A User's Perspective on the Role of Lanseria Airport As

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Surname, Initial(s). (2012) Title of the thesis or dissertation. PhD. (Chemistry)/ M.Sc. (Physics)/ M.A. (Philosophy)/M.Com. (Finance) etc. [Unpublished]: University of Johannesburg. Retrieved from: https://ujdigispace.uj.ac.za (Accessed: Date).

A USER’S PERSPECTIVE ON THE ROLE

OF LANSERIA AIRPORT AS AN ALTERNATIVE

ELMARIE KRIEL

DISSERTATION

submitted in fulfilment of the requirements for the degree

MASTER COMMERCII

TRANSPORT ECONOMICS

in the

FACULTY OF MANAGEMENT

at the

UNIVERSITY OF JOHANNESBURG

Supervisor: Prof J Walters

October 2015

DECLARATION

I, the undersigned, hereby declare that this dissertation entitled ‘A user’s perspective on the role of Lanseria Airport as an alternative’ is my own work and all the sources I have used have been indicated or acknowledged by means of completed references. It is submitted in fulfilment of the requirements for the degree Master of Commerce in Transport Economics at the University of Johannesburg. It has not been submitted before for any degree or examination at this or any other university.

Elmarie Kriel

October 2015

ii ABSTRACT

The deregulation of the airline industry was a landmark event and brought about various changes in the air transport market, both locally and internationally. One important after- effect of deregulation was the entry of low-cost carriers (LCCs), which increased competition in the market and offered passengers the freedom to choose among airlines and the option of lower airfares.

Low-cost carriers have been very successful across the globe and the main reason for this lies in their simplified business model. These types of airlines try to keep costs as low as possible. One way of doing this is for LCCs to operate from secondary or alternative airports. This trend is observed in the United States of America as well as Europe.

When LCCs fly from secondary airports in areas where there is more than one airport, the need arises to determine what drives passengers to select the secondary or alternative airport.

In South Africa and more specifically, Gauteng, Lanseria International Airport1 is considered as an alternative airport and currently two LCCs operate from there.

The research presented in this dissertation reflects on the theoretical aspects passengers consider with regard to selecting an airport. Based on this, the research set out to determine the attributes passengers evaluate when selecting an airport. These attributes were grouped as follows:

 Price  Convenience  Service

Furthermore, the results of this research are compared to previous research conducted at Lanseria International Airport when only one LCC was operating from there.

The results indicated that passengers considered these attributes to be important when selecting an airport. When the results were compared with that of previous research, it was found that passengers still considered the same attributes to be important, even

1 Also referred to as Lanseria Airport iii after the entry of a second LCC. An identified difference was that the passengers in the second study tended to be more price-sensitive.

This research contributed to this field by examining the factors passengers consider when selecting to fly from Lanseria International Airport.

iv TABLE OF CONTENTS

DECLARATION ...... ii ABSTRACT ...... iii LIST OF FIGURES ...... x LIST OF TABLES ...... xi TABLE OF ACRONYMS ...... xiii

CHAPTER 1: BACKGROUND TO THE STUDY ...... 1

1.1 INTRODUCTION ...... 1 1.2 FUTURE PROSPECTS FOR AIR TRAVEL ...... 3 1.3 RECENT TRENDS IN AIR TRAVEL ...... 4 1.3.1 Low-cost airlines and secondary airports ...... 5 1.3.2 Passengers and secondary airports ...... 5 1.4 RESEARCH PROBLEM, RESEARCH QUESTIONS AND RESEARCH OBJECTIVES ...... 7 1.5 RESEARCH METHODOLOGY ...... 8 1.5.1 Research philosophy and approach ...... 8 1.5.2 Hypotheses ...... 9 1.5.3 Research design ...... 11 1.5.4 Unit of analysis...... 13 1.6 SCOPE AND LIMITATIONS OF THE STUDY ...... 13 1.7 OUTLINE OF THE STUDY ...... 14

CHAPTER 2: AN OVERVIEW OF THE AIRLINE INDUSTRY ...... 15

2.1 INTRODUCTION ...... 15 2.2 PHASES OF DEVELOPMENT IN AVIATION ...... 16 2.2.1 Regulation ...... 16 2.2.2 Liberalisation ...... 16 2.2.3 Deregulation ...... 18 2.2.4 Privatisation ...... 22 2.3 FULL-SERVICE CARRIERS ...... 24 2.3.1 Business model of full-service carriers ...... 25 2.3.2 Full-service carriers in South Africa ...... 25 2.3.2.1 South African Airways ...... 26 2.3.2.2 British Airways Comair ...... 27 2.4 DEVELOPMENT OF LOW-COST CARRIERS ...... 29 2.4.1 Benefits to consumers ...... 30 2.4.2 Growth of secondary airports ...... 30

v 2.4.3 Regional development ...... 32 2.4.4 Environment ...... 32 2.5 UNITED STATES OF AMERICA ...... 33 2.5.1 Southwest Airlines ...... 33 2.6 EUROPE ...... 35 2.6.1 Ryanair ...... 35 2.6.2 EasyJet ...... 36 2.7 SOUTH AFRICA ...... 38 2.7.1 Kulula ...... 38 2.7.2 1Time Airline ...... 40 2.7.3 Mango Airlines ...... 41 2.8 CONCLUSION ...... 42

CHAPTER 3: SECONDARY AIRPORTS AND LOW-COST CARRIERS ...... 43

3.1 INTRODUCTION ...... 43 3.2 ROLE OF AIRPORTS ...... 44 3.2.1 Economic impacts of airports ...... 44 3.2.2 The changing airport environment ...... 45 3.2.3 Competition among airports ...... 46 3.3 SECONDARY AIRPORTS ...... 48 3.3.1 Infrastructure ...... 50 3.3.2 Capacity at primary airports ...... 51 3.3.3 Low-cost carriers ...... 52 3.3.3.1 Business strategy of low-cost carriers ...... 54 3.3.3.2 Airport choice ...... 55 3.3.4 Air passenger market ...... 57 3.4 SOUTH AFRICAN AIRPORTS ...... 59 3.4.1 ACSA airports ...... 60 3.4.1.1 O R Tambo International Airport ...... 61 3.4.1.2 Cape Town International Airport ...... 62 3.4.1.3 King Shaka International Airport ...... 63 3.4.1.4 Other ACSA airports ...... 63 3.4.2 Municipal airports in Gauteng ...... 64 3.4.2.1 Rand Airport ...... 65 3.4.2.2 Wonderboom Airport ...... 65 3.4.3 Privately owned airports ...... 66 3.4.3.1 Grand Central Airport ...... 66 3.4.3.2 Lanseria International Airport ...... 66 3.5 THE SOUTH AFRICAN AIR PASSENGER MARKET ...... 69 3.5.1 Air transport in Africa...... 69

vi 3.5.2 Air transport in South Africa ...... 69 3.6 CONCLUSION ...... 71

CHAPTER 4: RESEARCH METHODOLOGY ...... 73

4.1 INTRODUCTION ...... 73 4.2 RESEARCH PHILOSOPHY ...... 74 4.2.1 Positivism ...... 74 4.2.2 Interpretivism ...... 74 4.2.3 Pragmatism ...... 75 4.3 RESEARCH APPROACH ...... 76 4.3.1 Deduction ...... 77 4.3.2 Induction ...... 78 4.3.3 Abduction ...... 78 4.4 RESEARCH DESIGN ...... 79 4.4.1 Research purpose ...... 80 4.4.1.1 Exploratory studies ...... 80 4.4.1.2 Descriptive studies ...... 81 4.4.1.3 Explanatory studies ...... 81 4.4.2 Research design ...... 82 4.4.2.1 Quantitative research ...... 82 4.4.2.2 Qualitative research ...... 82 4.4.2.3 Mixed method research ...... 84 4.4.3 Research strategy ...... 84 4.4.3.1 Experimental research ...... 85 4.4.3.2 Survey research ...... 85 4.4.3.3 Archival research ...... 86 4.4.3.4 Case study research ...... 86 4.4.3.5 Ethnography research ...... 87 4.4.3.6 Action research ...... 87 4.4.3.7 Grounded theory research ...... 87 4.4.3.8 Narrative inquiry research ...... 88 4.4.4 Time horizon ...... 90 4.4.4.1 Cross-sectional study ...... 90 4.4.4.2 Longitudinal study ...... 90 4.5 DATA COLLECTION...... 91 4.5.1 Unit of analysis...... 91 4.5.2 Population ...... 91 4.5.2.1 Nature of research population ...... 91 4.5.2.2 Size of research population and sampling frame ...... 92 4.5.3 Sampling strategy ...... 92

vii 4.5.3.1 Probability sampling ...... 92 4.5.3.2 Non-probability sampling ...... 94 4.5.4 Data collection instrument ...... 97 4.5.5 Type of data collected ...... 97 4.5.5.1 Observations ...... 97 4.5.5.2 Questionnaires ...... 98 4.5.6 Data analysis ...... 100 4.5.6.1 Analysing quantitative data ...... 100 4.6 VALIDITY AND RELIABILITY ...... 101 4.6.1 Reliability ...... 101 4.6.2 Validity ...... 102 4.7 CONCLUSION ...... 103

CHAPTER 5: SURVEY RESULTS AND FINDINGS ...... 104

5.1 INTRODUCTION ...... 104 5.2 DISCUSSION OF SURVEYS ...... 105 5.2.1 Survey conducted in 2010 ...... 105 5.2.2 Survey conducted in 2013 ...... 106 5.2.3 Demographic profile of respondents ...... 107 5.2.3.1 Gender distribution of respondents ...... 107 5.2.3.2 Purpose of travel ...... 108 5.2.3.3 Airline used ...... 108 5.2.3.4 Residential distribution of respondents ...... 109 5.2.4 Airport choice factors/ attributes ...... 113 5.2.4.1 Total cost of using the airport (price attributes)...... 113 5.2.4.2 Convenience attributes ...... 115 5.2.4.3 Customer experience ...... 116 5.2.4.4 Other attributes ...... 119 5.3 FACTOR ANALYSIS ...... 122 5.3.1 Defining factor analysis ...... 122 5.3.2 Confirmatory factor analysis and factor rotation ...... 125 5.3.3 Comparison of latent factors: 2010 and 2013 ...... 129 5.4 CONCLUSION ...... 134

CHAPTER 6: CONCLUSION AND RECOMMENDATIONS...... 137

6.1 INTRODUCTION ...... 137 6.2 AN OVERVIEW OF THE AIRLINE INDUSTRY ...... 138 6.3 SECONDARY AIRPORTS AND LOW-COST CARRIERS ...... 139 6.4 RESEARCH METHODOLOGY ...... 141

viii 6.5 SURVEY RESULTS AND FINDINGS ...... 142 6.6 RECOMMENDATIONS AND AREAS FOR FURTHER STUDY ...... 146

BIBLIOGRAPHY ...... 148 ANNEXURE A – PASSENGER CHOICE QUESTIONNAIRE (2010) ...... 161 ANNEXURE B – PASSENGER CHOICE QUESTIONNAIRE (2013) ...... 164

LIST OF FIGURES

Figure 1.1: Hypotheses ...... 10

Figure 2.1: Outline of Chapter 2 ...... 15

Figure 3.1: Outline of Chapter 3 ...... 43 Figure 3.2: PAX: Total arrivals and departures Lanseria International Airport ...... 68 Figure 3.3: Airlines’ share of domestic market in South Africa ...... 70 Figure 3.4: Golden Triangle – serviced by domestic airlines in South Africa ...... 71

Figure 4.1: Outline of Chapter 4 ...... 73

Figure 5.1: Outline of Chapter 5 ...... 104 Figure 5.2: Gender distribution of respondents ...... 107 Figure 5.3: Purpose of travel ...... 108 Figure 5.4: Airline choice 2013 ...... 109 Figure 5.5: Province of residence ...... 109 Figure 5.6: Gauteng respondents’ residential distribution (2010) ...... 111 Figure 5.7: Gauteng respondents’ residential distribution (2013) ...... 112 Figure 5.8: Total cost of using the airport 2010 and 2013...... 113 Figure 5.9: Convenience attributes 2010 and 2013 ...... 115 Figure 5.10: Customer experience 2010 and 2013 (airline) ...... 118 Figure 5.11: Customer experience 2010 and 2013 (airport)...... 118 Figure 5.12: Other attributes 2010 and 2013 – safety and security ...... 120 Figure 5.13: Main attributes 2013 ...... 121 Figure 5.14: Scree plot ...... 125

LIST OF TABLES

Table 1.1: Differences between quantitative and qualitative research ...... 12

Table 2.1: Top US air carriers before and after deregulation ...... 21 Table 2.2: Elements of the full-service carrier business model ...... 25 Table 2.3: Domestic and regional routes serviced by SAA (including SA Express and SA Airlink) ...... 27 Table 2.4: Routes serviced by British Airways Comair ...... 28 Table 2.5: Airline product ...... 29 Table 2.6: Low-cost airlines in the US ...... 34 Table 2.7: Low-cost airlines in Europe ...... 37 Table 2.8: Domestic routes serviced by Kulula ...... 40 Table 2.9: Regional routes serviced by Kulula ...... 40 Table 2.10: Domestic routes serviced by Mango Airlines ...... 42

Table 3.1: Typical product features offered by primary and secondary airports ...... 47 Table 3.2: Primary and secondary airports in major European cities ...... 49 Table 3.3: Primary and secondary airports in the United States ...... 49 Table 3.4: Emergence of secondary airports (in terms of frequency of observation of both trends) ...... 51 Table 3.5: Growth in traffic at secondary airports developed by low-cost carriers (UK) ...... 53 Table 3.6: Presence of low-cost carriers (versus other airlines) at primary and secondary airports within multi-airport systems worldwide ...... 54 Table 3.7: Key terminal requirements and ramp operations ...... 56 Table 3.8: Classification of South African airports ...... 60 Table 3.9: Passenger throughput at ACSA airports ...... 64

Table 4.1: Strengths and weaknesses of positivism ...... 76 Table 4.2: Features of quantitative and qualitative research designs ...... 83 Table 4.3: Methods of conducting surveys ...... 89 Table 4.4: Summary of probability sampling techniques ...... 93 Table 4.5: Kulula’s weekly departure schedule from LIA to Cape Town (2010) ...... 95 Table 4.6: Kulula’s weekly departure schedule from LIA to Durban (2010) ...... 95 Table 4.7: Kulula’s weekly departure schedule from LIA to Cape Town (2013) ...... 96 Table 4.8: Kulula’s weekly departure schedule from LIA to Durban (2013) ...... 96 Table 4.9: Mango Airlines’ weekly departure schedule from LIA to Cape Town (2013) ...... 96

Table 5.1: Customer experience 2010 and 2013 (airline) ...... 117 Table 5.2: Initial factor analysis – Total variance explained ...... 124 Table 5.3: Confirmatory factor analysis – Four factors (2013) ...... 126 Table 5.4: Factor rotation – Four factors (2013) ...... 127 Table 5.5: Factor rotation – four factors (2013) (Price of ticket and Ease of check-in removed) ...... 128 Table 5.6: Latent factor structure of attributes (2013) ...... 129 Table 5.7: Latent factor structure of attributes (2010) ...... 129 Table 5.8: Latent factor structure of attributes (factor loadings in excess of 0.7) ..... 130 Table 5.9: Factor structure (rotated) – 2010 data ...... 131 Table 5.10: Factor structure (rotated) – 2013 data ...... 132 Table 5.11: Factor correlation matrix (2010 and 2013) ...... 132

xii

TABLE OF ACRONYMS

ACSA Airports Company South Africa AOPA Aircraft Owners and Pilots Association BA British Airways CCP City Council of Pretoria CFA Confirmatory Factor Analysis CRS Computerised Reservation System DIA Durban International Airport ELFAA European Low Fares Airline Association EU European Union FSC Full-Service Carrier GEPF Government Employee Pension Fund IATA International Air Transport Association ICAO International Civil Aviation Organisation IFR Instrument Flight Rules IPO Initial Public Offering ITLS Institute for Transport and Logistics Studies KIA King Shaka International Airport KMO Kaiser-Meyer-Olkin LCC Low-Cost Carrier LIA Lanseria International Airport ORTIA O R Tambo International Airport PIC Public Investment Corporation PLACO Pretoria Light Aircraft Company RPM Revenue Passenger Mile SAA South African Airways SADC Southern African Development Community UK United Kingdom US United States

xiii

CHAPTER 1: BACKGROUND TO THE STUDY

1.1 INTRODUCTION

Aviation has a long and fascinating history, dating back more than two thousand years. The Chinese can be credited with the first man-made flying objects – the earliest records refer to kites being flown there as long ago as 200 BC (Chinahighlights, 2012). Developments thereafter were slow.

Although inventors such as Leonardo da Vinci drew various designs for airborne craft, there is no indication that any examples were actually built at the time (The Dream of Flight, 2012). By the 17th century, hydrogen had been discovered. Its lighter-than-air properties allowed hydrogen balloons to be developed. At the same time inventors such as Newton started to experiment with various theories in aerodynamics, physics and fluid dynamics (The Dream of Flight, 2012).

Experiments with hang gliders took place in the late 1800s but it was only in 1903 that the Wright brothers made the world’s first sustained, powered, heavier-than-air flight (First Flight Centennial, 2012). After that, aviation developed rapidly. The first commercial flight in the United States of America took place in 1914, carrying one paying passenger between St Petersburg and Tampa. Three years later, the United States entered the First World War (Aviation Benefits, 2014).

Both world wars were to lead to major developments in aviation, not only in terms of improved techniques for aircraft design and construction but also facilities such as airfields, longer runways and improved maintenance facilities (Dierikx, n.d).

By the 1930s, a network of air routes covered the world, operated by various airlines, including Lufthansa, Qantas, SwissAir, Varig, United, American, TWA KLM and Imperial Airways – later known as BOAC (Wells, 1994). While most of these routes covered short distances, long-haul possibilities were being developed at the same time by Pan American Airways and Imperial Airways. These two airlines used flying boat airliners and competed with one another in trans-oceanic services (Wells, 1994).

It is ironic that much of the growth of air travel can be attributed to the unintended consequences of human conflict. The two world wars resulted in significant developments in technology, which aviation was later able to exploit for peacetime purposes. These developments include the growth of trans-oceanic air travel during the 1950s, when aircraft using jet engines which had been developed during wartime, were able to take over the passenger market from ocean liners. After the Second World War, in the United States, air travel captured most of the domestic inter-city passenger market from the railways (Wells, 1994).

After the Second World War, the flying boats were replaced by land-operating aircraft (Wells, 1994). Land-based airline services developed in Europe owing to the fact that a surplus of large airbases and long cement runways and hangar complexes were standing idle (Dierikx, n.d). Airports such as London Heathrow, among others, were developed after the Second World War in order to have an airport close to the main cities in Europe. The late 1940s saw the start of the European state airline BEA utilising aircraft like the Viking and Ambassador. The longer-range type aircraft, e.g. Douglas DC6s and 7s, Lockheed Constellations and Boeing Stratocruisers, were operated by Pan American World Airways and Trans World Airways, especially on the trans-Atlantic services (Wells, 1994).

The 1950s saw many developments on the aviation front. The first turbo-propeller aircraft were introduced and the first jet airliners followed shortly thereafter. The first jet airliners, however, had their fair share of problems. In the beginning there were many accidents due to pressurisation problems (Century of Flight, 2012). The De Havilland Comet 1, of BOAC, commenced service between London and Johannesburg in May 1952. Many other flights by other airlines followed – the routes served included Paris to Dakar and Paris to Beirut. South African Airways also offered a flight from Johannesburg to London (Vermooten, 1996).

In 1954 all Comet 1 jets were grounded after several accidents. Newer aircraft were introduced in the form of the Comet 4 and the Boeing 707-120 in 1958 (Century of Flight, 2012). As the years went by, the jet airliners were developed further, replacing and updating previous technologies. The 1960s saw the introduction of wide-body ‘jumbo jets’, such as the Boeing 747. During the 1980s many airlines acquired

aircraft, such as the Boeing 737-300 and Airbus A310, replacing various older types of aircraft (Aviation Benefits, 2014).

Worldwide, air travel continued to grow up to the end of the century. In the short period of ten years between 1990 and 2000, air travel increased from two to three trillion person-kilometres – an increase of 50% (Gilbert & Perl, 2010). Even the terrorist attacks of September 2001 on the World Trade Centre in New York and the Pentagon in Washington caused only a minor decline in air travel. By 2006 the backlog had not only been recovered but air travel had increased to nearly four trillion person-kilometres (Gilbert & Perl, 2010).

Air travel has generally been regarded as the fastest-growing mode of transport during the twentieth century. Now that the world is in the second decade of the twenty-first century, the question has arisen – can this growth be sustained indefinitely?

1.2 FUTURE PROSPECTS FOR AIR TRAVEL

For several decades, the world has become more aware of environmental concerns relating to pollution, global warming, and the availability of energy in the future. The sudden increase of the oil price in 2008 forced the world to think more deeply about these issues and a vast body of literature has developed in which many differing opinions have been expressed.

Although all forms of transport are being, or will be affected by these developments, the aviation industry is probably more vulnerable than most, owing to its total dependence on fossil fuel. A recent study by Gilbert and Perl (2010) can be considered to be ground-breaking in that it is one of the first attempts to quantify the frequency of air travel that should be undertaken by the world’s residents in future, in order to reduce their dependence on fossil fuel. Gilbert and Perl (2010) confine their proposals to two countries – the United States (US) and China – as examples of the world’s largest user of fossil fuel (US) and the world’s largest developing economy (China).

Gilbert and Perl (2010) paint a somewhat gloomy picture for air travel in the developed world. They suggest a modest increase in international air travel for US residents. Their predictions for the developing world are slightly more favourable for air travel – they suggest that China could maintain its present level of domestic air travel between now and 2025 as well as allow for a modest increase in international air travel by Chinese in 2025.

It is clear that as the world enters an uncertain future that all participants in air transport should be made aware of efforts to operate more efficiently, and decisions should as far as possible be based on proper research and not guesswork.

Two of the main reasons for the on-going growth in air travel during the latter half of the previous century was first the introduction of low-cost airlines, and secondly the use of secondary airports,2 as opposed to primary airports, by these airlines (Vasigh, Fleming & Tacker, 2008). The inter-relationship between these two concepts is important. It is unlikely that the international growth of low-cost airlines could have taken place without recognising the role of secondary airports (De Neufville, 2005).

This study endeavours to make a contribution by investigating in more detail the association between low-cost airlines and secondary airports, and more importantly, the reasons passengers choose to fly from a secondary airport, as this has been a significant development in the air travel industry globally as well as in developing countries such as South Africa.

1.3 RECENT TRENDS IN AIR TRAVEL

Low-cost airlines and secondary airports are both concepts that have emerged recently, and they are closely related, according to Barbot (2006). Many low-cost air carriers select to operate from secondary airports, and at the same time various secondary airports have seen increased traffic as a result of low-cost flights (Barbot, 2006).

2 An airport that receives regular traffic (serves a town or community) as an alternative to the primary airport (Transportation Dictionary [2015]) and not utilised by traditional full-service carriers (Boksberger & Schuckert [2011]) 4

1.3.1 Low-cost airlines and secondary airports

Following airline deregulation in the US, and liberalisation of the European markets, low-cost airlines emerged and have had a significant impact on the airline industry (de Wit & Zuidberg, 2012). In the US market, Southwest Airlines has had an intense effect on the airline market and has been the pioneering low-cost airline in this region (Bennet & Craun, 1993). In Europe the number of low-cost airlines increased significantly after the first flight of Ryanair commenced in 1986 (Barrett, 2004a).

Low-cost airlines are unique in the sense that they tend to utilise secondary airports instead of primary airports. Reasons for this are linked to the business model of low- cost airlines but also relate to the airport choice factors considered by low-cost airlines (Warnock-Smith & Potter, 2005). These factors relating to airport choice can be summarised as follows:  Lower airport charges  Quicker turnarounds  Modest terminals  Speedy check-in facilities  Good passenger facilities  Ease of access  Less congestion compared to major airports/hubs

A detailed discussion of the reasons and significance of low-cost airlines utilising secondary airports will follow in Chapter 3 of this study.

1.3.2 Passengers and secondary airports

In larger cities all over the world, passengers have a choice between various commercial airports. In these multi-airport cities/regions, airport choice becomes an essential air-travel related decision (Jiangtao, 2009). Various researchers have studied airport choice in order to explore the passengers’ airport choice determinants (Jiangtao, 2009). These studies have included different airports and/or different classes of passengers. Harvey (1987) researched passenger airport choice with

specific reference to airport access mode and found that in the San Francisco Bay Area, travel time and travel costs are determinants in choosing an airport access mode. Innes and Doucet (1990) found that aircraft type and flying time differences are considered as important factors influencing a passenger’s choice of airport. In 1995, Windle and Dresner analysed passenger airport choice in the Washington DC and Baltimore areas, and identified airport access time and flight frequencies as significant factors influencing airport choice. They ascertained that passengers who have used an airport before tended to use the same airport again, if all other factors are equal. In all the airport choice studies mentioned above, two variables consistently emerge as significant:  Travel access time  Flight frequencies

Studying passenger airport choice determinants may be of great value to airport managers as it can assist with determining passenger demand at the airport. It can inform airport planners from which catchment area an airport is likely to draw passengers (Windle & Dresner, 1995).

In Gauteng there are currently two airports that are used by scheduled airlines to provide domestic passenger services within South Africa.3 The first airport is O R Tambo International Airport (ORTIA), situated to the east of Johannesburg, which is regarded as the air transport hub of Southern Africa. Over 19 million passengers pass through this airport each year – these include international, regional and domestic passengers. It hosts more than 50 airlines (ACSA, 2013). The second airport is Lanseria International Airport (LIA or Lanseria), which has been identified as a potential secondary airport to ORTIA. This airport has been offering various domestic flight services since the 1990s.

The first airline to offer a scheduled passenger flight from Lanseria was Sun Air, a privately owned airline that began operations in 2002, which offered business class flights to Cape Town for a brief period. The airline was liquidated in March 2004 after it failed to pay various creditors (Sake24, 2012).

3 SA Airlink began a scheduled service from Wonderboom Airport in Pretoria in August 2015 (Traveller24, 2015) but was not included in this study as the fieldwork was conducted in 2013. 6

The airport experienced low volumes of scheduled passenger travel until 2006, when Kulula commenced operations from there (in addition to its services from ORTIA) as a low-cost airline. Since then, Kulula has gradually grown its passenger volumes from Lanseria (Leitch, 2011a). In June 2012, a second low-cost carrier began operations from this airport – Mango Airlines (Mokgata in Financial Mail, 2012).

The busiest domestic airline network in Africa can be found in South Africa between Johannesburg, Cape Town and Durban, and is termed the ‘Golden Triangle’ (News24, 2013a). The LCCs in South Africa also focus their operations on the so- called ‘Golden Triangle’ and these airlines have recently decided to offer additional flights to Durban and Cape Town from Lanseria (Luke & Walters, 2013). South African Airways used to dominate the Golden Triangle in the past but has lost market share recently on these high-density domestic routes, due to the entry of LCCs (Luke & Walters, 2013). In 2010 South African Airways also withdrew all flights on the Durban–Cape Town route. This route is now served by the low-cost carrier Mango Airlines (code share arrangements apply with SAA); it is mainly limited to tourists (Styan, 2010) and will not form part of this study.

Since passengers currently have a choice between ORTIA and Lanseria airports when flying to either Cape Town or Durban, and since the airlines operating from Lanseria also operate from ORTIA (serving the same destinations), it is opportune to determine the reasons for the customers’ choice of airport. The Institute of Transport and Logistics Studies (ITLS) (Africa) (2010) conducted a study to determine passenger choice decisions at Lanseria International Airport when only one low-cost airline, Kulula, operated from there. Now that another low-cost airline, Mango Airlines, also offers flights from Lanseria it is appropriate to investigate passenger choice again in order to establish if the factors influencing the passengers’ choice of airport have changed.

1.4 RESEARCH PROBLEM, RESEARCH QUESTIONS AND RESEARCH OBJECTIVES

Flowing from the background, the research questions this study aims to answer are:

Primary research question: Why is Lanseria International Airport a preferred airport for users? For the purpose of this study, the users of the airport refer to passengers.

Secondary research question: Will the passenger airport choice attributes differ with the entry of a second scheduled domestic low-cost airline that operates from the airport?

In order to find an answer to these research questions, various research objectives were identified and will now be highlighted. The primary objective of this study is to determine the reasons why passengers prefer to use Lanseria International Airport as a secondary airport. The following secondary objectives were derived:  To determine the passenger airport choice attributes relating to Lanseria International Airport since the introduction of a second low-cost airline operating from this airport  To compare the findings on attainment of the first objective with the results of the 2010 (ITLS, 2010) and 2011 (Heyns & Carstens, 2011) survey conducted when only one airline, Kulula, operated domestic flights from Lanseria International Airport  To determine whether the findings relating to the use of Lanseria International Airport as a secondary airport correspond with international literature findings

The aim is to gain a deeper understanding of the factors involved in secondary airport choice and, building on this knowledge, to make recommendations that will assist the airline industry, especially in a developing country such as South Africa.

1.5 RESEARCH METHODOLOGY

In the words of Saunders, Lewis and Thornhill (2012), research philosophy can be seen as the advancement of knowledge in a particular field.

1.5.1 Research philosophy and approach

The research philosophy adopted in this study is positivistic in nature since the researcher collected primary data about an observable reality in an attempt to

examine regularities and causal relationships within that data and to create generalisations similar to those produced by scientists (Saunders et al., 2012). Primary data was collected from a randomly selected number of departing passengers at Lanseria International Airport. This study utilised deductive reasoning which entails developing a theory that is then exposed to rigorous testing through various propositions. A deductive research approach will evolve along six progressive steps (Saunders et al., 2012): 1. Develop a tentative idea, a hypothesis or a set of hypotheses to form a theory. 2. Deduce a testable proposal by using current literature or stipulating circumstances under which the theory is expected to hold. 3. Scrutinise the logic of the argument; compare this argument with prevailing theories to see if it offers an advance in understanding. If it does, continue. 4. Assess the principle by collecting data to measure the variable and analyse it. 5. If the outcomes of the analysis are not consistent with the principle, the theory is not valid and should be rejected or modified. 6. If the outcomes of the analysis are consistent with the principle, the theory is confirmed.

From the existing theory on passenger choice factors, hypotheses were developed and tested by means of a survey.

1.5.2 Hypotheses

In order to test the influence of various attributes in passengers’ airport choice, three hypotheses were formulated, as summarised in Figure 1.1.

H1: Location of the airport

Lanseria International Airport H2: Cost of using the airporth as preferred airport

H3: Customer's airport experience

Figure 1.1: Hypotheses

Hypothesis 1: With regard to the choice of airport, a relationship exists between the geographic location of the airport and the residential location of the passengers.

Passengers’ airport choice attributes are influenced by various factors. Passengers do not want to make a long journey to reach the airport (Pels, Nijkamp & Rietveld, n.d); therefore, an airport in the close vicinity and with an access route with minimal congestion is preferred (Hess, 2010). Therefore people living in close proximity to Lanseria International Airport will rather make use of that airport instead of driving all the way to O R Tambo International Airport in the eastern suburbs of Johannesburg.

Hypothesis 2: A relationship exists between the cost of using an airport and the choice of a specific airport.

This hypothesis centres on the principle that the price of an air ticket, total cost of getting to the airport and cost of using the airport, will influence an individual’s choice of airport. Therefore in a region where there is more than one airport, passengers are likely to choose the airport where access costs are lower (Jiangtao, 2009). Passengers consider a combination of costs when selecting an airport, e.g. airfare, parking cost at the airport and cost to get to the airport (Goedegebuure, 2010). Low- cost airlines tend to operate from regional airports or secondary airports (Barbot, 2006) therefore the airline tickets tend to be more affordable from these airports (Forsyth, 2007). Therefore passengers will choose Lanseria International Airport if the cost of using the airport is acceptable.

Hypothesis 3: A relationship exists between the number of destinations, the flight departure and arrival times and efficient airport services, and the frequency of use of the same airport.

Passengers value the services available at the airport as important and these can include (Jiangtao, 2009):  Number of destinations serviced by the airport  Flight frequency  On-time arrivals and departures  Efficient baggage handling  Facilities at the airport

Jiangtao (2009) adds that passengers will return to an airport if they had a good experience previously.

Customer experience at Lanseria International Airport is an important choice consideration. If Lanseria International Airport serves an acceptable number of destinations, flights depart and arrive on time, and services at the airport are efficient, passengers will favour and repeatedly use this airport.

The following section will describe the research design utilised in this study.

1.5.3 Research design

Research design constitutes a general plan of how the researcher intends to go about answering the research question (Saunders et al., 2012).

Saunders et al. (2012) state that various research designs are available to researchers and these include quantitative and qualitative research designs. Altinay and Paraskevas (2008:75) state that quantitative research ‘aims to determine how a variable affects another in a population, by quantifying the relationships between variables.’ Altinay and Paraskevas (2008:75) further state that qualitative research

‘aims to develop an understanding of the context in which phenomena and behaviours take place.’ The most important differences between quantitative and qualitative research designs are highlighted in Table 1.1.

Table 1.1: Differences between quantitative and qualitative research

Quantitative research Qualitative research Deductive Inductive Generalisable Not generalisable Numbers Words Source: Altinay and Paraskevas (2008:75)

In this quantitative study, primary and secondary data will be analysed. The primary data to be analysed consist of responses from a passenger survey conducted at Lanseria International Airport in 2013. A questionnaire was designed by the researcher but a market research company was appointed to conduct the survey on behalf of the researcher after discussing the survey with them and training them on how to administer the survey. This 2013 survey followed the first survey by the Institute of Transport and Logistics Studies (ITLS) (Africa) which was conducted in 2010.

Secondary data to be analysed are from a similar survey conducted in 2010 when the Institute of Transport and Logistics Studies (ITLS) (Africa) was contracted to gather raw data, after which it was analysed by Heyns and Carstens, (2011). The latter survey consisted of a paper-based questionnaire completed by a random sample of departing passengers at Lanseria International Airport and was used to determine the most important passenger airport choice attributes. At the time of the survey, only Kulula offered scheduled domestic services from Lanseria International Airport to Cape Town International Airport and to the then Durban International Airport (in May 2010 the Durban International Airport [DIA] operations were moved to the new King Shaka International Airport north of Durban after the closure of DIA).

The 2013 survey, similar to that of the Institute of Transport and Logistics Studies (ITLS) (Africa) of 2010, was conducted again at Lanseria International Airport since the context at this airport had changed substantially. The purpose of the second

survey was to determine the current most important passenger airport choice attributes and to determine if these attributes were different after the entry of a second airline flying out from the airport. Therefore, passengers travelling on both Mango Airlines (who started offering scheduled domestic flights from Lanseria International Airport in 2012) and Kulula were interviewed in the 2013 survey. This survey was also paper-based and followed the same survey methodology used in the 2010 survey.

The purpose of the 2013 survey was therefore, among others, to enable a comparison of passenger responses over the two time periods in view of changing economic circumstances, additional airline operations, as well as increased flight frequencies offered at the airport.

1.5.4 Unit of analysis

The unit of analysis for this study is individuals, i.e. passengers travelling on scheduled domestic flights to and from Lanseria International Airport.

1.6 SCOPE AND LIMITATIONS OF THE STUDY

This study will investigate the passenger airport choice factors (attributes) considered by passengers when selecting an airport. Knowing the reasons why passengers prefer a specific airport could assist airport managers and owners to better position their airports to meet such demand.

Limiting this study is the fact that the research was done prior to the implementation of the Gauteng e-toll system in December 2013 and SA Airlink’s announcement to offer scheduled flights from Wonderboom Airport in Pretoria to Cape Town from August 2015. The effect these could have on passengers’ airport choice was therefore not included in this study. This offers the prospect for future research.

1.7 OUTLINE OF THE STUDY

The study consists of six chapters, commencing with an introduction to the study in Chapter 1.

The second chapter contains a description of the airline industry with attention to significant developments in air travel. This chapter will distinguish between full-cost airlines and low-cost airlines, and look at the role each of them plays in the South African airline industry.

In Chapter 3 the low-cost airlines, as well as their association with secondary airports, are examined. In this chapter the role of secondary airports, including airport choice factors, from the perspective of airlines as well as passengers internationally is investigated. In this chapter the role of Lanseria International Airport in the South African domestic airline industry will also be addressed.

In Chapter 4 the research methodology that was followed in the study is detailed.

In Chapter 5 the findings of the 2013 passenger survey are analysed and compared to the 2010 study conducted by the Institute of Transport and Logistics Studies (Africa) at Lanseria International Airport.

Finally in the last chapter, Chapter 6, a summary and conclusion of the study are provided.

CHAPTER 2: AN OVERVIEW OF THE AIRLINE INDUSTRY

2.1 INTRODUCTION

The introductory chapter referred to historical developments in aviation as well as the future prospects for aviation. It highlighted various trends in aviation, especially the emergence of LCCs. It is the aim of this chapter to provide an overview of the airline industry, distinguishing between full-service carriers and low-cost carriers. The chapter outline is depicted in Figure 2.1.

2.1 Introduction

2.2 Phases of development in aviation

Chapter 2 An overview of the airline industry 2.3 Full-service air carriers

2.4 Development of low-cost air carriers

2.5 Conclusion

Figure 2.1: Outline of Chapter 2

2.2 PHASES OF DEVELOPMENT IN AVIATION

In order to place the development of LCCs in perspective it is necessary to first examine the four significant phases of development in aviation. The four phases which will be described are: regulation, liberalisation, deregulation and privatisation. Each phase has impacted the airline industry, both locally and internationally, in significant ways.

2.2.1 Regulation

Historically, the airline industry was rigorously controlled by governments. Therefore airfares, routes, types of aircraft operated, capacity provided by the airline, frequency of flights (e.g. number of return flights per day on a certain route), relationships between airlines (e.g. agreements) and market entry of new airlines were strictly managed through the implementation of legislation by the respective authorities. Elements of an economic regulated airline industry include strict ownership control of airlines (mostly government-owned airlines), very limited competition on routes, service to a limited number of markets, and high airfares (Wensveen, 2011).

Economic regulation was historically motivated for various reasons including safety (high safety standards need to be adhered to), defence (especially in times of war or state of emergency) as well as the fact that air transport is viewed as a public utility (Smith, 1998). Innovations were severely limited owing to restricted levels of competition in the industry as a result of economic regulation of the industry and government restrictions imposed on new entrants.

2.2.2 Liberalisation

A liberalised international airline industry allows for less government control compared to a regulated environment in order to encourage competition in the market (International Civil Aviation Organisation [ICAO], 2013). The International Air Transport Association (IATA) permits diversification into new products and extension into new markets. It allows for an air carrier to exit a market if it is not successful in a specific market (Wensveen, 2011).

Liberalisation between Ireland and the United Kingdom (UK) preceded the deregulation of the European air transport market in the 1980s. In Europe, liberalisation took place in four steps and can be summarised as follows (European Low Fares Airline Association [ELFAA], 2004): 1. 1987 – Restrictions on fares were reduced and carriers were allowed flexibility to cooperate within the confines of existing air service agreements. 2. 1990 – All European airlines were permitted to transfer passengers to and from their home countries to other European Union (EU) states. Further reduction in fares and capacity were observed. 3. 1993 – Common licencing of carriers and freedom of access to the market was announced. Airlines in possession of a community licence were permitted to operate on any international route within the EU. Carriers were given almost complete freedom to set fares. 4. 1997 – Carriers in possession of a community licence were given the right of cabotage4 and therefore the right to operate domestic routes within the entire EU.

Liberalisation of the European air travel market created a single market for air transport and it increased competition in the market as well as consumer choice, together with lowering fares. It gave carriers the freedom to select their routes, capacity, schedules and fares. Intervention from national governments in these decisions was also minimised (IATA, 2006). Liberalisation can be beneficial to consumers (passengers) as well as producers (airlines) according to an analysis done by the International Air Transport Association (IATA). In this study IATA analysed the impact of liberalisation in four different industries (retail banking, energy, telecoms and media) and concluded that the results were relevant for the airline industry and included the following benefits for both passengers and airlines (IATA, n.d):  Lower fares (passengers)  Increased output and choice (passengers)  Better service quality (passengers)

4 ‘The carriage of air traffic that originates and terminates within the boundaries of a given country by an air carrier of another country’ Aircraft Owners and Pilots Association (AOPA) (2015)

 Improved capacity utilisation (airlines)  Increased productivity (airlines)  Increased investment (airlines)  Improved profitability (airlines)  Increased market value of airline (airlines)

The analysis by IATA indicated that organisations (airlines) can have four strategic responses to liberalisation (IATA, n.d): 1. Extension into new markets – liberalisation provides opportunities to expand into new markets 2. Diversification into new products or services – with an increase in competition and consideration of a wider product or service range 3. Specialisation in niche products – an airline may choose to focus on its competitive strength in order to ensure customers are retained and revenue maximised 4. Market exit – an airline may be forced to exit the market in response to competition, but at the same time, new entrants may find it difficult to gain a position in the market and are then forced to exit

The liberalisation of the European air transport market also created conditions for the emergence of the first European low-cost airline, Ryanair. Ryanair was allowed to service certain routes between Ireland and the UK, bringing competition to a market only served by Aer Lingus and British Airways (ELFAA, 2004). Low-cost carriers such as Ryanair and EasyJet expanded rapidly and also captured market share from Europe’s larger, more established carriers after liberalisation (Vasigh et al., 2008).

2.2.3 Deregulation

The aim with deregulation is to remove government from the operating and marketing of air services and at the same time stimulate competition in the airline industry. By doing this, lower prices or a variety of prices are possible, more services are available and objectives of efficiency are achieved (ICAO, 2013).

In a deregulated environment aircraft can be utilised optimally and service quality will improve as a result of competition. Air transport services are now provided based on the demand in the market instead of predetermined by airlines or government (Wensveen, 2011). Safety in aviation is by no means neglected in the process of deregulation as governments continue to regulate the technical and safety aspects of the industry. Deregulation allows new entrants to the industry thereby enhancing competition between airlines and the seeking of innovative ways of delivering air services to a market (IATA, 2006). After deregulation, airlines had to change the way in which their services were marketed in order to increase market share and keep costs down. In competing for passengers, airlines worldwide embarked on various marketing strategies (Wells, 1999) as follows:  Computerised Reservation Systems (CRSs) – airline schedules and prices are displayed for use by travel agents. Air services are much more complex and air ticket prices and schedules change so frequently that it is essential to have a system that assists travel agents to inform passengers timeously. CRSs provide an important marketing advantage for the airlines that own them. CRSs can be expanded to include additional reservations for accommodation and land transport rental. Fees accrued when passengers make use of such services contribute to the profit of an airline owning such a system. CRSs are designed to select flights based on published schedules and therefore airlines find it economically viable to develop schedules that include flights departing and arriving at major cities during the morning and evening peak hours.  Travel agents – because of CRSs, travel agents have now become an integral part of the commercial air travel system since deregulation. They deliver a valuable service to passengers by making complex travel options more accessible to them. Travel agents have become closely affiliated with airlines through CRSs and airlines rely on CRSs to influence travel agents; and together with commission overrides paid by airlines, travellers successfully shift to favoured airlines. However, reservations for flights on LCCs are mostly done electronically (on the internet) by the passengers themselves (Franta, 2009). This will be highlighted again later in Chapter 3 when the business model of low-cost airlines is discussed.

 Frequent-flyer programmes – a very successful marketing tool used by airlines because it builds customer loyalty, especially from business passengers. These passengers are less likely to take advantage of lower airfares and a specific frequent-flyer programme will most probably influence a passenger’s choice of airline, although this is not the only factor the passenger would consider. Factors such as flight frequency and on-time performance are considered. Larger airlines with extensive route coverage probably have the most attractive frequent-flyer programmes because of the availability of more trip choices with which frequent-flyer miles can be earned. Low-cost carriers generally do not offer a frequent-flyer programme and this strategy is related to their business model.  Business-class services – In 1979, Pan American World Airways introduced a programme intended to attract business passengers. Originally this service only consisted of free drinks and movies on board but it has since grown into a major element for most airlines, especially on international routes, due to the fact that organisations generally prohibit their employees to travel at first-class fares. Business-class seats are more comfortable and there is more leg room than in economy class, and the ticket price is typically more expensive than that of economy class (Diggines, 2010). Once again, LCCs have no class distinction on flights.  Code sharing – when two airlines share the same identification codes on airline timetables (usually a major and regional/commuter airline). By doing this, the larger airline promotes flights to a greater market and is able to develop its market at a lower cost. The regional or commuter airline often offers a low-cost operation and, as a result, a feeder service to the major airline at lower costs than what the major airline can achieve on the same route. This practice became so popular in the 1980s that some commuter airlines were taken over by their affiliate airlines (major airlines), and these greatly enhanced economies of scope.  Concentration of business – deregulation led to the concentration of business. Mega carriers were formed by absorbing small and midsized airlines. Table 2.1 indicates that five of the top 12 airlines (in terms of domestic market share measured by revenue passenger miles [RPMs]) of 1978 no longer exist. Two

airlines, Eastern and Braniff, went bankrupt. Delta absorbed Western; National was taken over by Pan American. With Pan American’s demise, the services were taken over by Delta and United (Wensveen, 2011). Southwest, an LCC, gained market share in 2013 and is among the top three airlines in the US in terms of domestic market share. In 2014 Southwest acquired AirTran, which will give the airline access to more destinations (Harty, 2014).

Table 2.1: Top US air carriers before and after deregulation

1978 2004 2013 Ranking Airline Percentage (%) Airline Percentage (%) Airline Percentage market share market share (%) market share 1 United 18.46 American 20.02 Delta 16.3 2 American 13.78 United 17.64 United 16.0 3 Trans World 12.7 Delta 15.10 Southwest 15.1 4 Eastern 11.86 Northwest 11.29 American 12.9 5 Delta 10.99 Continental 9.73 US Airways 8.2 6 Pan American 9.91 Southwest 8.24 JetBlue 5.0 7 Western 4.8 US Airways 6.24 Alaska 4.0 8 Braniff 4.5 America 3.59 AirTran 2.6 West 9 Continental 4.1 Alaska 2.50 ExpressJet 2.5 10 National 3.7 JetBlue 2.42 SkyWest 2.3 11 Northwest 3.3 American 1.93 Other 15.1 Trans Air 12 Allegheny 1.9 AirTran 1.30 Source: Wensveen (2011:166) and Centre for Aviation (2013a)

 Hub-and-spoke service – after deregulation, airlines decided to focus on eliminating non-profit routes and rather focused attention on profitable, high- density routes serving large- and medium-sized airports. A hub-and-spoke system consists of routes that are coupled to a central airport (hub) and passengers are transferred from feeder flights to other flights and then flown to their final destination (Fu, Oum and Zhang, 2010). Airlines mostly select busy airports as a hub and this then provides passengers with a widespread selection of potential connections. A drawback of hub-and-spoke operations is that they rely on tightly scheduled arrivals and departures which may result in

congestion and delays in peak hours, especially at the busier hub airports. These often result in additional costs and customer disappointment. For this reason, LCCs tend to focus operations from less congested secondary airports and mostly offer point-to-point services.  Advertising and sales promotion – after deregulation airline advertising mostly focuses on a combined product or service to passengers which includes a combination of acceptable price, favourable destinations and flight frequencies.

After deregulation of the air transport market in the US, major changes in the airline industry were observed. In the US these changes comprised the entry of LCCs, mergers among major airlines, a significant growth in the number of people travelling by air, overall lowering of airfares and the rise of hub-and-spoke systems (Cento, 2009). Ten years after deregulation in the US, Europe followed suit, but initially with a slower and smaller effect on routes and fares. The first after-effect of deregulation in Europe was an increase in alliances among international airlines. Secondly, the further development of the existing hub-and-spoke system by former flag carriers was evident and, thirdly, the phenomenal growth of LCCs, the likes of Ryanair and EasyJet (Cento, 2009).

South Africa’s policy in respect of air travel kept in step with these developments – deregulation of its domestic air transport industry took place in 1991. This brought about new prospects for airlines to enter the market, resulting in changes to the role of the established airlines at that time (Smith, 1998). Some of the consequences of airline deregulation in South Africa were service innovations such as frequent-flyer packages, a variety of fare classes, existing airlines expanding into the wider domestic market, new airlines being established, and eventually the introduction of LCCs in 2001.

2.2.4 Privatisation

With privatisation, governments tend to withdraw from airline ownership and management allowing it to be managed in a more commercial fashion to ensure survival in a hostile and competitive landscape, which also facilitates economic 22

growth in a country. The process and extent of privatisation differs between countries (Macchiati & Siciliano, 2007). When an organisation or an airline is privatised, a number of factors change simultaneously (Eckel, Eckel & Singal, 1997):  Ownership changes from the government to a private entity  Profit maximisation becomes the ultimate objective  Regulation changes to enhance competition in the market

Various major airlines were privatised in this manner such as British Airways (BA), Lufthansa and Iberia to mention a few.  British Airways used to be a fully state-owned company until 1986. The first announcement of privatisation was made in 1979 when the Conservative Party in Britain indicated the intention to sell some of the government’s shares in British Airways to the private sector (Başer, n.d). Shortly after the announcement, British Airways was seen as a ‘largely overstaffed and inefficient airline, which occasionally generated substantial losses’ (Macchiati & Siciliano, 2007). In 1987 the company was listed on the London Stock Exchange when the state sold its total stake through an Initial Public Offering (IPO). After privatisation British Airways acquired British Caledonian, its main domestic competitor. This allowed BA to expand its production capacity. Restructuring operations included opening new brands (World Traveller in international routes and Euro Traveller in internal routes) and services (self- ticketing and new routes that included Japan) (Macchiati & Siciliano, 2007).

 Iberia was a state-owned airline until 1999. In 2000, private investors (four Spanish institutional investors, British Airways and American Airlines) bought the 41% government stake by means of a private deal. In 2001 Iberia was listed through an IPO when the state sold its remaining 54% stake (Macchiati & Siciliano, 2007). In 2000 the unit cost of Iberia was below the industry average and therefore cost optimisation was one of the restructuring objectives. After privatisation Iberia also strengthened its dominance on the routes between Spain and Latin America (Macchiati & Siciliano, 2007).

 About 51% of the voting rights of Lufthansa were controlled by the German state until 1993. In 1994 new equity capital was raised and the state sold stock rights through a public offering. The state’s interest was reduced to 35%. By 1997 government sold a further stake in Lufthansa and the airline was privatised. A key issue Lufthansa had to deal with during its restructuring was the large pension deficit accrued by the company. Some divisions within the airline were transformed into separate businesses, e.g. Lufthansa Cargo. After privatisation Lufthansa also acquired a 20% stake in British Midland, an acquisition which ensured valuable slots at Heathrow airport (Macchiati & Siciliano, 2007).

Although several airlines have been successfully privatised, many governments resist privatisation, mainly owing to the fact that a national flag carrier is seen as prestigious, and regular scheduled services by a national carrier is a tool of commercial policy (Macchiati & Siciliano, 2007).

This section of the chapter highlighted the regulatory environments typically found in the airline industry and its impact on competition, ownership and new airline developments. Exposing the industry to competitive market forces has shaped the establishment of LCCs and the subsequent development of secondary airports in support of the low-cost airline business model.

The next section discusses the business model of full-service carriers (FSCs) and discusses the FSCs that operate in the South African domestic market. This will be followed by an exposition of the development of LCCs both internationally and in South Africa.

2.3 FULL-SERVICE CARRIERS

Two types of airlines mostly operate in the airline industry, namely full-service and low-cost carriers. There are noteworthy differences in the business model of each of these types of airlines.

2.3.1 Business model of full-service carriers

The elements of the business model of a full-service air carrier is summarised in Table 2.2.

Table 2.2: Elements of the full-service carrier business model

FSC business model elements Characteristics Core business Passengers, cargo and maintenance Hub-and-spoke network Objective is to cover as many demand categories as possible Global player Covers domestic, international and intercontinental markets Alliances Networks are increased with establishment of partner carriers Product differentiation All possible market segments are covered by means of vertical product differentiation Customer relationship management Loyalty programmes to personalise the airline’s service Yield management and pricing Yield management is sophisticated to maximise network revenues Distribution and sales channels Distribution system is supported technologically by external companies and sales channels include indirect off- line, indirect on-line, direct on-line and direct off-line Source: Summarised by author from Cento (2009)

The following section will discuss the typical South African full-service carriers and their respective characteristics. Even though the FSCs do not operate from Lanseria International Airport, it is beneficial to briefly describe these airlines in order to understand the role they play in the South African domestic air travel environment.

2.3.2 Full-service carriers in South Africa

The full-service carriers that service the domestic market in South Africa include South African Airways (SAA) and British Airways Comair. SAA provides domestic,

regional (within the Southern African Development Community [SADC] region), international and intercontinental flights, and meets most of the criteria for an FSC as alluded to by Cento (2009) although it is state-owned. British Airways Comair as a privately-owned airline operates on domestic and regional (SADC region) routes but does not have a global presence in terms of the criteria cited by Cento. However, through its alliance with British Airways (and shareholding of BA in Comair), passengers indirectly have access to a global network of BA services. SA Airlink and SA Express also service the domestic and regional (SADC) markets and provide the main feeder and distribution services to the main airports (hubs) in South Africa.

2.3.2.1 South African Airways

South African Airways (SAA) is an airline entirely owned by the South African government and has a long history. In 1934 Union Airways was acquired by the South African Railways and Harbour administration and in 1936 a service was introduced by SAA between Johannesburg, Kimberley and Cape Town, replacing the service operated by Imperial Airways since 1932. By 1938 SAA serviced the following routes: Johannesburg–Durban; Durban–Cape Town and the Johannesburg–Bulawayo route (Vermooten, 1996). In 1940, SAA became a military wing of the South African government at the time and no commercial services were offered until December 1944. In April 1945, SAA became one of the 44 active founding members of the International Air Transport Association (IATA) (SAA, 2012).

During 1970, SAA surpassed the one million mark for passengers carried domestically annually and it was necessary to expand its fleet in order to improve traffic growth on domestic and regional routes. The airline acquired its first Boeing 747 aircraft (ZS-SAN Lebombo) and it was primarily utilised on international routes. For the regional and domestic routes, SAA acquired 12 Boeing 737s, three Boeing 747SPs and four Airbus A300s (SAA Museum, 2013). SAA formed an alliance with SA Express and SA Airlink. The latter two airlines are feeder service operators and they acquired some of SAA’s low-density domestic routes (SAA Museum, 2013). Both SA Express and SA Airlink have code-share agreements with SAA, and SA Airlink also has a franchise agreement with SAA.

Table 2.3 indicates the domestic and regional routes serviced by SAA (inclusive of SA Express and SA Airlink).

Table 2.3: Domestic and regional routes serviced by SAA (including SA Express and SA Airlink)

Domestic Domestic Regional (operated by SAA) (operated by SA Express (African countries) and/or SA Airlink)  Johannesburg (OR Tambo  Polokwane  Angola International Airport)  Phalaborwa  Cameroon  Durban  Hoedspruit  Ethiopia  Cape Town  Mala Mala  Kenya  Port Elizabeth  Nelspruit  Mauritius  George  Pietermaritzburg  Sudan  East London  Richards Bay  Zambia  Mthatha  Dem. Rep. of Congo  Bloemfontein  Mozambique  Kimberley  Senegal  Upington  Zimbabwe  Mahikeng  Botswana  Ghana

 Madagascar  Seychelles  Tanzania  Burundi  Ivory Coast  Malawi  Uganda

Source: Summarised by author from SAA (2013)

2.3.2.2 British Airways Comair

In 1946 Commercial Air Services introduced a charter flight from Rand Airport in Germiston, to Durban. JMS Martin, Leon Zimmerman and AC Joubert established a business that would offer pilot training, a charter service and possibly the sale of aircraft (Comair, 2012). New South African Aviation regulations in 1948 paved the way for Comair to begin its first scheduled service utilising a Cessna model 195. A Cessna with a pilot and only four passengers on board flew daily from Johannesburg to Durban and back, via Kroonstad, Odendaalsrust, Bloemfontein, Bethlehem and

Ladysmith but when government support was rejected, the service had to end. Anglo American Corporation approached Comair to keep the service – even if it was just to the Free State Goldfields – and agreed to subsidise the losses within reason (Comair, 2012). The future of Comair was secured thereafter. Over the ensuing years, Comair continued to build as a prosperous organisation and entered the main domestic routes in 1992 (following airline deregulation in 1991 in South Africa), with a Boeing 737-200 and Fokker aircraft, transporting close to 100 000 people per year. The network serviced by Comair included services to Cape Town, Durban, Richards Bay, Skukuza, Manzini, Gabarone and Harare, with 200 departures per week. The target market was predominantly leisure passengers (Comair, 2012). In 1996, Comair Limited changed significantly when it became a franchise partner of British Airways and was thereafter known as British Airways Comair. The airline started to use the colours and uniform of British Airways (Comair, 2012).

Table 2.4 indicates domestic and regional destinations serviced by British Airways Comair.

Table 2.4: Routes serviced by British Airways Comair

Domestic Regional (African countries) Johannesburg Windhoek (Namibia) (O R Tambo International Airport) Durban Livingstone (Zambia) Cape Town Harare (Zimbabwe) Port Elizabeth Source: Summarised by author from British Airways (2013)

The aforesaid analysed the FSCs that operate in the South African domestic market. The mentioned FSCs do not operate from Lanseria International Airport but the analysis provided an understanding of the role these airlines play in the domestic air travel market in South Africa.

2.4 DEVELOPMENT OF LOW-COST CARRIERS

Worldwide, after the deregulation of domestic airline industries, LCCs began to appear in countries as diverse as the US, Asia, Europe, Australia and New Zealand. The fact that all these countries experienced the entry of LCCs as a common outcome of deregulation is of importance to this study.

Cento (2009:19) defines an LCC as ‘an airline company designed to have a competitive advantage in terms of costs over a full-service carrier. In order to achieve and maintain this advantage, an LCC relies on a simplified business model.’ The significance of LCCs in the aviation industry is that they have succeeded in generating or stimulating additional demand in air traffic. They have accomplished this by keeping their costs as low as possible in order to offer low fares to passengers (Max Planck Institute for Chemistry, 2012). A low-cost airline (sometimes known as a no-frills airline) can be seen as a basic product provider as depicted in Table 2.5.

Table 2.5: Airline product

Low-cost carrier Full-service carrier No frills Few frills Many frills Extensive frills Basic product Budget product Standard product Premium product (economy class) (business class) Adapted from source (Bjelicic, 2007:13)

In the US, low-cost airlines are seen as the fastest growing division in the American air transport market. Since deregulation air traffic has increased significantly especially since airlines restructured and offered lower fares (ELFAA, 2004). Low- cost carriers in Europe replicated low-cost operations found in the US, although with a slight variation to the model. Asia embraced the low-cost model and the benefits of LCCs are widely documented (ELFAA, 2004). The European Low Fares Airline Association (2004) highlights the benefits of LCCs in terms of the benefit to consumers, including consumer choice and lower fares; the growth of secondary airports; regional development with increased tourism as well as increased employment and environmental benefits.

2.4.1 Benefits to consumers

Passengers have benefited the most from air transport deregulation and liberalisation together with the development of LCCs.  Increased choice: After deregulation, barriers for new entrants into the air transport market were removed, which increased the number of airlines. This resulted in passengers no longer being restricted to national carriers but having the freedom to choose between various airlines. Routes were served by more airlines than before as a result of the removal of air service agreements that restricted traffic on routes. Passengers at the origin and destination of a route had a greater choice of schedules, frequencies and airports to fly from. The number of direct routes served increased especially due to the direct (point-to-point) services offered by LCCs as opposed to a connecting (hub-and-spoke) service.  Lower fares: Increased competition in the air transport market and the growth of LCCs led to a decrease in airfares. Traditional airlines are in many cases forced by competitive pressure from LCCs to lower their fares in order to retain their market share on routes serviced by both types of airlines. Research indicates that passengers flying with LCCs ‘would not have travelled by air had it not been for low fares’ (ELFAA, 2004:16).

2.4.2 Growth of secondary airports

Deregulation and liberalisation of the air transport market and the subsequent emergence of LCCs have benefited airports. Various airports, especially the formerly underserved regional or secondary airports have grown tremendously.  Emergence of low-cost airports: Regional and secondary airports offer greater freedom in terms of slot availability. Airlines would therefore base their choice of airport on costs. Inefficiencies of state-owned airports used to be passed on to the airline and ultimately the passengers by means of higher airfares. With the entry of LCCs to the air transport market this is no longer the case. Low- cost airlines are ensuring passenger growth at underutilised airports by

negotiating lower fees from these airports, forcing increased efficiency. All airports have fixed costs irrespective of passenger throughput. An increase in passenger numbers increases aeronautical and non-aeronautical revenue, making it easier to cover these costs. Airports and especially low-cost or secondary airports rather focus on non-aeronautical charges as the primary source of income. A good example of this is Love Field Airport in the US, base of Southwest Airlines, where non-aeronautical revenue is ‘three times higher’ than revenue generated from aeronautical charges (ELFAA, 2004:18).

Low-cost carriers often operate from regional or secondary airports which allow them to have quicker turnaround times and lower airport charges. Bonnefoy, de Neufville and Hansman (2010) established that in the US ‘13 airports emerged’ because Southwest Airlines focused their operations on ‘existing non-used airports’. One example shows that Southwest Airlines was responsible for an average annual 45% growth rate in passengers from Boston to Manchester in 1998 compared to an annual average of 6% between 1990 to 1997 (Bonnefoy et al., 2010).  Traffic growth at low-cost airports: In the UK the low-cost airport model proved to be very successful after liberalisation between Ireland and the UK. London Stansted Airport and Glasgow Prestwick were transformed from unprofitable secondary airports to major international airports now serving metropolitan areas. All over Europe this model was copied and secondary airports provide a competitive alternative to congested, more expensive hub airports. Catchment areas of these airports can drastically increase as passengers are willing to travel further in order to pay lower airfares (ELFAA, 2004).

Passengers’ choice to fly from a secondary airport as well as the development of these secondary airports will be highlighted further in Chapter 3.

In many cases the arrival of an LCC to these secondary and underutilised airports created a new market dynamic by opening new market opportunities and stimulating traffic (Bonnefoy et al., n.d.).

2.4.3 Regional development

Regional economies benefit greatly from airports (Van de Voorde, n.d). Low-cost airlines servicing a regional or secondary airport can greatly increase tourism and encourage businesses to locate near such an airport. Prior to deregulation, few individuals could afford to travel by air and many cities lacked access by air and were only reachable by connecting through a hub airport resulting in expensive and long journeys (Donzelli, 2010).

Increased employment in various sectors of the economy can be attributed to the development of low-cost airlines and can be allocated as follows (Donzelli, 2010):  Employment created within airlines themselves  Employment created at airports  Employment created in regional businesses

2.4.4 Environment

The environment can benefit greatly from low-cost airlines and their contribution to environmentally efficient travel in Europe due to the nature of their operations and newer fleets of aircraft which are mostly technologically advanced and energy efficient. The factors that contribute to the lower environmental impacts by LCCs include (ELFAA, 2004):  More efficient seat configuration  Lower fuel consumption  Decreased noise emissions  Direct services, therefore fewer connecting flights  Reduced waste

Although the first LCCs started operating in North America, the emergence of LCCs is not restricted to the US. It has been a global phenomenon with almost every market being serviced by a low-cost air carrier (Vasigh, Fleming & Tacker, 2008). The development of LCCs has differed from continent to continent in terms of when they came into existence, the number of carriers in the market as well as the

success of these LCCs. Although there are many regions where LCCs operate, the following section will describe the US and European markets as the pioneers in the development of LCCs as well as the South African market as it is the focus of the research.

2.5 UNITED STATES OF AMERICA

The US Airline Deregulation Act of 1978 opened up the low-cost air transport phenomenon because it brought about liberation of the market for flight routes and flight prices between the states in America (Max Planck Institute for Chemistry, 2012). The world’s largest regional air traffic market can be found in North America and it is here where the concept of the LCC originated. Pacific Southwest Airlines started offering low prices as early as the 1950s and was followed in 1967 by Southwest Airlines, but their services were limited to Texas (Max Planck Institute for Chemistry, 2012).

2.5.1 Southwest Airlines

The fastest-growing and most profitable airline in the US is Southwest Airlines. This airline focuses on dense, short-haul markets providing a regular service instead of operating a hub-and-spoke system (Bennett & Craun, 1993). According to Rigas Doganis (2010:134), the strategy of Southwest Airlines was to offer passengers a service that is ‘simple, uncluttered, low fare and point-to-point.’ They aimed at achieving ‘high aircraft and crew utilisation by operating from secondary and uncongested airports’. The story of Southwest Airlines started in March 1967 when Rollin King and Herb Kelleher wanted to provide an air service within the state of Texas and incorporated Air Southwest Co. In 1971 the airline’s name was changed to Southwest Airlines Co. and the headquarters was situated in Dallas (Southwest Airlines, 2014a). In 1971 Southwest Airlines offered its first scheduled passenger flights from Dallas to Houston and Dallas to San Antonio after overcoming various legal battles. Initial load factors were low but this soon improved when the airline moved its operation from Houston’s Intercontinental airport to the smaller and older Hobby Airport. This airport was closer to the city centre (Calder, 2003). First profits were realised in 1973. With the oil crisis in 1973 aviation fuel prices tripled thus

straining airlines. Southwest Airlines refused to let this impact on profits. The airline simply maximised the utilisation of the aircraft by improving turnaround time at airports (Calder, 2003).

During the 1980s and 1990s Southwest Airlines acquired and sold off various other airlines, a common trend among airlines after deregulation (Southwest Airlines, 2014b & c). In 1995, Southwest Airlines became one of the first airlines to have a website where passengers could view flight schedules, route maps and company information, and by 2006 as much as 70% of flight reservations were done on the airline’s website (Southwest Airlines, 2014d & e). The airline’s headquarters and facilities at Love Field Airport were upgraded significantly between 1996 and 1997 (Southwest Airlines, 2014d). In 2011 Southwest Airlines acquired the common stock, corporate identity and operating assets of AirTran Airways. With this acquisition a direct low-cost competitor was eliminated and Southwest Airlines could enjoy access to Atlanta, additional landing slots in the New York and Washington DC areas, as well as 25 additional destinations not previously serviced. The integration of these two operations was set to continue until 2014 (Southwest Airlines, 2014f).

After many years, Southwest Airlines is still the most profitable low-cost airline (Vasigh, Fleming & Tacker, 2008). The airline’s success may be attributed to its simple proposition: ‘Keep planes flying, because that is where they make money. And keep fares low enough to keep people travelling’ (Calder, 2003:31). Table 2.6 lists most of the low-cost airlines operating in the United States.

Table 2.6: Low-cost airlines in the US

Allegiant Air Domestic flights from Las Vegas AirTan Airways Low-cost domestic services along the Atlantic Coast Frontier Airlines Scheduled low-cost services from Denver JetBlue Airways Low-cost flights in the east of the US Southwest Airlines Largest low-cost airline in the world. Domestic services within the US Spirit Airlines Domestic and international services in the northeast of the US Sun Country Airlines Low-cost services and charter flights to the Caribbean VivaAerobus Budget flights from Monterrey in Mexico and to the US WestJet Airlines Low-cost operations in Canada and to the US Source: Summarised by author from Airlines Inform (2013)

2.6 EUROPE

In Europe, liberation of the aviation market in the European Union motivated LCCs to start operating. In Europe the low-cost concept was introduced by EasyJet and Ryanair in the UK and Ireland respectively. Their business model was based on that of Southwest Airlines (Max Planck Institute for Chemistry, 2012). Europeans, especially the younger generation from Western Europe, are changing their habits. They have more leisure time and prefer to travel further for recreational activities. The availability of low-cost air travel encourages them to have these preferences (Bjelicic, 2007.).

This study will only concentrate on the leading low-cost airlines servicing the European market, namely Ryanair and EasyJet (Bjelicic, 2007).

2.6.1 Ryanair

Ryanair took to the skies in July 1985 after it was set up by the Ryan family. The first 15-seater flight was from Waterford in the south of Ireland to London Gatwick airport. In 1986, flights from Dublin to London Luton Airport were introduced and in the first year of operation the airline transported around 80 000 passengers (Calder, 2003). A year later the airline increased its network by adding routes from Dublin to Liverpool, Manchester, Glasgow and Cardiff. In 1989 their routes included services to Brussels and Munich (Ryanair, 2014). In 1990 the airline was restructured and relaunched as Europe’s first low-cost airline, copying the Southwest Airlines’ business model. It now offered the lowest fare in every market, operated a single aircraft fleet type with increased flight frequencies, and carried 745 000 passengers. During the Gulf War London Stansted Airport became Ryanair’s London base (Ryanair, 2014).

Ryanair became the largest passenger airline in 1995 on the biggest international scheduled route in Europe (Dublin–London route), overtaking Aer Lingus and British Airways and proving that the low-fare, high-frequency approach is successful (Ryanair, 2014). In September 1995 a domestic route, London Stansted to Glasgow Prestwick, was serviced for the first time by a low-cost air carrier (Calder, 2003). By

the late 1990s more European routes were added to Ryanair’s network, including London Stansted to Stockholm and Oslo, as well as Dublin to Paris. A third airport base, Glasgow Prestwick, was launched (Ryanair, 2014).

In 2000, Ryanair launched internet reservations and it gave passengers the opportunity to reserve lowest-cost car hire, hotel accommodation, travel insurance and rail services together with their airline tickets (Ryanair, 2014).

The first continental European base, Brussels Charleroi Airport, proved to be very successful despite negativity from competitors that people will never fly from Charleroi Airport or that low fares will not take off in Brussels. For the first time ever, Ryanair carried one million passengers within a month. Frankfurt Han Airport was selected as a second continental European base with two more bases, Milan Bergamo and Stockholm Skavsta, to follow. By 2005, Ryanair had 15 bases throughout Europe. In 2006, it became the first airline in the world to carry four million international passengers in one month (Ryanair, 2014).

Ryanair’s product, efficiency, low-cost base and utilisation of secondary airports seem to contribute positively to its future (Barrett, 2004a).

2.6.2 EasyJet

The airline was established in 1995 and the first flight took off on 10 November 1995, flying from London Luton to Glasgow. Two routes were serviced initially – London Luton to Glasgow and London Luton to Edinburgh (Jones, 2005); and in 1996 the airline served its first international route to Amsterdam (EasyJet, 2014). In 1998, EasyJet acquired a 40% stake in a Swiss Charter Airline, TEA Basle, and the airline was named EasyJet Switzerland. The operating base was Geneva International Airport, the first base outside the United Kingdom for EasyJet (EasyJet, 2014). In 2002, EasyJet acquired yet another airline, its rival Go. This gave the airline three new bases to operate from: Bristol Airport, East Midlands Airport and London Stansted. In 2002 EasyJet opened a base at Gatwick Airport (Jones, 2005). By 2007, EasyJet was well known throughout Europe and bases included Germany, France, Italy and Spain. In 2007, it expanded its operations at London Gatwick

Airport and established a base at Manchester Airport. By 2011, the airline operated from 11 United Kingdom bases when London Southend Airport was added (EasyJet, 2014). In a rather short life-time EasyJet has developed as one of Europe’s most successful low-cost airlines (Koenigsberg, Muller & Vilcassim, 2004). Table 2.7 indicates most of the low-cost airlines operating in Europe.

Table 2.7: Low-cost airlines in Europe

Aer Lingus Ireland Air Berlin Germany Air One Italy AnadoluJet Turkey Blu-Express Italy Blue Air Romania EasyJet United Kingdom EasyJet Switzerland Switzerland Flybe United Kingdom Freshline Germany Germanwings Germany Helvetic Airways Switzerland Iberia Express Spain Intersky Austria Jet2.com United Kingdom Monarch Airlines United Kingdom Niki Austria Onur Air Turkey Pegasus Airlines Turkey Ryanair Ireland Smart Wings Czech Republic Thomson Airways United Kingdom Transavia Airlines Netherlands TUIfly Germany Volotea Italy Vueling Airlines Spain Wizz Air Hungary Wizz Air Bulgaria Bulgaria Source: Summarised by author from Airlines Inform (2013)

From the aforementioned it manifested that deregulation of the air transport industry in the US and Europe led to the establishment and subsequent growth of LCCs. Low-cost carriers provide benefits to passengers by offering lower fares as well as increased choice since deregulation allowed new entrants into the market which led

to an increase in competition. The LCCs that entered the market after deregulation stimulated the growth of secondary airports. These airports were previously underutilised but due to LCCs choosing to operate from such airports to save costs and avoid congestion at primary airports, secondary airports have become prevalent.

The following section will examine the South African scenario pertaining to LCCs entering the market after deregulation.

2.7 SOUTH AFRICA

In South Africa there are currently two LCCs that serve the domestic passenger market, namely: Kulula and Mango Airlines. From 2004 1Time Airline also offered low-cost tickets to the South African domestic market until operations were terminated in 2012 (News24, 2012). FlySafair commenced operations in October 2014 (FlySafair, 2015) but was not included as the fieldwork for the study was conducted in 2013.

2.7.1 Kulula

In 2001 British Airways Comair announced that it intended to introduce a new, budget airline to serve the domestic airline industry. At that time the local South African airline industry was under pressure, and average load factors were low and ticket prices high. This could be attributed to various factors but the main culprit was elevated fuel costs (Lawrence, 2011). The idea was to have a low-cost, ‘no-frills’ airline with low ticket prices. No frills meant that there would not be any free refreshments served during the flight. If passengers wish to have snacks and refreshments, they had to purchase them (Lawrence, 2011). The new low-cost airline was owned by British Airways Comair and this gave passengers the assurance that good safety and maintenance standards were adhered to as with the British Airways liveried aircraft, and it was hoped that the Comair name would bring loyalty to the new airline (Lawrence, 2011).

Kulula started operations on 1 August 2001 with a striking green and blue aircraft, carrying 156 passengers (Lawrence, 2011). Kulula is a Zulu word for ‘easily’ and currently over 80% of their reservations are done online (Kulula, 2012).

Kulula has turned out to be successful, despite competition in the market. One reason has to be that the airline kept initial costs low by utilising much of the already existing infrastructure of British Airways Comair in the start-up phases. This included reservation and ticketing systems, as well as aircraft handling and maintenance facilities. Pilots were available from a total pool of pilots. Dedicated pilots for Kulula were recruited as the operation grew (Lawrence, 2011). Currently Kulula operates more than 325 flights a week on 15 routes, which includes three regional destinations. Kulula offers domestic and regional flights from ORTIA as well as domestic flights from Lanseria.

A five-year Memorandum of Understanding between Kulula and Lanseria International Airport, signed in 2006, gave Kulula ‘exclusive rights for five years to operate a domestic scheduled passenger airline service from Lanseria; and a ‘right of first refusal’ for the remaining duration of the agreement’ (Competition Commission, 2003:3). This meant that any new operator planning to operate from Lanseria had to hand in a flying schedule; this would be given to Kulula. Kulula could then exercise their ‘right of first refusal’ if they so wished. This right allowed Kulula 12 weeks to fly the proposed routes or times. If Kulula failed to do this, Lanseria could allow the new operator to operate (Competition Commission, 2013). This agreement greatly assisted Kulula in launching their operation as the airline and Lanseria airport both contributed substantial investments and no other scheduled passenger airline has been able to sustain a scheduled domestic airline service from Lanseria prior to 2001 (Competition Commission, 2013).

A study conducted by Luke (2015) concluded that passengers select Kulula for two main reasons: first, because of its low fares and secondly, for the number of flights the airline offers from Lanseria (in addition to the flights offered from ORTIA), which is seen as a competitive advantage for Kulula. Business travellers, higher income people and older people are typically passengers that select to fly with Kulula according to Luke (2015).

Tables 2.8 and 2.9 respectively depict the domestic and regional routes serviced by Kulula.

Table 2.8: Domestic routes serviced by Kulula

Departing city Arrival city Johannesburg (ORTIA)  Cape Town  Durban  George  East London  Port Elizabeth Johannesburg (Lanseria)  Cape Town  Durban Cape Town  Johannesburg (ORTIA)  Johannesburg (Lanseria)  Durban Durban  Johannesburg (ORTIA)  Johannesburg (Lanseria)  Cape Town East London  Johannesburg (ORTIA) George  Johannesburg (ORTIA) Port Elizabeth  Johannesburg (ORTIA) Source: Summarised by author from Kulula (2013b)

Table 2.9: Regional routes serviced by Kulula

Departing city Arrival city Johannesburg (ORTIA)  Maputo (Mozambique)  Windhoek (Namibia)  Harare (Zimbabwe)  Mauritius  Victoria Falls (Zimbabwe)  Livingstone (Zambia) Source: Summarised by author from Kulula (2013b&c)

2.7.2 1Time Airline

1Time Airline was the second largest, privately owned, LCC in South Africa in terms of domestic market share in 2012 (1Time, 2012a). The airline commenced operations in February 2004 and offered low price tickets but only serviced profitable

selected routes. 1Time Airline had ten aircraft and operated about 33 flights per day on eight domestic routes (1Time, 2012b). When the airline launched operations it initially offered only three return flights a day between Johannesburg and Cape Town but soon expanded to also offer services between Johannesburg and Durban, East London, Port Elizabeth, Cape Town and George. In addition, the airline operated from Cape Town to Port Elizabeth, East London and Durban and carried approximately 120 000 passengers per month (1Time, 2012b).

Unfortunately 1Time Airline was officially liquidated in November 2012, bringing its service to domestic passengers to an end (News24, 2012).

2.7.3 Mango Airlines

Mango Airlines is South Africa’s third low-cost airline and is based in Johannesburg. The first bright orange-coloured aircraft of this airline took to the skies in November 2006 (Aviation Live, 2012). Although the airline is owned by SAA it operates separately and independently from the national carrier and has its own board and management. Aircraft are leased from SAA (Staisch, 2007). As from June 2012, Mango Airlines offered flights from Lanseria in addition to the flights already offered from O R Tambo. Mango Airlines is perceived by passengers as the airline that offers the lowest fares in the South African domestic market. This is reflected in the finding that price is the most important attribute passengers consider when selecting Mango Airlines. The airline considers the leisure market to be their main focus area and typical passengers include younger people, students, and lower income individuals (Luke, 2015).

The domestic cities serviced by Mango Airlines are listed in Table 2.10.

Table 2.10: Domestic routes serviced by Mango Airlines

Departing city Arrival city Johannesburg (ORTIA)  Cape Town  Durban  Port Elizabeth Johannesburg (Lanseria)  Cape Town Cape Town  Bloemfontein  Durban  Johannesburg (Lanseria)  Johannesburg (ORTIA)  Port Elizabeth Bloemfontein  Cape Town Durban  Cape Town  Johannesburg (ORTIA) Port Elizabeth  Cape Town  Johannesburg (ORTIA) Source: Summarised by author from Mango Airlines (2013)

2.8 CONCLUSION

Deregulation, liberalisation and privatisation of airlines increased the rise of commercial airline activities and with the birth of low-cost airlines the airport–airline relationship faces new challenges (Francis, Humphreys & Ison, 2004).

In this chapter it became evident that all over the world most low-cost airlines have a tendency to locate their operations at secondary or alternative airports for various reasons. This chapter further highlighted the South African domestic airline industry by profiling both FSCs and LCCs currently operating.

The next chapter will examine the emergence of secondary airports as well as their relationship with LCCs in more detail. The choice factors passengers consider when choosing to fly from a secondary airport and/or use an LCC will be discussed in the chapter that follows.

CHAPTER 3: SECONDARY AIRPORTS AND LOW-COST CARRIERS

3.1 INTRODUCTION

It became evident in the previous chapter that LCCs mostly favour secondary airports when they start their operations. This chapter will therefore provide an overview of South Africa’s airport system and then focus on the role and importance of secondary airports, in relation to LCCs. It will then conclude with an analysis of the domestic air transport market in South Africa. Figure 3.1 depicts the outline of this chapter.

3.1 Introduction

3.2 Role of airports

Chapter 3 3.3 Secondary airports Secondary airports and low-cost carriers

3.4 South African airports

3.5 The South African air passenger market

3.6 Conclusion

Figure 3.1: Outline of Chapter 3

3.2 ROLE OF AIRPORTS

Airports impact local and regional geographical areas in different ways. In terms of economic impact, airports continue to handle growing numbers of international passengers and an ever-increasing volume of high-value cargo, which is flown in preference to the use of rail or sea transport. International businesses and opportunities are more accessible due to airports and airports being regarded as an important element of infrastructure (Andrew & Bailey, n.d.).

3.2.1 Economic impacts of airports

A complex chain of economic impacts is derived from the operation of airports in general. First, passenger and freight movements by airlines and airport operators generate direct revenue. Secondly, revenue is supplemented by indirect revenue from passenger spending on retail services, hotels and transport. Thirdly, subsequent purchase of goods and services from supporting business sectors produces induced expenditure that is dispersed widely into the local economy. In the short-to-medium term, direct employment will tend to grow more slowly than traffic because of rising industry productivity (Andrew & Bailey, n.d.).

Tourism development can enjoy great benefits from secondary airports. In recent years secondary airports have grown, particularly due to the combination with low- cost flights throughout Europe. Secondary airports can be valuable assets in regional economic development especially when combined with a neighbouring industrial, business or technology park (European Transport Conference, 2006). Air transport and airports enable world trade as well as boost efficiency across the global economy by improving the effectiveness of the supply chain. This allows for investment both into and out of a specific country (Luke & Walters, 2010).

According to Luke and Walters (2010) the typical impacts of an airport can be broadly summarised as follows:  Generating work opportunities  Creating wealth

 Stimulating tourism  Having wider benefits to the economy  Contributing to the tax base  Contributing to world trade

3.2.2 The changing airport environment

According to IATA (2013) airports were regarded as monopolies prior to air transport deregulation and liberalisation. Airports operated in a milieu where airlines were strictly regulated and competition was limited. In the last 20 years this scenario has changed dramatically. The fact that airlines compete for passengers also has an impact on airports and airport developments. Airports are competing with each other to attract both airlines and passengers. This has motivated airports to have a more commercialised tactic and in turn a more competitive and dynamic airport market is established (IATA, 2013).

To understand the competitive burdens on airports, the context of the economic nature of the airport business needs to be examined. First, airport costs are mainly fixed due to investment in infrastructure and related operational costs, including safety and security. It is therefore essential that airports attract traffic in order to cover these costs. Thus, commercial revenues, such as airport retail and car parking, are a new focus and almost as important as aeronautical revenues (IATA, 2013). An airport’s profitability thus depends on traffic volumes because unit costs decline significantly as traffic volumes increase (Francis et al., 2004). Therefore airports aim to retain and attract traffic. Secondly, the geographic location of an airport may be advantageous relative to passengers living close to the airport, although some airports cannot achieve the desired scale of passengers by drawing only the ones close to the airport. Therefore airport performance is constrained by the existence of rival airports and by the readiness of passengers and airlines to take their business elsewhere if airport price or quality is not acceptable. However, the elasticity of passenger demand in terms of price and/or quality differs from airport to airport (IATA, 2013).

IATA (2013) mentions that a study conducted by the Airports Council International in Europe indicated three changes that drive competitive constraints on airports:  Airline behaviour: Airlines have the freedom to fly between airports and this implies that airlines are able to switch away from airports if conditions are not to their liking. Numerous routes open and close, and route closure means traffic loss. Traffic may not always be replaced when a route closes, especially where an airport is dependent on a single carrier to operate that specific route. Airlines can vary the size of their operations or open and close bases at individual airports.  Passenger choice: Most passengers (internationally) today have a choice between two or more airports in the same geographical area. In Europe, most citizens are within two hours’ drive of at least two airports, giving airports a major opportunity to compete for passengers. The variety of routes serviced means that more passengers can find comparable services at a nearby airport. Passengers are better informed and more price sensitive, giving them an increasing degree of choice over which airport to fly from.  Airport response: Worldwide airports are becoming more commercially focused and spend more on promotion and route expansion activities. In addition, airports attempt to differentiate their products in order to accommodate different types of airlines.

3.2.3 Competition among airports

A common phenomenon, especially in Europe and the US, is rivalry between a major city airport and a secondary airport. A main city airport is generally situated within the city precincts, is convenient for passengers, and handles nearly all the air traffic for the city. Recently, secondary airports, located a distance from the city, entered the market for airport services. These airports may seem less convenient than the major airports, but they have been successful in attracting cost-conscious traffic by providing lower airport charges, especially to LCCs (Forsyth, 2006).

Forsyth (2006) explains that an airport’s response to opposition will hinge on the incentives the airport receives. Publicly owned airports may not be interested in

maximising profits and therefore there is no incentive to capture business from LCCs. An airport operating under incentive regulation may, however, benefit from acquiring an LCC’s business because the aim is usually to lower costs in order to achieve lower overall prices and grow business and service in this market segment. Competition between major and secondary airports for LCC traffic can be regarded as the main form of active competition between airports (Forsyth, 2006). Airports in Europe compete with one another on various levels (Tretheway & Kincaid, 2005):  Competing for serving a common local market  Competing for connecting traffic  Competing for cargo traffic  Destination competition  Competing for non-aeronautical services, such as retail and food  Competition with other modes of transport, such as Eurostar

According to Tretheway and Kincaid (2005), each airport should consider the product it offers to airlines and passengers very carefully as it can impact the type and quantity of traffic handled. Both primary and secondary airports may attract different passengers but it is the task of the airport management to ensure that their product fits the target market. Table 3.1 indicates the typical product features offered by a primary airport as opposed to a secondary airport.

Table 3.1: Typical product features offered by primary and secondary airports

Primary airport Secondary airport Closer to the city More remote location (closer to some parts of metropolitan region) Higher flight frequencies Lower flight frequencies Wider range of non-stop destinations Limited range of non-stop destinations Enables connecting traffic Focus on point-to-point traffic Higher airfares Lower airfares Wider range of retail facilities Limited range of retail facilities Capacity constraints Sufficient capacity (uncongested) Subject to noise quotas and night curfew Typical 24-hour operation Wide range of handling equipment and Limited range of handling equipment facilities Higher airline operating costs Lower airline operating costs Source: Tretheway and Kincaid (2005:7)

In conclusion of this section, it emerged that the infrastructure of secondary airports is often less elaborate and more basic than that of the main airport. This appeals to LCCs because these airlines are not interested in major infrastructure as it involves high capital investment and increases costs (Barrett, 2004).

The following section of this chapter will look at secondary airports specifically, and the reasons why airlines and passengers prefer to use secondary airports.

3.3 SECONDARY AIRPORTS

In this section of the chapter, secondary airports will be investigated in more detail by paying attention to the motivation of airlines and passengers to utilise these airports.

A secondary airport can be seen as an airport within a specific radius of the city centre and is not regarded as the primary airport for that city or area. It can be regarded as a reliever airport which complements the main airport. In most cases such an airport is located a distance from the city centre (Airline Business Models, 2010). In recent years, especially in Europe and the US, there has been a significant increase in the use of secondary airports, many of them located some distance from the main origin or destination city.

Tables 3.2 and 3.3 respectively, display the prominent primary and secondary airports in major European and US cities.

Table 3.2: Primary and secondary airports in major European cities

City Primary airport(s) Secondary airport(s) Amsterdam Schiphol Rotterdam Barcelona Aeroport del Prat Girona Reus Berlin Tegel Schőnefeld Brussels Zaventem Charleroi Copenhagen Kastrup Malmő Dusseldorf Dusseldorf International Cologne/Bonn Weeze Frankfurt Main Hahn Glasgow Abbotsinch Prestwick Hamburg Hamburg Airport Lűbeck London Heathrow Stansted Gatwick Luton Milan Malpensa Bergamo Paris Charles de Gaulle Beauvais Orly Rome Flumicino Ciampino Stockholm Arlanda Skavsta Västerås Vienna Vienna International Bratislava Source: ELFAA (2004:21)

Table 3.3: Primary and secondary airports in the United States

Primary airport Secondary airport Miami Fort Lauderdale Boston Providence Manchester Orlando Orlando Sanford Melbourne Tampa St Petersburg Sarasota San Francisco Oakland San Jose Los Angeles Burbank Ontario Orange County Long Beach La Guardia Islip Newark J F Kennedy Chicago O’Hare Chicago Midway Dallas Forth Worth Dallas Houston International Houston Hobby Source: Bonnefoy and Hansman (2005b:39)

It is evident from the above tables that there are some areas that have more than one secondary airport, such as Los Angles with four secondary airports and San Francisco with two secondary airports. A situation like this is termed a multi-airport system and can present itself in various forms, each with its own complexities (Bonnefoy, de Neufville & Hansman, 2010) as follows:  One primary airport and one secondary airport  Two primary airports  One primary airport and four secondary airports  Two primary airports and three secondary airports  Three primary airports and one secondary airport

A multi-airport system therefore serves commercial air traffic in a metropolitan area through a set of two or more significant airports (Bonnefoy et al., 2010). For the purpose of this study the focus will be on a multi-airport system that consists of one primary airport and one secondary airport. There are various factors that lead to the emergence of secondary airports and once they are established they share certain characteristics. The following section will identify the reasons behind the emergence of secondary airports (mostly found in the US and Europe).

3.3.1 Infrastructure

The demand for air transport around the world has increased significantly in recent years. Many key airports have limited prospects to expand infrastructure and this poses the question: Will the air transport system be able to meet the rising demand?

Bonnefoy et al. (2010) explains that in order to meet future air travel demand multi- airport systems are developed all over the globe, and in Europe and North America multi-airport systems evolved primarily through the emergence of secondary airports through the use of an already existing airport. In the Middle East, Latin America and Asia-Pacific regions, secondary airports emerged by constructing new airports; these secondary airports have various advantages (Bonnefoy et al., 2010) such as:  Relieve congestion at primary airports  Reduce the effects of disruptions

 Offer new travel alternatives for citizens in a specific metropolitan area  Create regional economic impacts

Many secondary airports, especially in Europe and the US, were not initially built to be secondary airports. They are airports that were already there, and in some instances had other purposes such as military use.

Table 3.4 illustrates the trend (across Europe and America) that secondary airports tend to emerge through the use of an existing airport, rather than the construction of a new facility (Bonnefoy et al., 2010).

Table 3.4: Emergence of secondary airports (in terms of frequency of observation of both trends)

World region Emergence of secondary airport Construction of a new through the use of an existing airport airport (%) (%) Europe 81 19 North America 81 19 Middle East 50 50 Latin America 20 80 Asia-Pacific 10 90 Source: Bonnefoy et al. (2010:5)

3.3.2 Capacity at primary airports

The overall demand for air travel has increased in the last decade. This placed an enormous burden on airport capacity, resulting in congestion at airports, especially the major hub airports (Goedegebuure, 2010). Another contributing factor is the fact that the schedules and networks at primary airports have become more complex and only a slight disruption is needed to cause delays throughout the entire network. This can have a chain reaction effect which means more delayed flights (even arrivals and departures of other airlines), longer waiting periods for passengers, quicker turnaround times of aircraft, and the inclusion of buffers in the flight schedules. All of this can contribute to higher operating costs for an airline at a specific airport (Goedegebuure, 2010).

In the US many primary airports have reached maximum capacity and are very congested. The reason for this phenomenon is the growth in air traffic. Many secondary airports have emerged, especially at the periphery and they are now alternative gateways to access the metropolitan areas (Bonnefoy & Hansman, 2005a). Many major airports in Europe are currently congested and in such a situation secondary airports can offer a number of advantages. Faster turnaround times are possible and this increases productivity of aircraft and crew (Dennis, 2002).

Forsyth (2007) concludes that the increased use of secondary airports may in fact alleviate primary airport capacity problems in the short term.

3.3.3 Low-cost carriers

In most of the literature studied, it was found that the start-up of an LCC mostly took place alongside the emergence of a secondary airport. In the US, 13 airports emerged as a result of the entry of Southwest Airlines to the market (Bonnefoy et al., 2010). Prior to the entry of the LCC, these airports were not serviced. According to the ‘Southwest effect,’ the entry of an LCC changes the dynamic of the market and typically leads to lowers fares, which opens up new market opportunities and stimulates traffic’ (Bennett & Craun, 1993:7).

In the US, LCCs chose to operate from secondary airports. Southwest Airlines was the pioneer in this regard when they initiated a service within Texas between two secondary airports – Dallas Love and Houston Hobby – that had been abandoned by major airlines (de Neufville, 2005). The airline was very successful in facilitating the emergence of secondary airports in the US (Bonnefoy et al., 2010). Another example shows that Southwest Airlines was responsible for an average annual 45% growth rate in passengers from Boston to Manchester in 1998 compared to an annual average of 6% between 1990 to 1997 (Bonnefoy et al., 2010).

Europe is well known for the growing number of LCCs that prefer to operate from secondary airports. Most of Europe’s airports that were initially used as military

airports are now functioning as regional airports. In most cases, LCCs increased the initial low regional flight frequency. A good example is the Frankfurt-Hahn airport, a former military base that started operating for civil purposes, initially accommodating 7 000 passengers per year. After the entry of an LCC, the airport handled 8 000 passengers per day in 2004 (Barbot, 2006).

Table 3.5 indicates the growth in traffic experienced by secondary airports in the UK after the entry of an LCC. Ryanair has been operating from Stansted Airport since 1991 and this airport is currently the third busiest airport in London and the fourth busiest airport in the UK (Stansted Airport, 2015). Luton Airport in London has been the base for EasyJet since 1995 and as seen in this table, the airport has grown considerably (Luton Airport, 2015). Liverpool Airport has been home to EasyJet since the early 1990s and has shown tremendous growth in passenger numbers (Liverpool Airport, 2015).

Table 3.5: Growth in traffic at secondary airports developed by low-cost carriers (UK)

Scheduled terminal passengers (million) Airport 1995 2001 2013 Stansted 2.94 12.46 17.5 Luton 0.56 5.13 10.5 Liverpool 0.37 2.03 4.45 Source: Summarised by author from Dennis (2002) and Airport Watch (2015)

Ryanair was one of the biggest players in developing secondary airports in Europe. Their presence boosted traffic at airports and it also appeared that they started to instruct their suppliers what to offer. This is evident in the development agreement between Brussels Charleroi Airport and Ryanair. The contract allows the airline important privileges at the public airport as well as from the regional government on a purely exclusive basis for a period of 15 years (Dobruszkes, 2006).

Table 3.6 compares the percentage of LCCs versus the percentage of other carriers at primary and secondary airports (in a multi-airport system). It is clear that secondary airports tend to be dominated by LCCs (Bonnefoy et al., 2010).

Table 3.6: Presence of low-cost carriers (versus other airlines) at primary and secondary airports within multi-airport systems worldwide

Percentage (%) flights Percentage (%) flights World region operated by LCCs at operated by LCCs at primary airports secondary airports Asia-Pacific 9 50 Europe 19 44 Latin America 9 43 North America 12 21 Middle East 7 7 Source: Bonnefoy et al. (2010:6)

In a study conducted by Dennis and Graham (2006) it was established that passenger growth at secondary airports in the UK and Ireland could mostly be attributed to LCCs. It is now evident that LCCs play a significant role in developing and supporting secondary airports, and in keeping them alive. It therefore seems appropriate to investigate the LCCs in more detail in order to determine why they prefer to operate from secondary airports. This is done in the ensuing sections.

3.3.3.1 Business strategy of low-cost carriers

Keeping costs low is seen as the core operating strategy of an LCC. To achieve this, LCCs prefer to operate from secondary airports located close to urban areas instead of making use of the existing major airports. Following this approach rewards them with lower levels of congestion, lower airport charges and faster turnaround times for their aircraft (Transportation Research Board, 2010). As mentioned earlier, LCCs depend on a simplified business model to reduce frills in order to minimise operational cost, and, in turn, offer the passengers consistently lower fares, compared to FSCs (Diggines, 2004).

Cento (2009:19) defines an LCC as ‘an airline that is intended to have a competitive advantage in terms of costs over a full-service carrier’. He further typifies the business model of an LCC to have the following fundamental foundation:  The core business of an LCC is passenger air services.

 LCCs operate a network that consists of one or a few airports, known as bases.  City-pairs are connected from secondary airports that are usually more affordable in terms of airport fees and there is less congestion.  LCCs operate one type of aircraft and mostly serve short- or medium-haul routes.  The aircraft of an LCC spend more time in the air when compared with an FSC; therefore, utilisation of aircraft is much higher.  LCCs do not offer lounge services at the airport, in-flight services or frequent- flyer programmes. In some situations tickets are not refundable.  Air tickets are sold and distributed through direct channels, such as the internet.  LCCs also generate revenue from other sources, such as commissions from hotels, car rental companies, credit card fees, in-flight food and beverage sales, and advertising space.

Although not all LCCs implement all the above elements, these airlines do operate somewhere along the lines of the business model described.

Having discussed the LCC’s business model, the following sections will discuss some of the reasons why LCCs prefer to use secondary airports.

3.3.3.2 Airport choice

Secondary airports are the airports of choice for LCCs because they are vital to their efficiency. This statement is further motivated by the fact that secondary airports offer lower charges and are less congested, resulting in quicker turnaround time for aircraft, and less ground and air traffic control delays. The combination of these factors ensures a substantial cost advantage for the LCC (de Neufville, 2008).

Warnock-Smith and Potter (2005:2) suggest that ‘it is imperative that an airport has either a high demand for LCC traffic or an optimistic economic prediction to increase

demand for point-to-point traffic’. They further identified the following as some of the most important choice factors for an LCC to operate from a secondary airport:  High demand for LCC service within the airport’s catchment area  Convenient slot times for take-offs and landings  Quick turnaround facilities  Convenient slot times throughout the day (increases aircraft fleet utilisation)  Lower aeronautical charges  Positive economic and tourism forecasts  Good surface access  Spare capacity at the airport  Privatised, deregulated airport

Low-cost carriers require simple products and services at airports. This means that they will prefer not to use unnecessary infrastructure and services, such as air bridges and business lounges (Njoya, 2010).

Table 3.7 compares the requirements of an LCC and FSC in terms of terminal and ramp operations at an airport.

Table 3.7: Key terminal requirements and ramp operations

Airport area LCC requirements FSC requirements Access and car High demand for car parking facilities Higher use of taxis parking (at secondary airports) Check-in Fewer check-in desks (may result in More check-in desks (separate longer queues) desks for each class of travel) Security Procedures should not delay flight May request separate channel for premium class passengers Baggage handling Simplified (flights are point-to-point) More sophisticated (bags need to be transferred between flights at hub airports) Boarding bridges Prefer not to use it to accelerate Prefer to use it for convenience and boarding and unloading of aircraft luxury of passengers Ramp operations: Passengers walk to aircraft (avoid Used where possible for passenger Aircraft boarding use of buses to save costs) convenience Ramp operations: Prefer self-power manoeuvring (to Necessary if aircraft uses boarding Aircraft push-back save cost and speed up operations) bridge Source: Echevarne (2008) cited in Njoya (2010:7)

The airport choice factors mentioned in Table 3.7 focuses on a range of terminal and ramp attributes that are of importance to LCCs. These factors are mostly linked to operational effectiveness and efficiencies of such airports. Warnock-Smith and Potter (2005) however, concluded that cost may not always be the primary consideration for an LCC when selecting an airport. In many cases there needs to be satisfactory demand to justify providing a service.

3.3.4 Air passenger market

The aim of this study is to examine the factors passengers consider when deciding to use a regional or secondary airport as opposed to a primary airport in a specific metropolitan area, and it is therefore essential to investigate similar international trends. Extensive research (Skinner, 1976; Windle & Dresner, 1995; Barbot, 2009 and Marucci & Gatta 2011) has been done on airport choice models from a passenger perspective, especially in metropolitan areas with multiple airports. Various factors were found to be important to passengers when choosing an airport.

Prior to the emergence of secondary airports, passengers only had the choice to fly from the primary or core airport in a specific region. With the increase in the number of destinations, passengers can now choose to fly from an alternative airport in relatively the same area as the primary airport. Many studies have shown that passengers will actually choose the airport that is located closest to them (Goedegebuure, 2010).

Barbot (2009) suggests that when passengers have to choose between two airports, they actually consider the grouping of airport and airline and not the airport alone. The passenger will therefore consider factors such as the cost of travelling to the airport as well as the fare charged by the airline. Airport choice is a complex decision in a multi-airport region and can be influenced by various factors such as (Marucci & Gatta, 2011):  Capacity expansion  Parking policies  Ground transportation improvements

 Ground service efficiency  Connectivity

As early as 1976 Skinner determined that flight schedules and ground accessibility played a significant role in passenger airport choice. A study conducted by Windle and Dresner (1995) in the Washington DC and Baltimore areas indicated that:  Airport access time and flight frequencies from airports were vital elements of airport choice.  Passenger experience with an airport is a rather important determinant of airport choice.  Where there are competing airports, the importance of airport access time declined but flight frequencies became more important.

When airports in a specific metropolitan area are located close to one another, airfares for the same destinations should be similar, and therefore the only major difference will be airport access time and flight frequency (Zhang & Xie, 2005).

A study conducted by Pels, Nijkamp and Rietveld (n.d) found that travellers make a sequential decision; in other words, they will choose the departure airport first, and the airline second. Hess (2010) determined that passengers tend to have a dislike of larger airports due to the perceived stress of using such airports and also the possibility of delays. Passengers tended to favour airports closer to their homes. Although passengers seem to dislike the larger airports, they would still choose flight options from such an airport owing to the perceived higher levels of service, such as back-up options in case of flight cancellation.

Goedegebuure (2010) found that the following are the most important factors in passengers’ airport choice:  Cost: Air travel cost consists of various components including the airfare itself, parking costs, as well as cost of getting to the airport.  Flight characteristics: These include aspects such as flight connection quality, flight schedules and aircraft type (jet aircraft vs non-jet aircraft).

 Travel time: Important elements include distance to the airport and accessibility of the airport.  Airport facilities: Elements include the number and quality of facilities at airports, such as number of shops, number and quality of restaurants as well as number and quality of lounges.  Time between arrival at airport and boarding: Variables that determine the time a passenger spends at the airport before boarding the aircraft include parking facilities, check-in time, security issues and distance from check-in counter to boarding gate.

It is suggested that the process of selecting a departure airport may be different when a passenger has a choice between one major airport and a secondary airport as opposed to a decision where all the airports are major airports (Goedegebuure 2010).

In conclusion, this section of the chapter investigated secondary airports in more detail. Specific attention was given to the reasons LCCs operate from them as well as the reasons passengers prefer to travel from secondary airports.

The following section of the chapter will look at the South African scenario where the various airports in South Africa as well as the domestic air passenger market in South Africa will be considered.

3.4 SOUTH AFRICAN AIRPORTS

This section will briefly look at the various airports in South Africa in order to understand the South African airport scenario.

Table 3.8 indicates some of the airports in South Africa that provide scheduled domestic passenger services and include technical details such as International Civil Aviation Organisation (ICAO) code, International Air Transport Association (IATA) code, category of usage, availability of customs services, runway length and runway type, and if the airport has an officially published instrument approach procedure

(Instrument Flight Rules or IFR). Cape Town International Airport, Durban King Shaka International Airport and O R Tambo International Airport were selected as these are the three major international airports in South Africa (Luke & Walters, 2010). Lanseria International Airport is also included in the table as the airport is the focus of this study.

Table 3.8: Classification of South African airports

Airport name ICAO IATA Usage Customs service Runway Runway IFR code code available length (m) type

Cape Town FACT CPT Civil Customs service 3 200 Paved Yes International available during Airport operating hours Durban King FALE DUR Civil Customs service 3 700 Paved Yes Shaka available during International operating hours Airport OR Tambo FAJS JNB Civil Customs service 4 389 Paved Yes International available during Airport operating hours (Johannesburg) Lanseria FALA HLA Civil Part-time customs 3 048 Paved Yes International services available Airport Source: Summarised by author from Aircraft Charter World (2013) and Flightstats (2013)

Airports in South Africa can further be categorised into three distinct groups based on their ownership and management structure: Airports Company South Africa (ACSA) airports, municipal airports and privately owned airports.

The following section will briefly explain these groups and highlight the significant role each fulfils within the South African aviation industry.

3.4.1 ACSA airports

The state-owned airports in South Africa were owned and operated by the government (Department of Transport) until July 1993, when Airports Company South Africa Limited (ACSA), a state-owned entity at arm’s length from the Department of Transport, was formally established and the nine state-owned airports

were transferred to the company. ACSA owns and operates the nine principal South African airports, including the three main international airports: O R Tambo International Airport, Cape Town International Airport and the King Shaka International Airport (ACSA, 2012) that form the core of the state-owned airport foci of LCC carriers in South Africa (excluding Lanseria International Airport which is the subject of this dissertation).

3.4.1.1 O R Tambo International Airport

Rand Airport in Germiston was initially built to serve the air traffic needs of Johannesburg in the 1920s. By the 1940s it was no longer able to accommodate larger aircraft and the Palmietfontein Airport (a wartime air force base), in the south- east of Johannesburg, was transformed into a temporary airport to handle flights from Europe, while construction of the new Jan Smuts airport was taking place (Why Joburg, 2014). Jan Smuts Airport, named after a politician at the time, opened in 1952 near Kempton Park in the east of Johannesburg and consisted of two parallel runways running north-south. In 1994 it was renamed Johannesburg International Airport and since 2006 it is known as O R Tambo International Airport (Johannesburg Airport, 2014).

O R Tambo International Airport (ORTIA) is the African continent’s busiest airport and has a route network that stretches across five continents (Global Airport Cities, 2012). The airport is conveniently situated between Johannesburg and Pretoria and fulfils an essential role in providing local, regional, intra- and intercontinental air transport in South Africa. It is also the dominant hub for Sub-Saharan Africa (ACSA, 2014). More than 19 million passengers move though the airport each year, and an estimated 18 000 people are directly employed to ensure the infrastructure and services for local and international travellers are running as they should, as well as contributing to the economy of Johannesburg and Gauteng (South Africa Info, 2012d).

Due to the size and scope of ORTIA’s aviation activities, an aerotropolis – ‘a city that is built around an airport offering businesses speedy connectivity to their suppliers, customers and enterprise partners, nationally and internationally’ – is being

conceptualised around ORTIA and is set to become the first of its kind in Africa (Ekurhuleni, 2014). Judged on international passenger movements, ORTIA is ranked second in Africa but in terms of total passenger movements, air freight volumes and total air traffic movements, it is the number one airport in Africa. The airport offers the biggest variety of technical support facilities in South Africa (Global Airport Cities, 2012).

South Africa’s two LCCs operate daily flights from ORTIA. Kulula offers flights from ORTIA to various South African cities including Cape Town, Durban, George, East London and Port Elizabeth (Kulula, 2013). Mango Airlines services Cape Town, Durban and Port Elizabeth from ORTIA daily (Mango Airlines, 2013).

3.4.1.2 Cape Town International Airport

D F Malan Airport opened in 1954 to replace Cape Town’s first airport – Wingfield Aerodrome – and was named after the then prime minister of South Africa. Two international flights operated from there, one direct flight to Britain and one flight to Britain via Johannesburg (Leitch, 2014). During the early 1990s the ownership of the airport was transferred to the newly formed Airports Company of South Africa and the airport was renamed Cape Town International Airport (Leitch, 2014). The 60- year-old Cape Town International Airport is the third busiest airport in Africa and is the primary airport to serve this popular tourism destination. In the metropolitan area of Cape Town, it is the only airport that provides scheduled passenger services and these include direct flights to Johannesburg and Durban as well as flights to other centres in South Africa. Direct international flights are offered to destinations in Africa, Asia and Europe (Leitch, 2014).

As a popular tourist destination, Cape Town attracts millions of tourists each year and during the period 2012–2013, more than 8 million passengers passed through Cape Town International Airport (Leitch, 2014). The two LCCs in South Africa, Kulula and Mango Airlines, operate daily domestic flights from Cape Town International Airport. Kulula flies to Johannesburg (ORTIA and Lanseria) and Durban (Kulula, 2013) and Mango Airlines fly to Bloemfontein, Durban, Johannesburg (ORTIA and Lanseria) and Port Elizabeth (Mango Airlines, 2013).

3.4.1.3 King Shaka International Airport

In 1951, the Louis Botha Airport opened in Durban replacing the Stamford Hill Aerodrome. When ownership of the airport was transferred to ACSA in the 1990s it was renamed Durban International Airport (Facts about Durban, 2015). Plans to build a new airport north of Durban have been a point of discussion from the 1960s. In 1973 plans to construct the new airport was approved and by 1975 earthworks had begun on the site but it was halted again in 1982 owing to slow economic growth. In 1994 it was announced that the plans to construct a new airport will go ahead, and in 2002 final approval from government was received to continue with construction of the airport 30 kilometres north of Durban (La Mercy, 2014). In 2008 construction of the new airport along with the development of the Dube Trade Port commenced on the original La Mercy Airport site. This development was set to develop a world-class aviation-linked logistics platform and in turn provide private sector investment as well as sustainable employment creation (Dube Trade Port, 2014).

Named after the great 19th century Zulu warrior-king, King Shaka International Airport (KIA) became operational on 1 May 2010 after the existing Durban International Airport was decommissioned. The new airport has the capacity to handle 7.5 million passengers annually with room for future development (South Africa Info, 2012c). One year after KIA opened its doors, 4 million passengers had passed through the airport (Fin24, 2011).

South Africa’s LCCs operate daily domestic flights from KIA. Kulula provide flights to Johannesburg (ORTIA and Lanseria) and Cape Town (Kulula, 2013) whereas Mango Airlines offer flights to Cape Town and Johannesburg (ORTIA only) (Mango Airlines, 2013).

3.4.1.4 Other ACSA airports

In addition to the three major airports, the other state-owned airports that ACSA manages include Bram Fischer Airport in Bloemfontein, and airports in Port

Elizabeth, East London, George, Kimberley and Upington (ACSA, 2013). These six airports are feeder airports for the three international airports (ACSA, 2014). All nine airports are major generators in the creation of employment and business opportunities, whether direct or indirect. The core role of airports is likely to change in future with a variety of facilities, including manufacturing, logistics and commerce as well as hotels, retail outlets and entertainment venues clustering around an airport (ACSA, 2013).

Table 3.9 indicates passenger throughput for the last two years, together with passenger handling capacity at the ACSA airports in South Africa as provided in the ACSA Integrated Annual Report 2014.

Table 3.9: Passenger throughput at ACSA airports

Passenger Passenger Passenger ACSA airport handling throughput throughput capacity 2014 2013 O R Tambo International Airport 28 000 000 18 820 988 18 621 259 (Johannesburg) Cape Town International Airport 14 000 000 8 392 989 8 434 799 King Shaka International Airport 7 500 000 4 465 088 4 668 467 (Durban) Source: ACSA (2014:23)

Passengers utilising these airports include both business passengers and leisure passengers travelling domestically, internationally and regionally (ACSA, 2014).

3.4.2 Municipal airports in Gauteng

In Gauteng there are number of smaller airports, such as Rand Airport and Wonderboom Airport, which are significant to air transport. Some of these are still owned by a local authority or municipality and some of them have had changes in their ownership and management structures in recent years.

3.4.2.1 Rand Airport

In 1929, Imperial Airways wanted to organise a service to South Africa. The municipality of Germiston, towards the east of Johannesburg, saw to it that Rand Airport was built in the 1930s and the first flight of Imperial Airways from London landed at Rand Airport in December 1931. The airport was officially opened by the Governor General, the Earl of Clarendon (Leitch, 2011c). Today, Rand Airport is still a busy airport, handling about 5 500 movements a month, although these are mostly circuits flown by the flight training schools. Rand Airport hosts various air charter operators and aircraft maintenance companies (Leitch, 2011c).

Unfortunately the runway at Rand Airport cannot be lengthened as a result of geographical constraints at the site making it difficult for larger aircraft to use the airport, and there are currently no commercial scheduled passenger air services that operate from this airport (Leitch, 2011c).

3.4.2.2 Wonderboom Airport

In the 1930s the City Council of Pretoria (CCP) decided to build a landing strip on the farm Wonderboom, roughly 15 km north of central Pretoria. This landing welcomed air traffic in 1937 and the Wonderboom Airport became the base for the Pretoria Light Aircraft Company (Placo) and the Pretoria Flying Club. Placo managed the airport, even though it was the property of the City Council of Pretoria (Leitch, 2011b). The airport was further developed in 1993 to accommodate larger aircraft and cargo. The runway was extended to 1 828 m, which is still the length today.

Wonderboom Airport was identified as a strategic municipality asset by the The City of Tshwane Metropolitan Government and has set out a long-term development plan. The most important part of this plan is to reinstate the airport’s international status. With this in place, the airport could become the third international airport in Gauteng (Leitch, 2011b).

It is argued that a third international airport would not only lessen the traffic burden experienced at the existing surrounding airports, but rather encourage investment,

economic growth and employment creation. The City of Tshwane will effectively be connected with trading partners. Wonderboom Airport is identified as a deviation airport when unfavourable weather conditions are present at ORTIA or Lanseria (Leitch, 2011c). In August 2015, SA Airlink introduced a commercial scheduled service to Cape Town from this airport (Traveller24, 2015) but was not included in this study as the fieldwork was conducted in 2013.

3.4.3 Privately owned airports

There are two privately owned airports in Gauteng, namely, Grand Central Airport and Lanseria International Airport.

3.4.3.1 Grand Central Airport

In the heart of Midrand, halfway between Johannesburg and Tshwane (Pretoria) lies Grand Central Airport. It was established in 1937 when Mr Harry Shires of African Flying Services bought land as a speculative deal. He gave flyers from a flying club permission to form a flying club (Grand Central, 2012). Over the years there have been various developments and Grand Central has been the home of numerous commercial and private operators, flight training schools and maintenance organisations (Grand Central, 2012). There are currently no commercial scheduled passenger air services that operate from this airport.

3.4.3.2 Lanseria International Airport

Lanseria was opened in 1974 after Fanie Haacke and Abe Sher identified the need for a new airport north-west of Johannesburg. The Lanseria site was ideal due to its close proximity to residential areas as well as the suitability to construct a long runway. Lanseria hosted a number of air shows in the years that followed. It was home to various squadrons of the South African Air Force (Leitch, 2011a).

When former President Nelson Mandela was released from prison in 1990, he was flown to Johannesburg and his aircraft landed at Lanseria (Gauteng Tourism Authority, 2013). In 1991, the co-owners, Roodepoort and Krugersdorp Municipalities

and the Transvaal Administration, decided to sell the airport to a consortium of private investors. By 1999 the airport infrastructure experienced significant strain due to the increase in passenger and freight operators. In 2002 a larger terminal building was unveiled and the runways and taxiways were upgraded.

After an international status review of port of entry airports, the nine ACSA airports together with Lanseria were the only airports to retain international status. In 2010 the airport was upgraded once again thereby further contributing to the success of Lanseria International Airport (Leitch, 2011a). In recent years Lanseria has gained popularity as an alternative airport to Gauteng’s larger airport, ORTIA. The airport managed to grow remarkably with various factors contributing to this, including its location, ease of access, convenient parking facilities, as well as efficient embarking and disembarking procedures (Gauteng Tourism Authority, 2013).

The airport is conveniently situated close to Sandton, a business hub in Gauteng. The downtown areas of the cities of Johannesburg and Tshwane are both approximately 50 km away.

Currently, Kulula and Mango Airlines operate scheduled, daily flights from Lanseria to Cape Town and Durban. Lanseria International Airport offers various charter services to a variety of destinations. Other services offered include aircraft sales, flight schools and freight services as well as aircraft maintenance. Government facilities, including immigration, border police and customs are present at Lanseria International Airport (Gauteng Tourism Authority, 2013).

In November 2012 Lanseria was sold to a consortium of investors comprising Harith (a Pan African infrastructure development fund manager) and a Black Economic Empowerment Consortium (a women’s empowerment company, Nozala, and the Government Employee Pension Fund [GEPF] through the Public Investment Corporation [PIC]) (News24, 2013b).

Lanseria has experienced tremendous growth over the last five years necessitating capacity upgrades. A new three kilometre runway was commissioned in November 2013 in expectation of growing air transport demand. The new runway is able to

accommodate wide-bodied aircraft (Lanseria, 2013). Currently Lanseria is one of only two international airports in Gauteng, with ORTIA the primary international airport. Passenger numbers at Lanseria reached more than 1 million in 2010 and according to the airport manager, Gavin Sayce, the airport handles 1.5 million passengers per year (Booyens, 2012). Luke and Walters (2013) pointed out that Lanseria has grown in recent years since the two LCCs started operating from there in 2006 and 2011 respectively. After low initial passenger numbers, Lanseria currently handles around 150 000 passengers per month as indicated in Figure 3.2.

160 000

140 000

120 000

100 000

80 000 Lanseria 60 000 HP(Lanseria) 40 000

Number of Passengers of Passengers NumberMonthper 20 000

2003M04 2003M11 2004M06 2005M01 2005M08 2006M03 2006M10 2007M05 2007M12 2008M07 2009M02 2009M09 2010M04 2010M11 2011M06 2012M01 2012M08 2013M03 2013M10 Figure 3.2: PAX: Total arrivals and departures Lanseria International Airport Source: Luke and Walters (2013:9)

Continued investment in infrastructure at Lanseria will improve the airport’s role as an alternative to ORTIA (News24, 2013b).

The preceding section highlighted the state-owned, municipal and privately owned airports in South Africa. From this discussion it emerged that Lanseria International Airport has grown especially with regard to scheduled passenger traffic and is playing a significant role in air transport, specifically in Gauteng. The following

section will study the South African air passenger market in more detail with a specific focus on the domestic passenger market.

3.5 THE SOUTH AFRICAN AIR PASSENGER MARKET

3.5.1 Air transport in Africa

Africa is the continent with the lowest demand for air travel and the reasons for this can be attributed to the low income and lack of air transport infrastructure. The domestic markets in Africa in general are not well developed and most passengers travelling by air in Africa travel on international flights (Oxford Economic Forecasting, 2003). Although African airports experienced a 7% increase in passenger numbers in 2012, flying is still somewhat expensive in Africa and the continent only recently saw the introduction of LCCs (Aviation Benefits, 2014a). Only 2.3% of global air passenger traffic can be attributed to Africa and of the top 20 international airports in Africa, three can be found in South Africa and another three in Egypt. Therefore these two countries are seen as the countries with the biggest air transport markets in Africa (Aviation Benefits, 2014b).

The biggest markets for passenger air travel in Africa comprise South Africa, Egypt and Morocco. The best developed domestic market on the continent can be found in South Africa as it contributes 40% of the total domestic seats in Africa (Oxford Economic Forecasting, 2003).

The next section will specifically look at the domestic air transport industry in South Africa.

3.5.2 Air transport in South Africa

The scheduled domestic air passenger transport market in South Africa is serviced by SAA, Kulula, British Airways Comair, Mango Airlines, SA Express and SA Airlink. The latter two airlines serve feeder routes to the main hubs in South Africa and serve the lower density domestic routes such as Bloemfontein, Kimberley and East London respectively. Both these airlines also provide regional air services (Luke & Walters,

2013). Figure 3.3 depicts each airline’s share of the domestic market (excluding SA Express and SA Airlink) (Centre for Aviation, 2013b).

15%

45% SAA

25% BA Comair Kulula Mango 15%

Figure 3.3: Airlines’ share of domestic market in South Africa Source: Centre for Aviation (2013b)

The busiest domestic airline network in Africa is termed the ‘Golden Triangle’ as depicted in Figure 3.4, and services three cities, namely Johannesburg, Cape Town and Durban on a daily basis (News24, 2013a). Passenger movements on these routes have a noteworthy impact on infrastructure and operations at all three international airports. In 2013, around 320 000 passengers per week were carried on the South African domestic route network with 250 000 passengers on the so-called Golden Triangle network (Johannesburg/Durban/Cape Town) (Centre for Aviation, 2013b).

The Johannesburg–Cape Town and the Johannesburg–Durban routes are of importance to this study. The reason for this is that scheduled passenger flights on these routes are offered from ORTIA and are currently serviced by traditional FCCs as well as LCCs. Scheduled flights are offered daily from Lanseria to Cape Town as well as from Lanseria to Durban. These are currently serviced by LCCs.

Figure 3.4: Golden Triangle – serviced by domestic airlines in South Africa Source map: www.mapstudio.co.za

The Johannesburg–Cape Town route was identified as one of the world’s ten busiest flight routes measured by passenger volume, carrying 4.4 million passengers in 2012, from a survey conducted by Amadeus Air Traffic Travel Intelligence Solution. (News24, 2013a).

3.6 CONCLUSION

Airports play an important role in the economy of a region but face a challenging environment in the sense that they have to compete with one another for airlines and passengers. This challenging environment has led to the emergence of secondary airports in various regions of Europe and the US. Different factors lead to the emergence of secondary airports, but the most noteworthy are the factors that users of the airport, both the airlines and the passengers, consider when choosing between alternative airports. These factors are of importance to this study.

The South African airports, with an emphasis on the airports in Gauteng, were studied as well as the domestic air passenger market. From this it emanated that the Johannesburg–Cape Town and Johannesburg–Durban routes are the most popular domestic routes and are serviced by both FCCs and LCCs. It emerged that Lanseria International Airport is increasingly used by passengers as well as LCCs. The two high density routes mentioned above are served from Lanseria. Kulula offers flights to Cape Town and Durban from Lanseria whereas Mango Airlines only flies to Cape Town from Lanseria.

The next chapter will describe the research methodology followed in the study.

CHAPTER 4: RESEARCH METHODOLOGY

4.1 INTRODUCTION

In the previous chapter the relationship between secondary airports and LCCs were discussed. The factors that LCCs and passengers consider when selecting a departure airport were examined.

The aim of this chapter is to discuss the research methodology used for this study in order to gather data from which conclusions can be drawn as well as the reasons for these choices. The outline of this chapter is illustrated in Figure 4.1.

4.1 Introduction

4.2 Research philosophy

4.3 Research approach

4.4 Research purpose and Chapter 4 design Research Methodology

4.5 Data collection

4.6 Validity and Reliability

4.7 Conclusion

Figure 4.1: Outline of Chapter 4

4.2 RESEARCH PHILOSOPHY

The development of knowledge and the nature of that knowledge are known as research philosophy, and pertain to the assumptions about the way in which a researcher sees the world. The research philosophy will therefore relate to the research strategy as well as the research methods chosen (Saunders, Lewis & Thornhill, 2012). Research philosophy chosen by a researcher is important for various reasons, according to Altinay and Paraskevas (2008):  It aids the researcher in selecting an inclusive research strategy, including type of evidence to be gathered, the way in which evidence will be analysed and how it will answer the research question.  Familiarity with research philosophies assists a researcher to avoid unnecessary work by highlighting limitations of research approaches timeously.

The various research philosophies will be described briefly in the section that follows.

4.2.1 Positivism

A researcher adopts a positivistic research philosophy if he/she prefers to ‘collect data about an observable reality and search for regularities and causal relationships to create generalisations like those produced by scientists’ (Saunders et al., 2012: 134). According to Babbie and Mouton (2001), an important feature of positivism is objectivity and this is highlighted as the ‘distance between subject and object, and insists on a value-free approach to the object of study’ (p.44). Characteristics of positivism include hypothesis testing and using data initially gathered in in-depth interviews to formulate hypotheses (Saunders et al., 2012).

4.2.2 Interpretivism

Interpretivism is used to study people and their social actions (Altinay & Paraskevas, 2008) and the researcher maintains an objective stance (Saunders, et al., 2012).

Interpretivism stems from two academic backgrounds, according to Saunders et al. (2012), namely:  Phenomenology, which relates to the way humans make sense of the world around them and  Symbolic interactionism, which is a continuous process of interpreting the social world around humans where the actions of others are interpreted.

Interpretivism encourages the researcher to enter the social world of the research subjects and to understand their world from their point of view (Altinay & Paraskevas, 2008).

4.2.3 Pragmatism

The pragmatism research philosophy emphasises that ideas are only significant where they support action (Kelemen & Rumens, 2008). Pragmatism advocates that, depending on the research questions, either or both evident occurrences and subjective beliefs can deliver adequate knowledge. Value is essential in understanding results and the researcher therefore assumes an objective as well as a subjective point of view (Saunders et al., 2012). A pragmatic researcher therefore knows that there are various ways in which the world can be interpreted when doing research and that there will most likely be numerous truths because a single viewpoint can never reflect the complete picture (Saunders et al., 2012).

A research philosophy is selected based on a few factors as described by Altinay and Paraskevas (2008):  Current knowledge in the researched area – Are there gaps in the research or is it a well-studied field?  Research question – Is the researcher exploring new facts or is current data being tested?  Researcher skills – Is the researcher able to design questionnaires and then analyse it? Or does the researcher prefer to interact with people and therefore explore their domain?

 Time and resources – Does the researcher have sufficient time and resources available to allow for exploration or do the resources only allow for testing of theories?

A positivistic research philosophy was chosen for this study because it focuses on facts, and hypotheses can be formulated and tested. Data was collected by means of a survey (Altinay & Paraskevas, 2008). The strengths and weakness of positivism are listed in Table 4.1.

Table 4.1: Strengths and weaknesses of positivism

Strengths Weaknesses

Extensive reporting of the range of Approaches can be inflexible and artificial circumstances

Researcher retains control of research Not effective when understanding of process processes is required

Data collection can be effective and efficient Not effective to determine the meaning due to clarity of what needs to be people attach to actions investigated

Generalise previous findings and test Not useful to generate concepts previously developed theories

Source: Altinay and Paraskevas (2008:70)

Positivism as a research philosophy was selected as it allowed for effective and efficient data collection and the possibility of generalising the findings and testing predefined hypotheses.

4.3 RESEARCH APPROACH

Research approach entails a decision by the researcher on whether to construct the knowledge in the research process at the beginning or the end of the project. A researcher can decide to review literature, develop a theory and hypotheses, and then design the study in such a way that it tests the hypotheses. Or a researcher may decide to utilise theory to design research in such a way that when the collected data is analysed theory is developed (Altinay & Paraskevas, 2008). This decision

relates to the reasoning a researcher adopts and is classified as a research approach. The decision about research approach is important for various reasons as emphasised by Saunders et al. (2012):  It enables an informed decision about research design.  It stimulates thinking about research strategies and methodological choices.  It enables a researcher to adapt the research design to accommodate constraints.

The section that follows will briefly highlight the different research approaches.

4.3.1 Deduction

According to Ketokivi and Mantere (2010), deductive reasoning is an approach whereby a conclusion is derived rationally from a set of evidences, the conclusion being true when all evidences are true. Deductive reasoning means the researcher draws a conclusion first and the research is all about demonstrating the conclusion to be true or false. In other words the researcher uses what is known to move to what cannot be concluded directly (Altinay & Paraskevas, 2008).

Altinay and Paraskevas (2008) add that deductive reasoning assists a researcher to define and explain the connections between the variables selected for the research. According to Robson (2000), adopting a deductive reasoning approach entails five chronological steps: 1. Develop hypotheses. 2. Express hypotheses in operational terms (measuring hypotheses). 3. Test hypotheses (by means of experiment, survey, etc.). 4. Scrutinise the outcome of the analysis (agree with the hypotheses or disagree with the hypotheses). 5. If deemed necessary, alter the theory in light of the outcomes.

4.3.2 Induction

Inductive research begins with an observation and not with assumptions; therefore, a researcher will observe a sample whereafter he/she draws conclusions about the population that the sample represents (Leedy & Ormrod, 2014). Altinay and Paraskevas (2008) highlight the advantages of an inductive approach as follows:  It assists the researcher to establish a cause-and-effect relation between variables and the way in which individuals understand these variables in their milieu.  It is a flexible approach because the researcher can identify alternative theories on the research topic and it allows for alteration of the research emphasis as the research evolves.  Inductive reasoning explains why a certain phenomenon is taking place.

On the negative side, inductive research tends to be more effective with smaller samples. It is a time-consuming process because thoughts are generated over an extended period of data collection and analysis, and the researcher runs the risk of yielding no valuable statistics and theories as opposed to deductive research (Altinay & Paraskevas, 2008).

4.3.3 Abduction

Most of the great advances in science were not realised by means of pure deductive reasoning or with inductive research (Kovács & Spens, 2005). ‘Abduction begins with the observation of a “surprising fact”; it then works out a plausible theory of how this could have occurred’ (Saunders et al., 2012:147). A researcher will therefore test a theory by means of evidence provided by current data as well as new data, and review his/her theory as necessary (Saunders et al., 2012). In deduction, a researcher progresses from theory to data, and in induction, the researcher moves from data to theory, but abduction allows a researcher to move back and forth thus in effect combining deductive and inductive reasoning (Suddaby, 2006). The researcher therefore highlights the pursuit for appropriate theories to an empirical observation (sometimes termed theory matching) (Kovács & Spens, 2005).

For the purpose of this study a deductive approach was followed in order to test existing theory to determine if the theory relates to the particular situation (Hyde, 2000). The main characteristics of deductive reasoning are summarised by Saunders et al. (2012) as:  Exploring the underlying relationships between concepts and variables. For the purpose of this study the researcher studied literature on low-cost airlines as well as secondary airports and developed a theory that there is a relationship between the two.  The researcher then developed various hypotheses to support the theory. To test the hypotheses quantitative data was collected to measure and analyse the concepts and variables. If the results were inconsistent with the hypotheses, the hypotheses were rejected indicating that the theory was false. The theory was substantiated if the results were consistent with the hypotheses.  For facts to be measured concepts need to be operationalised, meaning problems are better understood if they are reduced to simpler, more understandable elements.  In order to generalise, the sample selected needs to be representative and of sufficient size.

In this study hypotheses were developed in order to test the theory relating to the reasons why domestic passengers prefer to utilise Lanseria International Airport for departures and arrivals from selected destinations. The following section explores research design, including research purpose, research strategy and research method.

4.4 RESEARCH DESIGN

The broad plan of how a researcher intends to solve the research questions is known as the research design. Research design will therefore consist of the following important elements, according to Saunders et al. (2012):  Clear objectives (derived from the research question)

 The sources data is to be collected from  How data will be collected and analysed  Ethical issues  Possible constraints that may be encountered

Consistent with Babbie and Mouton (2001), research design is a systematic process that focuses on the end product.

4.4.1 Research purpose

The way in which a researcher asks the research questions will lead to an answer that is exploratory, descriptive or explanatory.

4.4.1.1 Exploratory studies

Exploratory research is useful to a researcher when the aim is to clarify his/her understanding of a particular problem. The focus of an exploratory study narrows down or become more specific as the researcher progresses with the research (Saunders et al., 2012). Babbie and Mouton (2001) indicate that exploratory research is usually done for the following reasons:  Fulfilling a researcher’s interest and aspiration for better understanding of phenomena  Testing viability by means of a wide-ranging study  Developing methods to utilise in any following study  Clarifying theories and hypotheses of a study  Determining prospective research priorities  Developing new premises about prevailing occurrences

An exploratory study can be conducted by means of a review, e.g. literature review, a survey and an analysis of examples (Babbie & Mouton, 2001).

4.4.1.2 Descriptive studies

The intention of descriptive research is ‘to gain an accurate profile of events, persons or situations’ (Saunders et al., 2012:171). Often descriptive research can be seen as an ‘extension’ of exploratory research. Babbie and Mouton (2001) clarify descriptive research as the researcher making observations and then describing what was observed with the aim of describing situations and events. Descriptive studies may be used in various situations and include narrative description (e.g. historical inquiry), conceptual analysis (e.g. typologies), structured statistical analysis (e.g. correlation study) and case studies (Babbie & Mouton, 2001).

The situation being researched will not be altered or amended with descriptive research nor is the intention to determine a cause-and-effect relationship, according to Leedy and Ormrod (2014).

4.4.1.3 Explanatory studies

Explanatory research creates causal relationships between variables and the emphasis is on explaining the relationship between variables by studying a situation or problem (Saunders et al., 2012). For a researcher to indicate that a causal relationship indeed exists between variables, certain requirements have to be met (Babbie & Mouton, 2001), such as:  The cause paves the way for the effect.  The two variables have to be empirically associated with one another.  The observed association cannot be detailed by means of a third variable that causes both of them.

Furthermore, ‘a necessary cause represents a condition that must be present for the effect to follow’ (Babbie & Mouton, 2001:82) and ‘a sufficient cause represents a condition that, if it is present, will pretty much guarantee the effect in question’ (Babbie & Mouton, 2001:82).

The purpose of this study is to explore the attributes that are important to passengers when electing to use Lanseria International Airport.

In the section that follows attention will be given to research design.

4.4.2 Research design

Research design is a broad plan of how a researcher intends to provide a solution to the research question, according to Saunders et al. (2012). It is necessary for a researcher to first determine what it is he/she wants to observe and thereafter select the most appropriate way to do so (Babbie & Mouton, 2001).

Research can broadly be classified as either quantitative or qualitative.

4.4.2.1 Quantitative research

Quantitative research requires a researcher to look at quantities of one or more variables. In other words a quantitative researcher will attempt to measure variables in a statistical manner (Leedy & Ormrod, 2014). To describe, predict and control is the aim of quantitative research. Controlling the environment to isolate specific variables and remove the effects of confusing variables, allows a researcher to test the variables’ relationship to several behaviours (Borland, 2001).

4.4.2.2 Qualitative research

In qualitative research a researcher is required to explore qualities that cannot be reduced to mathematical values. The researcher will rather attempt to study the intricacies of a specific phenomenon (Leedy & Ormrod, 2014). Qualitative research firstly is used to advance theory which can be verified via quantitative research and secondly it is used to discover the significance individuals attach to quantitatively derived conclusions (Borland, 2001).

A similar process of identifying the research problem, reviewing literature and then collecting and analysing data is followed in both quantitative and qualitative research

approaches. However, a quantitative researcher will commence a study with one or more hypotheses to be tested whereas a qualitative researcher will have a general research question, collect data and make use of verbal explanations to interpret the situation studied (Leedy & Ormrod, 2014). Table 4.2 highlights the differentiating features of quantitative and qualitative research designs.

Table 4.2: Features of quantitative and qualitative research designs

Quantitative research Qualitative research Research philosophy  Positivism  Interpretivism Purpose of research  Explain and predict  Describe and explain  Confirm and validate  Explore and interpret  Test theory  Build theory Nature of research  Focused  Holistic process  Known variables  Unknown variables  Established guidelines  Flexible guidelines  Predetermined methods  Emergent methods  Detached view  Personal view Research strategy  Experimental research  In-depth interviews  Survey research  Participative observation  Structured observation  Action research  Case study  Ethnography  Grounded theory  Narrative research Type of data and data  Numeric data  Textual or image-based data collection method  Large, representative sample  Small, informative sample  Standardised instruments  Non-standardised observations and interviews Data analysis  Statistical analysis  Search for themes and categories  Objective  Subjective and potentially biased  Deductive reasoning  Inductive reasoning Communication of  Numbers  Words findings  Statistics  Narrative and individual quotes  Scientifically  Literary style Source: Summarised by author from Leedy and Ormrod (2014) and Saunders et al. (2012)

When a researcher selects either a quantitative or qualitative approach only, it is termed a mono method. On the other hand a multi-method approach is when a researcher utilises more than one data collection technique and analytical procedure to answer the research questions. This can be done within both the quantitative and qualitative paradigm of research as it reduces the weakness associated with using

only one, especially where business and management research are concerned (Saunders et al., 2012).

4.4.2.3 Mixed method research

The mixed method research approach involves an amalgamation of the quantitative and qualitative approaches in the research methodology of a single study (Plano Clark & Creswell, 2008) and integrates conclusions from both the qualitative and quantitative data (Leedy & Ormrod, 2014).

The mixed methods approach is an ideal choice for various reasons, according to Leedy and Ormrod (2014):  A researcher can completely address a research problem by gathering and scrutinising both qualitative and quantitative data.  Quantitative features of a study may compensate for flaws in qualitative features.  Hypotheses are formulated from insights provided by qualitative data and are tested by means of quantitative data.  Conclusions are more convincing if both qualitative and quantitative data lead to them.

The section that follows describes the various research strategies available for researchers to select.

This study applied a mono method research, using only a quantitative data collection method by means of a survey.

4.4.3 Research strategy

A research strategy reveals how a researcher intends to solve the research question and forms the practical linkage between the research philosophy and method to collect and analyse data (Denzin & Lincoln, 2005).

Various research strategies are available and are described in the next section.

4.4.3.1 Experimental research

Hakim (2000) describes an experiment as studying the likelihood of a change in an independent variable realising a variation in another dependent variable. Babbie and Mouton (2001:208) simplify it as ‘taking action and observing the consequences of that action’. Hypotheses are often used in experiments instead of research questions because the researcher expects that a relationship will exist between the variables (Saunders et al., 2012).

Lastly, for the results of an experiment to be reliable, they should illustrate a high level of internal and external validity. Internal validity indicates that appropriate control over variables was present and that the independent variable resulted in the change in the dependent variable. External validity indicates that the findings of the experiment can be generalised to the entire population. A high degree of external validity therefore means that the findings of the experiment should be true in real life (Maree, 2007).

4.4.3.2 Survey research

Survey research is one of the oldest and most widely used research techniques and is employed in various fields, including political science, social psychology, economics and education. Applied research fields such as marketing and mass media research rely on surveys (Babbie & Mouton, 2001). Surveys are utilised frequently in deductive research approaches, according to Saunders et al., (2012). According to Babbie and Mouton (2001:232) survey research is ‘probably the best method available to the social scientist interested in collecting original data for describing a population too large to observe directly’. Surveys are ‘excellent vehicles for measuring attitudes and orientations in a large population’.

Thus, a survey is a technique of assembling primary data by means of communication with a representative sample of entities. This provides a ‘snapshot’ at a given point in time (Zikmund, Babin, Carr & Griffin, 2013).

4.4.3.3 Archival research

Administrative records and documents (historical and recent) are the main source of data when conducting archival research. This data is considered to be secondary data because it was previously collected for an alternative purpose (Saunders et al., 2012).

Archival data therefore forms part of the reality being studied because it stems from day-to-day activities (Hakim, 2000) and allows research questions to be exploratory, descriptive or explanatory by focusing on the past and present, including changes over time (Saunders et al., 2012). A drawback of archival research is that the availability of data can be affected by the nature of records and documents. In some cases available records may not be able to assist the researcher in answering the research question. Data may have been misplaced or the researcher may be denied access. Therefore the researcher needs to carefully design a research strategy that is aimed at making the most of the situation (Saunders et al., 2012).

4.4.3.4 Case study research

Yin (2009) explains that case study research allows a researcher to explore a phenomenon within a real-life context and the researcher may use qualitative or quantitative methods to gather and study data; however, case study research usually consists of a mix of these methods. Saunders et al. (2012) stress that when utilising case study research, triangulation – ‘the use of two or more independent sources of data or data collection methods within one study in order to help ensure that the data are telling you what you think they are telling you’ (Saunders et al., 2012:683) – of multiple data sources is essential. An advantage of case study research, as alluded to by Maree (2007), is the fact that multiple sources and techniques to collect data are utilised. A drawback of case study research, according to Maree (2007), is that case study research cannot provide a generalisable conclusion because it is reliant on a single case.

4.4.3.5 Ethnography research

Ethnography is one of the earliest forms of qualitative research (Saunders et al., 2012) and is derived from two Greek words, ethnos and graphein, and can be understood as writing about people. It is mainly used in the field of anthropology where researchers spend a lot of time in the field in order to observe people in their naturalistic setting and then write about that specific culture or way of life. The researcher tries to make sense of the reasoning behind people’s actions (Maree, 2007).

4.4.3.6 Action research

When a researcher selects an organisation to study, spends time at that organisation and then draws conclusions in order to assist the organisation to solve problems, it is known as action research (Altinay & Paraskevas, 2008). Action research can be seen as an ‘iterative process of inquiry’ (Saunders et al., 2012:183) which aims to solve organisational problems by means of participation and collaboration. It will involve contributors and the organisation beyond the research project (Saunders et al., 2012). Action research is suited for the following purposes as highlighted by Creswell, (2005):  Addressing specific everyday problems (and solutions)  Applying systematic procedures to collect data and solve a specific problem  Improving self-development  Creating an opportunity to reflect on own performance

Action research offers great opportunities to reduce the knowledge gap between the academic world and industry (Altinay & Paraskevas, 2008).

4.4.3.7 Grounded theory research

Grounded theory was developed around 1967 by Glaser and Strauss as a research approach within the positivist paradigm. The grounded theory research strategy has its roots in the fact that it is a qualitative approach that seeks to develop theory that

is grounded in data which is gathered and analysed in an analytical method (Maree, 2007; Leedy & Ormrod, 2014). The basis of this research strategy is that the researcher has an open mind and no presumed relationships when conducting the research. The researcher will generate knowledge about the relationships between variables from the data collected during the fieldwork stage. It is imperative that numerous data sources are consulted in order to scrutinise the same phenomenon from diverse perspectives in the grounded theory strategy (Altinay & Paraskevas, 2008). Methodologically, grounded theory is an easy strategy to make use of; however, it requires practice and dedication as it is a time-consuming, demanding and reflective process (Saunders et al., 2012).

4.4.3.8 Narrative inquiry research

The alternative word for narrative is story which describes a personal event or a sequence of events (Maree, 2007). However, as a research strategy, narrative inquiry has a more specific meaning (Saunders et al., 2012). When following a narrative research strategy, the researcher will document participants’ experiences as stories rather than data which can be derived from interview questions (Maree, 2007). It is an appropriate strategy where the researcher wishes to maintain the continuity of the narrator’s version of events in order to enhance understanding and support analysis. A narrative research strategy is laborious and demanding in nature; it is therefore usually characterised by small, purposive samples (Saunders et al., 2012).

The research strategy chosen for this study is survey research. Survey research is a popular choice when following a deductive approach (Altinay & Paraskevas, 2008).

Two types of surveys, descriptive or analytical, can be conducted. Descriptive surveys gather data on what participants think whereas analytical surveys answer research questions or test hypotheses with an emphasis on variables used in the study (Altinay & Paraskevas, 2008).

Using surveys has various advantages and disadvantages. The advantages include:  Surveys are a fast, low-cost, effective and accurate way of judging information about a population.  Surveys are flexible.  Surveys, when conducted properly, provide valuable information. (Zikmund, et al. 2013)

There are many ways in which surveys can be conducted and it is of utmost importance that a researcher chooses the correct one (Altinay & Paraskevas, 2008). Methods in which surveys can be conducted are summarised in Table 4.3.

Table 4.3: Methods of conducting surveys

Type of survey Conducting method Advantages Disadvantages

Group Researcher waits while  Many respondents in a  Researcher has administration of a group of respondents short space of time limited control over questionnaires completes  Affordable and easy what happens in questionnaires method the field  Response rate is good Postal survey Questionnaires are  Affordable and easy to do  Poor response rate mailed to respondents  Respondents can  Respondents must who have to read complete questionnaire at be literate instructions, answer their leisure questions and mail  No interviewer to answers back influence respondents

Telephone survey Respondents receive a  Survey completed quickly  Expensive method phone call and are  Respondents who are  Questionnaire has asked questions, and geographically removed to be short the interviewer records can be reached  Can only reach the answers  Response rate is good people with telephones

Face-to-face Qualified interviewers  Very high response rate  Expensive method survey visit respondents to ask  Long questionnaires may  Interviewers need questions and record be used to be qualified or responses  Interviewer can assist trained with unclear issues  Risk of interview bias is high

Source: Summarised by author from Babbie and Mouton (2001) and Maree (2007)

A face-to-face survey was selected for this study. Trained interviewers from an independent research company approached passengers at Lanseria International

Airport with questions and recorded the answers. Although this survey method is more expensive, it was the preferred survey method because it has a good response rate, and a longer questionnaire could be used. The questionnaire used for this study will be discussed in Section 4.5.5.2.

4.4.4 Time horizon

Time is an important aspect to consider in research design as well as the completing of the research – not just the actual time taken to do the research but also the time required to make observations or gather data (Babbie & Mouton, 2001).

4.4.4.1 Cross-sectional study

A cross-sectional study is ‘based on observations representing a single point in time’ (Babbie & Mouton, 2001:641). In many cases a cross-sectional study employs a survey strategy in order to describe the occurrence of a phenomenon at a given point in time (Saunders et al., 2012).

4.4.4.2 Longitudinal study

Babbie and Mouton (2001:644) define a longitudinal study as a study ‘involving the collection of data at different points in time’. With longitudinal studies, change and development can be observed (Saunders et al., 2012).

This study is a cross-sectional study during which passengers at Lanseria International Airport were surveyed at one specific point in time in 2013. However, the findings of this study are compared with a study completed in 2010 by Heyns and Carstens (2011) to determine if the way in which passengers rate attributes had changed once a second airline started to operate from this airport.

The next section of this chapter will describe the data collection and analysis techniques used.

4.5 DATA COLLECTION

Various data-collecting techniques are at the disposal of researchers to accomplish the requirements of their research. The data-collecting technique selected depends on the purpose of the research considering the strengths and weaknesses of the various techniques (Altinay & Paraskevas, 2008). Data is required in order to test theories. When data is collected it is important to first determine what needs to be measured and secondly how to measure it (Field, 2009).

4.5.1 Unit of analysis

Unit of analysis refers to ‘what object, phenomenon, entity, process, or event’ (Babbie & Mouton, 2001:84) are you planning to study or investigate. Units of analysis are furthermore something a researcher observes in order to construct summary descriptions and to explain variances among them. Typical units of analysis found in social research include individuals, groups, organisations, social artefacts/cultural objects, social actions and interventions (Babbie & Mouton, 2001).

Individuals – passengers flying on domestic flights to and from Lanseria International Airport – were chosen as the unit of analysis for this study. Agreeing with Babbie and Mouton (2001), individuals (human beings) are the most typical units of analysis and can represent a population in descriptive research studies.

4.5.2 Population

The theoretical identification of a collection of study elements is known as the population and the group of elements from which the sample is actually drawn is known as the study population (Babbie & Mouton, 2001).

4.5.2.1 Nature of research population

For the purpose of this study, the research population had to be individuals who travelled on domestic flights to and from Lanseria International Airport to determine which choice factors they consider when selecting to fly from this specific airport.

4.5.2.2 Size of research population and sampling frame

It is not always possible to survey the entire population for various reasons (Saunders et al., 2012), such as:  It is not practical to survey the entire population.  Budget constraints can prevent a researcher from surveying the entire population.  Time constraints make it difficult to survey the entire population.

For these reasons, it was decided not to survey all passengers travelling on domestic flights to and from Lanseria International Airport but to select a more workable population size. Therefore, the sampling frame consisted only of passengers travelling either on Mango Airlines or Kulula from Lanseria International Airport.

4.5.3 Sampling strategy

The process of sampling entails selecting a representative division of the total population to study in order to draw conclusions regarding the complete population. Selecting a smaller portion of the entire population to work with certainly has advantages. It makes the research more manageable, efficient, affordable and possibly more accurate (Altinay & Paraskevas, 2008).

Sampling techniques or strategies can be divided into two types: 1. Probability or representative sampling, and 2. Non-probability sampling (Saunders et al., 2012).

4.5.3.1 Probability sampling

Probability sampling entails that every portion of the population has the possibility to be represented in the sample because the sample is selected randomly from the total population; this assumes that the characteristics of the sample will be more or

less similar to that of the population (Leedy & Ormrod, 2014). Probability sampling, also known as representative sampling, usually accompanies survey research strategies and consists of four phases (Saunders et al., 2012): 1. Select a suitable sampling frame – this is the inclusive list of all the cases in the population from which a sample can be selected 2. Determine a suitable sample size – a larger sample lowers the likelihood of errors when generalising findings to the population 3. Identify sampling technique and select the sample – four popular sampling techniques can be chosen from and will be discussed in the section that follows 4. Verify that the sample is representative of the population – the sample needs to resemble more or less the same aggregate characteristics as the population (Babbie & Mouton, 2001)

Four popular probability sampling techniques are summarised in Table 4.4 below.

Table 4.4: Summary of probability sampling techniques

Sampling technique Method Advantages Disadvantages Selecting a sample at random from the  Most basic sampling  Not suitable to (Simple) random sampling frame using a computer or technique collect data over sampling random number tables  Selects sample large geographical  Number each case in sampling frame without bias area (when face-to- with unique number  Best when accurate face contact is  Select cases using random numbers and accessible required) until desired sample size is reached sampling frame that  Lengthy if done by lists entire population hand is available Selecting a sample at regular intervals  Unsophisticated  If list of cases is Systematic (random) from sampling frame method arranged cyclically sampling  Number each case in sampling frame  Useful when and coincides with with unique number population size is sampling interval,  Select first case using random unknown and the sample will be number population elements biased  Calculate sampling fraction come to a location  Select following cases methodically over a period of time using sampling fraction to decide  Works well with small frequency of selection number or large number of cases Alteration of random sampling. Divide  Sample is likely to be  Process takes Stratified (random) population into two or more sections more representative longer sampling based on attributes (homogeneous  More expensive groups)  Complicated to  Select section variable(s) explain  Divide sampling frame in discrete sections

 Number each case within each section with unique number  Select sample using random or systematic sampling Divide population into distinct groups  Maximise amount of  Represents Cluster sampling before sampling. These groups are data that can be population less known as clusters collected face to face accurately than  Choose clusters for sampling frame other methods  Number each cluster with unique number  Select sample of clusters by means of random sampling Source: Summarised by author from Babbie and Mouton (2001), Maree (2007), Saunders et al. (2012)

4.5.3.2 Non-probability sampling

Non-probability sampling cannot assure or even envisage that each element of the total population will be represented in the sample selected, and some elements of the population have little or no chance of being included in the sample (Leedy & Ormrod, 2014).

Three general non-probability sampling methods used are: 1. Convenience sampling: also known as haphazard or accidental sampling. Participants are selected because they are conveniently accessible. These types of samples tend to be non-representative in nature and biased (Altinay & Paraskevas, 2008). 2. Quota sampling: a non-random method which can be effectively used for structured interviews as part of survey research. The population is divided into groups; quotas are calculated for the groups (based on available data); each interviewer receives the number of cases in each quota from which data should be collected; and finally all data from all interviewers are pooled to deliver a full sample (Saunders et al., 2012). 3. Purposive sampling: also sometimes called judgmental or expert sampling. This is used in situations where sampling is done with an explicit purpose in mind. Participants are specifically selected from the available population (Maree, 2007).

For the purpose of this study, a stratified random sample, representative of the population of passengers was selected so that the findings of the survey could inform the researcher more about the population (Maree, 2007).

The sample in the 2010 survey used stratified random sampling to be representative of the weekly departure schedule of Kulula from Lanseria International Airport (Heyns & Carstens, 2011) as depicted in Tables 4.5 and 4.6 below.

Table 4.5: Kulula’s weekly departure schedule from LIA to Cape Town (2010)

Monday Tuesday Wednesday Thursday Friday Saturday Sunday 06:00 06:00 06:00 06:00 06:00 06:55 06:55 07:55 07:55 07:55 07:55 07:55 07:30 07:30 08:30 08:30 08:30 08:30 08:30 13:40 13:40 14:40 14:40 14:40 14:40 14:40 16:10 16:10 17:10 17:10 17:10 17:10 17:10 19:00 20:00 20:00 20:00 20:00 20:00 20:45 21:45 21:45 Source: Heyns and Carstens (2011:189)

Table 4.6: Kulula’s weekly departure schedule from LIA to Durban (2010)

Monday Tuesday Wednesday Thursday Friday Saturday Sunday 06:15 06:15 06:15 06:15 06:15 10:20 10:20 11:20 11:20 11:20 11:20 11:20 12:50 12:50 13:50 13:50 13:50 13:50 13:50 17:25 17:25 18:25 18:25 18:25 18:25 18:25 19:15 20:15 20:15 20:15 20:15 20:15 21:30 22:30 22:30 Source: Heyns and Carstens (2011:189)

Similarly in 2013, a stratified random sample of passengers was selected to be representative of the weekly departure schedules of both Kulula and Mango Airlines from Lanseria International Airport as depicted in Tables 4.7, 4.8 and 4.9 respectively.

Table 4.7: Kulula’s weekly departure schedule from LIA to Cape Town (2013)

Monday Tuesday Wednesday Thursday Friday Saturday Sunday 06:00 06:00 06:00 06:00 06:00 06:55 06:55 07:55 07:55 07:55 07:55 07:55 07:30 07:30 08:30 08:30 08:30 08:30 08:30 09:35 09:35 09:35 09:35 09:35 09:35 09:35 13:45 13:45 14:55 14:55 14:55 14:55 14:55 16:10 16:10 17:10 17:10 17:10 17:10 17:10 19:00 20:00 20:00 20:00 20:00 20:00 20:45 Source: Kulula (2013)

Table 4.8: Kulula’s weekly departure schedule from LIA to Durban (2013)

Monday Tuesday Wednesday Thursday Friday Saturday Sunday 06:15 06:15 06:15 06:15 06:15 10:20 10:20 11:20 11:20 11:20 11:20 11:20 12:50 12:50 13:50 13:50 13:50 13:50 13:50 14:40 14:40 14:40 14:40 14:40 14:40 14:40 17:25 17:25 18:25 18:25 18:25 18:25 18:25 20:10 21:25 21:30 Source: Kulula (2013)

Table 4.9: Mango Airlines’ weekly departure schedule from LIA to Cape Town (2013)

Monday Tuesday Wednesday Thursday Friday Saturday Sunday 06:45 06:45 06:45 06:45 06:45 07:05 06:45 12:20 12:20 12:20 12:20 12:20 14:05 12:20 16:25 16:25 16:25 16:25 16:25 16:25 Source: Mango Airlines (2013)

Respondents resident in Gauteng as well as other provinces were included in the sample. For the 2010 survey, a random sample of 210 departing passengers was surveyed over the period of 29 September to 4 October 2010 (Heyns & Carstens, 2011). In the 2013 survey, 308 randomly selected passengers were surveyed during the first week of February 2013.

For both surveys the sample sizes were verified by STATCON5 as being adequate for the type of survey undertaken.

4.5.4 Data collection instrument

One of the objectives of this study is to compare the results of this study with an earlier similar survey. This required a degree of alignment of data collection instruments.

4.5.5 Type of data collected

Data collected for research purposes can either be classified as primary data or secondary data (Saunders et al., 2012). Primary data is seen as data that are specifically collected for the research project at hand as opposed to secondary data which was previously gathered for another purpose. Secondary data can be further analysed to provide different interpretations and conclusions (Saunders et al., 2012). The data collected during the 2010 survey (Heyns & Carstens, 2011) can therefore be considered to be secondary data which will be used for comparative purposes.

According to Saunders et al. (2012), primary data can be collected in various ways, such as observations, questionnaires and interviews.

4.5.5.1 Observations

Collecting data by means of observation can add tremendous value to research data because the researcher learns by being part of the research setting. Observation entails the surveillance, explanation, analysis and understanding of individuals’ behaviour. Two types of observation can be distinguished, namely, participant observation and structured observation (Saunders et al., 2012). Taking part in the situation under study makes the researcher a participant observer because it increases his or her understanding of the study context (Altinay & Paraskevas,

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2008). Structured observation is another method in which primary data can be collected and with this method the researcher is disconnected from the group or organisation being observed. The aim is to determine how often things happen instead of why they happen and is a popular tool in business research to evaluate the manner in which staff perform their duties (Saunders et al., 2012).

4.5.5.2 Questionnaires

In business and management research questionnaires are widely used and are usually paired with a survey strategy although experiment and case study research strategies can also make use of questionnaires (Saunders et al., 2012). A questionnaire can be interpreted as a data-collection method in which individuals are requested to answer an identical set of questions in a prearranged sequence; it can include structured interviews, telephone questionnaires and online questionnaires (de Vaus, 2002). Questionnaires are also a very effective means to systematically collect information affordably from a large number of respondents and, because it is a very structured data collection technique, it is essential to follow a process when designing the questionnaire (Altinay & Paraskevas, 2008).

Altinay and Paraskevas (2008) propose an eight-step process to be followed in designing a questionnaire: 1. Determine the information required. 2. Determine the target respondents. 3. Select a method to reach the respondents. 4. Determine the question content. 5. Phrase questions. 6. Assess the length of the questionnaire. 7. Pre-test the questionnaire. 8. Finalise the questionnaire.

Questionnaires are also mainly used for descriptive or explanatory research where attitudes and opinions are researched or relationships between variables are explained (Saunders et al., 2012). A range of different types of questionnaires is at a researcher’s disposal and can be divided into two distinct groups, namely: self-

completed questionnaires, including internet (web-based) questionnaires; postal questionnaires as well as delivery-and-collection questionnaires; and interviewer- completed questionnaires, consisting of telephone questionnaires and structured interviews (Saunders et al., 2012).

For the purpose of this study, primary data was collected by means of an interviewer-completed questionnaire (interviewer records the responses of respondents [Saunders et al., 2012]) and more specifically structured interviews (interviewer asks questions to respondents face to face [Babbie & Mouton, 2001]). These structured interview questions were comprehensive and developed in advance by the researcher (Maree, 2007). This allowed total control over the areas of the topic to be covered during the interview. The interviewers read out each question and then recorded the reply on a standardised answer sheet (Altinay & Paraskevas, 2008).

Following a literature study, discussions with air transport specialists and personal experience, the questionnaire was compiled, taking into consideration the questions included in the 2010 survey (Heyns & Carstens, 2011). Thereafter it was evaluated by academics and aviation experts for relevance and ambiguity. The questionnaire contained attributes concerning the following areas of importance:  Demographics  Price  Service  Convenience  Safety

The first part of the questionnaire was similar to the one used in the 2010 survey (Heyns & Carstens, 2011) (Annexure A). However, additional questions were added in the 2013 questionnaire (Annexure B). These additional questions related to Lanseria International Airport specifically, and respondents were requested to comment on their preference with regard to aspects such as:  Additional airport facilities or services  Possibility to connect to other destinations

 Parking facilities and the cost thereof

An open-ended question allowed respondents to add additional attributes if they wished to do so. Respondents were also asked to state why they chose Lanseria International Airport as opposed to ORTIA.

Respondents had to complete a 4-point Likert-type scale to rank the influence of each attribute on their decision to use Lanseria International Airport. The response options included:  To no extent  To a small extent  To a moderate extent  To a large extent

In this forced-choice method, the middle option of undecided or neutral is not available (Maree, 2007).

4.5.6 Data analysis

The concluding phase of research is analysing the data collected (Field, 2009).

4.5.6.1 Analysing quantitative data

Presenting quantitative data in a convenient format is often referred to as descriptive statistics (Babbie & Mouton, 2001). Analysing quantitative data requires a researcher to look at data graphically in order to recognise trends and also fit statistical models to the data (Field, 2009). Fitting statistical models to the data can be done by means of various statistical techniques and can, according to Babbie and Mouton (2001), include, among others:  Correlation – a statistical method to calculate whether two or more variables are somehow related to each other (Leedy & Ormrod, 2014)

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 Regression analysis – results in a mathematical equation which points out a relationship between variables; this is then used to make predictions (Maree, 2007)  Time-series analysis – provides a long-term trend (a trend observed over a period of time) in a regression layout in order to test reasons for the trend (Babbie & Mouton, 2001)  Factor analysis – determines patterns among deviations in values of different variables (Babbie & Mouton, 2001)

For the purpose of this study, a statistician from STATCON at the University of Johannesburg was consulted and it was decided to utilise a factor analysis approach in order to understand the latent variables that describe the set of variables (Field, 2013).

The factor analysis was based on the correlation matrix, and was conducted with SPSS for Windows version 22 using the Principle Component Extraction method with Varimax Rotation and Kaiser Normalisation.

Further details on the factor analysis are included in the Chapter 5.

4.6 VALIDITY AND RELIABILITY

The extent to which researchers can acquire knowledge from their research and draw significant conclusions depends on the reliability and validity of the measurement instruments (e.g. questionnaire). Reliability and validity will depend largely on the research methodology followed and reflect whether there are errors in the measurements (Leedy & Ormrod, 2014).

4.6.1 Reliability

If the data-gathering method and analytical technique deliver dependable conclusions when repeated at another time or by another researcher on the same population, it is regarded as reliable (Saunders et al., 2012). Reliability tends to

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reflect errors in the use of the measuring instrument and can differ from one instance to the next (Leedy & Ormrod, 2014).

Reliability in this study will be ensured by means of Cronbach’s alpha coefficient which is based on correlations among items. A Cronbach’s alpha coefficient close to 1 represents a high internal consistency, which indicates a strong correlation among items (Maree, 2007).

4.6.2 Validity

If the data collection method accurately measures what it was intended to measure, it is seen to be valid (Altinay & Paraskevas, 2008). Various forms of validity exist to ensure quality of research, and will now be briefly mentioned:  External validity – applies when a quantitative study’s research findings can be generalised to other related groups (Plano Clark & Creswell, 2008). By using random sampling the respondents can be deemed to be representative and therefore the findings can be generalised to passengers at the selected airport.  Construct validity – refers to the logical association between variables which cannot be directly witnessed but is implied to exist based on individuals’ actions (Leedy & Ormrod, 2014). In both surveys conducted in 2010 and again in 2013, respondents rated the attributes based on their own preference and experience. Similar research has been done in this field where respondents are requested to rate attributes, and therefore this research can be deemed valid.  Face validity – a subjective measurement referring to the extent to which the measurement instrument appears to be valid (does it look as if it measures what it is intended to measure?) (Maree, 2007). To ensure face validity, the questionnaire was evaluated by industry experts and academics specialising in the field of aviation, as well as by a statistician.

Validity has a tendency to reveal biases in the measuring instrument and is usually a persistent cause of errors (Leedy & Ormrod, 2014).

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4.7 CONCLUSION

In this chapter the research methodology followed in this study was discussed. A positivistic research philosophy was identified and a deductive research approach was followed. It was also established that this was an exploratory study that utilised a quantitative research approach.

Survey research was selected to study the critical factors passengers consider when selecting to fly from Lanseria International Airport, and a stratified random sample of passengers was surveyed by means of a questionnaire. The data collected were analysed by means of factor analysis because it allows understanding of latent variables that describe a set of variables. The next chapter will describe the factor analysis in greater detail and present the survey results.

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CHAPTER 5: SURVEY RESULTS AND FINDINGS

5.1 INTRODUCTION

In the previous chapter the research methodology used in this study was discussed. It was determined that a deductive approach will be followed in order to explore the relationship between variables; furthermore, the exploratory research design will enable the researcher to explore the attributes passengers consider when electing to fly from Lanseria International Airport.

In this quantitative study, comparisons will be drawn between the results of this study, conducted in 2013, and that of a similar study conducted in 2010 by the Institute for Transport and Logistics Studies (ITLS) (Africa), thereby addressing the primary objective of the research – namely, to determine the reasons passengers prefer to fly to and from Lanseria International Airport. Secondly, this study aims to explore whether passenger airport choices have changed since a second airline started flying from the airport. The data collected from the survey conducted in 2013 will be statistically analysed by means of a factor analysis. This will be compared to a factors analysis conducted by Heyns and Carstens (2011) to establish if respondents rated the attributes differently in the two studies.

The outline of this chapter is schematically represented in Figure 5.1.

5.1 Introduction

5.2 Discussion of surveys Chapter 5 Survey results and findings 5.3 Factor analysis

5.4 Conclusion

Figure 5.1: Outline of Chapter 5

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5.2 DISCUSSION OF SURVEYS

In this section the two surveys conducted at Lanseria International Airport in 2010 and 2013 respectively will be discussed in more detail.

5.2.1 Survey conducted in 2010

The purpose of the research conducted in 2010 was to identify the underlying factors which influence passenger airport choice decisions at Lanseria International Airport in the Gauteng area in South Africa. At that time only one low-cost airline, Kulula, operated scheduled domestic services from the airport to both Cape Town and Durban. The Institute of Transport and Logistics Studies (ITLS) (Africa) was contracted to obtain the data through a paper-based survey of departing passengers at the airport, and Heyns and Carstens (2011) analysed the data statistically using factor analysis.

The 2010 questionnaire (Annexure 1) (ITLS, 2010) comprised 18 attributes related to the passengers, airline offerings and the airport, such as:  Demographics  Price  Service  Convenience

The respondents were requested to complete a 4-point Likert-type scale to rank the influence of each attribute on their decision to use Lanseria International Airport. The scale included the following range of choices: to no extent (1), to a small extent (2), to a moderate extent (3) and to a large extent (4) (Heyns & Carstens, 2011).

The survey included a systematic random sample of 210 departing passengers at Lanseria International Airport. The random selection of passengers was systematically structured to be representative of the weekly departure schedule of the low-cost airline, Kulula (Heyns & Carstens, 2011). The sample size of 210 was deemed acceptable owing to the respondents being homogeneous with respect to

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the variables significant to the study (Maree, 2007). The respondents were all passengers flying to and from Lanseria International Airport on domestic flights and considered similar attributes as important when selecting an airport.

5.2.2 Survey conducted in 2013

The purpose of the study conducted in 2013 was to identify the underlying factors which influence passenger airport choice decisions at Lanseria International Airport following the entry of a second low-cost airline. The information was obtained through a paper-based survey of departing passengers at the airport.

The 2013 questionnaire (Annexure 2) comprised 19 attributes relating to the following aspects of the passengers, airline offerings and airport:  Demographics  Price  Service  Convenience

Respondents were requested to complete a 4-point Likert-type scale to rank the influence of each attribute on their decision to use Lanseria International Airport. The scale included the following range of choices: to no extent (1), to a small extent (2), to a moderate extent (3) and to a large extent (4). In this forced choice method the middle option of undecided or neutral is not available.

The survey included a systematic random sample of 308 departing passengers at Lanseria International Airport. The random selection of passengers was systematically structured to be representative of the weekly departure schedule of the two low-cost airlines, namely Kulula and Mango Airlines. The sample size was considered acceptable as the respondents were homogeneous in terms of the variables that are important to this study (Maree, 2007). Again, all the respondents were passengers travelling on domestic flights to and from Lanseria International Airport and they considered similar attributes which influence their choice of airport.

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The following section will compare the findings with regard to the demographic aspects of the two surveys conducted at Lanseria International Airport in 2010 and 2013 respectively.

5.2.3 Demographic profile of respondents

5.2.3.1 Gender distribution of respondents

The sample included passengers departing for Cape Town and Durban, and included respondents resident in Gauteng as well as other provinces. The sample composition in terms of gender is depicted in Figure 5.2, for both the 2010 and the 2013 surveys.

80 70 60 50 40 2010 2013 Percentage 30 20 10 0 Female Male

Figure 5.2: Gender distribution of respondents Source: Respondents’ responses obtained during 2010 and 2013 interview processes

In both surveys the majority of the respondents were male, with 56% in 2010 (ITLS, 2010) and 67% in 2013. More male than female respondents seem to be an international trend as a recent IATA Global Passenger Survey (IATA, 2013) similarly included more males than females.

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5.2.3.2 Purpose of travel

In 2013 the majority of passengers travelled for either business 59% or leisure 33% purposes (Figure 5.3). This finding applied to both surveys. In 2010, 51% of the passengers interviewed (ITLS, 2010) travelled for business purposes and in 2013 that figure was slightly higher at 59%. Leisure travel accounted for 37% in the 2010 study (ITLS, 2010) and 33% in 2013. The increase in business travel from the airport in 2013 can be attributed to the fact that another airline started operating from there which allows for greater choice.

70 60 50 40 30 2010

Percentage 20 2013 10 0 Business Leisure Other VFR (visiting friends and relatives)

Figure 5.3: Purpose of travel Source: Respondents’ responses obtained during 2010 and 2013 interview processes

5.2.3.3 Airline used

The majority of the respondents (70.7%) used Kulula to travel in 2013 as opposed to Mango Airlines, as depicted in Figure 5.4. A possible reason for this could be that Kulula offers more flights per week (Kulula, 2013) than Mango Airlines, and the latter only offers flights to Cape Town and not to Durban (Mango Airlines, 2013). In 2010 only Kulula offered flights from Lanseria International Airport (Heyns & Carstens, 2011).

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30 Percentage 20

0 Kulula Mango

Figure 5.4: Airline choice 2013 Source: Respondents’ responses obtained during 2010 and 2013 interview processes

5.2.3.4 Residential distribution of respondents

With regard to the distribution by province in which passengers reside, it is evident from Figure 5.5 that in 2013 respondents mainly resided in Gauteng (59.7%), followed by the Western Cape (23.4%) and KwaZulu-Natal (12.3%). The same distribution by province of residence was evident in the 2010 survey (ITLS, 2010), as indicated in Figure 5.5.

70 60 50 40 2010 30 2013

Percentage 20 10 0 Gauteng Western Cape KwaZulu-Natal Other provinces

Figure 5.5: Province of residence Source: Respondents’ responses obtained during 2010 and 2013 interview processes

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Lanseria International Airport is situated in Gauteng and therefore it is to be expected that a significant number of users are resident in Gauteng. Goedegebuure (2010) stated that passengers are likely to choose an airport situated close to them. However, Gauteng is also served by OR Tambo International Airport which is situated in the eastern region of the province as opposed to Lanseria International Airport in the north-western region.

Zhang and Xie (2005) found that when airports in a metropolitan area are located close to one another, one of the main factors passengers consider when choosing an airport is access time. Lanseria International Airport is easily accessible for air passengers residing in the northern, central and western suburbs of Gauteng.

To test the theory that passengers choose the airport closest to them, the questionnaire information of both surveys was used to plot the residential (suburb) postal codes on a map of Gauteng. In order to determine the geographical location of each suburb on the map an estimated x- and y-value was given to each suburb. The number of respondents per suburb was presented as a percentage of the total respondents who reside in Gauteng. These percentages are indicated by the green dots in Figure 5.6 (2010) and Figure 5.7 (2013).

According to the survey conducted in 2010 (ITLS, 2010) the passengers using Lanseria International Airport generally resided in the northern, western and central regions of Gauteng as indicated by the green dots in Figure 5.6.

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100

0 0 10 20 30 40 50 60 70 80 90 100

Figure 5.6: Gauteng respondents’ residential distribution (2010) Source: Respondents’ postal codes obtained during 2010 interview process Source map: www.places.co.za

In 2013, the respondents using Lanseria International Airport similarly resided in the northern, western and central regions of Gauteng, as indicated by the green dots on Figure 5.7.

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0 0 10 20 30 40 50 60 70 80 90 100 Figure 5.7: Gauteng respondents’ residential distribution (2013) Source: Respondents’ postal codes obtained during 2010 interview process Source map: www.places.co.za

Hess (2010) confirms that passengers tend to favour airports closer to their homes and tend to dislike larger airports. Therefore the residential distribution remained relatively the same for the two surveys because people resident in the northern, central and western suburbs of Gauteng prefer to fly from Lanseria as opposed to ORTIA.

This section described the two surveys conducted at Lanseria International Airport in detail. The demographic profile of respondents in the 2013 survey were analysed and the findings compared to that of the 2010 research. The section that follows will investigate the 2013 respondents’ rating of airport choice factors and the findings will be compared to that of the 2010 survey.

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5.2.4 Airport choice factors/ attributes

In this section the respondents’ rating of the airport choice factors are discussed, with relevance to Lanseria International Airport. The 2010 and 2013 findings are compared. Respondents were asked to rate the influence of the following main attributes on their decision to use the airport:  Total cost of using the airport (price attributes)  Convenience of getting to the airport (convenience attributes)  Customer experience at the airport (service attributes related to an airline and airport)

5.2.4.1 Total cost of using the airport (price attributes)

The total cost of using the airport included three variables, namely cost of transport to the airport, price of parking and price of the air ticket.

30 Percentage 20 Cost of transport to airport Price of parking 10 Price of ticket 0

Figure 5.8: Total cost of using the airport 2010 and 2013 Source: Respondents’ responses obtained during 2010 and 2013 interview processes

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 Cost of transport to the airport In 2013, 35% of the respondents indicated that the cost of transport to the airport influenced their airport choice decision to a large extent, compared to 32% in 2010 as seen in Figure 5.8 (ITLS, 2010), whereas in 2010 36% of respondents were not influenced by it (to no extent). In 2013, 26% were not influenced by it (Figure 5.8). Respondents may be more aware of cost as a price increase of 73c per litre of fuel urged consumers to reconsider their expenditures (Steyn, 2012).

 Price of parking In both 2013 and 2010, the price of parking at the airport seemed not to influence respondents’ choice to use Lanseria International Airport, with 48% (ITLS, 2010) and 48% of the respondents, respectively, indicating that it would to no extent influence their decision (Figure 5.8). In 2013, only 15% of the respondents indicated that it influenced to a large extent their decision to use Lanseria International Airport.

 Price of the air ticket In 2013 the price of the air ticket to a large extent influenced 38% of the respondents’ decision to use Lanseria International Airport, with a further 27% of the respondents being influenced to a moderate extent (Figure 5.8). In 2010, the respondents considered the price of the air ticket less important as seen in Figure 5.8 (ITLS, 2010). The reason that the price of the air ticket is more important in 2013 could be attributed to the fact that in 2013 two airlines offered services from Lanseria (Gauteng Tourism Authority, 2013) and respondents now had a choice of two airlines from which to purchase tickets. Mango Airlines has been able to offer passengers consistently affordable flights (SA Airlines, 2015) and since they now offer flights from Lanseria the respondents in 2013 may be more price-sensitive than in 2010. Research conducted by Luke (2015) confirms that passengers choosing to fly with Mango Airlines are typically lower-income individuals and students, both of whom are more sensitive to prices than passengers flying with Kulula who tend to be business people.

Cost is a very important component of a passenger’s decision to use a specific airport and include elements such as airfare, parking cost and cost to get to the

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airport (Goedegebuure, 2010). When passengers decide on which airport to use they will consider a combination of factors. The one, rather important factor is the cost to travel to the airport and the other factor is the price of the air ticket (Barbot, 2009).

5.2.4.2 Convenience attributes

Convenience attributes are significant in passengers’ airport choice (Heyns & Carstens, 2011). When asked to rate the importance of convenience attributes, respondents had to consider factors such as ease of check-in procedure, ease of parking at the airport, ease of access to airport (e.g. traffic congestion) and time to get to and from the airport.

In both the 2010 and 2013 studies the majority of the respondents were influenced to a large extent by all four of the convenience attributes relating to their decision to use Lanseria International Airport. This is evident in the fact that a large proportion of the respondents indicated that these attributes influenced their decision ‘to a large extent’. The importance of these attributes ranged between 46% and 70% in 2013 as seen in Figure 5.9.

80 70 60 50 40 30 Ease of check-in Percentage 20 Ease of parking 10 Ease of access 0 Time to and from airport

Figure 5.9: Convenience attributes 2010 and 2013 Source: Respondents’ responses obtained during 2010 and 2013 interview processes

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A similar trend was observed in 2010. It was established that respondents viewed the convenience attributes as fairly important (ranging between 65% and 75%) as indicated in Figure 5.9 (ITLS, 2010). When selecting an airport, Goedegebuure (2010) found that various convenience elements influence a passenger’s decision. These elements include distance to and time taken to travel to the airport, accessibility of the airport, as well as time spent at airport before boarding flight (including time taken to park and time to check in).

5.2.4.3 Customer experience

A customer’s experience at an airport is a crucial factor in airport choice decision because passengers who used an airport tend to continue to use that airport based on their experience, according to Suzuki, Crum, & Audino (2003), as citied in Jiang- tao (2008). A passenger’s experience at the airport can entail aspects such as frequency of services, flight schedules (departure and arrival times), destinations serviced, seat availability and purpose of travel (Heyns & Carstens, 2011).

In the 2013 survey, respondents were required to rate their experience at Lanseria International Airport. Service attributes that were included in the questionnaire related to the service respondents received from the airline as well as the services related to the airport. Attributes related to service from the airline included:  Destinations serviced  On-time departure and arrival  Service frequency  Availability of seats  Departure times

Attributes relating to the airport specifically included facilities at the airport and baggage collection. The attributes that relate to the services received from the airline seemed to be of importance for respondents when considering to fly from Lanseria International Airport in 2013 (Figure 5.10). Table 5.1 indicates that when the responses ‘to a moderate extent’ and ‘to a large extent’ are combined, these

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attributes have a strong influence on the airport selection decision of respondents as evident from the percentages given in the table.

Table 5.1 points to a similar trend in 2010. When the responses ‘to a moderate extent’ and ‘to a large extent’ were combined it proved that respondents consider these attributes as significant in their selection of airport (ITLS, 2010).

Table 5.1: Customer experience 2010 and 2013 (airline)

2013 2010 Destinations serviced by airport 71.4% 75.7% On-time departure and arrival 70.5% 68.7% Service frequency 68.1% 69.5% Availability of seats 67.2% 70.9% Departure times 67.5% 70.5% Source: Respondents’ responses obtained during 2010 and 2013 interview processes

Goedegebuure (2010) established that when passengers select a departure airport they consider features such as flight schedules (including frequency of flights and departure times). It is evident in both surveys conducted in 2010 and 2013 that respondents considered customer services related to an airline such as departure times, seat availability and frequency of flights, important when choosing to fly from Lanseria International Airport as depicted in Figure 5.10.

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60 50 40 Destinations serviced 30 On-time departure and 20 arrival

Percentage 10 Service frequency 0 Availability of seats

Departure times

Figure 5.10: Customer experience 2010 and 2013 (airline) Source: Respondents’ responses obtained during 2010 and 2013 interview processes

The time it takes to collect baggage is an influencing factor when passengers are deciding to use Lanseria International Airport as indicated by 36% (to a large extent) of the respondents in 2013 and depicted in Figure 5.11. The facilities at the airport were not seen as an important attribute to consider when using Lanseria International Airport as only 18.5% of respondents were influence to a large extend by it in 2013.

60 50 40 30

Percentage 10 Baggage collection 0 Facilities at airport

Figure 5.11: Customer experience 2010 and 2013 (airport) Source: Respondents’ responses obtained during 2010 and 2013 interview processes

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In 2010, baggage collection had a greater influence on airport selection, since 52% of respondents indicated that they were influenced by it to a large extent (ITLS, 2010). With regard to the facilities at the airport, a larger percentage (39%) (ITLS, 2010) were influence by these to a large extent. The fact that baggage collection and airport facilities are not as influential in the decision to use the airport can possibly be contributed to a number of passenger-friendly improvements that were introduced at the airport such as:  Shorter check-in times  Self-service kiosks  Quick baggage collection  Fast drop off and go facilities (The African Business Journal, 2010)

Airport facilities such as shops and restaurants as well as baggage collection facilities and time taken to do so were identified by Goedegebuure (2010) as factors passengers take into account when selecting an airport.

5.2.4.4 Other attributes

Other attributes were included in the survey in order to discover whether they would influence a respondent’s decision to use Lanseria International Airport. These safety and security attributes included:  Baggage security  Parking security  Airport safety

When combining the responses ‘to a moderate extent’ and ‘to a large extent’, it follows that in 2013 approximately half of the respondents’ decision to use Lanseria was influenced by baggage security (58%), parking security (48%) and airport safety (52%) as seen in Figure 5.12. In 2010, these attributes had a greater influence, since about three-quarters of the respondents were influenced by the combined percentages for baggage security (68%), parking security (63%) and airport safety (68%) as depicted in Figure 5.12. The reason for this can be attributed to airport

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security that was upgraded in 2010 in anticipation for the Soccer World Cup that was held in South Africa the same year (DoT Aviaition sub-sector task team, 2009).

30 25 20

Percentage 15 Baggage security 10 5 Parking security

0 Airport safety

Figure 5.12: Other attributes 2010 and 2013 – safety and security Source: Respondents’ responses obtained during 2010 and 2013 interview processes

Safety and security (including baggage and parking) are attributes that passengers take into consideration when selecting to fly from a specific airport according to Goedegebuure (2010).

In conclusion, this section analysed the airport choice factors passengers consider when deciding to fly from Lanseria International Airport. These choice factors were also compared to that of the 2010 survey conducted at Lanseria International Airport.

From this comparison it emerged that choice factors can be grouped into main attributes, namely:  Price  Convenience  Service  Other

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In the 2013 survey respondents were asked to rate the main attributes according to the extent they would influence their decision to use Lanseria International Airport, whereafter they had to rate the various choice factors individually (similar to the 2010 survey). Figure 5.13 illustrates the rating of the main attributes by respondents in 2013.

90.0

80.0

70.0

60.0

50.0 Price Attribute 40.0 Convenience Attribute

30.0 Service Attribute

Percentage 20.0

10.0

0.0 To no extent To a small To a moderate To a large extent extent extent

Figure 5.13: Main attributes 2013 Source: Respondents’ responses obtained during 2013 interview process

It is evident that when the choice factors are grouped into three main attributes, passengers consider price, convenience and service as important considerations when deciding to fly from Lanseria. In this particular survey, convenience (77%) was seen as the attribute that has the greatest influence in a passenger’s airport choice decision. Therefore passengers would consider aspects such as airport access time, ease of check-in and ease of parking at the airports (convenience attributes) first before considering the price of an air ticket (Figure 5.13).

Passengers therefore choose to fly from an airport that is located closer to them because travel time to the airport will be lower (Barbot, 2006), and passengers also prefer airports with rapid check-in facilities (Barrett, 2004b).

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The section that follows will discuss the statistical analysis, namely factor analysis of the data. The factor analysis of 2010 will be compared to that of 2013 in order to determine if respondents rated the attributes differently.

5.3 FACTOR ANALYSIS

The primary objective of this study is to determine if the choice factors passengers consider when selecting to fly from Lanseria International Airport changed after the entry of a second airline and if passengers viewed the factors differently. In the section that follows the findings that emerged as a result of factor analysis will be explained and will be compared to the findings of Heyns and Carstens (2011).

5.3.1 Defining factor analysis

In research it is often required to measure things that cannot be measured directly. To overcome this, a large number of variables can be collapsed into a few understandable, underlying factors. The essential part of factor analysis is that numerous observed variables have related patterns of responses because they are related to a variable that cannot be directly measured, also known as a latent variable (Rahn, 2015). The same number of factors and variables are present in every factor analysis and ‘each factor captures a certain amount of the overall variance in the observed variables, and the factors are listed in order of how much variation they explain’ (Rahn, 2015:1) Factor analysis is useful in situations where the following is required (Field 2013):  The structure of a set of variables needs to be understood.  A questionnaire needs to be compiled to measure an underlying variable. A data set needs to be reduced to a manageable size while as much of the original information as possible is retained

Factor analysis aims to achieve ‘parsimony’ (Field, 2013:667) by clarifying the full amount of mutual discrepancy in a correlation matrix with the minimum quantity of descriptive concepts. The descriptive concepts are the factors or latent variables in

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factor analysis and they characterise the variables that correlate greatly with one another (Field, 2013).

A factor analysis approach was used to understand the structure of the attributes (variables) (Field, 2013). This approach allows for the reduction of the number of attributes (19) to a smaller number of underlying factors (latent variables) that increase the ease of comparison and interpretation.

Factor analysis can be of benefit in various scenarios. First, factor analysis is an objective method (Darlington, 1997) of testing attributes that passengers would consider when selecting to fly from Lanseria International Airport. Secondly, it allows for an understandable comparison (Darlington, 1997) between the 2013 research to that of Heyns and Carstens (2011) and lastly, factor analysis can provide sustenance to theories that are difficult to prove otherwise (Darlington, 1997).

The factor analysis was based on a correlation matrix and was conducted with SPSS for Windows version 22 using the Principle Component Extraction method with Varimax Rotation and Kaiser Normalisation.

The survey results are suitable for factor analysis as indicated by a Kaiser-Meyer- Olkin (KMO) measure of sampling adequacy that produced a KMO measure of 0.889 (Field, 2013). A KMO measure close to 1 indicates that correlation patterns are concentrated and thus a factor analysis will produce distinctive and trustworthy factors (Field, 2013).

This is confirmed by the KMO measures for the individual variables which were all in excess of 0.6. Bartlett’s test is significant in indicating that the underlying latent structure of the variables can be identified with factor analysis. The reliability of the questionnaire is acceptable as measured by a Cronbach’s alpha (Field, 2013) of 0.913. Internal consistency or reliability is measured by Cronbach’s alpha and indicates correlation among items or factors. When a strong correlation is present between items they are strongly correlated with one another and the Cronbach alpha will measure 0.90 or higher (Maree, 2007).

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To determine the number of significant factors the eigenvalues of the correlation matrix need to be examined. The measure of how much of the variance of the observed variables a factor explains is known as the eigenvalue. Therefore an eigenvalue equal to or greater than 1 describes more variance (represents substantial variation [Field, 2013]) than a single observed variable. A factor that defines the least amount of variable is rejected (Rahn, 2015). Exploratory factor analysis on the 2013 data resulted in the identification of four factors (eigenvalues > 1) that explained 65% of the variation (the results are shown in Table 5.2).

Table 5.2: Initial factor analysis – Total variance explained

Total variance explained Rotation Initial eigenvalues Extraction sums of squared loadings sums of squared loadings % of Cumulative Total % of Cumulative Factor Total variance % variance % Total 1 7.755 40.816 40.816 7.353 38.698 38.698 6.110 2 1.657 8.719 49.534 1.276 6.718 45.416 2.484 3 1.516 7.978 57.512 1.140 5.998 51.414 5.376 4 1.182 6.221 63.733 .853 4.491 55.905 2.982 5 .962 5.066 68.799 6 .799 4.204 73.003 7 .706 3.717 76.720 8 .677 3.562 80.283 9 .603 3.176 83.458 10 .544 2.866 86.324 11 .462 2.432 88.757 12 .416 2.191 90.947 13 .337 1.774 92.722 14 .290 1.525 94.246 15 .282 1.482 95.728 16 .257 1.351 97.079 17 .209 1.102 98.181 18 .186 .979 99.160 19 .160 .840 100.00 Source: Respondents’ responses obtained during 2013 interview process

Deciding how many factors need to be retained is known as extraction (Field, 2013). Eigenvalues indicate the importance of a factor, and it is rational to retain the factors with high eigenvalues (Field, 2009). Plotting each eigenvalue against the associated

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factor on a graph is known as a scree plot (Cattell, 1966 as cited in Field, 2013). Typically the graph will include factors with high eigenvalues and many factors with lower eigenvalues creating a unique shape. Cattell (1966 as cited in Field, 2013) suggests that the point where the slope of the line changes is the cut-off for factors to be retained.

The scree plot associated with Table 5.2 shows the relative importance of each factor (Field, 2013) and it is apparent from Figure 5.14 that four factors should be retained.

Figure 5.14: Scree plot Source: Respondents’ responses obtained during 2013 interview process

5.3.2 Confirmatory factor analysis and factor rotation

Testing how well the measured variables represent the number of factors is called confirmatory factor analysis; it specifies the number of factors required in the data and which measured variables are related to latent variables (Statistics Solutions, 2015).

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A confirmatory factor analysis (CFA) for four factors was subsequently conducted and the results are shown in Table 5.3.

The factor loadings clearly indicate the four factors, but there are a number of attributes with significant cross-loadings. For example, Ease of getting to the airport has a loading of 0.554 on factor 1 and a loading of −0.636 on factor 2.

Table 5.3: Confirmatory factor analysis – Four factors (2013)

Component matrix Component 1 2 3 4 Price of ticket .153 .572 −.145 .504 Price of parking .452 .148 .334 .618 Cost of getting to/from .473 −.066 .418 .471 Destinations .622 .119 −.194 113 On time .721 .109 −.333 −.060 Frequency of service .785 .037 −.263 −.077 Seat availability .703 .161 −.327 .039 Short check-in .642 −.164 −.343 .183 Departure times .689 .164 −.352 .042 Facilities .614 .160 −.135 −.113 Baggage collection time .683 −.029 −.207 −.122 Time to get to airport .610 −.605 .065 .036 Ease of getting to airport .554 −.636 .034 −.007 Ease of parking .637 −.281 .258 .085 Ease of check-in .728 −.343 −.053 .050 Airline brand .556 .305 .236 −.250 Airport safety .744 .256 .375 −.291 Parking security .736 .148 .456 −.156 Baggage security .759 .244 .299 −.271 Extraction method: Principle Component Analysis 4 components extracted Source: Respondents’ responses obtained during 2013 interview process

In order to get a clear factor structure (no significant cross-loadings), factor rotation can be used (Field, 2013). The results of the factor rotation are shown in Table 5.4 below.

The rotated factor matrix contained a clear factor structure, but Price of ticket recorded a significant cross-loading (>0.4) on factors 2 and 4, as well as Ease of check-in that recorded significant cross-loadings on factors 1 and 3. In order to

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address this issue, the attributes associated with the significant cross-loadings (Price of ticket and Ease of check-in) were removed from the data set.

Table 5.4: Factor rotation – Four factors (2013)

Rotated component matrix Component 1 2 3 4 Price of ticket .331 −.052 −.430 .528 Price of parking .131 .190 .118 .808 Cost of getting to/from .390 .241 .331 .675 Destinations .589 .206 .126 .214 On time .745 .257 .154 .036 Frequency of service .725 .314 .258 .050 Seat availability .743 .222 .101 .129 Short check-in 657 −.010 .360 .171 Departure times .752 .200 .088 .120 Facilities .540 .361 .098 .044 Baggage collection time .601 .290 .283 −.009 Time to get to airport .257 .118 .809 .098 Ease of getting to airport .232 .079 .807 .028 Ease of parking .204 .343 .566 .281 Ease of check-in .472 .203 .607 .148 Airline brand .261 .669 .009 .073 Airport safety .281 .851 .158 .127 Parking security .204 .789 .264 .252 Baggage security .343 .801 .162 .118 Extraction method: Principle Component Analysis Rotation converged in 7 iterations Source: Respondents’ responses obtained during 2013 interview process

Factor analysis on the reduced data set (KMO measure = 0.89) resulted in the structure shown in Table 5.5.

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Table 5.5: Factor rotation – four factors (2013) (Price of ticket and Ease of check-in removed)

Rotated component matrix Component 1 2 3 4 Price of parking .208 .099 -.073 .864 Cost of getting to/from .064 .201 .264 .710 Destinations .568 .224 .192 .139 On time .757 .244 .144 .054 Frequency of service .728 .313 .251 .074 Seat availability .748 .208 .121 .111 Short check-in .683 −.023 .253 .218 Departure times .781 .168 .026 .143 Facilities .582 .320 .007 .123 Baggage collection time .616 .288 .197 .060 Time to get to airport .247 .149 .871 .157 Ease of getting to airport .221 .123 .891 .075 Ease of parking .279 .278 .368 .485 Airline brand .208 .728 .091 −.005 Airport safety .287 .842 .121 .199 Parking security .255 .740 .142 .394 Baggage security .348 .795 .125 .182 Extraction method: Principle Component Analysis Rotation converged in 6 iterations Source: Respondents’ responses obtained during 2013 interview process

The analysis resulted in a clear factor structure, but Ease of parking did not record significant loadings (>0.5) on any of the factors. The removal of Ease of parking from further analysis resulted in a factor structure similar to that depicted in Table 5.4.

The following four latent factors, depicted in Table 5.6, can be identified from the factor analysis results and can be grouped as follows:  Airline efficiency and facilities (factor 1)  Brand, safety and security (factor 2)  Access to the airport (factor 3)  Cost (factor 4)

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Table 5.6: Latent factor structure of attributes (2013)

Factor 1 – Airline efficiency and facilities Factor 2 – Safety and security (factor loadings > 0.5) (factor loadings > 0.5) Destinations Airport safety On time Parking security Frequency of service Baggage security Seat availability Airline brand Short check-in Departure times Facilities Baggage collection time Factor 3 – Access to airport Factor 4 – Cost (factor loadings > 0.5) (factor loadings > 0.5) Time to get to airport Price of parking Ease of getting to airport Cost of getting to/from Source: Respondents’ responses obtained during 2013 interview process

5.3.3 Comparison of latent factors: 2010 and 2013

Heyns and Carstens (2011) completed a similar survey at Lanseria in 2010. However, the questionnaire used in their survey was based on 18 attributes as Short check-in and Airline brand which were included in the 2013 questionnaire were not included in the 2010 survey.

The latent factors obtained from the 2010 survey were similar to the 2013 latent factors as shown in Table 5.7 below.

Table 5.7: Latent factor structure of attributes (2010)

Factor 1 – Airline efficiency and facilities Factor 2 – Access to airport (factor loadings >0.7) (factor loadings >0.7) On time arrival/departure Time to/and from airport Frequency of service Ease of access Seat availability Ease of check-in Departure times Factor 3 – Safety and security Factor 4 – Cost (factor loadings >0.7) (factor loadings >0.7) Airport safety Price of ticket Parking security Price of parking Cost of transport to the airport Source: Heyns and Carstens (2011:196)

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Heyns and Carstens (2011) used factor loadings in excess of 0.7 to identify the significant attributes whereas the attributes identified in Table 5.6 relate to attributes with a factor loading in excess of 0.5.

Although the factor loadings were different, the objective of factor analysis is to identify groups of variables that correlate significantly. Incidentally, if factor loadings in excess of 0.7 were also used for the 2013 data, the result would be as shown in Table 5.8.

Table 5.8: Latent factor structure of attributes (factor loadings in excess of 0.7)

Factor 1 – Airline efficiency and facilities Factor 2 – Safety and security

On-time arrival Airport safety Frequency of service Parking security Seat availability Baggage Security Departure time Airline brand Factor 3 – Access to airport Factor 4 – Cost

Time to get to airport Price of parking Ease of getting to airport Cost of getting to/from

Source: Respondents’ responses obtained during 2013 interview process

Various approaches may be used to compare the latent factors obtained from the two data sets (2013 and 2010). However, for comparative purposes it is necessary to ensure that the data sets include the same attributes and to this end Short check-in was excluded from the 2013 data. An exploratory factor analysis was completed on both sets of data and the results are shown in Tables 5.9 and 5.10.

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Table 5.9: Factor structure (rotated) – 2010 data

Component 1 2 3 4 Price of ticket .180 −.064 −.029 .754 Price of parking .093 .075 .169 .819 Cost of transport to airport −.020 .318 .147 .776 Destinations serviced .574 .454 .044 .108 On time dep_arr .767 .104 .296 .024 Frequency of service .825 .167 .248 .108 Seat availability .753 .202 .221 .145 Departure times .828 .100 .218 .099 Facilities at airport .510 .390 .372 −.010 Baggage collection .276 .571 .342 .170 Time to/from airport .158 .844 .098 .007 Ease of access .184 .830 .118 .042 Ease of parking .030 .664 352 .214 Ease of check-in .273 .760 .357 .075 Airline loyalty .269 .096 .682 .055 Airport safety .358 .373 .757 .016 Parking security .222 .231 .740 .227 Baggage security .334 .427 .676 .115 Extraction method: Principle Component Analysis Rotation converged in 6 iterations Source: Heyns and Carstens (2011)

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Table 5.10: Factor structure (rotated) – 2013 data

Component 1 2 3 4 Price of ticket .350 −.075 −.404 .544 Price of parking .111 .213 .127 .795 Cost of getting to/from .032 .236 .341 .676 Destinations .640 .129 .172 .241 On time .764 .225 .189 .045 Frequency of service .728 .295 .286 .056 Seat availability .760 .192 .137 .139 Departure times .733 .215 .109 .115 Facilities .534 .372 .112 .035 Baggage collection time .558 .340 .287 −.031 Time to get to airport .253 .092 .829 .103 Ease of getting to airport .228 .055 .826 .032 Ease of parking .178 .368 .570 .261 Ease of check-in .414 .256 .609 .124 Airline brand .283 .639 .013 .088 Airport safety .284 .849 .154 .128 Parking security .198 .796 .259 .245 Baggage security .339 .807 .159 .115 Extraction method: Principle Component Analysis Rotation method: Varimax Source: Respondents’ responses obtained during 2013 interview process

One approach to compare the factors of the different data sets is to calculate the correlations between the factors of the two data sets. The factor correlation matrix is shown in Table 5.11.

Table 5.11: Factor correlation matrix (2010 and 2013)

F1 2010 F1 2013 F2 2010 F2 2013 F3 2010 F3 2013 F4 2010 F4 2013 F1 2010 1 F1 2013 0.938604 1 F2 2010 −0.3673068 −0.2511564 1 F2 2013 −0.0646374 −0.2184239 −0.0686797 1 F3 2010 −0.0429046 −0.1748216 −0.0503197 0.9732955 1 F3 2013 −0.2726172 −0.2537802 0.8698234 −0.1154944 −0.0882472 1 F4 2010 −0.4933592 −0.4811646 −0.4235782 −0.2972016 −0.3806004 −0.3704852 1 F4 2013 −0.5076041 −0.5552107 −0.3730986 −0.2325397 −0.3327631 −0.2937927 0.9457849 1 Source: Respondents’ responses obtained during 2013 interview process

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The information in Table 5.11 indicates high levels of correlation between the following factors of the two data sets:  Factor 1 2010 & Factor 1 2013 (airline efficiency, facilities) 0.94  Factor 2 2010 & Factor 3 2013 (access to airport) 0.87  Factor 3 2010 & Factor 2 2013 (brand, safety and security) 0.97  Factor 4 2010 & Factor 4 2013 (cost) 0.95

Comparing the latent factors from the 2010 data set with that of 2013 indicated similarity between the factors. Another approach to compare the factors of the two data sets and to confirm the findings of the first comparison is known as Tucker’s congruence coefficient (Lorenzo-Seva & ten Berge, 2006). The congruence coefficient can be interpreted as a measure of proportionality and is calculated as follows:

∑ 푥 푦 푖 푖 2 2 √∑ 푥푖 푦푖

where xi and yi are the loadings of the attribute i of factor x and y respectively (i = 1, …, n) (Lorenzo-Seva et al., 2006). The calculated congruence coefficients are shown below:  Factor 1 2010 & Factor 1 2013 (airline efficiency, facilities) 0.98  Factor 2 2010 & Factor 3 2013 (access to airport) 0.93  Factor 3 2010 & Factor 2 2013 (brand, safety and security) 0.99  Factor 4 2010 & Factor 4 2013 (cost) 0.97

Lorenzo-Seva et al. (2006) suggested that congruence coefficients ranging between 0.85 and 0.94 can be considered as factors with ‘fair similarity’ whereas congruence coefficients with a value of 0.95 and higher can be considered as identical. Therefore the factors are considered to be equal.

From the above it is evident that airline efficiency and facilities, brand, safety and security as well as cost are considered identical (congruence coefficient of 0.95 and

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higher) for both studies, while access to the airport has a reasonable similarity (congruence coefficient of 0.93).

Based on both approaches it can be concluded that there were no differences in the way that passengers evaluated the attributes in 2010 compared to 2013. It is evident that the respondents in both surveys considered the same attributes to be influential in their choice of airport.

Thus, airline efficiency and facilities, access to airport, safety and security as well as cost are the most important attributes passengers will consider when deciding to fly from Lanseria International Airport. Even after the entry of an additional LCC, the attributes respondents regarded as important, and the way in which they evaluated the attributes, in their airport choice decision remained unchanged.

5.4 CONCLUSION

In this chapter the findings of a survey conducted at Lanseria International Airport in 2013 were discussed. These findings were compared to the findings of a similar survey conducted there in 2010.

The objective of this study was to determine the reasons passengers prefer to fly from Lanseria International Airport and, in this regard, three hypotheses were formulated:  Hypothesis 1: A relationship exists between the geographic location of the airport and the residential location of the passengers. Therefore people living in close proximity to Lanseria International Airport will prefer to make use of the airport.  Hypothesis 2: A relationship exists between the cost of using an airport and the choice of a specific airport. Therefore cost is identified as an important factor to consider when choosing Lanseria International Airport.  Hypothesis 3: A relationship exists between the number of destinations, the flight departure and arrival times and efficient airport services, and the frequency of use of the same airport. Therefore, if Lanseria International

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Airport serves an acceptable number of destinations, flights depart and arrive on time and services at the airport are efficient, passengers will favour and repeatedly use this airport.

The survey conducted in 2013 found that respondents who resided in Gauteng – and more specifically the northern, western and central parts of the province – chose to use Lanseria International Airport because it is in close proximity to them. When a comparison was drawn with the 2010 study it was established that the respondents residing in the northern, western and central regions of Gauteng preferred to use Lanseria International Airport because of the fact that it is conveniently situated to them.

Based on this finding, hypothesis 1: A relationship exists between the geographic location of the airport and the residential location of the passengers, can be accepted to be true because people living in close proximity to Lanseria International Airport prefer to make use of the airport.

Subsequently the study intended to determine the airport choice factors passengers would consider when deciding to use Lanseria International Airport. This study identified the following important factors or attributes passengers considered important when selecting an airport:  Cost  Convenience  Customer experience

When compared to the 2010 study, it became evident that these three attributes were significant to respondents in both 2010 and 2013.

Based on these findings, hypothesis 2: A relationship exists between the cost of using an airport and the choice of a specific airport, can be accepted to be true as cost was identified as an important factor to consider when choosing Lanseria International Airport.

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Hypothesis 3: A relationship exists between the number of destinations, the flight departure and arrival times and efficient airport services, and the frequency of use of the same airport can be accepted to be true because Lanseria International Airport serves an acceptable number of destinations, flights depart and arrive on time and services at the airport are efficient; therefore, passengers will favour and repeatedly use this airport.

Finally a factor analysis was conducted and the following latent factors were identified as the prominent factors respondents would consider in choosing to fly from Lanseria International Airport:  Airline efficiency and facilities  Brand, safety and security  Access to the airport  Cost

The abovementioned latent factors identified in the factor analysis were then compared to the latent factors resulting from the 2010 factor analysis. It was established that the factor analysis conducted by Heyns and Carstens (2011) on the 2010 data resulted in identifying the same latent factors. Based on the comparison of the 2010 and 2013 factor analysis, it was determined that even after the entry of a second LCC, respondents still considered the same attributes to be important in their airport choice decision.

The concluding chapter of the study will draw final conclusions and make recommendations.

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CHAPTER 6: CONCLUSION AND RECOMMENDATIONS

6.1 INTRODUCTION

In this study research was conducted to determine why Lanseria International Airport is a preferred airport for passengers. The research focused on airport choice factors, and a comparative analysis with a passenger choice study undertaken by the Institute of Transport and Logistics Studies (ITLS) (Africa) in 2010. This study, in addition, focused on a factor analysis and a comparative investigation of a factor analysis undertaken by Heyns and Carstens in 2011.

It was confirmed that passengers prefer to fly from Lanseria International Airport by considering certain factors. When the first study was conducted in 2010, only Kulula operated domestic flights from Lanseria. Since the previous study was conducted, a second low-cost carrier, Mango Airlines, started operating from Lanseria, and it created a motivation for this study to determine whether the reasons passengers choose Lanseria International Airport changed. The objectives of the study were as follows:

The primary objective of the study was ‘to determine the reasons why passengers prefer to fly to and from Lanseria International Airport.’ This objective was met in Chapter 5 of the study.

The secondary objectives of the study were:  To determine the passenger airport choice factors relating to Lanseria International Airport since the introduction of a second airline flying from this airport to the same destinations as the first airline  To compare the findings on attainment of the first objective with the results of the 2010 (ITLS, 2010) and Heyns and Carstens (2011) survey conducted when only one airline, Kulula, operated domestic flights from Lanseria International Airport These objectives were met in Chapter 5 of the study.

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Three hypotheses were formulated:  Hypothesis 1: A relationship exists between the geographic location of the airport and the residential location of the passengers. Therefore people living in close proximity to Lanseria International Airport will prefer to make use of the airport.  Hypothesis 2: A relationship exists between the cost of using an airport and the choice of a specific airport. Therefore cost is an important factor to consider when choosing Lanseria International Airport.  Hypothesis 3: A relationship exists between the number of destinations, the flight departure and arrival times and efficient airport services, and the frequency of use of the same airport. Therefore if Lanseria International Airport serves an acceptable number of destinations, flights depart and arrive on time and services at the airport are efficient, passengers will favour and repeatedly use this airport.

In order to meet the objectives of the study, the methodology consisted of a literature review as well as a survey conducted at Lanseria International Airport.

The ensuing section reviews the key findings of each chapter.

6.2 AN OVERVIEW OF THE AIRLINE INDUSTRY

Chapter 2 discussed the historical developments such as regulation, liberalisation, deregulation and privatisation in aviation in order to highlight specific trends in aviation. One specific trend that was identified is the emergence of LCCs especially as a result of deregulation of the airline industry.

Chapter 2 further identified that two types of airlines operate in the airline industry, namely full-service carriers (FSCs) and low-cost carriers (LCCs). The FSCs and LCCs operational in the South African domestic air transport market were also identified. The development of LCCs was discussed in detail and it was highlighted that these airlines have benefited the following in various ways:

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 Consumers – After deregulation there was an increase in the number of airlines in the market which allows passengers the freedom to choose among airlines. Increase competition in the airline market also ensured a decrease in airfares.  Growth of secondary airports – Deregulation and the subsequent emergence of LCCs led to the emergence or increased usage of secondary airports. This is due to the fact that LCCs prefer to operate from these airports because of quicker turnaround times and lower airport charges.  Regional development – LCCs serving a secondary airport can stimulate tourism and business development in the surrounding region.  Environment – LCCs contribute to lowering negative environmental impacts due to their more efficient seat configuration, their newer aircraft having decreased noise levels and better fuel consumption, and direct services.

The development of LCCs in the US and Europe was also highlighted with specific reference to LCCs that are regarded as pioneers in this arena, such as Southwest Airlines (US), Ryanair (Europe) and EasyJet (Europe).

Chapter 2 concluded with a portrayal of the LCCs operating in the South African domestic air transport industry, which included Kulula and Mango Airlines.

6.3 SECONDARY AIRPORTS AND LOW-COST CARRIERS

In Chapter 3 of this study an overview of the role airports play in local and regional environments was provided including a discussion on the changing airport environment. A common phenomenon in the US and Europe was identified, which is that major city airports and secondary airports are competing with one another for LCC traffic. It became evident that the product offerings of a secondary airport such as basic infrastructure, lower congestion and lower airport charges appeal greatly to LCCs.

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Chapter 3 investigated secondary airports by identifying the reasons for their emergence with specific reference to the US and Europe scenarios. It was established that secondary airports came into being for various reasons including:  Infrastructure: In order to meet the growing demand for air travel, multi-airport systems have been developed globally. Multi-airport systems are established when secondary airports emerge by utilising an already-existing airport that previously had another purpose, for example military airports. The focus of this study was on multi-airport systems that comprise one primary airport and one secondary airport.  Capacity at primary airports: An increased demand for air travel has resulted in increased congestion at primary airports as these airports are operating at maximum capacity which contributes to higher airline operating costs and longer waiting periods for passengers.  Low-cost carriers: The start-up of an LCC in most cases (in the US and Europe) coincided with the emergence of a secondary airport. Southwest Airlines was found to be successful in facilitating the development of secondary airports in the US while Ryanair was the biggest player in developing secondary airports in Europe.

An analysis of the business model of LCCs was provided in Chapter 3 and identified that keeping costs at a minimum is the main operating strategy of an LCC. For this reason LCCs opt to operate from secondary airports because it increases efficiency.

Chapter 3 examined the air passenger market with specific reference to airport choice and the factors considered by passengers when selecting an airport. Some prominent airport choice factors identified from the various literature sources included:  Airport access time  Flight frequencies  Passenger experience  Airfares  Airport facilities

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An overview of the important airports in South Africa, including airports owned and operated by ACSA, including O R Tambo International Airport, Cape Town International Airport and King Shaka International Airport in Durban, municipal as well as privately owned airports such as Lanseria International Airport was provided in Chapter 3. From this discussion it emerged that Lanseria International Airport has experienced tremendous growth since two LCCs started operating from there. Itcurrently handles around 150 000 passengers per month making it a significant alternative to ORTIA.

Chapter 3 concluded with a description of the South African domestic air passenger market and attention was given to the busiest domestic airline network in Africa, the so called ‘Golden Triangle’, servicing Johannesburg, Cape Town and Durban.

6.4 RESEARCH METHODOLOGY

Chapter 4 of this study described the research methodology used to collect data from which conclusions was drawn. The research philosophies described included positivism, interpretivism and pragmatism. Positivism was selected as the research philosophy for this study as it allowed for effective and efficient data collection.

Different research approaches were also highlighted in Chapter 4. Deductive reasoning was selected above induction and abduction as the preferred research approach for this study. The reason for this is that it allowed testing of existing theory in order to determine if the theory relates to a specific situation. In this study hypotheses were developed to test theory relating to the reasons passengers prefer to fly from Lanseria International Airport.

Chapter 4 further indicated that this was an exploratory study and the research design was selected as a mono method research using a survey as the quantitative data collection method. Survey research was chosen as it is well suited to a deductive research approach and has the following advantages:  Surveys are a fast, low-cost and effective way of judging information about a population.

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 Surveys are flexible.  Surveys provide valuable information.

A face-to-face survey was selected for this study, which was conducted at Lanseria International Airport by trained interviewees from an independent research company.

Chapter 4 identified passengers flying on domestic flights to and from Lanseria International Airport as the unit of analysis for this study. Because it is not possible to survey an entire population, a sampling frame of passengers departing either on Kulula or Mango Airlines from Lanseria International Airport was identified by means of stratified random sampling in order to be representative of the weekly departure schedules of both Kulula and Mango Airlines. Primary data was collected by means of interviewer-completed questionnaires, specifically structured interviews.

The final stage of research is data analysis as discussed in Chapter 4. Factor analysis was selected as the statistical method to analyse the data collected and a statistician from STATCON at the University of Johannesburg was consulted in this regard.

6.5 SURVEY RESULTS AND FINDINGS

Chapter 5 provided an in-depth discussion of and comparison between the surveys conducted at Lanseria International Airport in 2010 and 2013 respectively.

As stated in Chapter 5, the purpose of the study conducted in 2010 was to identify fundamental factors that influenced passenger airport choice decisions at Lanseria International Airport in Gauteng. At that time only one low-cost airline, Kulula, operated flights to both Cape Town and Durban. The Institute of Transport and Logistics Studies (ITLS) (Africa) was contracted to obtain the data, and Heyns and Carstens (2011) analysed the data statistically by way of a factor analysis.

Chapter 5 further described that the purpose of the 2013 study was to identify essential factors that influence passenger airport choice decisions at Lanseria

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International Airport after the entry of a second low-cost carrier. Data was obtained through a paper-based survey of departing passengers at the airport. In both studies respondents were required to rate the influence of attributes on their decision to use Lanseria International Airport. The questionnaires comprised attributes relating to the passengers, airline offerings and the airport, such as:  Demographics  Price  Service  Convenience

Some of the interesting findings from Chapter 5 will be highlighted here.

In both surveys it was established that most of the respondents resided in Gauteng. It became evident that when airports in a metropolitan area are close to one another, passengers consider access time when selecting an airport. This finding was confirmed by plotting the residential (suburb) postal codes on a map of Gauteng. The number of respondents per suburb was presented as a percentage of the total number of respondents resident in Gauteng.

This exercise was done for both the 2010 and 2013 studies and in both instances it emerged that most of the Gauteng respondents resided in the northern, western and central regions of Gauteng thereby confirming the literature findings that passengers prefer to use airports situated close to their homes.

Respondents in both studies were requested to rate the influence of the following attributes on their decision to use the airport:

 Total cost of using the airport (price attribute) Passengers seemed to be more concerned about cost of transport to the airport in 2013 than in 2010. This could be attributed to significant fuel price increases in 2012 that point toward people being more conscious about spending money.

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The price of parking did not have any significant influence on passengers’ decision to use Lanseria International Airport in either 2010 or 2013.

The price of air ticket was more important to respondents in 2013 than in 2010. The reason for this lies in the entry of a second LCC at the airport. Respondents now had a choice between two airlines, Kulula or Mango Airlines, and may be more price sensitive than before. This finding is further supported by the research of Luke (2015) that found that passengers choosing to fly with Mango Airlines were more sensitive with regard to prices. The demand for Mango flights was found to be driven by price, which makes it an ideal selection to lower income passengers as well as younger individuals, such as students.

It was concluded that cost is an important factor passengers consider when choosing Lanseria International Airport. Cost included cost of transport to airport, price of ticket and price of parking.

 Convenience of getting to the airport (convenience attribute) In both 2010 and 2013 convenience attributes had a noteworthy influence on respondents’ decision to use Lanseria International Airport. It was concluded that convenience attributes such as ease of accessing the airport, ease of parking, ease of check-in and time taken to travel to and from the airport were identified as important attributes in airport choice decisions.

 Customer experience (service attribute related to airline and airport) Customer experience related to an airline is an essential factor in airport choice decisions. In both 2010 and 2013 destinations serviced, on-time departure and arrival, service frequency, availability of seats and departure times were important considerations for respondents.

It was established that when selecting an airport passengers consider customer service related to an airline as important. As Lanseria International Airport serves an acceptable number of destinations and services at the airport are efficient, passengers will therefore favour and repeatedly use this airport.

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Based on these findings all three hypotheses created in this study were found to be true. It was found that all three the parameters influence the decision of selecting an airport.

The objective of this study was to determine if airport choice factors passenger consider have changed after the entry of a second LCC and if passengers viewed the factors differently. In this regard a factor analysis was conducted in order to understand the structure of the attributes. A factor analysis reduced the number of attributes to a smaller number of factors that were easier to compare. The following latent factors were identified:  Airline efficiency and facilities (factor 1)  Brand, safety and security (factor 2)  Access to the airport (factor 3)  Cost (factor 4)

In 2010 a factor analysis was also conducted, and information obtained from this factor analysis was similar to the latent factors identified in the 2013 factor analysis. In order to compare the 2010 data set with the 2013 data set, the correlations between the factors of the data sets were calculated and produced. Comparing the latent factors from the 2010 data set with that of 2013 indicated similarity between the factors.

Tucker’s congruence coefficient was calculated as a confirmatory method to compare the 2010 data set with the 2013 data set. It was concluded that airline efficiency and facilities, brand, safety and security as well as cost were considered to be the same for both studies, while access to airport had a reasonable similarity.

It was further concluded that there were no differences in the way that passengers evaluated the attributes in 2010 compared to 2013. In both surveys, respondents evaluated the same attributes as important in their choice of airport. Therefore, airline efficiency and facilities, access to airport, safety and security as well as cost are the main attributes passengers will consider when deciding to fly from Lanseria International Airport. Even after the entry of a second LCC, the attributes

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respondents regarded as important and the way in which they evaluated the attributes in their airport choice decision remained unchanged.

6.6 RECOMMENDATIONS AND AREAS FOR FURTHER STUDY

The results of this study provided an insight in the attributes passengers consider when selecting an airport.

It was found that passengers choose to fly from Lanseria International Airport after considering certain attributes. Through the surveys conducted it was found that a passenger’s decision to use the airport is influenced by the location of the airport and the time it takes to travel to and from the airport, the cost involved with using the airport and service received from the airline.

The airport choice factors passengers in Gauteng consider have an impact on the airport’s as well as airlines’ ability to deliver the required service at a suitable cost. The research indicated that a passenger’s airport choice decision is influenced mostly by four underlying factors:  Airline efficiency and facilities  Access to the airport  Brand, safety and security  Cost

It is recommended that the owners of both Lanseria International Airport as well as Wonderboom familiarise themselves with the findings of this research project in order to assist them in understanding the factors that are important for potential future passengers, and in which areas they need to improve and invest to make their respective airports preferred airports.

Since the study was undertaken in 2013, SA Airlink began operating a scheduled passenger service from Wonderboom Airport in Pretoria to Cape Town. It is therefore recommended that the study be repeated in order to determine whether passengers from the northern region of Gauteng would prefer to travel from

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Wonderboom as opposed to Lanseria International Airport and what the impact would most likely be on Lanseria.

As the study was also undertaken prior to the implementation of the e-tolling system on the main freeways in Gauteng, it is recommended that the study be repeated to gain insight into the effect this might have had on passengers’ airport choice decision.

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ANNEXURE A – PASSENGER CHOICE QUESTIONNAIRE (2010)

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CUSTOMER QUESTIONNAIRE AT LANSERIA AIRPORT

Please answer the following questions by crossing (x) the relevant block provided and fill in your answer where necessary. The figures in the blocks are for office use only.

Gender Male Female

Purpose of travel Business VFR Sport Leisure

Destination Cape Town Durban Port Elizabeth

Suburb / Town / Province

1. To what extent have the following PRICE ATTRIBUTES influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent Price of air ticket 1 2 3 4 Price of parking at airport 1 2 3 4 Costs of getting to airport 1 2 3 4

2. To what extent have the following SERVICE ATTRIBUTES influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent Destinations serviced by the airport 1 2 3 4

On-time arrival/departure 1 2 3 4

Frequency of service 1 2 3 4

Seat availability 1 2 3 4 Departure times 1 2 3 4 Facilities at airport 1 2 3 4 Time taken to collect baggage 1 2 3 4

3. To what extent have the following CONVENIENCE ATTRIBUTES influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent Time to get to/from the airport 1 2 3 4

Ease of parking at airport 1 2 3 4 Ease of check-in procedures 1 2 3 4

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Ease of getting to the airport (i.e. traffic congestion, state of roads) 1 2 3 4

4. To what extent have the following OTHER ATTRIBUTES influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent Airline brand reputation / loyalty 1 2 3 4 Airport safety 1 2 3 4 Parking security 1 2 3 4 Baggage security 1 2 3 4

If any other Attributes – please specify:

1 2 3 4

THANK YOU FOR YOUR PARTICIPATION! WE VALUE YOUR TIME!

163

ANNEXURE B – PASSENGER CHOICE QUESTIONNAIRE (2013)

164

PASSENGER QUESTIONNAIRE AT LANSERIA AIRPORT

Please answer the following questions by crossing (x) the relevant block provided and fill in your answer where necessary. The figures in the blocks are for office use only.

Gender Male Female Age Group 16–24 years 25–34 years 35–44 years 45–54 years > 55 years Purpose of travel Business VFR Sport Leisure Airline Kulula Mango Destination Cape Town Durban Suburb / Town / Province

2. How did you get to LANSERIA AIRPORT?

Self-drive Drop-off Taxi Other

3. To what extent has the following MAIN ATTRIBUTE CATEGORIES influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent Total COST of using the airport (incl. access cost, parking, ticket) 1 2 3 4 CONVENIENCE of getting to airport 1 2 3 4 CUSTOMER EXPERIENCE at airport 1 2 3 4

4. To what extent have the following PRICE ATTRIBUTES influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent Price of air ticket 1 2 3 4 Price of parking at airport 1 2 3 4 Costs of getting to airport 1 2 3 4

5. To what extent have the following SERVICE ATTRIBUTES influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent Destinations serviced by the airport 1 2 3 4 On-time arrival/departure 1 2 3 4 Frequency of service 1 2 3 4 Seat availability 1 2 3 4 Departure times 1 2 3 4 Facilities at airport 1 2 3 4 Time taken to collect baggage 1 2 3 4

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6. To what extent have the following CONVENIENCE ATTRIBUTES influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent Time to get to/from the airport 1 2 3 4 Ease of parking at airport 1 2 3 4 Ease of check-in procedures 1 2 3 4 Ease of getting to the airport (i.e. traffic congestion, state of roads) 1 2 3 4

7. To what extent have the following OTHER ATTRIBUTES influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent Airline brand reputation / loyalty 1 2 3 4 Airport safety 1 2 3 4 Parking security 1 2 3 4 Baggage security 1 2 3 4

8. Are there any OTHER ATTRIBUTES which influenced your decision to select LANSERIA AIRPORT? To no To a To a To a Factors extent small moderate large extent extent extent 1 2 3 4 1 2 3 4 1 2 3 4

9. What OTHER airport facilities / services would you prefer at LANSERIA AIRPORT?

10. Would you prefer to connect to other destinations from LANSERIA AIRPORT?

Yes No Unsure

If answered YES, which other destinations?

11. Would you welcome a multi-level parking facility?

Yes No Unsure

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12. Would you agree that R120 per day (current daily cost is R80) would be a reasonable cost for a safe, under covered and multi-level parking facility?

Yes No Unsure

13. For your purpose of travel, why did you not fly from O R TAMBO INTERNATIONAL AIRPORT?

THANK YOU FOR YOUR PARTICIPATION – WE VALUE YOUR TIME!

167