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- W652086306 abstract "Parking search creates environmental and economic externalities through heightened vehicle pollutant emissions, congestion-related time delays and safety hazards arising from drivers performing on-street parking manoeuvres. Current modelling techniques applied to parking search time have not utilised a more comprehensive analysis in which hierarchically structured data on multiple levels could be addressed. The aim of this paper is to identify factors influencing parking search time using multilevel mixed-effects linear regression models. A revealed-preference on-street parking survey (N=1,003) was undertaken in four cities in the East Midlands region of the UK to obtain individual driver-level socioeconomic and other parking related factors that may influence parking search time. Statistically significant variables for each of the cities were identified by employing separate linear regression models. A multilevel mixed-effects model in which drivers are nested within streets was then applied to the pooled dataset. Significant differences in the set of statistically significant variables and coefficient values of influencing factors between the two modelling approaches were obtained. A large value of intra-class coefficient (ICC) indicates that the use of a multilevel model in identifying the factors affecting on-street parking search time is more appropriate. Important factors were identified as: arrival time at parking place; trip length from origin to parking; parking habits; driver stress; walking distance from parking to destination; parking tariff; income; and weather. Interpretation of these variables has been presented." @default.
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- W652086306 date "2015-01-01" @default.
- W652086306 modified "2023-09-23" @default.
- W652086306 title "Factors Influencing Parking Search Time Using Multilevel Modeling: A Case Study of East Midlands, UK" @default.
- W652086306 hasPublicationYear "2015" @default.
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