الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
 |  | from | 78 |  |  |
| | | from | 78 | | |
Abstract
Car ownership plays a key role in the travel decisions made by households. The travel forecasting procedures in many urban areas include car ownership as an independent variable in trip generation and mode choice. This study determined factors that influence car ownership intending to develop a more appropriate basis for its forecasting. The variables that influence car ownership are selected based on the findings of the previous studies. The explanatory variables include three categories: Economic, socio-demographic, and urbanization (and Public transportation availability). Economic variables include income (GDP per capita and disposable income per capita) and car expenses. Socio-demographic variables are basically about household such as size, age structure, age and type of household head, number of workers, number of drivers (licenses) and the literacy level. Urbanization includes residential location urbanization, population density and public transportation such as bus, taxi, tram, train, subways and other alternative (access to other alternative). The study also compiled the types of data and models used to develop car ownership. In terms of details, the data is divided into aggregate and disaggregate data. The data is also divided based on their relation to time into panel data, time series and cross sectional data. The models types are also categorized into logit and regression. The moving average and the cohort-based models are also addressed as special model type. The study also incorporated the calibration of simple car ownership model using multiple regression technique based on the available aggregate and cross sectional time series data over several years. The study concluded with a complete numeration of factors affecting car ownership and clear categorization of the data and model types. The study also made recommendations about maintaining the car ownership data in Egypt (mostly aggregate data) and the surveying techniques that should be used if a disaggregate and more accurate car ownership model needs to be developed in the future.