Motorcycle ownership modesl were formulated using Poisson Regression and Negative binomial logist... more Motorcycle ownership modesl were formulated using Poisson Regression and Negative binomial logistic regression models. Three different zones were selected and classified based on their population density. Data which include factors affecting the ownership of motorcycles were collected by administering well structured questionnaires to the respondents. Data obtained were analyzed with Statistical Package for Social Sciences version 22 (SPSS 22) to formulate predictive models. The two models show quite similar results as they both show that the number of motorcycles owned will reduce as educational status of the rider and average monthly income of household increases while there will be an increase in the number of motorcycles owned as the age range of the rider increases. The number of motorcycles owned is increased by 1.5 times for the lowest income category and 0.4times for the secondary education category; but this is reduced by 0.54 times for the highest age range of household head category. The test of model effects shows that all the predictor variables are significant. The results of the study will be helpful in low cost transportation planning for the study area.
Article Info Abstract Keywords: Binomial Logistic Regression Density Household Motorcycle Transpo... more Article Info Abstract Keywords: Binomial Logistic Regression Density Household Motorcycle Transportation In order to forecast and make provisions for future demand of motorcycle in Akure, there is a need to understand factors driving motorcycle ownership, therefore, this study examines factors which affect motorcycle ownership in Akure metropolis. Three different zones namely, Low Density (LD), Medium Density (MD) and High Density (HD) were considered,, both close-ended and open-ended questionnaire were administered to 900 households representing 75% of the total population. Using Statistical Package for Social Sciences version 16 data were analyzed and binomial logistic regression analysis was used in developing a model which showed that only academic qualification of household head, number of household members and average monthly income of household significantly influences motorcycle ownership across the zones at the 95% confidence level. Both average monthly income of household and academic qualification of household head had a negative influence on motorcycle ownership whereas number of household members had a positive relationship with motorcycle ownership. The results shows that there is a 1.43 times likelihood of owning a motorcycle with a unit increase in the number of household members, while there is a reduction in the likelihood of owning a motorcycle by 1.66 times and 2.17 times for a unit increase in the average monthly income and academic qualification of household head respectively. The results obtained can be used in developing policy framework to improve public transport and control motorcycle ownership in the city of Akure.
Motorcycle ownership modesl were formulated using Poisson Regression and Negative binomial logist... more Motorcycle ownership modesl were formulated using Poisson Regression and Negative binomial logistic regression models. Three different zones were selected and classified based on their population density. Data which include factors affecting the ownership of motorcycles were collected by administering well structured questionnaires to the respondents. Data obtained were analyzed with Statistical Package for Social Sciences version 22 (SPSS 22) to formulate predictive models. The two models show quite similar results as they both show that the number of motorcycles owned will reduce as educational status of the rider and average monthly income of household increases while there will be an increase in the number of motorcycles owned as the age range of the rider increases. The number of motorcycles owned is increased by 1.5 times for the lowest income category and 0.4times for the secondary education category; but this is reduced by 0.54 times for the highest age range of household head category. The test of model effects shows that all the predictor variables are significant. The results of the study will be helpful in low cost transportation planning for the study area.
In order to forecast and make provisions for future demand of motorcycle in Akure, there is a ne... more In order to forecast and make provisions for future demand of motorcycle in Akure, there is a need to understand factors driving motorcycle ownership, therefore, this study examines factors which affect motorcycle ownership in Akure metropolis. Three different zones namely, Low Density (LD), Medium Density (MD) and High Density (HD) were considered,, both close-ended and open-ended questionnaire were administered to 900 households representing 75% of the total population. Using Statistical Package for Social Sciences version 16 data were analyzed and binomial logistic regression analysis was used in developing a model which showed that only academic qualification of household head, number of household members and average monthly income of household significantly influences motorcycle ownership across the zones at the 95% confidence level. Both average monthly income of household and academic qualification of household head had a negative influence on motorcycle ownership whereas number of household members had a positive relationship with motorcycle ownership. The results shows that there is a 1.43 times likelihood of owning a motorcycle with a unit increase in the number of household members, while there is a reduction in the likelihood of owning a motorcycle by 1.66 times and 2.17 times for a unit increase in the average monthly income and academic qualification of household head respectively. The results obtained can be used in developing policy framework to improve public transport and control motorcycle ownership in the city of Akure.
Motorcycle ownership modesl were formulated using Poisson Regression and Negative binomial logist... more Motorcycle ownership modesl were formulated using Poisson Regression and Negative binomial logistic regression models. Three different zones were selected and classified based on their population density. Data which include factors affecting the ownership of motorcycles were collected by administering well structured questionnaires to the respondents. Data obtained were analyzed with Statistical Package for Social Sciences version 22 (SPSS 22) to formulate predictive models. The two models show quite similar results as they both show that the number of motorcycles owned will reduce as educational status of the rider and average monthly income of household increases while there will be an increase in the number of motorcycles owned as the age range of the rider increases. The number of motorcycles owned is increased by 1.5 times for the lowest income category and 0.4times for the secondary education category; but this is reduced by 0.54 times for the highest age range of household head category. The test of model effects shows that all the predictor variables are significant. The results of the study will be helpful in low cost transportation planning for the study area.
Article Info Abstract Keywords: Binomial Logistic Regression Density Household Motorcycle Transpo... more Article Info Abstract Keywords: Binomial Logistic Regression Density Household Motorcycle Transportation In order to forecast and make provisions for future demand of motorcycle in Akure, there is a need to understand factors driving motorcycle ownership, therefore, this study examines factors which affect motorcycle ownership in Akure metropolis. Three different zones namely, Low Density (LD), Medium Density (MD) and High Density (HD) were considered,, both close-ended and open-ended questionnaire were administered to 900 households representing 75% of the total population. Using Statistical Package for Social Sciences version 16 data were analyzed and binomial logistic regression analysis was used in developing a model which showed that only academic qualification of household head, number of household members and average monthly income of household significantly influences motorcycle ownership across the zones at the 95% confidence level. Both average monthly income of household and academic qualification of household head had a negative influence on motorcycle ownership whereas number of household members had a positive relationship with motorcycle ownership. The results shows that there is a 1.43 times likelihood of owning a motorcycle with a unit increase in the number of household members, while there is a reduction in the likelihood of owning a motorcycle by 1.66 times and 2.17 times for a unit increase in the average monthly income and academic qualification of household head respectively. The results obtained can be used in developing policy framework to improve public transport and control motorcycle ownership in the city of Akure.
Motorcycle ownership modesl were formulated using Poisson Regression and Negative binomial logist... more Motorcycle ownership modesl were formulated using Poisson Regression and Negative binomial logistic regression models. Three different zones were selected and classified based on their population density. Data which include factors affecting the ownership of motorcycles were collected by administering well structured questionnaires to the respondents. Data obtained were analyzed with Statistical Package for Social Sciences version 22 (SPSS 22) to formulate predictive models. The two models show quite similar results as they both show that the number of motorcycles owned will reduce as educational status of the rider and average monthly income of household increases while there will be an increase in the number of motorcycles owned as the age range of the rider increases. The number of motorcycles owned is increased by 1.5 times for the lowest income category and 0.4times for the secondary education category; but this is reduced by 0.54 times for the highest age range of household head category. The test of model effects shows that all the predictor variables are significant. The results of the study will be helpful in low cost transportation planning for the study area.
In order to forecast and make provisions for future demand of motorcycle in Akure, there is a ne... more In order to forecast and make provisions for future demand of motorcycle in Akure, there is a need to understand factors driving motorcycle ownership, therefore, this study examines factors which affect motorcycle ownership in Akure metropolis. Three different zones namely, Low Density (LD), Medium Density (MD) and High Density (HD) were considered,, both close-ended and open-ended questionnaire were administered to 900 households representing 75% of the total population. Using Statistical Package for Social Sciences version 16 data were analyzed and binomial logistic regression analysis was used in developing a model which showed that only academic qualification of household head, number of household members and average monthly income of household significantly influences motorcycle ownership across the zones at the 95% confidence level. Both average monthly income of household and academic qualification of household head had a negative influence on motorcycle ownership whereas number of household members had a positive relationship with motorcycle ownership. The results shows that there is a 1.43 times likelihood of owning a motorcycle with a unit increase in the number of household members, while there is a reduction in the likelihood of owning a motorcycle by 1.66 times and 2.17 times for a unit increase in the average monthly income and academic qualification of household head respectively. The results obtained can be used in developing policy framework to improve public transport and control motorcycle ownership in the city of Akure.
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