ABSTRACT
The airline industry in most countries is strategic to economic development as it ensures safe and timely travelling and encourages business activities while generating employment opportunities. The Nigerian air transport industry system faces a lot of challenges due to unwanted waiting lines or delay of passengers who are eager to meet up for appointments or in preference to road transport systems. These problems include many passengers queuing for boarding, departure with different arrival rates. This project developed a queuing model as part solution to the problem. The Nnamdi Azikiwe International Airport (NAIA) Abuja was used as a case study to model a solution to this general problem. Arik Airline Limited, British Airways, Ethiopian Airline and Aero Contractors were the companies used for the study. The waiting modelling involved the use of Birth and Death Rate (BDR) and Multi-Server (MS) Models, which are the most commonly, used models to solve this type of problems. Data was collected from the companies to validate the result of the models. The results showed that in order to meet the current demand of passengers in NAIA, Abuja it is required that each airline to operate with minimum of five (5) aircrafts for daily service to cope with the average demand of 21863 passengers per month on their present routes. Service factors of 0.5 (utilisation factor of 0.4, 0.6 and 0.9) at 5% significance level were used for both BDR and MS model. The model when applied showed that the system became more reliable and efficient with minimal delay of service in all sectors considered in this work. However, BDR and MS models should be applied to other airports in Nigeria to minimise delay while the relevant authorities should monitor the recording of passenger patronage in Nigerian airports.
CHAPTER ONE
1.0 INTRODUCTION
1.1 Background of the study
Africa is yet to be industrialised and this affect its contribution in global market especially in air transport sector “with less than 3.7 percent” in the recent (Bofinger, 2009). This value was found primarily in intercontinental traffic, in certain regions and countries, domestic traffic, such as in Nigeria. Market forecasts for the airline industry are difficult to make because of fluctuating fuel prices and the global economic crisis.
Queuing which always takes place in the form of lining up, is rarely anyone’s favourite activity. It is the cornerstone of efficiency and organisational ability for most service industry especially in the airline industry. At any given moment, there may be more people or cases needing service, help or attention the industry can handle. Queues help workers and managers track, prioritise and ensure the delivery of services and transactions. Queuing modelling has helped in tracking customers’ services and needs through customer service departments by creating virtual queues, assigning people needing service case numbers and priority statuses. Queuing modelling helps for assessing air industry responses to passengers needs. It helps technicians and specialists stay on top of all the situations and cases before them. For instance, a company’s information technology help desk may serve hundreds and even thousands of employees using personal computers, mobile devices and proprietary devices. This requires a detailed and comprehensive tracking system to help managers efficiently allocate their team members’ time and expertise. It has been used for managing businesses through the use of mathematical models and formulas to determine the best way of serving the greatest number of customer based on staffing resources. In retail businesses outlet, the volume of transactions is extremely important in maximising revenues and profitability. Thus, lines and queues are critical and important in servicing industry. This is the reason why supermarkets typically operate on multiple lines using several check stands, while banks and airlines usually use long queues that lead to delay. Queueing of passengers in Nnamdi Azikiwe International Airport (NAIA) causes delays due to irregularities in service processes. According to Mehri, H., Djemel, T., and Kammoun, H.(2009), there are three basic components of a queuing process which are arrivals, service facilities, and the actual waiting line. Arrival is an input source that generates arrivals or passengers for NAIA, Abuja system. It is important to consider the size of the calling population as infinite because the passengers arrive into the system at different rates. Hence the pattern of arrivals of the queueing system in the study would be first come first served (FCFS).
Therefore, in order to minimise delay of passenger and also to ensure improved performance in the system, the queueing data of the NAIA, Abuja were collected and modelled using both Birth and Death Rate (BDR) and Multi-Server (MS) approach.
1.2 Problem statement
Road safety factors have contributed to better responses of air transport systems in Nigeria due to bad road network, inadequate driver training and predominance of non-motorised traffic and pedestrian. These problems have increased much more passenger queuing for airline transport system which helps in turn to aid their business transaction, ease their journey, meeting up with their promising deadlines. As a result, Nigeria air transport industry system faces a lot of waiting time or delay of passengers who are ready to meet up for business or in preference for life safety to road transport systems. The air industry in Nigeria faces problems of many passengers queuing for boarding, departure with different arrival rate especially in Nnamdi Azikiwe International Airport (NAIA) the only airport facility in the nation’s capital city, Abuja.
Queuing in NAIA, Abuja has become much more complex to solve manually due to the pattern and irregularities in the arrival or service processes. The airport has less capacity to serve all arrivals and departures promptly resulting into randomness that results to some waiting. Waiting or queuing could be eliminated if the irregularity could be taken care of, without increasing overall service capacity or diminishing the overall flow of arriving passenger. Waiting is therefore a consequence of irregularity in the airport.
NAIA, Abuja faces problem of waiting line or queuing in its system such as cargo and ticket clearance, departure and arrival rate. The average number of travellers in the system tends to be uncontrollable. The possible prediction of various numbers of passengers in the system is necessary for minimising the waiting line called queuing. Number of delay of passenger waiting for departure would be minimised and therefore the industry service will improve as well. As part of a solution to this complex problem that frustrate travellers on arrivals through the airport. This study is designed to develop a queuing model to facilitate prediction and processing of travellers on arrivals for effectiveness.
1.3 Aim of study
The study is aimed at minimising waiting lines of air transport services system in Nnamdi Azikiwe International Airport (NAIA) Abuja, in order to reduce delay in departure rate of passenger boarding by the air system, so as to predict performance of service level that would bring improvement of traffic flow management into the system.
1.4 Objectives of study
The objectives of the study include the followings:
a) Predicting the arrival and departure rate of passengers in the system
b) Predicting the expected number of passenger in the system and the system’s service level of performance
c) Development of a queuing model to harmonise the passenger arrival rate, departure rate with the capacity of the handling facilities of the airport and expected passengers population in the system at a period for improved service.
d) Validation of the models with test data obtained from selected airlines that use the NAIA, Abuja to ascertain the performance of the model
1.5 Significance of the study
The main significance of the project when completed includes the following:
a) It will reduce airline operators’ inefficiency in NAIA Abuja, which is essential for managing queuing practices.
b) The different models of queuing based on Birth and Death Rate (BDR) and Multi-Server (MS) models would reduce the delay in the system and improve operation economics.
c) The use of the model will give better outcome and maximum efficiency for managing available resources as it would significantly shorten the waiting periods of passengers, the number of waiting points and servers.
d) Successful application of the model at NAIA, Abuja would prompt the application of the models to other airports in Nigeria that have similar problems for better service.
e) It would reduce delay in services, quicken departures, and eliminate airport congestions with the attendant benefits of improved security especially in respect to terrorists that may be hanging around waiting passenger to execute their plans and other negative vices that occur in most airports of the world.
1.6 Scope of the study
The study focuses on modelling of waiting line of passengers boarding by air in NAIA, Abuja. It will entail the application of Birth and Death Rate (BDR) and Multi-Server (MS) models. The method is used for predicting performance level of the system because it helps in minimising delay of service. The study will use experimental data from the services company within (NAIA) Abuja such as number of passengers in the system and ticket fares. It will be based on required variables like the waiting line model of this system are number of passengers. The study result if successful may be extended to solve similar problems in other Nigerian airports.
1.7 Limitation
The study is limited to air transport systems in NAIA, Abuja to enable a handy and precise collection of data and analysis. It will involve predicting of waiting line of airline passengers in Abuja and departure rate of the passenger. Consequently, the performance service level of the airline in NAIA, Abuja will be predetermined using queueing modelling analysis and Chi-square distributional assumption based on empirical industrial data of past records and observations. The delimiting factor that affected effectiveness of the study was lack of full co-operation of some of the industry staff in giving the correct past data of their operations due to unavailability of such data for the purposes of tax evasion. The sampling data for passengers would be collected from NAIA, Abuja. The study would select two international and two domestic airline servicing companies as representatives of the entire system.
1.8 Research methodology
In the study, a quantitative approach was adopted. Therefore existing passenger’s data in the system were collected for analysis. The source of information and data for the study was mostly through questionnaire on sampled groups, companies and passengers. The collected data were analysed using queuing modelling for determining the waiting lines of the passengers. An appropriate queuing model will be developed based on the data and information available to handle the peculiar situation at NAIA, Abuja.
1.9 Definition of terminologies
NAIA, Abuja: Nnamdi Azikiwe International Airport (NAIA)
Queue length: The total number of passengers in the air system
Arrival rate: Number of passengers coming into NAIA for airline services per time
Departure rate: Number of passengers being served per unit time
Queuing Modelling: Analysis of arrival and departure rate of the passengers in the system
First come first served: The servicing rate of the system in accordance to arriving rate
This material content is developed to serve as a GUIDE for students to conduct academic research
QUEUEING MODELLING OF AIR TRANSPORT SYSTEM PASSENGERS A CASE STUDY OF NNAMDI AZIKIWE INTERNATIONAL AIRPORT, ABUJA
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