Route choice stickiness of public transport passengers: Measuring habitual bus ridership behaviour using smart card data

Kim, Jiwon; Corcoran, Jonathan; Papamanolis, Marty

doi:10.1016/j.trc.2017.08.005

Cited by 73 publications

(38 citation statements)

References 32 publications

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“…quartiles according to the conventions of disease mapping (70)(71)(72). Again the quantile regression was iterated for each week using formula 2 (69):…”

Section: Methodsmentioning

confidence: 99%

The Socio-Spatial Determinants of COVID-19 Diffusion: The Impact of Globalisation, Settlement Characteristics and Population

Sigler

Mahmuda

Kimpton

et al. 2020

Preprint

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Background: COVID-19 is an emergent infectious disease that has spread geographically to become a global pandemic. While much research focuses on the epidemiological and virological aspects of the COVID-19 transmission, there remains a gap in knowledge regarding the drivers of geographical diffusion between places. Here, we use quantile regression to model the roles of globalisation, human settlement and population characteristics as socio-spatial determinants of COVID-19 diffusion over a six-week period in March and April 2020. Results: The quantile regression model suggest that globalisation and settlement population characteristics related to high human mobility predict disease diffusion. Human development level (HDI) and total population predict COVID-19 diffusion in countries with a high number of total confirmed cases per million whereas larger household size, older populations, and globalisation tied to human interaction predict COVID-19 diffusion in countries with a low number of total confirmed cases per million. Conclusions: The analysis confirms that globalisation, settlement and population characteristics lead to greater disease diffusion, and primarily variables tied to high human mobility. These outcomes serve to inform policies around ‘flattening the curve’, particularly as they related to anticipated relocation diffusion from more- to less-developed countries and regions, and hierarchical diffusion from countries with higher population and density. Epidemiological strategies must be tailored to suit the range of human mobility patterns, as well as the variety of settlement and population characteristics.

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“…quartiles according to the conventions of disease mapping (70)(71)(72). Again the quantile regression was iterated for each week using formula 2 (69):…”

Section: Methodsmentioning

confidence: 99%

The Socio-Spatial Determinants of COVID-19 Diffusion: The Impact of Globalisation, Settlement Characteristics and Population

Sigler

Mahmuda

Kimpton

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…, 50th, 75th, and 90th quartiles according to the conventions of disease mapping(66)(67)(68). Again the quantile regression was iterated for each week using formula 2The output tables for these regression models in Additional Files 1-6.…”

mentioning

confidence: 99%

The Socio-Spatial Determinants of COVID-19 Diffusion: The Impact of Globalisation, Settlement Characteristics and Population

Sigler

Mahmuda

Kimpton

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Background: COVID-19 is an emergent infectious disease that has spread geographically to become a global pandemic. While much research focuses on the epidemiological and virological aspects of the COVID-19 transmission, there remains a gap in knowledge regarding the drivers of geographical diffusion between places. Here, we use quantile regression to model the roles of globalisation, human settlement and population characteristics as socio-spatial determinants of COVID-19 diffusion over a six-week period in March and April 2020.Results: The quantile regression model suggest that globalisation and settlement population characteristics related to high human mobility predict disease diffusion. Human development level (HDI) and total population predict COVID-19 diffusion in countries with a high number of total confirmed cases per million whereas larger household size, older populations, and globalisation tied to human interaction predict COVID-19 diffusion in countries with a low number of total confirmed cases per million. Conclusions: The analysis confirms that globalisation, settlement and population characteristics lead to greater disease diffusion, and primarily variables tied to high human mobility. These outcomes serve to inform policies around ‘flattening the curve’, particularly as they related to anticipated relocation diffusion from more- to less-developed countries and regions, and hierarchical diffusion from countries with higher population and density. Epidemiological strategies must be tailored to suit the range of human mobility patterns, as well as the variety of settlement and population characteristics.

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“…With the provision of traffic information or route guidance along the trip, dynamic rerouting behaviour is prevalent under stochastic travel conditions (Zhao, et al, 2017;Xu, et al, 2017). As indicated in the empirical study by Kim et al (2017), passengers would present lower stickiness on the same route with the increase in the number of alternative routes. The performance of transit operation is highly related to the temporal and spatial passenger flow distribution and running fleet (Liu and Singha, 2007;Sorrantina et al, 2006;Wu et al, 2017).…”

Section: Introductionmentioning

confidence: 76%

Stochastic bus schedule coordination considering demand assignment and rerouting of passengers

Liu

Jin

et al. 2019

Transportation Research Part B: Methodological

111

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Route choice stickiness of public transport passengers: Measuring habitual bus ridership behaviour using smart card data

Cited by 73 publications

References 32 publications

The Socio-Spatial Determinants of COVID-19 Diffusion: The Impact of Globalisation, Settlement Characteristics and Population

The Socio-Spatial Determinants of COVID-19 Diffusion: The Impact of Globalisation, Settlement Characteristics and Population

The Socio-Spatial Determinants of COVID-19 Diffusion: The Impact of Globalisation, Settlement Characteristics and Population

Stochastic bus schedule coordination considering demand assignment and rerouting of passengers

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