Matches in SemOpenAlex for { <https://semopenalex.org/work/W4381663102> ?p ?o ?g. }
- W4381663102 endingPage "958" @default.
- W4381663102 startingPage "958" @default.
- W4381663102 abstract "Describing travel patterns and identifying significant locations is a crucial area of research in transportation geography and social dynamics. Our study aims to contribute to this field by analyzing taxi trip data from Chengdu and New York City. Specifically, we investigate the probability density distribution of trip distance in each city, which enables us to construct long- and short-distance trip networks. To identify critical nodes within these networks, we employ the PageRank algorithm and categorize them using centrality and participation indices. Furthermore, we explore the factors that contribute to their influence and observe a clear hierarchical multi-centre structure in Chengdu's trip networks, while no such phenomenon is evident in New York City's. Our study provides insight into the impact of trip distance on important nodes within trip networks in both cities and serves as a reference for distinguishing between long and short taxi trips. Our findings also reveal substantial differences in network structures between the two cities, highlighting the nuanced relationship between network structure and socio-economic factors. Ultimately, our research sheds light on the underlying mechanisms shaping transportation networks in urban areas and offers valuable insights into urban planning and policy making." @default.
- W4381663102 created "2023-06-23" @default.
- W4381663102 creator A5012846566 @default.
- W4381663102 creator A5032738927 @default.
- W4381663102 creator A5032838695 @default.
- W4381663102 creator A5034595624 @default.
- W4381663102 creator A5090925242 @default.
- W4381663102 date "2023-06-20" @default.
- W4381663102 modified "2023-10-05" @default.
- W4381663102 title "Identifying Important Nodes in Trip Networks and Investigating Their Determinants" @default.
- W4381663102 cites W1595544516 @default.
- W4381663102 cites W1970070993 @default.
- W4381663102 cites W1972309850 @default.
- W4381663102 cites W1974080240 @default.
- W4381663102 cites W1982300822 @default.
- W4381663102 cites W1988580225 @default.
- W4381663102 cites W2008620264 @default.
- W4381663102 cites W2014511119 @default.
- W4381663102 cites W2021333958 @default.
- W4381663102 cites W2021674713 @default.
- W4381663102 cites W2024177114 @default.
- W4381663102 cites W2039350330 @default.
- W4381663102 cites W2049176600 @default.
- W4381663102 cites W2052169465 @default.
- W4381663102 cites W2056284729 @default.
- W4381663102 cites W2063680947 @default.
- W4381663102 cites W2082729958 @default.
- W4381663102 cites W2091223625 @default.
- W4381663102 cites W2112090702 @default.
- W4381663102 cites W2112615110 @default.
- W4381663102 cites W2114733299 @default.
- W4381663102 cites W2118275987 @default.
- W4381663102 cites W2124637492 @default.
- W4381663102 cites W2133286823 @default.
- W4381663102 cites W2133400794 @default.
- W4381663102 cites W2148604310 @default.
- W4381663102 cites W2148606196 @default.
- W4381663102 cites W2148641067 @default.
- W4381663102 cites W2154056116 @default.
- W4381663102 cites W2166292977 @default.
- W4381663102 cites W2337281148 @default.
- W4381663102 cites W2398561167 @default.
- W4381663102 cites W2766311542 @default.
- W4381663102 cites W2789474340 @default.
- W4381663102 cites W2791677100 @default.
- W4381663102 cites W2803241079 @default.
- W4381663102 cites W2808583541 @default.
- W4381663102 cites W2965695285 @default.
- W4381663102 cites W2987340650 @default.
- W4381663102 cites W2990801024 @default.
- W4381663102 cites W3028110392 @default.
- W4381663102 cites W3034085708 @default.
- W4381663102 cites W3111020351 @default.
- W4381663102 cites W3149700931 @default.
- W4381663102 cites W3158431285 @default.
- W4381663102 cites W3186943418 @default.
- W4381663102 cites W387207231 @default.
- W4381663102 cites W4225966352 @default.
- W4381663102 cites W4235571646 @default.
- W4381663102 cites W4295836091 @default.
- W4381663102 cites W4310834699 @default.
- W4381663102 cites W4312115719 @default.
- W4381663102 doi "https://doi.org/10.3390/e25060958" @default.
- W4381663102 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37372303" @default.
- W4381663102 hasPublicationYear "2023" @default.
- W4381663102 type Work @default.
- W4381663102 citedByCount "1" @default.
- W4381663102 countsByYear W43816631022023 @default.
- W4381663102 crossrefType "journal-article" @default.
- W4381663102 hasAuthorship W4381663102A5012846566 @default.
- W4381663102 hasAuthorship W4381663102A5032738927 @default.
- W4381663102 hasAuthorship W4381663102A5032838695 @default.
- W4381663102 hasAuthorship W4381663102A5034595624 @default.
- W4381663102 hasAuthorship W4381663102A5090925242 @default.
- W4381663102 hasBestOaLocation W43816631021 @default.
- W4381663102 hasConcept C114614502 @default.
- W4381663102 hasConcept C127413603 @default.
- W4381663102 hasConcept C136764020 @default.
- W4381663102 hasConcept C137753397 @default.
- W4381663102 hasConcept C148383697 @default.
- W4381663102 hasConcept C154945302 @default.
- W4381663102 hasConcept C157085824 @default.
- W4381663102 hasConcept C173608175 @default.
- W4381663102 hasConcept C202444582 @default.
- W4381663102 hasConcept C205649164 @default.
- W4381663102 hasConcept C22212356 @default.
- W4381663102 hasConcept C2522767166 @default.
- W4381663102 hasConcept C26271046 @default.
- W4381663102 hasConcept C2779172887 @default.
- W4381663102 hasConcept C2780801425 @default.
- W4381663102 hasConcept C31258907 @default.
- W4381663102 hasConcept C33923547 @default.
- W4381663102 hasConcept C34947359 @default.
- W4381663102 hasConcept C41008148 @default.
- W4381663102 hasConcept C53811970 @default.
- W4381663102 hasConcept C80444323 @default.
- W4381663102 hasConcept C94124525 @default.
- W4381663102 hasConcept C9652623 @default.