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EN
The study aims to estimate the air travel demand forecast for domestic passengers' travels in Nigeria from 2002-2016. Data resourced from the Central Bank of Nigeria, the National Bureau of Statistics, and the Federal Airport Authority of Nigeria. The study utilized a multiple regression model using a Stata-Graphic software solver to analyze the data. From the analysis, the result shows that there is a significant relationship between the explanatory variable (passengers) and unexplanatory variables National Disposable Income, Population, Average Airfare, Gross Domestic Product, Exchange Rate, Total Expenditure, and Crude oil price, accounted for adjusted R of 93.624% relationship with demand for domestic air travel of passenger. The R-square statistic shows that the fitted model explains the variability in the number of passengers (NPAX), which is 96.8124%. The Hypothesis testing reveals that National Disposable Income and Airfare have a strong statistically significant relationship with the demand for domestic air travel with a P-value of 0.0013. Mores, a statistically significant relationship exists between National Disposable Income, Average airfare, and Crude oil price with P-values of 0.0017 and 0.0445, respectively. Furthermore, a forecast of the number of passengers and average airfare was carried out using ARIMA (1,0,0) model, which made available the future predicted values for the number of passenger movements and average airfare for the next 10-12 years to come. Thus, the study recommends that stakeholders in the air transport sector should work towards improving the capacity and infrastructure to accommodate the growth of air travel demand for domestic air travel in Nigeria. Policy implications were made on regulating the sector by having a good pricing policy to control the air fare for the industry.
EN
This study assesses the operational safety and security of a category one airport in Nigeria, using the Nnamdi Azikiwe International Airport, Abuja (NAIA) as the case study airport. Data were sourced using structured questionnaire and oral interviews. A total of 180 questionnaires were administered and 165 questionnaires were retrieved, amounting to a 91.7% rate of response. The structured questionnaire used aimed at identifying various safety and security parameters in the study area. This study examined the trend of the effectiveness of safety and security variable in airport operations, safety and employee’s attitude towards safety risk management using the Multicriteria Decision Analysis model to achieve this objective. The results show the weighty level, satisfaction index and effective index of the safety and security parameters used in the analysis with their score and effective index graph. Recommendation on how to improve the airport safety operations were made following policy implication on how to improve the safety management system of the airport.
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