2c&pid=1-s2.0-S2772586324000212-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Multimodal Transportation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772586324000212\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimodal Transportation","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772586324000212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spatiotemporal patterns and influences of demographic characteristics and land use patterns on micromobility ridership in Birmingham, Alabama
The rise of the sharing economy in recent years led to changes in transportation service delivery, including the introduction of micromobility services. Case studies are needed to better understand determinants of micromobility mode choice and its impacts on transportation operations. This study used data from a micromobility pilot program in Birmingham, Alabama to analyze spatiotemporal demand variations and explore correlations between micromobility ridership and demographic characteristics and land use patterns. Using space-time pattern mining techniques, temporal and spatial variations in micromobility usage were confirmed, with peak usage observed on Fridays, Saturdays and Sundays, during afternoon and evening hours, and during warmer months. Spatial analysis employed Kernel Density techniques and revealed concentrated micromobility trip origins in high-density areas such as Railroad Park, downtown, the University of Alabama at Birmingham (UAB) campus, and the Five Points South neighborhood. Correlations between Birmingham micromobility ridership and demographic characteristics and land use patterns were studied using clustering approaches and a multilevel negative binomial model. The model identified significant positive associations between micromobility ridership and the younger population (18–34 years of age), with a negative association in the 45–54 age group, signaling a decline in usage among older individuals. Regarding land uses, the model results showed significant positive correlations with the presence of park areas and commercial, residential, and industrial land uses, and the university campus. Furthermore, a positive correlation was observed with the National Walkability Index and parking facilities, whereas increased distance from the city center was associated with reduced micromobility ridership. The study offers valuable insights that can assist decision and policymakers in Birmingham as well as other medium-sized cities, in planning, and implementing micromobility programs that serve the local needs.