Causal Factors of Flight Delay in Nigerian
Airport: A Case Study of Murtala Muhammed International Airport
Ayo-Agunbiade Oluwafisayo T.
Department of Transport Management Technology
Federal University of Technology Akure, Nigeria
E-mail: [email protected]
Stephens Mobolaji
S.
Department of Transport Management Technology
Federal University of Technology Akure, Nigeria
E-mail: [email protected]
Abstract
Delay is a prominent event
mostly experienced at the airport by both airline and passengers. Globally
delay is permitted at 15mins later than the scheduled time. Assessing the level
of delay in the airport is a major criterion for measuring airport performance.
Aircraft not adhering to schedule flight results in increased airport
congestion, cancellation flight and flight delay. This study made use of
primary data through well-structured questionnaires to obtain information from
selected NAMA Staff at the Murtala Muhammed International Airport (MMIA).
Operational delay report for a month and Airlines flight were examined for two
months under the MMA2 to know the deviation of scheduled flight time from
actual flight time. Descriptive Analysis, Wilcoxon Rank test, Factor Analysis
and Step Wise Regression were the statistical tools deployed for this research.
Findings showed that on a monthly base, 63% of the domestic traffic flows are
delayed. Some factors responsible for delay were considered: aircraft damage,
bad weather, aircraft maintenance, VIP movement and fueling are the major
factor responsible for delay of aircraft Movement.
Keywords: Flight Delay, Factor Analysis, Congestion, Scheduling.������������������������������������������������������������������������������������������������������
1. Introduction
Flight planning requires accurate weather
forecasts, enhances safety regulations, whereby adequate or excess fuel are
carried beyond the minimum needed to fly from origin to destination (Simpson, Bashroum and Carr, 1965). Scheduling
process is where many of the implications that stem from the earlier work come
together. The scheduler allocates each aircraft to each service, taking into
account:� turnaround time; the minimum
time needed to empty and refill an aircraft when it passes through an airport
where aircraft will be overnight, as not all aircraft will necessarily be at
the hub on every night of the week. With each schedule, the airline defines its
daily operations and commits its resources to satisfying its customers� air
travel needs. Therefore, one of the basic requirements all airlines place on
the ground handling is to ensure high efficiency of handling activities, avoiding
delays. This approach of a flight schedule will reduce delay and improve the
operation of the airport. Jianfeng (2012) observed
that a delayed air flight which might have occurred out of positive and
negative circumstances tends to have resultant effects on the passengers,
airlines and airport running costs and on other flights arrivals and
departures. Lack of adherence to the schedule designed by airport results in
increased airport costs, congestion, flight delays and cancellations will have
medium and long term reduced patronage effects, fewer passenger will want to
fly through such airports as well as fewer airliners will want to fly airport
prone to disruptions. Some flights are also affected by reactionary delays, due
to late arrival of previous flight.
Flight delays not only
annoy air travelers and disrupt their schedules, but they incur costs to the
airlines when flight connections are missed, or flight crews and aircraft need
to be reallocated due to maintenance problems or crew duty time limits. Flight
delay can have subsequent effect on those on board and the operation of the
flight and other scheduled flight at an arrival and departure airport. Aircraft
schedule recovery and crew re-assignment, taking into account all constraints,
factors and regulations, while trying to find solutions in a few minutes. The
problem is to keep the effects of disturbances as low as possible and to return
to regular operations. (Mueller & Chattigi,
2002).
Many major airports around
the world have significant delay problems as a result of an imbalance between
capacities and demand. Delay often results in the increase in fuel consumption
of aircrafts, affects passengers getting to their destination on time (Boye, 2015). When traffic occurs in bunches or peaks, there
may be delays even when the number of aircraft using the airport is less than
the capacity for that peak time period. Some amount of delay arises every time
two aircraft are scheduled to use a runway at the same time. The probability of
simultaneous arrivals increases rapidly with traffic density, so that average
delay per aircraft increases exponentially well before traffic levels reach
capacity levels. Having considered all these, there are various factors
instituting delay in airline operation such as the relationship of demand to
available capacity of an airport causes delays to aircraft movements as a
result of limited runway capacity.
In developing economy like
Nigeria, delay experienced by passengers is a point of consideration in the
development of a nation as a whole as it affects personal expenses. Developing
countries need to focus on the delay of aircraft movement at their airport to
ensure increased patronage by airliners.
In summary, an accurate overview of
the literature related to aircraft flight scheduling and delay has been x-ray by
building upon the sections addressing this topic in the literature reviews by
Mueller and Chatterji (2002), the effects of not
adhering to schedules are increased airport costs, congestion, cancellation of
flights and flight delay. Studies such as Mohleji
(2001), Schaefer and Miller (2011), Hansen (2002), Mueller and Chatterji (2002) and Rosen (2002)) on airport congestion
have identified several factors which generate flight delays: saturation of
airport capacity (including air transportation control activities), airline
problems, reactionary delays, passengers and cargo, weather and other
unpredictable disruptions (e.g. strikes).
This research considered the major
factor(s) responsible for delay of scheduled flight by considering the
capacities utilizations, runway usage, and deviations in departures and
arrivals. Grigoriy (2014), opines that there is
acceptable level of flight delay, which might have positive effect on the
overall operation of the airport system. The study was on flight delay
performance at Hartsfield Jackson Atlanta International Airport with objective
of determine the delay at the airport. This research was carried out at
Hartsfield Jackson Atlanta International Airport and not Muritala
Mohammed Nigeria Airport Nigeria. The researchers conducted a field based
qualitative research and quantitative research, based at Murtala Mohammed
Airport, in other to analyse the delay of aircraft at
the airport. The various possible factors responsible for delay were also
addressed. For the purpose of this study the MMIA is chosen as the case study.
This is because this airport serves main aviation hub in the Nigerian aviation
industry for domestic and international traffic (cargo and passengers).
The aim of the paper is to analyze
aircraft delay of selected airline at the airport. A case study of Muritala Muhammed International Airport, Lagos, Nigeria. To
achieve this aim, the following objectives are delineated as to estimate the
average rate of deviation of actual arrivals, and departures from scheduled
arrivals and departures; and evaluate the factors causing delay of scheduled
flights.
2. Theoretical
Framework
Time space analysis is a simple technique to assess runway and
airspace capacity if the headway between aircraft is known. It is a method to ascertain the time complexity and
space complexity of an algorithm. Time complexity is a measurement of how much
computational time an algorithm uses as its input size changes. Analyzing
algorithms in this way provides an indicator as to how quickly the runtime
increases, how it does so in relation to the input and weather the algorithm is
costly for small/large inputs (Trani, 2013).
Queuing theory is concerned with the issue of waiting; it is
important to note that waiting can be quite boring, hence queuing theory
examines how customers (vehicles) arrive to receive service by servers which is
between arrivals of vehicles, start of service, and wait in queue. The basic applications
of queue are:
� Number of
customers in queue L (for length);
� Time spent in
queue W for (wait) (Adeniran and Kanyio, 2019).
The basic process assumed by most queuing
models is the following. Customers (Passengers) requiring service are
generated over time by an input source. These customers (Passengers)
enter the queuing system and join a queue. At certain times, a
member of the queue is selected for service by some rule known as the queue
discipline. The required service is then performed for the customer by the service
mechanism, after which the customer leaves the queuing system (Fredick, 2001). Queues are called infinite or finite,
according to whether this number is infinite or finite.
The assumption of an infinite queue
is the standard one for most queuing models, even for situations where
there actually is a (relatively large) finite upper bound on the permissible
number of customers, because dealing with such an upper bound would be a
complicating factor in the analysis. At a high level, we can view this problem
from the perspective of queuing theory. Delays are fundamentally related to one
of several issues: (a) higher scheduled demand than capacity or over-scheduling
(b) a larger arrival rate than scheduled, (c) a lower service rate than scheduled,
or (d) a smaller number of servers than scheduled. In the context of this
paper, the gates are the servers and the service rate are the rate that
aircraft can be turned at the gate. For example, if an aircraft has a longer
turnaround time than scheduled, this is effectively a reduction in the service
rate of the gate.
The model
adopted to assess this research is Queue theory, it is the process whereby
customer enters a system and service is being rendered. For this research the
customer is Aircraft (both passengers and freight), the input source is the
gate, the queue discipline is mostly First Come First Serve, Last in last out
and emergency and the size is the total number of the
aircraft per day for a period of 2 months.
2.3 Flight Delay
Wu (2005) states that flight delay is a complex phenomenon,
because it can be due to problems at the origin airport, at the destination
airport, or during airborne. A combination of these factors often occurs.
Delays can sometimes also be attributable to airlines. Some flights are
affected by reactionary delays, due to late arrival of previous flights. These
reactionary delays can be aggravated by the schedule operation. Mueller and Chatterji (2002) states the flight
schedules are often subjected to irregularity. Due to the tight connection
among airlines resources, delays could dramatically propagate over time and
space unless the proper recovery actions are taken. Even if complex, flight
delays are nowadays measurable. And there exists some pattern of flight delay
due to the schedule performance and airline itself (Wu, 2005). Flight delay
might be initiated by the airline, when airplane is not field to capacity and
have might resultant effect on subsequent arrivals. The delay can be attributed
to the airport, when there are limited ground-handling facilities, with
increase demand. Failure of an aircraft to be cleared and failure to take off
within 15mins of scheduled timing is delay.
There are general arrival and
departure delays. This usually indicates that arrival traffic is doing airborne
holding or departing traffic is experiencing longer than normal taxi times or
holding at the gate. These could be due to a number of reasons, including
thunderstorms in the area, a high departure demand, or a runway change. In
order to understand flight delay, it is useful to consider the phenomenon of
scheduled delay. The simplest way of reducing delays is not to increase the
speed and efficiency of the system to meet the scheduled time, but to push back
the scheduled time to absorb the system delays (Bai, 2006).
Figure 1. Factors influencing departure delay
Source: Yufeng, Michael
and Wolfgang (2005)
This study relies on secondary data sourced from the Federal Airport Authority
of Nigeria (FAAN), Nigeria Airspace Management Agency (NAMA) and Nigeria Civil
Aviation Authority (NCAA). The data obtained were records of flights over a
period of sixteen (16) years. To address the first objective, the installed
airside capacity, and the hourly and daily traffic movements were examined.
Daily traffic flow for two months and report of flight delay for a month were
obtained. Daily traffic flow, for two months was gotten and report of flight
delay. Descriptive
Analysis, Wilcoxon Rank test, Factor Analysis and step wise regression were
employed for the analysis. 198 respondents were given questionnaire and 160
were retrieved, the sample size where obtained according to Cochran�s Sample
Size Formula. For the first objective, the traffic flow of aircraft for
Standard at MMA2 was worked on, the Standard and Actual time of Arrival and
Departure was analysed with the use of Wilcoxon,
descriptive analysis, also with the aid of Excel Sheet. Secondly, several
factors affecting delay where analysed through the
use of factor analysis where the factors were categorized into three
categories.
Table 1:�� Executive summary on international and domestic flight operations
Routes |
Number of Airlines in Operation |
Total Flights Operated |
No. of Delays |
Flight Cancellations |
Remarks |
International Airlines |
29 |
1,478 |
587 |
14 |
Cancelled Flights: Africa World (7),
British Airways (3), Air Peace (1), Arik Air (1), Asky
(1), Egypt (1) Air/Ramp Return: Air Peace (1) |
Domestic Airlines |
8 |
5,168 |
3,244 |
29 |
Cancelled Flights: Arik Air (10),
Air Peace (7), Overland Air (4), Medview Air (3),
Aero (2), Azman (2), Dana (1) Air/Ramp Return: Arik Air (2), Dana
Air (1) |
Source:
Nigerian Civil Aviation Authority, August 2018
For the period under review, a total
number of 1,478 flights were operated on international
routes while 5,168 flights were operated on domestic routes.� 587 flights out of 1478 were delayed for International
flight and 3244 out of 5168 flights were also delay, so therefore delay is
evident for both.
Source: Murtala Muhammed Airport
Terminal 2, 201
Table 3: Wilcoxon rank test of difference between group
Group |
Observe |
Rank Sum |
Expected |
Arrival |
8 |
75.5 |
68 |
Departure |
8 |
60.5 |
68 |
Combined |
16 |
136 |
136 |
Wilcoxon Statistic |
0.791 |
||
P value |
0.4292 |
Source: Authors� Compilation, 2018
We reject
Since the P value is not less than
0.05, this gives a numerical evidence to conclude that the delay caused by
flight departure is relatively the same for delay caused by flight arrival.
It can be seen that flight delay was
most experienced on the 29th April to 5th May 2018 during
the month of April to May. It has been observed that 53.08% of the total flight
arrivals experienced delay within the space of two months at 15mins beyond the
scheduled time. Table 3 shows the weekly occurrence of flight delay in the
airport within the period of two months, April to May. It can be observed that
flight delay is evident and occur often in arrival and departure of aircrafts.
This might be due to bad weather after take-off.
Factor analysis was conducted on the nine variables using the
Principal Component Analysis method of Varimax Rotation with Kaismer Normalization. The principal components grouped the
factors causing delay in both international and Local Flight by ensuring the
variables were not inter-correlated and that the variables were grouped
properly.
Table 4: Total Variance Explained
Component |
Initial Eigenvalues |
Extraction Sums of Squared Loadings |
||||
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
|
1 |
4.951 |
55.016 |
55.016 |
4.951 |
55.016 |
55.016 |
2 |
1.305 |
14.502 |
69.518 |
1.305 |
14.502 |
69.518 |
3 |
1.011 |
11.237 |
80.754 |
1.011 |
11.237 |
80.754 |
4 |
.804 |
8.932 |
89.686 |
|
|
|
5 |
.439 |
4.875 |
94.561 |
|
|
|
6 |
.189 |
2.103 |
96.664 |
|
|
|
7 |
.134 |
1.486 |
98.150 |
|
|
|
8 |
.121 |
1.341 |
99.492 |
|
|
|
9 |
.046 |
.508 |
100.000 |
|
|
|
Source: Authors� Compilation, 2018
Table 4. shows the variance in flight
delay accounted for by the first three principal components, extracted by
principal component method using SPSS. It can be seen that about 81% variation
causing flight delay was accounted for by three components. About 19% of
variation was accounted for by the remaining six components. The initial Eigen
values are flight delay variations accounted for by the entire components,
while the Extraction loadings are those variation accounted for by the factors
extracted.
Table 5: KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. |
.691 |
|
Bartlett's Test of Sphericity |
Approx. Chi-Square |
395.315 |
Df |
36 |
|
Sig. |
.000 |
Source: Authors� Compilation, 2018
Only factors with Eigen values equal
to or greater than 1 were considered as significant. The Eigen value of a
factor represents the amount of the total variance explained by that factor.
The results lead to three categories for the factors causing delay.
These factors that causes delay can be
attributed to Aircraft course as component one, processing factor as component
two and customer factor as component three.
We can generally conclude from the study that delay is evident in
the airport and may be as a result from the airplane maintenance, delay due to
customer arrival or attitude and the method of processing information.
4.3 Step Wise Regression
Table 6: Step wise Regression
Model Summary |
||||
Model |
R |
R Square |
Adjusted R Square |
Std. Error of
the Estimate |
1 |
.379a |
.143 |
.081 |
.727 |
2 |
.378b |
.143 |
.088 |
.724 |
3 |
.378c |
.143 |
.095 |
.722 |
4 |
.370d |
.137 |
.096 |
.721 |
5 |
.361e |
.131 |
.097 |
.721 |
6 |
.353f |
.124 |
.097 |
.721 |
Source: Authors� Compilation, 2018
From table 6, above where the analysis
of factor causing delay is represented. Factors with little or no effect are
baggage handling, aircraft fueling, VIP movement, congestion of airspace and
flight documentation. The factor retained by the analysis has the most
important factors are Aircraft damage, bad weather, aircraft maintenance and
late boarding.
5. Conclusion
The delay experienced by aircraft out of every schedule is high,
because most aircraft don�t takeoff at the scheduled time which might be as a result
of disruption. Aircraft damage, Bad weather, aircraft Maintenance, Aircraft fuelling, Congestion of the Airspace, Flight Documentation,
Late Boarding, Baggage handling and VIP movement with the aid of Factor
Analysis these factors were categorized into 3 components; Aircraft causes,
Processing and Customer Factor which implies that the first was noted to be the
major cause of delay. In addition, all contingencies must be incorporated into
the schedule plan to give allowances for all forms of disruptions.
The research recommends that Schedule
disruption has impact on the turnaround operation considering the effects on
the overall performance of Airport, Gates and Slots restriction, Operational
restriction, Airports Restrictions and other factors make planning difficult
but they must be considered in the process. Airlines should be realistic in
their flight planning/schedules. Airlines should develop responsive crisis
management systems and file their Operation Disruption Manuals with NCAA as required
by law. Airlines should also adhere to the Nigerian Civil Aviation Regulations
and Passengers Bill of ���Rights in their
dealings with passengers. This will motivate Passengers, by getting value for
their money.
Considering the factors causing delay,
the resultant effect can be on passengers, consideration should be given in
case of missed connection flight, so airlines to ensure they provide right to
care to passengers in times of delays/cancellations.
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