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.

Improving Analytical Procedures: A Case of Using Disaggregate Multilocation Data

According to SAS No. 56, Analytical Procedures, the use of disaggregate, individual location data can improve the effectiveness of analytical procedures used in multilocation audits. Using a case-study approach, we investigate whether improvements in the accuracy and precision of account balance expectations can be obtained by using disaggregate, individual location data in a large, multilocation company. Specifically, we examine two issues: (1) whether the summation of individual location expectations generates more accurate and precise expectations of company-wide account balances than expectations based on company-wide data only and (2) whether the accuracy and precision of analytical procedures is enhanced by including peer location observations of the account balance in individual location expectation models. We find that for the multilocation company examined in this case study the summation of individual location account balance expectations is not more accurate or precise than an expectation derived from aggregate models unless the individual location models include peer location observations of the account balance. When the individual location models include the same account observations from other peer locations within the company, the company-wide account balance expectations developed from disaggregate models are more accurate and precise (less variable) than expectations developed using aggregate, company-wide data only. The results from this case study indicate that when auditors are generating expectations of company-wide balances, disaggregate models incorporating peer location account observations provide account balance expectations that are both more accurate and more precise than company-wide, aggregate models. Given the limitations of a case-study approach, future research should be directed at establishing the generalizability of these findings.

Disaggregate Safety Performance Models for Signalized Intersections on Ontario Provincial Roads

The more advanced methods for identifying unsafe intersections and evaluating the safety effect of treatment are based on an Empirical Bayesian framework that requires the use of safety performance functions relating the expected safety of an intersection to characteristics such as traffic flow. Aggregate and disaggregate models were developed to estimate the safety performance of three-legged and four-legged signalized intersections on Ontario provincial roads. Models were disaggregated by time period, accident severity, and environment class. Two levels of models were calibrated for different levels of data availability and model requirements. For Level 1, the safety of an intersection was estimated as a function of the sum of all entering flows; separate estimates were obtained for rear-end, right angle, and turning movement accidents, the three most prominent impact types. In Level 2, specific patterns were defined by the movements of involved vehicles prior to collision, and accidents for the main patterns at four-legged intersections were estimated as a function of flows relevant to each pattern. Aside from the theoretical aspects, the models provide a basis for comparison with available models for other jurisdictions. There are some novel aspects in that, unlike most models available for roads outside municipalities, the ones presented here do allow for safety estimates to be disaggregated by time period, accident severity, impact type, and accident pattern. Moreover, the calibrated models can be used in an Empirical Bayesian framework to estimate the safety of an individual intersection. This is an important feature generally lacking in available models.

Disaggregate mode choice models for intercity passenger travel in Canada

Disaggregate mode choice models were calibrated for intercity passenger travel in Canada using a data base drawn from the Canadian Travel Survey. Multinomial logit models were calibrated for business and nonbusiness trips in the eastern and the western regions of Canada. The calibrated models produced reliable results in terms of goodness-of-fit measures. The likelihood ratio index, ρ2(c), varied from 0.282 to 0.436. Results obtained were comparable to those of previous studies. The research identified the significance of level-of-service factors in determining mode choice. The findings from the study indicated that the Canadian Travel Survey data could be used for developing disaggregate models for possible use in policy impact analysis. The potential for the use of this data base in the transportation planning process could be enhanced if some relatively minor modifications were made. Key words: models, disaggregate, choice, intercity, passenger, travel time, cost, frequency, service.