Browsing by Author "Jehopio, Peter"

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    Modelling Airport Efficiency With Distributions Of The Inefficient Error Term: An Application Of Time Series Data For Aircraft Departure Delay
    (International Journal of Sciences: Basic and Applied Research, 2013) Wesonga, Ronald; Nabugoomu, Fabian; Jehopio, Peter; Mugisha, Xavier
    The study employs determinants of the aircraft departure delay to estimate airport efficiency. Two main parameters were applied to fit the stochastic frontier model using transcendental logarithmic function where both frontier and inefficiency models were generated. The estimated airport efficiencies over a period of 1827 days applying the half-normal and exponential distributions for the inefficiency error terms were (0.7498; δ=0.1417, n=1827) and (0.8181; δ=0.1224, n=1827) respectively. The correlation coefficient for the efficiency estimates (ρ=0.9791, n=1827, p<0.05) between the half-normal and exponential distributions showed no significant statistical difference. Further analysis showed that airport inefficiency was significantly associated with higher number of persons on board, lower visibility level, lower air pressure tendency, higher wind speed and a higher proportion of arrival aircraft delays. The study offers a contribution towards assessing the dynamics for the distribution of inefficient error term to estimate airport efficiency by employing both meteorological and aviation parameters. The study recommends that although either half-normal or exponential distributions could be used; the exponential distribution for the error term was found more suitable when estimating the efficiency score for the airport.
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    Parameterized framework for the analysis of probabilities of aircraft delay at an airport
    (Journal of Air Transport Management, 2012) Wesonga, Ronald; Nabugoomu, Fabian; Jehopio, Peter
    The study analyses ground delays and air holding at Entebbe International Airport over five years. Daily probabilities for aircraft departure and arrival delays at are generated for each. The mean probabilities of delay for ground delays and air holding at 50% delay threshold levels are 0.94 and 0.82 that fall to 0.49 and 0.36 when 60% delay threshold levels are used. Simulations are performance for delay threshold levels to monitor for the trends of the daily probabilities for the study period. The general conclusion is that a parameter-based framework is best suited to determine the probability of aircraft delay at an airport.