Determinants of Vehicle Ownership in the Greater Tamale Area, Ghana

Existing models of vehicle ownership in most developing countries, such as Ghana, are aggregate models which explain the factors that contribute to the rise in individual vehicle ownership. In fact, disaggregate models would be a better approach than aggregate models, but the latter is often adopted as a result of inadequate data on individual vehicle ownership. This study attempts to fill this gap by developing a disaggregate model to analyze the factors influencing the rise of private vehicle ownership (motorcycles and cars) in Ghana using the Greater Tamale Area (GTA) as the case study. We approach this by using recently collected data on a cross-section of workers within the city with average monthly incomes, distances to work, perceptions of the provision of non-motorized infrastructure, and sociodemographic factors as the explanatory variables. The findings show that a higher average monthly income, a greater traveling distance to work, a perception that the provision of non-motorized infrastructure is inadequate, increasing age, being married, and being male correlate with a higher likelihood of owning a car or a motorcycle, while living within 2 km of the Central Business District (CBD) correlates with a lower likelihood of car ownership but a higher likelihood of motorcycle ownership. The determination of these factors will help the government to develop policies that will improve mobility but reduce private vehicle dependency.

Masked Heterogeneity in Aggregation: Incorporating Beliefs and Geographic Information into Consumer Willingness to Pay for State Brands

State marketing programs for food and agricultural products are largely driven by consumers’ desires to purchase in-state products. Evaluations of state marketing programs have largely ignored consumer location and proximity to surrounding states, measures of ethnocentrism, and the presence of other geographic marketing labels. This study examines willingness to pay for own and out-of-state labels for a generic commodity, milk, within an eight-state region. The results show that an aggregate model conceals consumer heterogeneity in marginal willingness to pay values for state brands as compared to a disaggregate model, even when using random parameter logit models.

Research on Public Bicycle Traffic Mode Choice Based on Disaggregate Model

First, four transportation forecasting methods were analyzed, and these characteristics and applicable conditions were summarized, so we can conclude that the disaggregate model is more suitable to predict the public bicycle traffic mode choice. Secondly, the utility function model of bike, bus and motor vehicle was established to determine the utility of each traffic mode and predict the share rate by disaggregate function model. Finally, the analysis of public bicycle transportation impact factors through an example, and gives quantitative indicators.