University of Oulu

Oluwafemi Samson BALOGUN, Sunday Adewale OLALEYE, Xiao-Zhi GAO, and Pekka TOIVANEN “Concomitant with Nigerian Road Traffic Accidents: An Application of a Generalized Linear Model” Proceedings of the 37th International Business Information Management Association (IBIMA), ISBN: 978-0-9998551-6-4, 1-2 April 2021, Cordoba, Spain

Concomitant with Nigerian road traffic accidents : an application of a generalized linear model

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Author: Balogun, Oluwafemi Samson1; Olaleye, Sunday Adewale2; Gao, Xiao-Zhi1;
Organizations: 1School of Computing, University of Eastern, Finland
2Department of Marketing, Management and International Business, University of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.1 MB)
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Language: English
Published: International Business Information Management Association, 2021
Publish Date: 2021-05-18


This study aims to apply a generalized linear model for investigating the relationship between road traffic accidents and the resulting fatalities in Nigeria. The main objectives are to determine the most suitable model fits, compare the models used, and examine the relationship between the total cases and log deaths by modelling the number of road traffic accidents in Nigeria. The study adopts Poisson regression and negative binomial regression model for data analysis to achieve the set goals. The data used for this research are secondary data collected from annual reports on road traffic accidents of the Federal Road Safety Commission of Nigeria between 1960 and 2017. The study establishes that the number of traffic accidents on roads in Nigeria is continually increasing, and efforts by the government and relevant agencies have been mostly unsuccessful in addressing this danger. Moreover, the highly dangerous conditions on Nigerian roads result in a daily loss of innocent lives that otherwise would have significantly contributed to economic growth.

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Series: International Business Information Management Association Conference
ISSN: 2767-9640
ISSN-E: 2767-9640
ISSN-L: 2767-9640
ISBN: 978-0-9998551-6-4
Pages: 1040 - 1055
Host publication: Proceedings of the 37th International Business Information Management Association (IBIMA)
Conference: IBIMA Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 112 Statistics and probability
113 Computer and information sciences
3142 Public health care science, environmental and occupational health
Copyright information: © 2021 The Authors. Published by International business information management association. Creative Commons Attribution License 4.0 Unported.