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How to cite this thesis

Surname, Initial(s). (2012). Title of the thesis or dissertation (Doctoral Thesis / Master’s Dissertation). Johannesburg: University of Johannesburg. Available from: http://hdl.handle.net/102000/0002 (Accessed: 22 August 2017). ASSESSING THE IMPACT OF LEAN MANUFACTURING IN THE SOUTH AFRICAN AIRLINE INDUSTRY

A Thesis Submitted in Partial Fulfilment of the Degree of

MASTERS OF TECHNOLOGY In the Department of Quality and Operations Management At the

FACULTY OF ENGINEERING AND THE BUILT ENVIRONMENT

Of the

UNIVERSITY OF JOHANNESBURG

LINDA MALIFETE 216001282 FEBRUARY 2019

Supervisor: Dr Ndala Yves Mulongo

Co-supervisor: Prof Pule Kholopane

PREFACE

The work presented in this master’s thesis was conducted at the Department of Quality and Operations Management within the faculty of Engineering and Built Environment of the University of Johannesburg, under the supervision of Mr Ndala Yves Mulongo and Prof Pule Kholopane. One peer-reviewed conference proceeding was generated out of the content of this master’s thesis.

1. Malifete, L; Ndala Yves Mulongo & Pule Kholopane (2018). A Theoretical analysis of Lean implementation in Airline industry. The 3rd North American International Conference on Industrial Engineering and Operations Management, United States, Washington DC.

ACKNOWLEDGEMENTS

I want to take this opportunity to thank the Lord almighty for his endless love for me, for giving me life and for his guidance throughout this project. Heavenly Father, Creator of all, I humble myself before you with a grateful heart. Without you father, I would not have made it. You are worthy of all my praise.

To my wonderful, warm-hearted and dedicated supervisor: Dr. Ndala Mulongo, you are one in a million. Thank you so much for your amazing support, encouragement, dedication and guidance during this project. I truly appreciate your patience, your time and your willingness to help. It was such a great honour and privilege working with you; may you continue to be an awesome supervisor to others.

My heartfelt appreciation goes to Dr Lwazi Ndlwana. Thank you so much for your valuable and constructive suggestions throughout this project. The time you spent helping me and the support you gave me to ensure that I complete this research, I will forever be grateful.

To my parents, Mr Nceba Malifethe and Mrs Nothandekile Grace Malifethe for teaching me the importance of education and giving me the right platform, I thank you.

I further wish to thank my friends, family, colleagues and everyone who participated in this survey especially to Lwazi Phambuka, Ayanda Mabusela, Nosipho Mjelo, Rachel Masilela and Khayakazi Vumazonke for going an extra mile for me. I thank you so much for your continuous support.

Lastly, I wish to thank my two beautiful kids: Phiko Oyama Malifete and Alunamida Luhlelo Malifete. This is for us; I did this for you. Thank you for being a reason enough to inspire me to go this far. Together we made it.

DECLARATION: MASTER’S AND DOCTORAL STUDENTS

TO WHOM IT MAY CONCERN

This serves to confirm that I, Linda Malifete

Student number: 216001282

Enrolled for: Maters in Operations Management

Faculty: Engineering and Built Environment

I hereby declare that the thesis submitted for the Masters of Technology to the University of Johannesburg, apart from the help recognized, is my own work and has not previously been submitted to another university or institution of higher education for a degree.

Signed at Bunting Campus on 18 of February 2019

Signature: Print name: Linda Malifete

4 ABSTRACT

Over the last decade, the concept of Lean manufacturing has brought in an innovative management method for various business organisations, exclusively multinational firms that were previously organised and administered by means of conventional push systems. Enhancement outcomes could be dramatic with regard to quality, cycle times, and consumer’s responsiveness that is more than a set of apparatuses and techniques and have been largely implemented by various manufacturing firms. Although, lean manufacturing has gained so much attention within the manufacturing sector, however, literature presented in the present study clearly shows that there is a dearth of studies concerning lean implementation within the airline service industry. To date, over the last decades, the airline sector has been growing and expanding at a fast speed, especially in the African continent. Hence, decision makers within this industry have been facing various challenges associated with creating a balance between long-run strategies with short-term solutions. One possible explanation to this is because consumer’s satisfaction is becoming more and more considerably imperative for airline operations and consequently service quality is gaining utmost significance within this industry. Hence, this study aimed at filling this gap by assessing the impact of lean manufacturing in the airline industry, using South Africa as case study.

To achieve the overall aim of this study, a two-fold approach was adopted in the present study; firstly, the study critically reviewed and assessed a set of scientific research works that were previously conducted on lean phenomena within different sectors, during the past twenty years. Secondly, the present study used a quantitative research methodology in order to explore the impact of lean manufacturing in the South Airline industry. To this end, the research findings presented in this study clearly demonstrated that in terms of current literature there is a lack of studies on lean manufacturing implementation in airline industry, especially in the context of South Africa. Secondly, the results obtained from quantitative research questionnaire demonstrated that the factors that negatively affect the implementation of lean were lack of commitment by senior staff; staff resistance; lack of training; discomfort with change; poor communication regarding change and culture of no change.

To sum up, it is expected that the study will significantly assist decision makers within this industry in order to improve the sector business performance and to alleviate barriers efficiently before employing lean manufacturing.

Table of Contents PREFACE ...... 2 ACKNOWLEDGEMENTS ...... 3 ABSTRACT ...... 5 Table of Contents ...... 6 LIST OF FIGURES ...... 11 LIST OF TABLES ...... 12 CHAPTER 1: INTRODUCTION ...... 15 1.1 Background ...... 15 1.1.1 South African case study ...... 16 1.2 Research Problem ...... 17 1.3 Research Goal ...... 18 1.4 Research Objectives ...... 18 1.5 Research Questions ...... 18 1.6 Rationale and Significance of the study ...... 18 1.7 Research Methodology ...... 19 1.8 Overview of the study ...... 20 CHAPTER 2: THEORETICAL FRAMEWORK ...... 22 2.1 Dissemination of lean literature ...... 24 2.2 Chapter Summary ...... 36 2.3 Lesson Learnt ...... 36 CHAPTER 3: LEAN ASSESSMENT ...... 38 3.1 Introduction ...... 38 3.2 Overview of business improvement methodologies ...... 38 3.3 Lean Theory ...... 38 3.3.1 Start of mass production ...... 39 3.3.1.1 Ford’s moving assembly line ...... 39 3.3.1.2 Toyota ...... 40 3.4 Lean Principles ...... 40 3.5 Lean Tools and Techniques ...... 42 3.6 Main factors that are critical and fundamental for the implementation of lean manufacturing ...... 43

3.7 Six-Sigma ...... 44 3.7.1 Basic principles and concepts ...... 45 3.7.2 Lean and Six-Sigma ...... 46 3.8 Total Quality Management ...... 47 3.9 Business Process Reengineering (BPR) ...... 48 3.10 Service Definition ...... 48 3.11 Service Quality ...... 49 3.10 Chapter Summary ...... 52 3.9 Lesson Learnt ...... 52 CHAPTER 4: INTERNATIONAL AIRLINE INDUSTRY ...... 54 4.1 Introduction ...... 54 4.2 Overview of the airline industry ...... 54 4.2.1 Airline industry structure ...... 54 4.2.2 The importance of airline industry ...... 57 4.2.3 The impact of airline industry on global economic growth ...... 58 4.2.4 Air traffic trends ...... 58 4.3 UNITED KINGDOM (UK) CASE ...... 59 4.3.1. Historical background of the UK airline industry ...... 59 4.3.2 The United Kingdom economy ...... 60 4.3.3 Factors affecting the UK airline market ...... 62 4.3.4 Aims, objectives and strategy of UK aviation industry ...... 63 4.3.5 The importance of airline in UK ...... 64 4.3.6 Competitiveness of UK airline industry ...... 64 4.4 UNITED ARAB EMIRATES (UAE) CASE ...... 65 4.4.1 Historical background of the United Arab Emirates Airline industry ...... 66 4.4.2 UAE’s economy ...... 67 4.4.3 Competitiveness of the UAE airline industry ...... 69 4.4.3.1 UAE airline competitiveness in 2017 ...... 70 4.5 Chapter Summary ...... 70 4.6 Lesson learnt ...... 71 CHAPTER 5: AIRLINE INDUSTRY ON AFRICAN SCALE ...... 72 5.1 Introduction ...... 72

5.2 Overview of the African Airline industry ...... 72 5.2.1 The importance of airline industry in Africa ...... 72 5.3 THE KENYA CASE ...... 73 5.3.1 Historical background of Kenya’s airline industry economy ...... 73 5.3.2 Kenyan economy ...... 74 5.3.3 Economic performance by sector ...... 75 5.3.4 Kenya’s airline and market ...... 78 5.3.4.1 Market positioning ...... 78 5.3.5 Factors affecting Kenyan airline market ...... 79 5.4 THE NIGERIAN CASE ...... 80 5.4.1 Historical background of the Nigerian airline industry ...... 81 5.4.2 Nigeria’s economy ...... 82 5.4.3 Nigerian airline industry and market ...... 85 5.4.3.1 Traffic rights and route entry regulation ...... 85 5.4.4 Economic performance of the Nigerian airline industry ...... 86 5.4.5 Competitiveness of Nigerian airline industry ...... 86 5.4.6 Factors affecting the Nigerian airline market ...... 87 5.5 Chapter Summary ...... 88 5.6 Lesson Learnt ...... 89 CHAPTER 6: SOUTH AFRICAN AIRLINE INDUSTRY ...... 90 6.1 Introduction ...... 90 6.2 Overview of the South African airline industry ...... 90 6.2.1 Historical background of the South African airline industry ...... 91 6.2.2 South African airline industry strategic policy objectives ...... 95 6.2.2.1 Flight Tariff Regulation ...... 96 6.2.3 The importance of airline industry in South Africa ...... Error! Bookmark not defined. 6.2.4 The impact of airline industry on the South African economic growth ...... 96 6.2.5 The South African economy ...... 97 6.2.6 Major trends in the South African airline industry ...... 99 6.2.7 Sustainability performance measurement in the South African airline ...... 99 6.3 Chapter Summary ...... 100 6.4 Lesson Learnt ...... 100

CHAPTER 7: RESEARCH METHODOLOGY ...... 101 7.1 Introduction ...... 101 7.2 Research Design ...... 101 7.3 Quantitative Research Methodology ...... 102 7.4 Research Methods ...... 102 7.4.1 Literature review ...... 102 7.4.2 Questionnaires ...... 103 7.4.3 Distribution and collection of the questionnaires ...... 103 7.4.4 Population and sample of the study ...... 104 7.4.5 Sampling ...... 104 7.4.6 Data collection ...... 104 7.5 Ethical Considerations ...... 105 7.5.1 Confidentiality and Privacy ...... 106 7.6 Reliability ...... 106 7.7 Chapter Conclusion ...... 106 CHAPTER 8: DATA ANALYSIS AND INTERPRETATION ...... 107 8.1 Introduction ...... 107 8.2 Section A: Biographical data analysis for airline customers ...... 107 8.3 Section B: Biographical data analysis for workforce ...... 111 8.4 Section C: Descriptive statistics for lean assessment...... 116 8.4.1 Descriptive statistics for Benefits of lean ...... 116 8.4.2 Descriptive statistics for Lean improvement areas ...... 117 8.4.3 Descriptive statistics for Lean improvement areas in Quality Dimensions ...... 118 8.4.4 Descriptive statistics for lean assessment on employee engagement ...... 120 8.4.5 Descriptive statistics for factors contributing to the implementation of lean ...... 122 8.4.6 Descriptive statistics for Barriers of Lean implementation ...... 122 8.4.7 Descriptive statistics for Customer service quality dimensions ...... 123 8.5 Section D: Exploratory factor analysis for customer service quality dimensions ...... 125 8.6 Section E: Exploratory factor analysis for benefits of lean ...... 130 8.7 section F: Exploratory factor analysis for lean improvement areas ...... 134 8.8 Section G: Exploratory factor analysis for company performance on quality dimensions ... 138

8.9 Section H: Exploratory factor analysis for factors contributing to the implementation of lean ...... 142 8.10 Section I: Exploratory factor analysis for barriers of implementation of lean ...... 145 8.6 Cronbach Test ...... 148 8.7 Normality Test ...... 149 8.8 Chapter Summary ...... 150 CHAPTER 9: DISCUSSION OF FINDINGS ...... 151 9.1 Introduction ...... 151 9.2 Discussion of customer’s biographic profile ...... 151 9.3 Discussion of workforce biographic profile ...... 152 9.4 Service Quality Dimensions ...... 153 9.5 LEAN ...... 153 9.5.1 Research Question 1 ...... 154 9.5.2 Research question 2 ...... 154 9.5.3 Research question 3 ...... 154 9.5.4 Research question 4 ...... 154 CHAPTER 10: CONCLUSION AND RECOMMENDATIONS ...... 155 10.1 Introduction ...... 155 10.2 Conclusion ...... 155 10.2.1 Conclusion on Research Objective one ...... 156 10.2.2 Conclusion on Research Objective two ...... 156 10.2.3 Conclusion on Research Objective three ...... 157 10.2.4 Conclusion on Research Objective four ...... 157 10.2.1 Conclusion on Research Objective five ...... 158 10.3 Recommendations ...... 159 10.4 Recommendation for a future research ...... 160 REFERENCES: ...... 161

LIST OF FIGURES Figure 3.1 Flow diagram depicting service and its quality related to client expectations (Seth et al.,

2005) ...... 49

Figure 3.2 Gronroos’ service quality framework (Ali, 2016)...... 50

Figure 4.1 The connectivity of UK to other cities Oxford economics. (UK country report, 2011). ... 65

Figure 4.2 Relative distribution of employment by sector: (UK country report, 2011)...... 69

Figure 5.1 Obstacles faced by the Nigerian businesses (World Bank Enterprise, 2014)...... 87

Figure 8.1 Customer demographics per age group...... 108

Figure 8.2 Customers/passengers demographic in terms of gender...... 109

Figure 8.3 Customers/passengers grouped according to qualification ...... 110

Figure 8.4 Passengers travelling frequency...... 111

Figure 8.5 Sector or department of workforce...... 112

Figure 8.6 Years of work experience with Lean ...... 113

Figure 8.7 Workforce demographic per title...... 113

Figure 8.8 Workforce demographic per age group...... 114

Figure 8.9 Workforce demographic per gender ...... 115

Figure 8.10 Workforce grouped according to qualification...... 116

Figure 8.11 Scree plot for factor analysis for customer service quality dimensions ...... 129

Figure 8.12: Scree plot for factor analysis for benefits of lean ...... 132

Figure 8.13: Scree plot for factor analysis for IMP ...... 136

Figure 8.14: Scree plot for factor analysis for QD ...... 140

Figure 8.15: Scree plot for factor analysis for R ...... 144

Figure 8.16: Scree plot for factor analysis for F ...... 147

Figure 8.17 Normality graph...... 150

LIST OF TABLES

Table 2.1 Critical Assessment Table ...... 22

Table 3.1 Comparisons between Six-Sigma and Lean (Bicheno, 2004)...... 46

Table 3.2 The SERQUAL dimensions (Ali, 2016)...... 51

Table 4.1 Employment and skills (UK Aviation industry socio-economic report)...... 60

Table 4.2 2016 vs 2017 of UAE’s competitiveness (UK country report, 2011)...... 70

Table 5.1 The top ten 10 performing economic sectors in Kenya for the year 2017...... 75

Table 5.2 Location of the international airport in Nigeria: (Nigerian Civil Aviation Authority, 2011). 80

Table 5.3 GDP by sector (percentage) (CBN, 2010)...... 84

Table 6.1 SA Airline history (Steyn & Mhlanga, 2016)...... 94

Table 8.1 Descriptive statistics for benefits of lean...... 117

Table 8.2 Descriptive statistics for improvement areas...... 118

Table 8.3 Descriptive statistics for quality dimensions...... 119

Table 8.4 Descriptive statistics for Employment engagement...... 120

Table 8.5 Descriptive statistics for factors contributing the implementation of lean...... 122

Table 8.6 Descriptive statistics for Barriers to lean implementation...... 123

Table 8.7 Descriptive statistics for service quality dimensions...... 124

Table 8.8 Definition of identified customer service quality dimensions ...... 126

Table 8.9 Correlation Matrix for quality service dimension ...... 127

Table 8.10 KMO and Bartlett’s Test for customer service quality dimensions ...... 127

Table 8.11 Total variance explained customer service quality dimensions ...... 128

Table 8.12 Pattern matrix for customer service quality dimensions ...... 130

Table 8.13: Definition of identified variables for benefits of lean ...... 131

Table 8.14: Correlation matrix for factor analysis for benefits of lean ...... 131

Table 8.15: KMO and Bartlett’s test for benefits of lean ...... 132

Table 8.16: Total variance explained for benefits of lean ...... 132

Table 8.17: Pattern Matrix for benefits of lean ...... 133

Table 8.18: Definition of identified variables lean improvement areas ...... 134

Table 8.19: Correlation matrix for factor analysis for IMP ...... 135

Table 8.20: KMO and Bartlett’s test for IMP ...... 135

Table 8.21: Total variance explained for IMP ...... 135

Table 8.22: Pattern Matrix for IMP ...... 137

Table 8.23: Definition of identified variables for QD ...... 138

Table 8.24: Correlation matrix for factor analysis for QD ...... 139

Table 8.25: KMO and Bartlett’s test for QD ...... 139

Table 8.26: Total variance explained for QD ...... 139

Table 8.27: Pattern Matrix for QD ...... 141

Table 8.28: Definition of identified variables for factors contributing to the implementation of lean.

...... 143

Table 8.29: Correlation matrix for factor analysis for R ...... Error! Bookmark not defined.

Table 8.30: KMO and Bartlett’s test for R ...... 143

Table 8.31: Total variance explained for R ...... Error! Bookmark not defined.

Table 8.32: Factor matrix for R ...... 144

Table 8.33: Definition of identified variables for lean Barriers (F) ...... 146

Table 8.34: Correlation matrix for factor analysis for F ...... 146

Table 8.35: KMO and Bartlett’s test for F...... 146

Table 8.36: Total variance explained for F ...... 147

Table 8.37: Factor Mattrix for F ...... 148

Table 8.38 Cronbach Table...... 149

Table 8.39 Normality table...... 149

LIST OF ACRONYMS

ACAP: Airport Carbon Accreditation Programme ACI: Airports Council International AEO: African Economic Outlook BA: British Airways CO2: Carbon dioxide DED: Department of Economic Development EU: European Union GDP: Gross Domestic Product IATA: International Air Transport Association ICAO: International Civil Aviation Organisation ITC: Independent Transport Commission NO2: Nitrogen dioxide NOx: Oxides of Nitrogen SA: South Africa SAA: South African Airways SAR&H: SA Railways & Harbors Administration SD: Standard Deviation SME: Small and Medium Enterprises TPM: Toyota Production Management: TQM: Total Quality Management: UK: United Kingdom

CHAPTER 1: INTRODUCTION

Lean manufacturing is a method that is employed to diminish the waste within production process, to form opinion of product or service for end-users. To date, value is any activity that consumers is willing to pay for. Hence, the overall aim of the concept of lean manufacturing is to offer perfect worth to the consumers by means of faultless worth creation process that does not have any waste within itself. Considering this, the research presented in this thesis aims at assessing the impact of lean manufacturing in the South African airline industry. The first chapter is the discussion about the background information related to this research. It starts with research in relation to the contextual background and a further brief supporting aspects with the literature.

1.1 Background The lives of human beings have been improved and how they conduct their businesses by the Air travel. Emmanuel (2015) defines transport as a main element in country’s growth and it plays a vital part in building nations because there is always the need to collect, transfer and dispense merchandises and persons. Air travelling is the well-known model of travel that people use for Leisure, business. It is convenient for people who want to reach their destination fast, Button (2008). This mode of transport has made it easy and possible to travel very long journeys, like crossing countries in a very short time and there is an increased demand for long trips.

With more airlines entering into this sector, the competition began and the travellers started to have a freedom of choosing their preferred airlines, depending on the preference and quality of service (Vonderembse et al., 2006). For the survival of organizations in any service sector, organizations constantly attempt to ascertain means of enhancing the total organisation recitation with the objective of increasing their turn over. The main drive of these development plans is to improve the systems, practices, complete customer experience and the business baseline. Lean approaches are well-known in the manufacturing industry as one of the improvement tools for its ability to improve processes, which is not the case in the service sector. Vermaak (2008) revealed that the success rate of lean thinking in South African manufacturing businesses is very low. However, Toyota has affirmed the effectiveness of Lean implementation beyond doubt.

The main aim of Lean thinking is continual process improvement by removing non-value added steps, and increasing customer value (Vermeulen et al., 2014). The Lean model is a management practice that centred on continuous improvement by reducing process discrepancies and poor work conditions (Vermeulen et al., 2014). Continuous improvement seeks to remove non-value added steps or waste. Taiichi Ohno (2012) initially defined waste in the manufacturing context, with the

15 adoption of Lean in service sectors, the phenomena were gradually adapted to service wastes (Anand et al., 2009). Vermeulen et al. (2014) defines waste as any movement that adds no value to the business processes, to products and services. The main goal of any business is to be lean due to its ability to eliminate unproductive resources with the aim to enhance processes, systems and supply chains (Bosilj-Vuksic et al., 2008).

According to Bosilj-Vuksic et al. (2008), waste contributes to underperformance of the organizations, process capability. As highlighted by (Vermeulen et al., 2014) to reduce waste, organisations must implement a continuous improvement system mainly concentrating on the reduction of waste; and achieving operating cost reductions and the determination to improve the effectiveness of business processes. Most researchers like Suki (2014) and Tolpa (2012) have attempted to analyse and understand the service dimensions linked to airline customers. In the airline industry, customer satisfaction is more critical because they do not offer any tangible items but just a service. For this reason, service quality is vital in this industry because of its ability to attract and retain customers as previously noted by (Chang & Yeh, 2002); Liou & Tzang, 2007). For this reason, this research will touch more on the implementation and sustainability of lean as an improvement model. The discoveries of this research will be of assistance in understanding the industry and lean better.

1.1.1 South African case study South Africa has an immense number of aircrafts that fly between its enormous urban communities, and littler ones, with rates that range from top notch to cut-value economy, Basnet (2015). The airline environment in SA was lightly regulated from 1934 (Mhlanga and Steyn, 2016). During World War2, the domestic airlines were offered by overseas airlines at affordable charges. This stopped when South African Airways (SAA) took over local services and increased all rates by more than 25% (Mhlanga, 2017). The reduction of rates was quickly enforced upon SAA. In 1993, the South African international air policy was liberalised, as also witnessed by (Scholtz, 1998). This resulted to a change in South African air transport environment. Among these changes, the country started experiencing an increase of international carriers flying to and from South Africa and more airlines started competing on the domestic market. These are the changes that were not previously experienced and which in turn, they placed further pressure on the South African airlines to increase the service quality and minimize costs Scholtz (1998). Lean methodology is implemented because it ensures a smooth, quick flow of resources or materials (Vermeulen et al., 2014). This research introduces impacts of implementation and knowledge framework to enable service organisations to implement lean processes towards sustainable performance and excellence.

Airline industry is worldwide known for its constant improvements, all in the pursuit of satisfying their customers. Airline industry has made an immense impact on the countries development, economy, and an impact upon the tourism industry, Basnet (2015). It builds associations and connections amongst cities, countries and markets, and allows foreign investment. This has stimulated governments to develop and advance the necessary infrastructure, like modern airports as means to get attention from tourists. This is the reason a lot of companies are implementing lean as the tool to improve services and company performance. Lean Manufacturing is defined by Shah and Ward (2007) as a model with a purpose to eliminate waste by reducing steps and processes that do not add value. It has been evident from the previous researchers that lean is used by many companies to address issues like time management, to reduce waste and errors. In air travel industry, to offer the best service to travellers is extremely significant for the continued existence of the organisation, effectiveness and continuous growth (Suki 2014). It has always been recommended that providing the best service quality to customers is an essential element to succeed and company survival in today’s competitive business environment (Basnet 2015).

1.2 Research Problem Over the past ten years, the notion of Lean manufacturing has carried in an inventive management method for numerous business associations, exclusively multinational firms that were previously organised and administered by means of conventional push systems. Enhancement outcomes could be dramatic with regard to quality, cycle times, and consumer’s responsiveness that is more than a set of apparatuses and techniques and have been largely implemented by various manufacturing firms. Although, lean manufacturing has gained so much attention within the manufacturing sector, however, literature presented in the present study clearly shows that there is a dearth of studies concerning lean implementation within the airline service industry. To date, over the last ten years, the airline sector has been growing and expanding at a fast speed, especially in the African continent. Hence, decision makers within this industry have been facing various challenges associated with creating a balance between long-run strategies with short-term solutions. One possible explanation to this is because consumer’s satisfaction is becoming more and more considerably imperative for airline operations and consequently service quality has gaining utmost significance within this industry. Hence, this study aimed at filling this gap by assessing the impact of lean manufacturing in the airline industry, using South Africa as case study.

1.3 Research Goal The overall goal of this study was to assess the impact of lean manufacturing in the airline industry, using South Africa as a case study. This will significantly assist decision makers within this industry in order to improve the sector business performance and to alleviate barriers efficiently before employing lean manufacturing.

1.4 Research Objectives To achieve the goal of this research, the following objectives were developed:

➢ RO1: To acknowledge and understand the benefits of implementing lean as an improvement model ➢ RO2: To understand how lean can advance company processes ➢ RO3: To measure and understand factors that can assist and contribute in the implementation of Lean ➢ RO4: To measure and understand the barriers to lean implementation ➢ RO5: To provide Guidelines and recommendation on how to implement and sustain the implementation of lean in the service industry.

1.5 Research Questions To address the research problem of this study, the following research questions emerged:

➢ RQ1: What benefits have been evident from Lean? ➢ RQ2: How can lean support to advance effectiveness of company processes? ➢ RQ3: What are the factors that contribute to the implementation of Lean? ➢ RQ4: What are the barriers of lean implementation? ➢ RQ5: What are the guidelines of successful implementation and sustainability of lean?

1.6 Rationale and Significance of the study To support the service industry performance overall, this study was chosen so that it may provide resolutions to failures of lean implementation and to provide guidelines on how to address them. It will provide organisations with a reasonable comprehension of the advantages of implementing lean as an improvement model as well as the critical factors affecting its implementation. We live in a world whereby customers do not endure substandard service. For the accomplishment of the organisation, it is fundamental for organisations to have enhanced systems and processes in order to have happy clients. Therefore, firms are facing a challenge of having to continuously enhance

18 their processes. An attempt shall be made to obtain all the conceivable strategies and practices that can be applied to remain competitive.

1.7 Research Methodology Research methodology is a technique used by researchers to achieve the research goals and objectives (Myers, 2013). This chapter explains the methods used by the researcher to collect primary data for the study as well as the techniques used to analyse the data and to draw reliable findings from the data collected.

1. Research Design The research design is essential and imperative for implementing the methodology (Maxwell, 2012). According to Creswell (2009), it reveals the kind of research undertaken to deliver suitable solutions to the research problem. The researcher used a quantitative method, descriptive in nature. The researcher used the survey method as means of obtaining the information. Two types of surveys were created; i.e. the online, and hard copies. The online surveys were created to reach a great volume of participants with different backgrounds. The hard copy surveys were also distributed to, university of Johannesburg students, airline, engineering and manufacturing companies.

2. Population and sample of the study This research was carried out in the Republic of South Africa at Johannesburg. The target population of the study was the airline customers, university students, engineering and manufacturing companies. The questionnaires were sent and distributed to all four targeted groups.

3. Sampling Sampling is a technique considered by a researcher to make sure that the sample used is representing the field of study concerned. According to Vos et al. (2011), there are two different types of techniques to use; these are probability sampling and non-probability sampling. This research adopted the probability sampling.

4. Data collection This study used the primary data collected using online surveys, and the hardcopies were distributed to the targeted population. Both surveys questions used to collect the data are included at the end of the thesis.

5. Data analysis The feedback received from the participants was transferred into an excel sheet then later analysed with the assistance of Statkon department from the University of Johannesburg. The data was discussed; presented in graphs and tables to get a meaningful conclusion.

1.8 Overview of the study This thesis consists of 10 chapters and below is a brief enlightenment on how the chapters were titled and arranged.

Chapter 1: Introduction Chapter 1 explores the background of the research, discussing the South African case study as well as the aim and the purpose of the study. This chapter further discusses the research problem, the objectives of the research and the research questions. The summary of the research methodology was also given on chapter one.

Chapter 2: Theoretical Framework Chapter 2 is more about the critical assessment of the selected best thirty studies on lean manufacturing. The researcher used the ISI web of science database with ‘Lean manufacturing’ as a key word. The search only focused on peer reviews articles published in English, falling under certain research areas

Chapter 3: Literature review This chapter focuses more on lean and other quality improvement tools that can be useful in the airline industry and other service industries.

Chapter 4: International case study Even though the study is about the South African airline. The researcher expanded the research to cover the literature review from an international aspect, by covering United Kingdom and United Arab Emirates.

Chapter 5: African case study The study was expanded more to cover the African continent. By doing so, the researcher selected Nigeria and Kenya.

Chapter 6: African case This chapter reveals the history of South African airline industry. Moreover, the manner in which the airline industry effects of the country’s economy. Also highlighting the importance of the industry to the country.

Chapter 7: Research Methodology

Chapter 7 highlights the approach and procedures used to collect and conduct the research. It presents the research area, population and targeted respondents.

Chapter 8: Data Analysis and Interpretation

This chapter is about the analysis and interpretation of the findings. The chapter makes use of the statistical techniques to analyse data.

Chapter 9: Discussion of findings

This chapter discusses the findings of chapter 8 in relation with the literature review. The discussion is aligned with the research objectives to determine if the objectives were met.

Chapter 10: Conclusions and Recommendations

This chapter concludes on the entire thesis and gives recommendations for future research.

CHAPTER 2: THEORETICAL FRAMEWORK

The below thirty studies were selected based on the key words, language, countries, publication year etc. To begin with the critical assessment of the existing literature on Lean, the ISI web of science database was used with ‘Lean manufacturing’ as a key word. The search only focused on peer reviews articles published in English, falling under certain research areas. The search resulted in 1 750 studies that were critically assessed by means of titles and abstract with the purpose of developing additional boundaries and eliminating incorrect or unrelated entries (screening phase). The articles that focused on the development and application of lean industrial principles were chosen to be assessed in this study. It is noteworthy that the studies that did not meet these requirements were ignored. This stage generated 305 studies focusing on lean manufacturing mainly in automotive industry, health care, electronics and general manufacturing. These studies were categorized on based on the set of standards, for instance in this research; the studies that were assessed were selected based on the citation. The underneath studies were chosen, ranging from 1997 – 2017 as they were cited the most.

Table 2.1: Previous studies on lean implementation in different companies

Nr. Authors Type of manufacturing Research Methodology Countries

Automotive Airline Electronics Qualitative Quantitative

1 Bowen x x and x U.S.A Youngdahl (1998) 2 Lewis x United (2000) Kingdom 3 Sanchez x x U.S.A et al. (2001) 4 Rothenber x x x U.S.A g et al. (2001) 5 King and x U.S.A Lenox (2001) 6 Yusuf & x United Adeleye Kingdom (2002)

7 Pavnaskar x U.S.A et al. (2003) 8 Zhu and x X x China Sarkis (2004) 9 Li et al. x U.S.A (2005) 10 Simpson x x Australia and Power (2005) 11 Agarwal et x India al. (2005) 12 Doolen & X x U.S.A Hecker (2005) 13 Vonderem x x U.S.A bse et al. (2006) 14 Seth & x x India Gupta (2005) 15 Narasimh x U.S.A an et al. (2006) 16 Cagliano x Not et al. specified (2006) 17 Ward & x U.S.A Zhou (2006) 18 Kim et al. x U.S.A (2006)

19 Liker and x x U.S.A Morgan (2006) 20 Holweg x x U.S.A (2007) 21 Shah and x United Ward Kingdom (2007) 22 Alford et x x United al. (2000) Kingdom 23 Fullerton & x U.S.A Wempe (2008)

24 Shah et al x U.S.A (2008) 25 Dickson et Not specified x U.S.A al. (2009) 26 Anand et x U.S.A al. (2009) 27 Bozarth et X x UK, al. (2009) Sweden, USA, Austria, Japan, Finland, Germany, South Korea 28 Eckel & x United Neary Kingdom (2010) 29 Yang et al. x U.S.A (2011) 30 Detty and X x U.S.A Yingling (2000)

2.1 Dissemination of lean literature The above studies, as tabulated in Table 2.1, were assessed and we have observed that the majority of the studies conducted to explore the effectiveness of lean have focused more in the automotive industry. This is because the management rationality and tools of “lean production” originate from the industrial sector, by Toyota Motor Corporation, regarded as the pioneer in making use of execution enhancement approaches. Below is the further discussion of the studies, and they were arranged from the oldest to the newest.

As presented in the Table 2.1 above, Bowen and Youngdahl (1998) conducted a study in USA focusing on lean service in three different sectors, namely, Airline, Automotive and Healthcare. They asserted that in previous years, transferring the manufacturing philosophy to service industry labelled as completely unsuitable. They added that in the late 1980s and 1990s the literature review argued against transmitting manufacturing principles to service industry, but it supported transferring service philosophies to manufacturing. The implementation of industrial philosophies or processes to service sectors believed to be unsuitable for the changing environment of consumer demand for services, to treat service workers like machines, and so on. On the other hand, industrial companies believed to profit when they find means to take along clients within their physical amenities, this is

24 something that is natural in companies like restaurants, hotels, and banks. They noted that many scholars ignored the service sector in the 1970s, and the investigation studies were fundamentally engaged on manufacturing firms. Due to poor quality, incompetence, the service sectors started to pull their socks and unfortunately, at this time, the service management models were growing much slower. The application of mass production line methods from industrial to services permitted the service sector to attain competent low rate production of client satisfying results. They touched on three successful service sectors; this includes South West Airline (SWA). They further added that the argument about service sectors benefiting from applying manufacturing philosophies is still valid.

Additionally, Lewis (2000) carried out a study of Lean production in SMEs based in UK. In his study, he adopted a qualitative methodology approach, which was used to interview Twenty Seven senior managers within three different companies. The objective was to establish the influence it had on the total competitive spots of adopter companies. He felt that Lean nowadays is not fashionable but its principles are the model for many companies, i.e. manufacturing and service companies. The author urged that lean production had a potential to strengthen the competitive advantage of the companies. According to the author, the uncertainty of lean assembly in practice can mean that the Lean application practice has the ability to make tactical resources to strengthen sustainable competitive advantage. He also recommended that applying Lean could limit the company’s capacity to attain long-term flexibility. He concluded with recommendations for further work.

Sanchez et al. (2001) conducted a quantitative analysis titled “Lean indicators and manufacturing strategies”. They used survey results obtained from automotive and industrial machinery plants situated in the Spanish region of Aragon in the beginning of 2000. The sample covered 107 organizations with 50 and above workers. They chose automotive and machinery sectors because other researches specify that they are the most serious adopters of JIT and other lean production

Rothenberg et al. (2001) also conducted a study to explore “Lean production”. They performed two different surveys from 31 automotive manufactures in North America and Japan. Interviews were also conducted in depth with 156 staff from the assembly plants from 17 different plants. The results from both surveys and interviews suggested that “lean management’’ and decrease of air emission of explosive organic compounds is adversely connected. Lean manufacturing processes were also used to add to more effective utilization of paints and cleaning solvents, but they are insufficient in process changes to meet the most stringent air controls. They established suggestion to support the relationship among lean processes and resources effectively. The findings were in theorised direction; they were not statistically imperative. On the other side, the interviews recommended a stronger connection. They utilised them to define some mechanisms by which buffer minimization, work system and HR management, which is the three aspects of lean management, may be linked

25 to environment management processes and performance. In both qualitative and quantitative methods, they found a perplexing connection among lean manufacturing and environmental execution that relied on the measure of environmental performance being assessed. They found proof that many lean manufactures have been willing to trade off a portion of the lean management principles so that they can reduce emissions. For instance, increasing painting batch sizes so that they reduce the voc emission in the pant, even though this is against the JIT principle of the pant.

King and Lenox (2001) conducted a quantitative in USA titled “An empirical examination of the relationship between lean production and environmental performance”. According to their research, “lean production” may have an important public worthy spill over and an enhanced “environmental performance”. Nevertheless, a practical evidence of the relationship among environmental performance and lean production processes has not resolved the nature of the connection. To discover this matter, they conducted a practical analysis of the environmental performance using data from 1991 -1996 obtained from 17,499 USA manufacturing companies. They discovered that most companies that implemented the “quality management standard ISO 9000” were more likely to implement the “environmental management standard ISO 14000”. Moreover, they discovered a robust practical confirmation that ‘lean production’, as estimated by ‘ISO 9000’ implementation and low synthetic inventories, is corresponding to the decrease of waste and contamination. They concluded that ‘lean production’ is relating to ‘environmental performance’. Furthermore, they suggested that the implementation of ‘lean production’ lowers the minimal expenses and reduces contamination. Due to the practical support they found, they concluded that “lean is green”.

Yusuf & Adeleye (2002) conducted a quantitative analysis titled “A comparative study of lean and agile manufacturing with a related survey of current practices in the UK”. The investigation offered in this research is across all major manufacturing segments. In line with changing success aspects, companies are moving from mass production to lean or agile. They performed a relative research of lean and agile modern with a connected overview of existing procedures in the UK. They found the dangers to lean and the drivers of agile manufacturing. They used the information gathered through the questionnaire survey, and the results indicated the benefits of agile manufacturing. Assessments performed to test the important difference in performance measures, showed that agile organisations always outperform the lean organisations. They concluded that, competing concurrently on numerous competitive competences improves performance better than only focusing on cost and quality.

Pavnaskar et al. (2003) conducted a study in USA to understand the classification scheme for lean manufacturing tools using a qualitative analysis. They noted that most manufacturing companies

26 have been trying to be lean from previous years. It was also noted that due to the hurry in applying lean, companies ended up misapplying the lean manufacturing tools often because of the lack of understanding the purpose of the tools. They conducted this research with the main purpose of proposing the grouping arrangement to serve the relationship among industrial waste challenges and lean manufacturing tools. They noted that an industrial company could match its business wastes with the suitable lean manufacturing apparatuses. The grouping of current information is always the first move from a practice to a science. This grouping arrangement scientifically put in order lean manufacturing apparatuses and metrics in accordance with their degree of abstraction, suitable position of use of the tool in the business. They organised 101 lean manufacturing tools and measurements making use of the grouping scheme. They also defined some of the common problems in manufacturing making use of the classification arrangement and presented the problem- tool relationship with examples. The grouping arrangement is not meant to be a decision-making tool, meaning it does not determine whether something is a waste. Nevertheless, the suggested scheme is doing an exceptional job of categorising all perceived lean manufacturing tool sand measurements and proposes lean manufacturing tools and measurements that will help to address manufacturing issues. They concluded that the grouping arrangement will help organisations who want to be lean and can be utilized as a reason for investigation into the exploration of lean.

Zhu and Sarkis (2004) conducted a study titled “Relationships between operational practices and performance among early adopters of green supply chain management practices in Chinese manufacturing enterprises”, focusing on automotive and electronics manufacturing enterprises, using quantitative analysis. Chinese enterprises are under a pressure to improve their environment performance because of globalisation. They have to balance their environmental and economic performances just like any emerging country. Environmental and economic performances of the Chinese enterprise are improving because China is using “Green supply chain management” (GSCM) as their emerging approach. The relationship between these two dimensions and GSCM was measured on GSCM practise using results obtained from 186 respondents in Chinese manufacturing. Remarkable verdicts on how the quality management and just–in-time manufacturing philosophies affects the connection among GSCM processes and performance were noted for several connections, including managerial consequences. The results recommended that Quality Management and Just-in-time have control special effects to a certain extent of the performance. They concluded that the expectations of connections among general GSCM processes and financial and environmental performance are favourable and it looks like there are positive chances for Chinese manufacturing enterprises that want to apply GSCM processes.

Li et al. (2005) conducted a research titled “Development and validation of a measurement instrument for studying supply chain management practices”. They collected data from 196 USA companies and measured it using quantitative analysis. It is extensively discussed the competition is not among companies anymore but among the supply chains. Effective supply chain management is now a possibly treasured approach to secure competitive advantage and enhancing the company performance. This research theorises, improves, and confirms six dimensions of supply chain management processes.

Another study done by Simpson and Power (2005) aimed to explore the connection amongst a supplier & company’s level of environmental management. The study was done in Australia’s automotive industry using a qualitative analysis. They presented a theoretical framework and intensely looked at previous studies to examine this connection. Through literature review, they found that attempts to advance or effect a supplier’s environmental handling processes result to serious matters of transaction rates and efficiency of approach for the purchaser. They concurred that the natural execution of providers to the supply capacity can be an expensive attempt when not handled in a correct manner and the supplier has to be certain that their utmost interest lies in accepting direction and support from their customers.

Agarwal et al. (2005) conducted a research titled “Modeling the metrics of lean, agile and leagile supply chain”. They agreed that nowadays businesses embrace change as one of the main characteristics; as a result, it is becoming tougher ensuring the success and survival of the business. They emphasized the ability of the business environment to be flexible to changes, also to address market and customer requirements in a proactive approach. A supply chain adjusts to alterations if they are flexible and agile in nature. Their study further summarises the sensitiveness of the market, practice incorporation, information driver and adaptability proportions of supply chain execution.

Doolen & Hecker (2005) conducted a study to review the lean assessment in organizations. The study focuses on electronics, using a quantitative methodology. They described the improvement of survey instrument to evaluate the application of lean processes. They used the literature review to classify lean industrial processes. Their findings synthesized to make an instrument to measure level of implementation. An empirical study completed using the survey across electronic organizations in the Pacific Northwest. It was discovered that even though electronic manufacturing organizations have applied a wide series of lean processes, the degree of implementation does not differ and may be linked to operational, economic, organizational or factors.

In another study conducted in UK automotive industry using a qualitative analysis. They discussed the types of supply chains that are required for triumph across 3 categories of items: standard,

28 creative, and cross breed. This study gives understandings to discrete part manufacturing organisations that structure, actualize, and partake in supply chains. It depicts the highlights for: standard, creative, and hybrid items and it gives a structure to the information of lean and agile supply chains. Lean Supply Chains (LSCs) employ on-going development attempts and emphasise on the reduction of non-value included stages throughout the supply chain. Agile Supply Chains (ASCs) react to fast moving, recurrently fragmenting worldwide markets by being active, context- specific, growth- focused, and agile supply chains to build a supply network that meets the items needs and requirements (Vonderembse et al., 2006).

In a similar way, Seth & Gupta (2005) conducted a research focusing on the Indian automotive sector. Their research noted that most of the manufacturing companies have been trying to be lean for the last few years. A rush to provide value to clients by adopting lean has generated determination for scholars and practitioners to use new approaches to attend to various wastes. Value stream mapping (VSM) has been effective in classifying and reducing wastes in a facility with related or same product routings, like in assembly amenities. They attempted to use value stream mapping as a tool to attain supplier productivity improvement in automotive industry. They concluded that all the suitable models and techniques must be applied in a manner that everybody who is linked in the value stream could work as a team to advance the overall flow to the clients with minimised or no waste at all.

Narasimhan et al. (2006) conducted a quantitative analysis in USA titled “Disentangling leanness and agility”. They mentioned that the industrial plant superiors have adhered to principles of lean and agility, as they wanted performance improvements. Lean and agile manufacturing paradigms have been greatly considered in operations management literature. They felt that there is inconsistently in the literature, lacks clarity and does not outline accurately the difference between leanness and agility. They added that it is vital to know the dissimilarities in these paradigms and what their basic dimensions are. This understanding is also important for developing and analysis philosophies concerning leanness and agility. A practical research was conducted to find out if lean and agile forms take place in industrial plants. The outcome established the presence of homogeneous groups that resemble lean and agile performing plants, and they classify significant dissimilarities relating to their constituent performance dimensions. The findings show that searching for agility might assume leanness; however, searching for leanness might not assume agility.

Cagliano et al. (2006) directed a quantitative research titled “The linkage between supply chain integration and manufacturing improvement programmes”. They used evidence taken from a sample of 297 European organisations. They noted that the focus of most Operations Management academics has moved to supply chain management but they needed to know how supply chain

29 approaches are related with internal industrial approaches. They mentioned that they have observed some studies in this field through literature review, but an in-depth investigation of the relationship between these two arrears is still needed. According to their findings, the implementation of the “lean production” model has a resilient effect on the incorporation of information and physical flows along the supply chain, while no substantial effect occurred from the implementation of Enterprise Resource Planning ERP. Their results open up new research questions about the missing relationship between Enterprise Resource Planning and information integration along the supply chain. Additional improvements are concerning the study of the influence of consistent implementation of internal and external processes on performance. Their research provides superiors with rich proof of the requirement for consistency among inner and outer coordination and handy proof of the relationship among manufacturing and supply chain Integration processes.

Ward & Zhou (2006) also conducted a quantitative study in USA titled “Impact of information technology integration and lean / just-in-time practices on lead time performance”. The study noted that managers who want to enhance lead-time performance are faced with a challenge of having to balance the assets and investments between process improvements attained through JIT processes and IT deployment. They felt that the existing literature offers small guidance on this question. They studied practically the links between, interfirm IT incorporation, Intrafirm IT incorporation, JIT procedures and lead-time execution with the use of data from industry week’s census of manufactures as encouraged by reasonable significance and absence of academic research. Their results provided deep insight on the connections between IT integration and JIT processes. Firstly, their results confirmed that the implementation of lean cuts lead-time. Secondly, lean arbitrates the impact of IT integration on lead-time performance. These results recommend that process upgrades that are because of lean are critical supporters to the victory of IT integration. They mentioned that organisations that have been enjoying victory by decreasing might profit by IT integration processes. The discoveries give senior management technical proof and a hypothetical structure on the parity of lean and IT for influencing enhancement in lead-time execution, henceforth-offering direction on this inquiry.

Kim et al. (2006) directed a research on “lean production” in USA health care services using a qualitative methodology. They noted that as health care rates continue to increase, a range of practice development approaches have been suggested to attend to the described incompetence in health care services. The management principle and tools of “lean production” originate from the industrial sector, in which they were founded by Toyota Motor Corporation (TMC), regarded as a pioneer in making use of these execution development approaches. They agreed that lean has already experienced the incredible achievement in enhancing quality and effectiveness in both the

30 industrial and the service businesses. Their findings showed that, even though lean methods are new in health care services, the improvements reports are starting to show in the literature. They depicted a portion of the fundamental rationalities and principles of “lean production” approach and the ways in which these ideas can be implemented in health care services. They further described a number of achievement stories and continuous activities of “lean production” in several health care companies. They highlighted that hospitals are the perfect setting to implement lean production methods, because this approach could make a positive impact on patients. They concluded a number of possible encounters in presenting and applying lean production methods. They added that Lean production is a unique tactic to bringing improved quality and effective attention to patients. Furthermore, it has been reported that the health care environment can expect the same extent of triumph as industrial and service sectors when applying this approach. Health care organisations are informed to ensure that they deliver caution of superior quality with extra competence by applying these new values in their environment.

Liker and Morgan (2006) conducted a qualitative study in USA to understand the lean production system in Toyota. They noted that the “Toyota’s production system” (TPS) is based on “Lean” philosophies; these include emphasis on clients, on-going improvements and quality through reducing waste, and strongly incorporated upstream and down-stream process as part of a lean value chain. Many industrial firms have implemented some kind of “lean initiatives.” Lately, Lean approaches have been adopted by many sectors including service sectors. However, a majority of these attempts represent limited, disorganised methods, speedy resolutions to lessen lead-time, costs and to improve quality. They explained the management principles of Toyota production system that can be implemented across all industries. In addition, they mentioned that most companies can learn from the Toyota approach, but the process is very complex than just attending a class. They explained this journey is a cultural transformation and a PDCA learning process. They concluded that it effectively joins individuals, practices and technology. As such, this system must be implemented as an on-going, inclusive and synchronised approach for change and learning of the entire organisation (Liker and Morgan, 2006).

In addition, Holweg (2007) performed a study to understand the lineage of “lean production” in UK automotive industry using a qualitative analysis. The purpose was to analyse an old research that resulted to the revolution of the most powerful manufacturing paradigms of current era. He realised that the “lean production” did not only well challenge the recognised mass production processes in this sector, meaningfully moving the trade-off amongst productivity and quality. “Lean production” also resulted to reconsidering of a comprehensive range of industrial and service processes further than the high-volume dull modern condition. The book called “The machine that changed the World”

31 presented the term “lean production” in 1990, is the highest widely quoted references in operations management. Even though the just-in-time (JIT) manufacturing model was recognised earlier, the book played a significant part in distributing the idea outside of Japan. Although the practical façades of “lean production” have been extensively argued, the author wanted to examine the growth of the study at the MIT International Motor Vehicle Program (IMVP) that resulted to the commencement of the term “lean production”. Regardless of the previous existing information of JIT, the program was so strong in encouraging the “Lean production” idea. The research done by Holweg (2007) presents a historic account of the study that resulted to the construction and distribution of best powerful industrial paradigms of modern times and this is due to repeating sequence of discussions done with the writers, contributors and academics of the time.

Shah and Ward (2007) conducted a quantitative study that aimed at exploring the lean production in UK did another quantitative study. These researchers wanted to address the misperception and discrepancies related with ‘‘lean production.’’ A wide spectrum of literature was performed to bring clarity in interpretation of lean production, using past evolutionary viewpoint in locating its main components. An important set of measurement tools was identified by recording the relationship among measurement devices that had been utilised to examine a number of mechanisms from historical literature, applying a 2-stage pragmatic technique and information from industrial companies. The authors narrowed the selected items to signify “lean production” of 48 substances, practically classifying ten fundamental mechanisms. The results were structured into three sections: 1. what lean production is, 2. in what way are the several elements of ‘lean production” linked to each other, 3. why are they connected. They recommended a theoretical explanation of “lean production” and an operative measure was derived from the content and intentions of its ancient roots in TPS. The findings connected with the CFA model recommended that “lean production” could be characterised with 10 aspects, in which each aspect signifies a different aspect. They concluded that “Lean production” is not a singular philosophy, and it cannot be merely associated to reduction of waste or on-going initiatives, which institute its managerial philosophies. “Lean production” is theoretically complex, and its description spans logical features that are always tough to quantity

Alford et al. (2000) conducted another research in UK to investigate the mass customisation in automotive industry. They noted that the automotive industrialists are progressively targeting for mass customisation, producing a number of products that almost every individual can get what they want. A number of product varieties are causing increasing rates and complication in manufacturing. Alford et al. (2000) recommended that an effective method must be built to back up conclusions on initiatives planned for supporting customisation and stopping increasing rates and complications in manufacturing. The study recognised the significance of knowing the assembly connections and its

32 supporting supply chain, and to shape an approach that is effective to update investment resolutions in technology and process management, to make a best structure for mass customisation.

Fullerton & Wempe (2008) conducted a research to explore the influence of non-financial manufacturing performance (NFMP) on “Lean manufacturing”. They collected information from 121 U.S. industrial executives and evaluated using a quantitative analysis. Furthermore, to investigating direct effects, they measured to see if the non-financial manufacturing performance measurement arbitrates or controls the lean manufacturing relationships. The results from the study give significant proof that applying NFMP measures, arbitrates the link between financial performance and lean and manufacturing. Results from the study concerning NFMP estimation shows that, the blended outcomes of the past researches of the “Lean manufacturing” maybe partly caused by inability to represent NFMP estimation. The findings from 26 studies confirm that the participation of the front office staff is an important element to the accomplishment of the implementation of “lean production”, and that “lean production” approaches inspire the utilization of NFMP measures. They highlighted that unsatisfactory financial outcomes may occur if managers apply lean manufacturing without utilizing steady NFMP measures.

Shah et al. (2008) conducted a quantitative study in USA titled “In pursuit of implementation of patterns: the context of lean and six-sigma”. They noted that the mix of lean processes and Six- Sigma has received much attention in latest years. Whether a joined Lean-Six Sigma methodology is the newest management trend, or result to important benefits of execution that outdo isolated usage is not yet obvious. Making use of implementation and performance data obtained from 2511 plants, they tried to discover associative and predictive design of implementation between 15 lean processes and the Six-Sigma program. Their results showed two main findings. Firstly, the usage of any process from a bigger set of Lean processes increases chances of implementing Six Sigma. Furthermore, processes usually under quality management forecast and differentiate the plants that apply Six Sigma comprehensively from non-implementers. Secondly, their results pointed out an important variance in the levels of performance in companies that apply Six-Sigma compared to companies that do not apply Six-Sigma.

Another research in the healthcare industry based is USA was done by Dickson et al. (2009) using a qualitative analysis. They noted that ‘lean’ is an arrangement of thoughts and approaches that lead firms to repeatedly improve the products they offer by improving the necessary process steps while reducing the ones that do not add value. This improvement methodology has been applied in industrial for years and has always been linked with improved product quality and largely company triumph. They aimed at assessing if the implementation of “Lean” philosophies by an Emergency Department (ED) will improve emergency delivery services. They implemented a range of Lean

33 techniques as means of improving patient and employee satisfaction in December 2005. The process redesign step emphasised mainly on producing development concepts from the forefront employees from all departments. Satisfaction of patients, expenditure per patient, time spend by patients/ length of admission, and number of patients were compared for calendar year 2005, i.e. before “Lean” and periodically after 2006 i.e. after Lean. Results showed that patient appointments went up by 9.23 percent in 2006. Even though this rise, the length of stay reduced to some extent and there was a massive increase in patient satisfaction. They concluded that lean enriched the value of the care they offered to patients. They noted that gathering information and ideas from the front employees was a better start to the success of the lean program. They further added that even though Lean signifies an important change to the way their services were delivered, the particular procedure modifications they did, tended to be easy to understand, little method changes particular to exceptional individuals, process, and place. Lastly, they recommended that organisations that plan to implement “Lean” should put their emphasis on the basic principles of “Lean” rather than imitating certain process modifications made by other companies.

Anand et al. (2009) conducted a qualitative analysis in USA to examine the content of on-going improvement approaches and to describe infrastructure decision parts that are significant for on- going improvement creativities. They offered a framework of infrastructure based on the concept that on-going improvement seen as a dynamic proficiency when it contains an inclusive organizational context. They further examined the initiatives of on-going improvement done in five different organisations, as means of investigating the processes used by these organisations in every single decision part of their framework. Their research adds to the theoretical knowledge of on-going improvement and results in grounded intentions about important areas of infrastructure for on-going improvement. Their research indicates the misconception of applying continuous improvement just offering training in companies’ new processes without setting up tools for handling and sustaining ongoing enhancement activities. They also emphasized the interrelationship among continuous improvement infrastructure elements, and suggested that efforts to handle continuous improvement through certain parts of its infrastructure may be futile.

Bozarth et al. (2009) conducted a quantitative analysis from 209 plants across UK, Sweden, USA, Austria, Japan, Finland, Germany and South Korea, titled “The impact of supply chain complexity on manufacturing plant Performance”. The study was directed to understand the impact of supply chain on execution of industrial plants. They established a connection among the “lean production” literature and the frameworks science writing that officially describes the features of higher-arrange multifaceted nature frameworks. Their justification was that industrialists are now skilful at handling such sources of detail complexity. The results indicated that in-house industrial complexity,

34 downstream complexity and upstream complexity have a bad influence on industrial plant performance. They concluded that supply chain includes that drive dynamic multifaceted nature bigly affect execution than those that drive just detail intricacy.

Eckel & Neary (2010) conducted a research on multi-product firms titled “multi-product firms and flexible manufacturing in the global economy”. The scale and scope of MPFs depend on globalization through competition and demand effects. They established a new model of MPFs, which emphasises the part of flexible manufacturing. Alterations in the range of products manufactured by companies are a significant factor of deviations in the final product and exports; this is in line with the increasing practical proof. Their emphasis was on the intra-firm adjustments within Multi Product Firms, they found that economy-wide shocks have an extensive influence on scale and scope. Furthermore, their investigation confirmed that general-equilibrium response, over fluctuations in salaries, are a significant factor of changes in product ranges. Their results suggested that modification practices within multi-product firms are diverse from modifications through exit and entry. Experiential confirmation recommends that multi-product firms are a significant feature of modern industries.

Yang et al. (2011) did another study in USA to explore the effect of “lean production” on organisation execution. They explored connections among “lean manufacturing practices”, “environmental management” and “business performance outcomes” using a quantitative analysis. AMOS was used to collect information from 309 global industrial companies to test theorised connections of this model. Past lean industrial practices are absolutely linked to environmental management processes as suggested by the results. They also discovered that these environmental management processes solely linked to market and financial performance. Nonetheless, the negative impact of environmental management rehearses on market and monetary execution can all be diminished by the enhanced environmental performance. Their study further provided experiential proofs that environmental management practices are now a significant facilitating factor to solve the battles among environmental performance and lean manufacturing. The existing variances are due to strong points and statistical significance of a number of suggested connections as recommended by background analyses. They concluded that to implement environmental management effectively, companies must quantity the environmental performance, and that the influence of environmental administration on further business performance results needs to thorough investigation.

Detty & Yingling (2000) conducted a study based in USA, tilted “Quantifying benefits of conversion to lean manufacturing with discrete event simulation”. Their objective was to show the use of discrete event simulation as an instrument to help companies with the resolution to apply lean manufacturing by measuring the profits that accumulate from impending lean principles in their specific condition.

Reproduction applied to help in the basic leadership to actualize lean manufacturing philosophies at a current assembly task. Models established for the current assembly and new systems that apply these philosophies. Furthermore, to the industrial practices, the related warehousing, stock administration, delivery, and production control/planning frameworks are incorporated in the model to allow the evaluation of lean manufacturing's impact on the aggregate framework. The experiments of simulation quantity the resource requirements and performance of each system and, thereby measuring advantages to have gotten from applying the shop floor standards of lean manufacturing. They concluded that imperative to know that lean manufacturing needs a factory floor focus.

2.2 Chapter Summary Many studies focused more on automotive manufacturing enterprises, electronics, healthcare and other manufacturing organisations. Unfortunately, from the above thirty best studies that were selected, very few studies focused on the service sector, especially the airline industry. Again, none of the studies conducted in Africa; instead, the majority of the studies were done in USA followed by United Kingdom. It has been also noted that the researchers have tried to explore both the quantitative and qualitative methodologies on their studies, with qualitative methodology used in 60% of the studies and followed by quantitative at 40%. Therefore, future researchers have an option to combine both methodologies or use only the quantitative as it was not used as many times as qualitative analysis. The studies highlighted that, management principles of Toyota production system are implemented across all industries. In addition, they mentioned that most firms can learn from the Toyota way, but the process is far complex than just going to class. They explained this journey as a cultural transformation and a PDCA learning process. The management philosophy and tools of lean production originate from the manufacturing sector, in which they founded by Toyota Motor Corporation, acknowledged as the innovator in making use of these implementation improvement tactics. It was noted that lean is known for its massive success to enhance quality and efficiency in manufacturing and the service ventures. The results received from service companies that are already implementing Lean, showed that although lean techniques are new in this sector, but the improvements are noted.

In line with continuous improvement, businesses are changing from mass production to lean or agile. It has been noted by some researchers that Lean can limit the organisation’s ability to accomplish lengthy haul adaptability. Some scholars revealed the threats to lean and the drivers of agile manufacturing. The measurements done to examine the significant variance in performance processes, presented that agile businesses continuously outdo the lean businesses. This philosophy is relevant to future studies.

2.3 Lesson Learnt As much as the lean concept is new in the service sector, some of the companies have adopted it already. The studies highlighted that Lean management principles are applicable across all industries. The principles of Lean are the model for many organizations; these include Industrial and service organizations. Lean production has the ability to toughen the competitive advantage of the organisations. Airline industry is not only offering services, but also customer-centered and it always finds ways of understanding the customer needs better in different stages of their services. In the airline industry, customer satisfaction is more critical because they do not offer any tangible items but just a service. For this reason, service quality is vital in this industry because of its capacity to draw in and hold clients. This is the reason the study aims to investigate lean implementation in airline industry. The outcome of the critical examination of the current literature clearly indicates that there are flaws related to the country and area of the studies. The airline industry has made a positive impact in the world and recognized for being one of the quickest developing divisions worldwide. This is a main service sector that provides support to other key economic sectors. As such, it is of utmost importance that the current researchers put their emphasis on this sector while closely monitoring the adoption and management of the quality improvement tools to advance the airline performance.

CHAPTER 3: LEAN ASSESSMENT

3.1 Introduction

The main point of this chapter is to find and debate main ideas linked to Lean implementation and management within the air travel industry. This chapter explores lean benefits and advantages of lean implementation, Lean principles, philosophy and techniques. The chapter reviews a range of educational sources of secondary data including journal articles, books and peer reviewed journals to conclude about what existing literature says about the research problem.

3.2 Overview of business improvement methodologies Many researchers like Ali (2016); Chakraborty & Tan (2012) have realised that improvement tools for corporate have been implemented in various services like government, education, law, healthcare government and finance. The four approaches that have become popular are Lean, Six Sigma, BPR and TQM and they are discussed in detail in the literature. We have reviewed the two latest techniques in depth, i.e. Lean and Six Sigma. We have also been explored TQM BPR methodologies because they have been implemented in services and therefore are briefly discussed.

3.3 Lean Theory Vermaak (2008) and Womack & Jones (2003) defines Lean as a set of ideas and methods that impart continuous improvement of the products they offer by improving the necessary process steps while reducing the ones that do not put in value. Lean is quickly spreading to all corners of the world because it is an available solution that is capable of continuously improving the company’s performance and productivity, while it intensely reduces errors, on-the-job accidents and all unnecessary costs (Womack and Jones 2003). Lean starts with the client who wants quality service, therefore, to make the most of good quality service, the process steps require a zero waste approach according to (Womack 2005). Client worth occurs by eliminating wastes and improving service characteristics without including additionally charges (Hines et al., 2004). Lean is a thought regarding 'accomplishing more with less' utilizing the optimal sequence with a little employee involvement, added (Dahlgaard and Dahlgaard-Park, 2006). In this manner, it enhances the stream of procedures in the conservative manner. Vermaak (2008) represented a guide for Lean implementation and notified for timeous manageable accomplishment.

They grouped the roadmap into four foremost stages as follows:

➢ Begin by getting a change operator, discovering awareness of Lean, recording value streams and expanding organization scope. ➢ Shape the company by recognizing product family, framing a Lean capacity, planning a development design and ingraining a "perfection" mind-set. ➢ Introduce corporate frameworks by presenting Lean accounting, relating pay to firm execution, starting approach organization and presenting Lean learning. ➢ Finish the execution by executing past steps to providers/clients, creating worldwide technique, changing from top-down to bottom-up improvement. To help this guide, they identified the five key standards of Lean and guaranteed that these standards are all around appropriate to any industry and are justifiable to fit in with service features.

3.3.1 Start of mass production Henry Ford started a conveyor belt determined car factory in 1914 (Bollbach 2012). Ford used a standard approach to carry out tasks and he used preferred employees with suitable skills for each position. He was then able to reduce costs with his new technique while improving the quality of products (Bollbach 2012). This is when he named his innovation system “Mass production”. Ford was able to make a huge number of affordable cars, joined with the continuous production flow. Bollbach (2012) stated that even so, Ford was not flexible, because the model T that they were producing at that time was only accessible in very little specifications. He further added that over the years, people’s needs, requirements and expectations changed, people wanted and expected a different feel, body and different car features. Customers required an increased product variety of cars. The Ford’s mass production line was unable to make cars in a flexible way in order to meet the customer’s requirements (Bollbach, 2012).

3.3.1.1 Ford’s moving assembly line Henry Ford started a conveyor belt determined car factory in 1914, Bollbach (2012). Ford used a standard approach to carry out tasks and he used preferred employees with suitable skills for each position. He was then able to reduce costs with his new technique while improving the quality of products (Bollbach 2012). This is when he named his innovation system “Mass production”. Ford was able to make a huge number of affordable cars, joined with the continuous production flow. Bollbach (2012) stated that even so, Ford was not flexible, because the model T that they were producing at that time was only accessible in very little specifications. He further added that over the years, people’s needs, requirements and expectations changed, people wanted and expected a different feel, body and different car features. Customers required an increased product variety of

39 cars. The Ford’s mass production line was unable to make cars in a flexible way in order to meet the customer’s requirements (Bollbach, 2012). This challenge was seen as an opportunity by Toyota.

3.3.1.2 Toyota Oeltjenbruns (2000) asserted that the enormous numbers produced by Ford, were eventually noticed by the Japanese car industry, Toyota. The Japanese were familiar with the North American assembly techniques in the 1930s, and more strongly after the Second World War. Kiichiro Toyoda, the founder of Toyota and the engineer Taichii Ohno examined the system of Ford (Fujimoto 1999). Toyota then started to integrate selected Ford’s philosophies into their assembly. However, they needed to adjust it in order to implement it in their country (Bollbach 2012). Toyota was able to produce more flexible few numbers of different parts, with the assistance of small multi-purpose equipment. This adaptability allowed Toyota to respond quickly to the market needs and requirements.

Bollbach (2012) noted that Ford’s consistent stream in the collection line lessened the time spend in the production process and enabled employees to work at full limit. However, high stock dimensions were required to make buffers amongst independent work phases. He further added that after examining Ford’s production, the Japanese engineers discovered a method to create with a continuous flow, still maintaining the flexibility. They named their productions system “Toyota Production System”.

3.4 Lean Principles The next five sections will record and define the five standards and discus the usability for air travel industry. Toyota also follows these five basic lean principles in order to produce high quality products, (Bollbach 2012). For an effective operation of Lean, it is imperative to clearly understand these principles (Womack and Jones 2003). These principles are also summarised by (Womack and Jones 2003) in their book “Lean Thinking” as follows:

a. Identify value for the customer This belief describes value from the end-client point of view. The important starting point of lean is value, it is that thing the client sees as critical and he is quick to pay for. The value is made for certain items/benefits that have particular capacities with particular cost at particular time. In the aircrafts setting, this implies giving what a traveller needs (fulfilling their necessities) through diminishing delivery and cost time at required area (Ali 2016).

b. Value Stream For lean, it is critical to recognize and comprehend the item or service value, and the product value can be characterized by the clients. The value has to meet the customer’s need and expectations. Hence, it is viewed as what the client is willing to spend on. According to Womack and Jones (2005)

40 a value stream is the ways of making, forming, and transporting a product or service to customers. Knowing the value stream is vital for basic two motives. One, it allows us to assemble items by the systems that make them. Two, understanding the value stream grants us to pay attention on an arrangement of associated methodology and maintains a strategic distance from interruption in examination.

This opinion emphasises on classifying, grouping and reducing waste along the value stream. Seven kinds of waste are categorised by Womack and Jones (2005) at first and later added one more waste to suit services. These wastes are recorded underneath with their expression within air travel industry:

➢ Deficiencies mean the defects which should be amended. For example, incompletely entire work or data, erroneous data, clashing data, deficient data, late work, guidelines that must be elucidated, miss-named records, lost records or data. ➢ Over-creation of merchandise that is not needed or delivering more than is instantly needed. Like composing formal archives or substance where just the table is required and frequently perused. ➢ Unnecessary queues refer to people or goods waiting to be processed. For instance, individuals are holding up in a line at numerous areas. ➢ Moving of items between forms with no valid reason. Pointers incorporate where the work is moved starting with one individual then onto the next ➢ Stock half-done items that are holding up to be prepared are viewed as pointless stock. Stock is a typical result in aircraft administrations of un-adjusted jobs. Inventory can be found in email, item improvement pipelines and to-do-lists. ➢ Movement is the meaningless motion of individuals and merchandise – individuals moving or working without delivering. ➢ Extra handling of merchandise and facilities that don't meet the client needs. This is a result of more tightly resilience. In an aircraft organization with a staggered pyramid of the board structure, extra handling appears in extra mark endorsements, information section at number of levels and creation of complex structures.

c. Flow Once the value is clearly well-defined by the client, the next step is to create flow of services/ products. With regards to airlines, client registration at the airplane terminals is immediately relocated from security, traditions, boarding lines, as easily as could reasonably be expected, influencing a flow in end-to-end to check in activities.

d. Pull

Customer pulls value. This rule empowers the customer to pull the item/service from the affiliation's value stream. For the aircrafts this standard demonstrates that the making of a goods/service should not to be created if the client has not articulated any need.

They recorded that individuals search for savvy crossover solutions that copy the thought of draw as found in manufacturing organizations. Like, making a cell phone design for aircraft services needs conceiving of brand-new ideas and this might be strengthened with innovation. For instance, an alerting message from the forefront employees to the obligation supervisor who might be located at the back office would practice Flow and Pull principles.

e. Perfection Chase perfection. This opinion inspires businesses to aim on excellence. It needs continuous efforts, keeping in mind the end goal to client satisfaction and an on-going arrangement of procedures and strategies. In the aircraft setting for persistent advancement, the value framed at each progression of the value stream needs a test to raise the flow, speed and strength, recognize and dispose of covered waste from their business forms.

Various researchers have confirmed that utilizing the Lean approach in a services setting is unique in relation to Lean manufacturing. In any case, they all confirm that the above principles/opinions of Lean are effective for services. Again, they accepted that these five principles can be adjusted for services and they keep on being unaltered. Even though these principles are thoughtfully fitting to any industry, however these must be personalised to suit to the industry where they are implemented (Ali, 2016).

3.5 Lean Tools and Techniques Bollbach (2012) defined “Lean” as a precise customary of linking methods, tools/apparatus, and activities created from a clear reference model. They accepted that Lean gives support to various tools and procedures, for instance: Kanban, Kaizen, 5S, Pull scheduling, Waste Analysis. For a long time, it has been evident that Lean manufacturing techniques and tools when applied correctly have the ability to reduce waste, improve stock control, quality of the goods and total monetary and operational systems (Bollbach, 2012; Womack and Jones, 2003).

Having right tools and methods is the way to reasonable execution of lean. Therefore, limiting the level of tools also restrict the performance of the business (Vermaak, 2008). He further states that insufficient lean tools and techniques is not the only factor that limits the organisation’s ability to

42 perform. It is important to understand that real time coaching, decision support will also limit the ability of an organisation to solve problems.

Various researchers have noticed that the application of Lean has solid conditions on instruments and strategies (Schiele and McCue, 2011; Atkinson, 2010). They prompted that Lean is not a tool- kit that just provides explicit particular devices for a business or process issue, where one apparatus/strategy can be picked by change team and utilized with a supposition that all will be settled. The basic thought of these organisation activity systems have one reason - to create business productivity and adequacy to enhance consumer loyalty and productivity for the association, in any case every technique has an alternate strategy.

3.6 Main factors that are critical and fundamental for the implementation of lean manufacturing The research done by Achanga et al. (2006) revealed that the following factors could critically affect the implementation of lean: Leadership, Finance, Company culture, Skills and Expertise. These factors are discussed in detail below.

1. Leadership The role of the senior management is critical and vital and can determine the success of the implementation of lean. The commitment of senior management is the foundation to the successful implementation of lean. Therefore, to successfully implement the idea of lean manufacturing, organisations should have strong management personalities. Appropriate senior management has to nurture effective skills to the employees. This approach benefits the organisations that are intending to implement the lean concept by the provision of readiness to learn, resource availability, acquire new ideas for its business competitiveness.

2. Financial capabilities The capacity of the company’s finance is a vital factor that determines the success and smooth implementation of lean. This is simple because the finance covers the avenues like training, consultancy, logistics etc. Therefore, lack of funds is a major barrier to the adoption and implementation of successful implementation of lean in any organisation. This is because the implementation of lean or any improvement model in any organisation always requires financial assistance to take care of the factors like hiring consultants, logistics and to cover the entire process of implementation.

3. Skills and expertise The technicalities in the implementation process of the improvement initiatives like lean manufacturing require employee skills and expertise.

4. Organisation culture It is vital to create a supportive company culture when intending to implement lean manufacturing. The culture of sustainable and proactive improvement is mostly noted in high performing businesses. It is the managers pre-requisite to work in different environments. They further add that it is imperative to have excellent communication skills, long-term focus and tactical team in the process of applying the new improvement models. Many companies are very careful in choosing the improvement initiatives.

3.7 Six-Sigma Six-sigma is a business improvement strategy that recognizes imperfections or troubles in company procedures (Ali, 2016). This method classifies and reduces main causes of defects as means of intention to attain developments in improvements. The discussion in the literature revealed that Motorola was a first organization to embrace the Six-Sigma idea. Hence, also other companies like Ford, American Express and others have likewise embraced this improvement tool. Ali (2016) remarked that emphasis of this improvement tool is on decreasing the procedure variety, by applying factual reasoning and strategies.

Checking on the writing featured a few cases of advantages of implementation of Six-Sigma in services. Ali (2016) noticed that banks, Citigroup and JPMorgan Chase profited from implementing Six-Sigma in their money related tasks, Lapré and Scudder (2004) recorded this improvement application in carriers, these are recorded beneath:

➢ Dropped credit handling time by a half in the call centre ➢ Dropped the time take to make a credit decision from 3 days to 1 day ➢ Dropped request handling process duration from 28 to 15 days ➢ Upgraded stream of data in account opening, and instalment handling and diminished client touch points.

Indeed, even with the prominence of this methodology in services, various difficulties of its operation have been discussed in theory. These are further discussed in the below lines:

➢ Combining information is a big challenge, due to unavailability of information for some procedures, and now and again it takes long to gather information, and this is time consuming (Ali, 2016).

➢ Hensley and Dobie (2005) asserted that it is key for Six-Sigma to pick the proper activities. They noticed that the selection of improvement activities is yet in light of subjective judgment in few organisations. ➢ The factual meaning of Six-Sigma is 3.4 defects in one million. In service sectors, it is characterized as anything that does not meet client desires or needs. Consequently, when we figure the sigma ability level of a procedure, not all defects are similarly great (Kuei and Madu, 2003). ➢ Building up this methodology into a business culture needs a huge investment. This would not encourage numerous little and medium size enterprises to utilize Six-Sigma as an improvement technique (Hoerl et al., 2001) ➢ Snee (2010) studied the method for certification of Six-Sigma for green and dark belts. Their confirmation was that the capacity of these two belts fluctuates massively over the service businesses, and the degree of accreditation is relied on the certification authorities. They inferred that capacities of these two belts are unequal. Regardless of the difficulties recorded above, Kuei and Madu (2003); Antony (2002) asked the question in the literature; ''How is this improvement methodology unique in relation to other methodologies?” and the next opinions were noted:

➢ It accomplishes measurable revenues to all that really matters (money related) for a company, thinking about certainties/information as opposed to expectations and guesses ➢ Reasoning is based on approved statistical tools ➢ It highlights significance for tough and passionate management and needs a help that is fundamental for distribution. Hoerl (2004) emphasized the way that, as separate from different approaches, the quality of Six-Sigma is that it builds a strong solid concentration for quantifiable incomes.

3.7.1 Basic principles and concepts Six-Sigma follows a certain model of DMAIC. This methodology is more like PDCA analysis of lean: ➢ Define the scope of the problem ➢ Measure the problem ➢ Scrutinise/Analyse the root cause of discrepancy and deficiencies ➢ Improve the process by fixing the problem ➢ Control and maintain the process

3.7.2 Lean and Six-Sigma Application of Six-Sigma techniques as a new concept in solving problem does produce significant results, (Bicheno, 2004). Loubser (2003) added that even so, to sustain these results, organisations need to demonstrate maturity and focus on Lean practices, Toyota Production Management (TPM), Theory of constraint and TQM. There is an agreement and understanding of tools and goals applied between Six-Sigma and Lean initiatives (Kaufman Global Group, 2003). They further added that knowing and understanding the exact problem is the best approach. We note that researchers confirm that both Lean and Six-Sigma are required because they do things differently (Vermaak, 2008). He also noted that if the organisations go big, process problems and quality issues are left unattended until they implement lean. On the other hand, if the entire market section is already going to that direction, the organisation cannot implement lean. While on the other side Six-Sigma cannot produce the desired results in reducing the inventory and cycle time on an appropriately broad basis fast enough.

Kaufman Global Group (2003) suggested that the best approach is to introduce a lean initiative that will start by improving all micro processes. While on the side developing resources like Six-Sigma black belts or well qualified re-engineering professionals to attend to the complex issues. The below table gives a differentiation between Six-Sigma and Lean.

Table 3.1: Comparisons between Six-Sigma and Lean (Bicheno, 2004).

Area Six-Sigma Lean Focus Projects / process Value stream Framework DMAIC (always applied) 5 Principles (not always applied) Impact Individual projects may have Can be large, system-wide large savings Improvement A lesser amount of large Numerous little projects. improvements, a few low kaizens. Everywhere, simultaneous. Objectives Reduce variation Reduce waste Shift distribution inside Improve value customer requirements People involvement in Black belts supported by green Team led by Lean experts improvement belts

Problem root causes Via e.g. Design-of- Via 5 why’s (weak) experiments (strong) Time horizon Short term. Project by project On-going, and short term kaizen Tools Sometimes complex statistical Often simplified but difficult to incorporate Typical early steps Collect data on process Map the value stream variation Typical goals Improved Sigma level Cost, quality, delivery, lead time

3.8 Total Quality Management Total Quality Management (TQM) is regarded as the "mother of all" of the modern improvement strategies. The development of quality started with TQM, and the view of constant change come into the management awareness. TQM was established on Deming's 14 focuses, and consolidated a logic that incorporates four noteworthy territories:

➢ Responsibility of the Management for on-going improvement ➢ Emphasis on the work procedures to attain improvements ➢ Usage of statistical tools to evaluate development performance ➢ The extent in which employees are involved and engaged Reducing errors made during the manufacturing or service processes is the main basis of TQM. This includes the increase in satisfaction of the clients; streamline supply chain management, purpose for transformation of tools and making sure that employees are well trained according to the job specifications (Ali, 2016). TQM resulted to a change in how the management thinks and was supported all over the world. Many scholars show in the review of the literature that after two decades or so, organisations needed something new and thus TQM developed Six-Sigma, which is another enhancement approach. TQM methods appeared to be derived from a combination of methodologies suggested by the quality Gurus like Deming and other.

Ali (2016) highlighted that this improvement tool has been effective in various measurements, for example, money related, performance, quality, and client aspects. However, there are reactions and worries that were observed by various scholars for the implementation of TQM. As per their clarification, these reactions are associated because of the absence of an organized approach connected for enhancing the procedure, troubles in estimating TQM results, and the expenses and

47 time size of implementing TQM. Various analysts have additionally asserted that TQM is not useful for companies that work in extremely rapid changing conditions. Narasimhan (2003) emphasised that these companies should put their focus on development instead of elevating their current functioning methods.

3.9 Business Process Reengineering (BPR) BRP is an essential rethinking and fundamental redesign of organisations procedures to attain huge enhancements in basic, contemporary proportions of execution, as cost; quality; service and speed (Ali, 2016). According to Shin and Jemella (2002), people from most of the related practical divisions should get together and plan as an enhancement group to enhance the organisation activity in order to accomplish the objective of BPR. Nevertheless, regardless of the prominence of BPR, Hammer (1990) noted that BPR was criticized and seen as a tactic that does not have a solid basis for its execution.

They included that it does not give much thoughtfulness to the gentler side of business change, for example, reward, inspiration and individuals’ inclusion. These factors are principal for services, for example, aircrafts where bleeding edge worker's association and interactions is basic for benefit conveyance (Shin and Jemella, 2002). Other than the TQM and BPR methodologies, it was observed in the writing that in year 2003, Six-Sigma and Lean have been extensively approved as business enhancement approaches in the service sector.

3.10 Service Definition This section covers some of well-known researchers’ explanations of services. A service is an activity or series of activities of more or less intangible nature that normally, but not necessarily, take place in interactions between the customer and service employees and/or systems of the service provider, which are provided as solutions to customer problems (Brady and Cronin, 2001). A service may be defined as a change in the condition of a person, or of a good belonging to some economic unit, which is brought about as the result of the activity of some other economic unit, with the prior agreement of the former person or economic unit.

While Maddern et al. (2007) defines a service as any act or performance that one party can offer to another that is essentially intangible and does not result in ownership of anything. Its production may or may not be tied to a physical product.

3.11 Service Quality Service quality is an extent to which the delivered service complies with the expectations of the client.

Expected

service

Service Customer Customer

quality satisfaction loyalty

Perceived service

Figure 3.1 Flow diagram depicting service and its quality related to client expectations (Seth et al., 2005)

The service sectors frequently evaluate the service quality offered to their customers in order to improve their service, to quickly identify problems and to better measure the client satisfaction, to examine the experience, opinions and suggestion of the customers and people who are potential customers (Frank & Enkawa, 2008). The improvement of service quality to meet customer’s standards and requirements should be an on-going organization’s activity. Frank & Enkawa (2008) highlighted that the customer satisfaction determines the organisation’s success, customer loyalty, revenue, profits, market share and survival.

Evans and Lindsay (2002) reveal an array of Service Quality Dimensions that are important for customers, these are: ➢ Empathy – This refers to the amount of attention and necessary care given to each client. ➢ Assurance – The ability of employees to demonstrate their knowledge, confidence and trust to customers. ➢ Reliability – The ability to deliver the promises.

➢ Responsiveness – The aspiration and availability to assist customers and provide quick service ➢ Tangibles – This refers to the employee appearance, competence, individual attention, and professionalism including the office equipment, facilities and well-designed company forms that are easily understandable.

The structure of the service quality has two proportions – 1) technical and 2) functional. It characterises the opinion on both, the manner in which the quality is observed influenced (Ali, 2016). The underneath diagram could be a pictorial representation as presented below.

Perceived service quality

Perceived Expected service service

Image

What? How?

Functional Technical quality quality

Figure 3.2: Gronroos’ service quality framework (Ali, 2016).

The technical service quality (TSQ) dimension symbolises what is received by the customer as service collaboration and may be thought of because of the item/service production method. This explanation is also confirmed by Jen et al. (2011); Brady and Cronin (2001) who highlighted that this approach is vital for measuring service quality. They also mentioned that there are not any hidden variables associated with the technical service quality dimension.

This impacts the clients' degree of fulfilment and is an imperative determining factor of overall service quality. In a comparison done by Seth et al. (2005) between specialized service quality and useful service quality measurements it was agreed that operational service quality can impact perceived service quality to as greater point than technical service quality and confirmed that operational quality impacts the apparent service quality at a more prominent point. Seth et al. (2005); Jen et al. (2011) closely analysed how service quality impacts clients' perception of significant worth and their eagerness to buy.

They affirmed that operational service quality functional quality of the service has a more noteworthy impact than technical service quality on buying choices; however technical service quality and functional service quality can be seen by clients in a similar occurrence. There is a solid relationship between business procedures and technical service quality (Maddern et al. 2007). They affirmed that technical service quality is vital for service quality and can be viewed as a primary driver for the satisfaction of the customer.

Service quality – SERVQUAL system, broadly known as PZB, gives knowledge on how clients see the service quality and it utilizes five particular dimensions to evaluate these perceptions (Ali, 2016). The next table incorporates these measurements and gives explanations.

Table 3.2: The SERQUAL dimensions (Ali, 2016). Tangibles Responsiveness Assurance Empathy Reliability Definition Facilities, Taking Know how, Caring, Providing furniture and responsibility/ ability and personalised services as appearance ownership to offer consideration attention to promised of employees service and of employees customers willingness to help Question Is the airline, Are the flight Are there Do they Is my flight that might gate neat? attendances employees recognise my on time? be asked by willing to respond knowledgeable needs, i.e. airline to my queries? and their special customers functions? seating, meal, transfer, luggage,

rebooking etc.

Seth et al. (2005) clarified that SERVQUAL maintenances an expansive scope of applications and announced that this system can be utilized to comprehend the view of targeted clients both internally and externally. They claimed that SERVQUAL gives an estimation of service quality.

3.9 Lesson Learnt In this chapter, we have learnt that Lean offers solutions to many problems and threats that organisations experience in their idea of becoming worldwide competitive. It is also a solution to most organisations that want to thrive in the worldwide market. Hence a lot of business organisations are thinking of applying lean as an improvement business management preference. Lean has the ability to offer organisations with a competitive advantage; it is therefore advisable for firms to have the idea of lean in place. Manufacturing companies have regular challenges with their services and processes; and this is one of the reasons the idea of lean was introduced. This model enables organisations to accomplish customer satisfaction, because it has the ability to focus on providing maximum value with only minimal resources. The foundation of this improvement model is accentuated in waste reduction in practices like, waiting time; over-production, inventory of finished products, transport of unnecessary materials etc. Once the removal of unnecessary process steps is made, the organisation is able to improve productivity and involve employees to contribute in the concept of proposing ideas for making things better.

3.10 Chapter Summary This chapter explained in detail the four improvement methodologies, i.e. Lean, Six-Sigma, TQM, and BRP. The expansion of quality began with TQM, and the opinion of continuous change came into the leadership awareness. Total Quality Management was founded on Deming's 14 points and it was emphasized that TQM has been in effect in numerous dimensions, like performance, quality, and customer aspects. While on the other side, Business Process Reengineering is a vital reconsidering and essential restructuring of the company’s processes to achieve enormous enhancements. Six-sigma is explained as an enhancement model that acknowledges deficiencies or difficulties in organisation’s processes. This technique categorizes and lessens the foremost bases of deficiencies to achieve improvements in the processes. It was discovered that Motorola was a first company to adopt the Six-Sigma notion. This is the reason that led other companies like Ford, American express and others to also implement this quality improvement tool. It is also noted that there are businesses that profited from implementing Six-Sigma in their money related tasks. It

52 has been recorded that service companies that apply Six-Sigma have drastically improved on services like customer handling time, time taken to answer calls or to time taken to assist the client, productivity etc.

Lean is also discussed in detail and characterized as an arrangement of thoughts and techniques that lead companies to continually improve the products, they offer by improving the necessary process steps while reducing the ones that do not add value. It is further added that lean is swiftly spreading worldwide because it is a straightway available answer that is able to intensely improve the organisation’s performance and production, while it hugely lessens errors, waste and on-the-job accidents. Lean is an idea concerning ‘achieving more with less’, using the best sequence with a little staff involvement. The chapter further explained the 5 lean principles, i.e. identify value, Value stream, flow and pull.

CHAPTER 4: INTERNATIONAL AIRLINE INDUSTRY

4.1 Introduction This chapter will discuss in detail the airline industry from an international viewpoint. It further explains the importance of airline industry and its impact on the global economic growth. This chapter will focus more on United Kingdom and United Arab Emirates where we will be discussing in detail their historical background and how their airline sectors influence and contribute to the economy of their countries.

4.2 Overview of the airline industry Airline industry is not only offering services, but also customer-centered and it always finds ways of understanding the customer needs better in different stages of their services. To measure passenger satisfaction has been a standard practice in the last two decades, Lin (2003). Only a limited number of studies have be done to investigate the effect of lean implementation in this sector. From the beginning of the airline industry in the early 20th century, this industry has gone through major alterations. This is a sector that has been flexible and robust through significant challenges (Ukpere et al., 2012 and Stephens and Ukpere, 2011). They further added that the landmark alterations in the market environment are the results of the ever more grounded rivalry in the airline business. The study done by Teichert et al. (2008) affirms that while the sector used to be ruled and controlled by government, currently it is organized by focused offensives of organizations.

Aguirregabiria and Ho, 2012 mentioned that in the airline industry, service reliability is a frequent theme, highlighted by both government reports and mass media and on-time performance and cancellation rates are two important metrics that consumers and investors consider when assessing airline performance. Because of the importance of managing cancellations and delays, airlines use various tools, such as cushion times, on-time incentive programs, and plane maintenance, and they frequently make tangible investments to improve their service reliability

4.2.1 Airline industry structure The structure of the air travel sector is categorised by an oligopoly showcase organization, a limited competition whereby services are offered by a small number of firms. Oligopoly companies have market influence to put or change prices for their services by making various yield stages, Rubin and Joy (2005). Since oligopoly firms produce more or less the same outputs and contest with their industry rivals, any change an oligopoly organisation makes is observed by its opponents. Subsequently, competitors may respond by reducing prices or other efforts to improve market share.

Rubin and Joy (2005) further added that this is the reason most companies in an oligopoly are interdepended, and each is aware that its market control is frail to disintegration by contenders or new market contestants.

Generally, before an air company starts to operate global services to countries, the officials must first negotiate the extent of the contract agreement with the government of the destination country in the form of a Bilateral Air Service Agreement (BASA). This agreement (BASA) is finalised by the two contracting countries which certificate commercial civil flight facilities amongst the two nations. The contract permits the chosen carriers of those states to run business flights that cover passenger’s transportation among the two countries.

The three different core carriers as explained by Cento (2009); Wafik et al., (2017); Chen & Chang (2005); Khuong (2014); Widmann (2016). Are summarised below:

a. Full-Service Carriers (FSC) Full-service carrier (FSC) is an aircraft firm that is built up from the before state-claimed hail bearer, through the market deregulation practice, into a carrier business.

b. Low-Cost Carriers (LCC) The idea of low-cost carriers or LCC started in the United States with Southwest Airlines in the early 1970s. Southwest Airlines was the first “No frills “airline. The literature reveals numerous related explanations of low-cost carriers; well known as a low fare or no-frills airline. Low cost carriers rely on a basic occupational model as compared with full service carriers.

c. Charter Carriers (CC) This is a carrier that runs outside normal timetables; it is normally hired for specific event by a particular customer or a small group. It operates from airports or designated terminals where there are no timetable services.

d. Airline Passenger Travel Cycle The aircraft benefit is an arrangement of services in which the desires and experience of clients may change at various stages. Taking a look at the environment of air transport, air travel is divided into two phases: ground services and in-flight benefits. Ground services comprise of social occasion of data, obtaining of tickets, reservations; air terminal registration and post flight services. The nature of in-flight service merits more consideration by the airlines simple because passengers spend most of the time flying.

➢ Aircraft benefit is a chain of services in which each of the services makes a different experience for passengers. The inflight stage adds a noteworthy value to customer’s experience (Wafik et al., 2017). According to Gliatis & Minis (2007) the service process involves sub-processes where by each sub-process contributes towards a service and affects customer experience. The research done by Wafik et al. (2017) indicated eight steps of passenger travel cycle: these steps are: purchasing of the ticket, pre-flight services, registration, air terminal services, take-off, inflight services, landing, and post entry services.

➢ The first step of travel cycle is ticket purchase. Now people prefer to buy the tickets online or through their travel agencies. Many passengers buy their tickets with no direct communication with the carrier and their first interaction with the carrier occurs at the check- in step. Wafik et al. (2017) purchasing of the ticket contains several phases: information gathering, selecting the ticket and purchase process.

➢ The second step of travel cycle is pre-flight services. There are other services provided by airlines prior the take-in; nevertheless, these services differ from airline to another. These services include, email or text message reminders sent to customers, (Wafik et al., 2017). Furthermore, in other scenarios air companies give customers a chance to bring their baggage a day in advance for example Finnair (El-deen et al., 2016). The main qualities for pre-flight services step consist of: accessibility of pre-flight services (i.e. early luggage registration, text or email reminders), airport convenience, and car parking services.

➢ Check-in is the third step in this cycle. The check-in step has gone through numerous changes and is almost completely enabled by the technology. The check-in step has been made easier as we now have options to check-in online, through text messages or at the airport check-in machines, (Wafik et al., 2017). The key attributes for check-in step take account of comfort, precise and speed check-in processes and availability of more than one option to check-in.

➢ The fourth step of the travel cycle is airport services. These services include security checks, meal services and airport lounges. Airport services may also take account of traveller’s useful information services, money exchange booths, and associations with close hotels, and so forth (Wafik et al., 2017). This may also include communication via short message services

or social media to let the travellers be aware of any delays where necessary. The key qualities for airport facilities include the airline living room, the airport amenities.

➢ The fifth step in passenger travel cycle is the departure services. The attributes of this step encompass accurate flight departure and arrival time, likelihood to receive vouchers for refreshments, hotel accommodation, or rebook a flight (Wafik et al., 2017).

➢ The sixth step in passenger travel cycle is on board services. The attributes of this step include the in-flight entertainment services, good quality refreshments of the airline, well- mannered and caring crew; neat and comfortable facilities and seats, (Wafik et al., 2017).

➢ The seventh step in the travel cycle is the arrivals. Arriving in time is an important factor of client’s view of a good quality of service, (Wafik et al., 2017).

➢ The last step in the passenger travel cycle is post-arrival services. These services encompass information about lost baggage, and assistance on arrival (Westwood et al., 2000). The main factor in this step is mishandled baggage, this includes, missing, damaged, or late delivery of the luggage (Gilbert & Wong, 2003). It is vital to understand that most of the time airlines subcontract their luggage services to third party supplier (Wafik et al., 2017). However, the airline should know that from the customer’s perception, it is still an airline offering those facilities, and this is the reason it is vital to ensure that the facility is standard in this phase as well (Osman & Ashraf, 2014).

In a different way, Khatib (1998) has categorised the above eight steps into three core phases: pre- flight, in-flight and post flight services. Pre-flight services encompass services of booking and buying tickets, airport amenities, check in facilities, and security measures. In-flight services encompass cabin staff service, quality of refreshments, airplane features, reading material, and security conscious. Post flight services encompass arriving on time, waiting for luggage, lost luggage; responsibility of the airline for a delayed passenger, effective complaint structure; staff assistant on arrival, and connections and transit services.

4.2.2 The importance of airline industry This is a main service segment that provides support to other economic segments like, international trade, tourism, manufacturing and businesses. It also contributes to national GDP (Belobaba et al.,

2009). They further identified it as strategic to the US economy. The worldwide airline industry has a strong impact on a worldwide economy. It provides services to every nation worldwide, and impacts positively on other business sectors, Belobaba et al. (2009). LCCs offer limited services, yet they make an effort to create incomes from the sale of additional amenities and on-board goods. Pate & Beaumont (2006), the business is aware of the significance of in-flight transaction to their profit margins.

4.2.3 The impact of airline industry on global economic growth About 62.7 million people’s jobs in the universe are directly and indirectly created by the aviation (Willer and Lernoud, 2017). According to their estimation, about 3.37 million people in the universe are employed to provide services like managing airports, airlines and navigation services and further 1.1 million for designing and building flying machines. Airline business has become the main economic and employment Influence to world GDP when compared to other sectors. It turned out to be greater than food industries, global chemicals, textiles, pharmaceuticals, and automotive industries. Airline industry has become the main component of worldwide financial growth. According to (ATAG, 2014), it has become the most important economic sector, together with the leisure industry, taking into account all direct, indirect and prompt financial effects. On top of the jobs offered by airline, there is approximately 5.5 million created worldwide because of the airline industry, such as car hire, retail, government agencies etc. (Willer and Lernoud, 2017). Airline business is important for leisure industry because above 50% of total international travellers and about 35% of products of international trade are shipped through airlines.

4.2.4 Air traffic trends Most people are flying than ever before. Due to flight convenience, the number of UK passengers increased in the last five years by over 20%. In 2016 UK recorded over 269 million travellers passing through United Kingdom. With the speed of growth in UK it is estimated by the HM Government report 2015 that the number of travellers is estimated to increase to 410 million in 2050. According to EU Report 2016, in 2016 the air traffic increased by 6.3% which is equivalent to 3.7 billion worldwide. This increase was due to 3.1% growth in the worldwide economies and decrease in flight prices due to fuel prices averaging 43% lesser in 2015 compared to the previous year. 2015 was an outstanding year for global air travel industry, in terms of number of travellers, EU Report 2016.

In 2017 the airline industry was characterised by two turning points. The first one was the election of the United States president Donald Trump in 2016. The second one, the land of the international

58 airline industry was altered by the beginning of the Brexit situation that marked a new era, (Blominvest Bank, 2017).

4.3 UNITED KINGDOM (UK) CASE

According to National Statistics 2017, the UK population on 30 June 2017 was estimated to be above 66 million people, which is higher than 2016. They further added that 59% of the UK population is international colonization and only 41% is UK natural birth minus death, even so UK has the 3rd highest population in the European Union. UK is served by over 50 airports offering commercial flights, with many more airports offering cargo and non-scheduled aviation services.

Ireland was united in 1801 with Scotland, England and Wales after the Act of Union of 1800. This union formed United Kingdom of Great Britain and Ireland. They then created a new version of the official flag, nowadays known as the Union Flag. To date the flag is used in UK as the country’s official flag (Yarrow, 1995).

4.3.1. Historical background of the UK airline industry According to the study done by Yarrow, 1995, The United Kingdome aviation is dominated by BA (British Airways). In 1992 BA was responsible for 64% of accessible mass kilometres. British Airways was when two major UK airlines, British Overseas Airways Corporation and British European Airways joined together in 1972. Prior to this merger, British Overseas Airways Corporation was operating on long-haul routes and British European Airways on short domestic and European routes. Unfortunately, both airlines were not productive and suffered from ineffective fleet arrangements and little profit. Nine years later after the merger, they selected a new management team, under the chairman of Lord King.

The company was re-arrangement and the new plan included the following structure changes:

➢ Transformation of British Airways’ fleet of air machines by getting new, large air machines and the speeded-up clearance of older carriers. ➢ Developments to run systems and terminal facilities ➢ Extensive elimination of employees through early retirement, rearrangement and dismissals. British Airways was public limited company until April 1984 when it started to be a public limited company in willingness for commencement. Since then BA started enjoying the same legal forms as most the rest of the large companies that are in the private sector, even though the government authorities held 100% of the shares (Yarrow, 1995).

Today BA transports on an international level and is in private ownership in de-regulating markets, British Airways, 2008.

4.3.2 The United Kingdom economy According to Molle, 2017 the growth in the worldwide economy was stronger and more synchronised in 2017, with more countries recording strong rated of economic growth. Just like in any other country, the core measure of economic growth for UK is Gross Domestic Product (GDP). UK’s economy has experienced a degree of resilience. With growth increasing to 1.7% in 2017 because of good export performance. The aviation industry in UK plays a significant part in country’s economy. According to HM Government report (2018) the UK aviation contributes not less than £22 billion to the UK economy every year. It is projected to provide above 500 thousand jobs all over UK, HM Government report 2018 The UK Airline industry contributes close to 8.7 billion in UK tax. According to Willer and Lernoud, 2017 UK’s airline, industry generally performs well when compared to the airline industry of other countries.

As emphasised by HM Government report (2018) the industry needs a variety of skills for different roles like, cabin crew, piloting, air navigation, maintenance, construction, air traffic services, and operations. Employment in overall airline industry is spread across all areas of UK.

Below is the summary of United Kingdom aviation contribution to UK employment and skills according to UK Aviation industry socio-economic report.

Table 4.1: Employment and skills (UK Aviation industry socio-economic report). Airline Contribution British Airways From 2010, more than 600 students were offered apprenticeships, with many graduating to permanent jobs. The airline is also offering a training course called British Airways Future Pilot programme. EasyJet In 2015, they started a 2.7-million-dollar teaching centre with the target of recruiting 1.140 crew. Flybe In 2010, they opened their own training academy, offering services like, engineering

apprentice workshop, cabin crew training facilities and pilot training. They also run a shared Engineering Diploma programme with Exeter College. Manchester Airports Group (MAG) They created employment and skills academies at Manchester, East Midlands and London Stansted in which the academies trained 651 people and placed 651 into jobs in 2014 and 2015. AGP The regional aerospace alliance and about 50 . the industry demands. AGP is supporting the young individuals who want to pursue career in aerospace. These include over 500 bursaries awarded to students at Masters-level in aerospace engineering, traineeships, apprenticeship and work experience.

Thomson Airways (UTI Group) They offer joint in-house accredited programmes with Skills Funding Agency. Airbus Airbus in UK is a supporter of Industrial Cadets. Just above 160 females graduated through their project. Birmingham Airport The partnership created more than 400 job opportunities at the Airport. Bombardier Bombardier supports a number of educational initiatives, like Women into Science, Engineering and Construction (WISE).

4.3.3 Factors affecting the UK airline market The aviation is affecting by different factors, of which the positive factors that affect the industry will be discussed more under the country’ economy. Below is the summary of the factors that affect the aviation negatively.

a. Aviation’s carbon footprint The aviation carbon footprint is a worldwide environmental challenge. It is not easy to get an accurate amount of carbon emissions associated with the airline industry. However, as estimated by White (2016), in 2015 the international passenger airline accounted for about 1.5% of synthetic carbon dioxide emissions, which is around 456 million tonnes, which then represented about 58% of the overall CO2 emissions by the airline industry. According to White (2016) it is predicated that the international demand of airline services will average around 3.4% between years 2015 -2050. This increase will then result in increase of carbon dioxide emission associated with international aviation to around 40%. However, if market liberalisation carries on with the same historical pattern, carbon dioxide emission will go up by over 130% and if the liberalisation goes up as a quicker rate, the carbon dioxide emission will go up by 180% between years 2015 – 20150.

They further mentioned that the Civil Aviation Organisation (ICAO) is working on measures and strategies that can be implemented by the airline to limit its impact on the climate change as means of promoting carbon neutral growth. These measures and strategies include, introducing carbon offsetting structure and setting of carbon dioxide efficiency standards for new aircraft. Airports have also introduced a programme called Airport Carbon Accreditation Programme (ACAP) under the support of Airports Council International (ACI) to inspire airports to control the carbon dioxide emission under their supervision. In October 2017, about 199 airports worldwide were already participating in this system, of which 35 of them had received highest level certification, these include Manchester, Gatwick and East Midlands. Another 43% had second highest level of certification; these include London Stansted, Heathrow and London city (White, 2016). Government’s current policy regarding the airline related air quality is to find enhanced international standards to minimise emissions from air machines and to encourage the airline industry to implement measures to minimise the carbon emission (White, 2016). Carbon dioxide emission is tacked at the sectoral level through ICAO. There are measures in place to achieve the goal of carbon neutral growth for aviation from year 2020. These measures include operational measures, sustainable alternatives fuels, market-based measures, technological improvements. It is important to take action to address carbon emissions from aviation, if the industry wants to meet the international goal set out in December 2015 in the UN climate change.

b. Aviation Noise Aviation noise is a basis of constant irritation to people who stay closer to airports or below airport flight routes and this noise can be a highest environmental cost (White, 2016). Even though there are benefits of living closer to airports, such as employment, easy access to airports, aviation noise can negatively affect those who live near airports, in terms of sleep distraction, irritation and health associated issues (White, 2016). However, the current engineers are now producing aircrafts that are less noisy. Airline industry has made extensive developments in minimising the aviation noise level with better technology, (White, 2016; HM Government report, 2018).

The level of fleet upgrade is not just about the available technology; it is also about the economic benefits related with investing in new aircrafts than the old ones.

According to (White, 2016; HM Government report 2018), all aircraft noise should be managed by the internationally agreed ICAO balanced approach. This approach consists of the following four elements:

➢ Minimising noise through technological advances to air machines ➢ Minimising noise through improved operational processes ➢ Restricted operations on air machines, such as taking out the nosiest air machines, night restrictions and noise measures. ➢ Land use planning, charging and compensation.

4.3.4 Aims, objectives and strategy of UK aviation industry According to HM Government report 2018, UK government is working on a new aviation strategy for the country. The industry strategy aims at setting out the long-term goals for aviation policy making to 2050 and after. This strategy focuses on consumers and covers the entire United Kingdom. The interest is on finding ways of assisting the UK government to make a difference in the country. Ways that will help the government to take into account passengers, private fillers, freight sectors, airports, communities, environmental groups and industry organisations. The new strategy aims at reviewing the aviation sector, its challenges and opportunities.

The strategy has the six following objectives:

➢ To assist the industry to work for its customers. ➢ To ensure secure and safe trips. ➢ To create a worldwide and connected Britain. ➢ To motivate economical markets.

➢ To support development while dealing with environmental impacts. ➢ To support innovation, technology and skills.

4.3.5 The importance of airline in UK United Kingdom is the key member of the International Civil Aviation Organisation (ICAO), the United Nations agency that is in charge of managing and regulating international aviation and a permanent representative on ICAO (HM Government report, 2018). UK is one of the top connected countries worldwide. Because of increase in flight demand in UK, in 2016 they added new routes to Costa Rica, Chile, Iran, Iceland, United States, Peru and Sri Lanka. Airline industry is a main fragment of the government’s country plan, with the aim to create a self-assured country that embraces the world. Airline is important to the way they present the country to the world. Leisure travel plays an important role in airline market, with a fixed number of individuals who travels just for pleasure. In 2015, UK recorded around 80% of the passengers who flew to and from UK for leisure. According to HM Government report (2018), it is estimated that tourism contributes £59 billion to the UK economy.

United Kingdom has a big aviation-manufacturing sector that specialises on important products like aircraft engines and wings. The airline manufacturing is part of an important global supply chains (White, 2016). United Kingdom has a world leading aerospace sector.

4.3.6 Competitiveness of UK airline industry London is the foremost hub city in the European region and remains the appropriate and important destination for doing business globally, HM Government report 2018. This is because London airports have much better connections to important business centres of the world than other European cities. According to HM Government report 2018, London Heathrow is the world’s busiest airport when measures by internal passenger traffic. Heathrow offers more flights to countries like South Africa, Asia, India, Gulf States, and many more countries.

The below diagram shows the connectivity of UK to other cities. The connections show the connectivity of United Arab Emirates with the world and the big cities.

Figure 4.1: The connectivity of UK to other cities Oxford economics. (UK country report, 2011).

4.4 UNITED ARAB EMIRATES (UAE) CASE

United Arab Emirates is a nation in the Mid-East simply called Emirates by many people. UAE is an alliance of seven emirates established in 1971, with Ras al-Khaimah being the seventh member since 1972, BTI Country report 2018. It is an Arabian Peninsula country established along Arabian Gulf. According to Federal Authority for Competitiveness and Statistics, the UAE’s population is estimated at 9.121 million people, which contains 2.823 million females and 6.298 million males. In December 2016, the country celebrated its 45th National Day underlining its development and persistence as a federal entity and its place as a globally recognised member of the international communal.

4.4.1 Historical background of the United Arab Emirates Airline industry The authorities of the UAE initiated a shared airline in 1974 named Gulf Air. However, the Dubai authorities did not come to an agreement with Gulf Air’s demand to leave its open skies policy. Gulf Airline reacted to this by decreasing regularities and volumes between Dubai government authorities around 1984 and 1985 with no advance announcement to Dubai Authorities.

Today United Arab Emirates has two well-known airlines: Emirates Airline and Etihad Airways. Emirates was founded in 1985 and is based in Dubai (Emirates, 2015). Just after six years of operations, Emirates was only operating between 23 destinations and planning to expand even more. Emirates was the primary airline to have displays with on-board entertainments in all carriers and classes in 1992, Wilson, 2007. He further adds that in 2000, Emirates was stated to have made $3.7 billion turnover. In 2010, Emirates flew above 2400 travelers each week to 105 capitals in sixty- two nations and six continents. It has over 28 000 workers, this includes 13 000 cabin team fellows. The success of Emirates is crucial because of the determined approach articulated by the governing family of AL-Naktum to convert Dubai into a provincial core of trade and leisure industry in the Middle East (Nataraja and Al-Aali, 2011). Today Emirates is acknowledged for its luxuries designs, primary chalets with fancy lounges and refreshing shower spa’s on board. Today Dubai is recognised as the biggest center in the Middle East area with mainly worldwide travelers. Emirates has been awarded above 400 worldwide awards in acknowledgement of its on-going attempts to provide supreme world class customer service, by making use of modern technology, giving excellent customer service and comfort for its travelers, (Nataraja and Al-Aali, 2011).

The second worldwide known UAE airline is Etihad. It is the UAE’s national Airways, based in Abu Dhabi. Etihad means United and serves as a sign of unity between the seven emirates (Abeyratne, 2008). Etihad was founded in 2003 and it continues to grow as the fastest developing national air company in the history of airlines. Nowadays, Middle East and Dubai are generally getting global travelers and giving services as one-stop hub continents based on the passenger air traffic (Wilson, 2007). In March 2002, UAE’s government signed a contract with United States about the open skies policy, which will permit the local carriers between US and UAE to fly to and from their counties, (Nataraja and Al-Aali, 2011).

4.4.2 UAE’s economy Shaikh (2012) defines economic development as the practice of enhancing the quality of human life by growing per capita revenue, which in turn reduces poverty. He further adds that this process embraces improved education, better health and nutrition, good maintenance of natural resources, a healthier environment, and a wealthy cultural life. UAE is one of the utmost important destinations for investment, economics and trade activities. All seven emirates conform to the primary UAE vision 2021 even though they don’t have similar economic conditions and priorities. Dubai executes as the country’s moneymaking centre while Abu Dhabi is in charge of most of the country’s oil, gas reserves and controls several national savings. Dubai and Abu Dhabi will continue to contribute largely in UAE’s GDP, with Dubai attracting massive foreign investments as it prepares to host the historic 2020 World Expo.

The economic activity in the UAE has a possibility of being threatened by the indirect effects and consequences of clashes in a number of countries. The increased level of fights will also increase doubts in the country’s economy and a go-slow in investment rate. Due to this, the growth rate in UAE has decreased as a result of weak oil sector. The low price oil is putting pressure on the UAE economy. According to Federal Competitiveness and Statistics Authority, the UAE’s GDP increased by 3% at the end of 2016 compared to 2015. 2017 was the most difficult year in UAE than other years due to factors like reduction of oil production, regional conflicts, exit of Britain from the European Union, the election of Donald Trump as the president of United States etc. Even though the appointment of President Donald Trump was the celebration in United States, it was not the case with other countries like UAE. The Federal Commission for Competitiveness confirmed that the inflation in the UAE increased in August 2017 by 1.6% compared to August of 2016. They also noted that sectors like housing, electricity and water recorded a high inflation rate in August 2017 than other sectors. The economy of this country is informed by various anthropogenic activities such as the tourism, education, transport, manufacturing, natural resources textiles, agriculture, energy, information and communication technology (ICT), building and construction, among other sectors. The joined effects of these sectors feed the macroeconomic indicators of national economic growth as reported by the National Bureau of Statistics (KNBS, 2017). We have discussed few key sectors below:

• Tourism. This sector has contributed a big part in the victory of UAE’s economic diversification. Abu Dhabi’s 156 hotels and 634 Dubai’s establishments are playing an important part in the UAE economy. The country’s two famous airlines, Emirates and Etihad as well as the continuous improvements in the UAE’s airline industry have played a notable

role in advancing the leisure industry and they are the main contributors to the economy of United Arab Emirates. In the analysis directed by the Dubai’s Chamber of Commerce and Industry, they confirmed that spending in UAE’s tourism sector will increase gradually and reach above USD 56 million by year 2022.

• Agriculture. This sector is a challenge in the United Arab Emirates due to arable land and water resources. After the government’s massive efforts to improve agriculture’s productivity, the sector started to recover. It improved from 4000 farms recorded in 1971 to 35,704 farms in 2011. The demand for foodstuff is estimated to increase because of the increase in the country’s population and the strong economic growth. For this reason, the food security is easily prioritised and gets the government’s attention. • Manufacturing. The United Arab Emirates manufacturing sector is reported to be exporting 53% of the country’s overall non-oil merchandises. It is expected to subsidise 25% of the total GDP in 2025. This sector is led by Dubai, instituting an industrial plan through the Dubai Industrial Park range over 55 square kilometres and houses over 680 businesses. After the execution of Dubai Industrial Strategy, the manufacturing sector is estimated to generate 27 000 job opportunities and contribute to Dubai’s GDP by AED 165 billion in 2030. • Unemployment. The UAE workforce predication is 6330.54 thousand workers of the total population. The minimum age requirement for employment at UAE is 15 years and above. The rate of employment is 91% and 42% of the total male and female population respectively. The unemployment rate in UAE dropped in 2016 to about 3.7% as compared to 3.8% of 2013.

Relative Distribution of employment by economic sector in 2016 (%)

Extractive industries 31%

Public administration & defense 13%

Wholesale, retail trade & repair 9%

Construction & building 8%

Transformative industries 7%

Transport & storage 6%

Financial activities & insurance 5%

Professional & scientific activities 4%

Other 3%

Accomodation 3%

Information & communications 2%

Human health 2%

Education 2%

Administrative & support services 2%

Real estate activities 1%

Electricity, gas & water 1%

Agriculture 1%

0% 5% 10% 15% 20% 25% 30% 35%

Figure 4.2: Relative distribution of employment by sector: (UK country report, 2011).

4.4.3 Competitiveness of the UAE airline industry Emirates has been awarded several times, this include twenty-eight record wins as the Best Cargo Airline Middle East at the annual cargo airline awards. Emirates has also been awarded at the IATA World Cargo Symposium in March 2017 for iQ certification in acknowledgement of their efforts to offer their clients with more transparency on the status of their exports and for eliminating possible errors in their processes. Emirates has also invested in launching a dedicated 24-hour working Cargo Operations Control Centre in Dubai that uses live cargo data and Cargo iQ metrics to track a delivery’s excursion against ideal route map (Emirates, 2017).

The role of the alternative fuel is understood in UAE, Etihad Airways has emphasised on their report 2018, that the company is ware of the role that alternative fuels will play in future. The UAE’s airline is the founding partner of Sustainable Bioenergy Research Consortium. UAE airline is determined to improve fuel efficiency by a yearly average of 1.5% by 2020 and to reduce the net of carbon footprint in 2050 by 50% compared to 2005.

4.4.3.1 UAE airline competitiveness in 2017 The World Competitiveness Yearbook Report measures the countries’ competitiveness through four key subjects: financial performance, government effectiveness, effectiveness of the business environment and the infrastructure. In 2017 United Arab Emirates was ranked the 10th worldwide most competitive country according to the World Competitiveness Yearbook. This was published by the Global Competitiveness Centre which follows the International Institute for Administrative Development. UAE greatly improved in 2017 compared to year 2016, below is the brief comparison between 2016 and 2017 of UAE’s competitiveness.

Table 4.2: 2016 vs 2017 of UAE’s competitiveness (UK country report, 2011).

Performance 2017 2016 Business efficiency 2nd Place 11th Place Economic performance 5th Place 12th Place Government efficiency 4th Place 7th Place

At the level of the themes and indicators in 2017, the United Arab Emirates has attained an exceptional performance. They achieved the fourth place in the theme of government efficiency. The findings from the report show that the United Arab Emirates’ economic policies have prospered in launching a concrete grip amongst the world’s foremost economies

4.5 Chapter Summary Throughout the universe, this include United Kingdom and United Arab Emirates, the core measure of the economic is Gross Domestic Product (GDP). The aviation is responsible for an imperative part in the country’s economy. Because of the flight convenience, the number of travellers is increasing yearly and this can also be related with the increase in population. Due to the high speed of population growth in UK, the amount of travellers is estimated to rise to 410 million in 2050. The industry needs a variety of skills for different roles like, cabin crew, piloting, air navigation, maintenance, construction, air traffic services and operations, therefore the airline is expected to play part in developing skills so that it may sustain and maximize their performance and services.

Even though the aviation seems to be all good and convenient to people, it has negative effect on people such as carbon footprint and aviation noise. The aeronautics carbon footprint is an international environmental challenge. The International Civil Aviation Organisation is working on processes and approaches that can be executed by air travel companies to minimize its effect on the climate change with the aim of encouraging carbon neutral growth. These processes and approaches include, presenting carbon offsetting structure and setting of carbon dioxide efficiency standards for new aircraft. A programme called ACAP has also been introduced by Airports under the support of ACI as means of inspiring airports to maintain the carbon dioxide emission.

The aviation noise is also noted an issue that affects the lives of human being living around airports. Although living closer to airports comes with benefits such as employment, easy access to airports, the aviation noise can negatively affect those who live near airports, in terms of sleep distraction, irritation and health associated issues. Nevertheless, the current engineers are in the mission of producing airplanes that are less noisy.

4.6 Lesson learnt In this chapter, we identified three different core carries, namely: full service, low service and charter carriers. In the airline passenger travel cycle, it is imperative to measure, monitor and sustain the good quality service to customers, because the airline service is a sequence of services in which expectation of customers may vary at different stages. Airline is an important industry because it provides support to other economic segments like, international trade, tourism, manufacturing and businesses and contributes to national GDP. This chapter also reveals that million of jobs in the universe are directly or indirectly created by aviation.

CHAPTER 5: AIRLINE INDUSTRY ON AFRICAN SCALE

5.1 Introduction This chapter covers the African viewpoint, emphasising more on Nigeria and Kenya. We explore the importance of airline industry in Africa as a whole and the Airline’s impact on African economic growth. Historical background of Kenya’s and Nigerian airline industry is also explored and how their airline industries contribute to their country’s economy.

5.2 Overview of the African Airline industry In Africa, air transport is an important category of transport because of the weak land transportation systems all over the continent, whereby in many cases air transport is the only sustainable alternate. In 2010 Africa presented the second highest traffic growth region worldwide at 12.9%. The air travel industry in Africa has encountered many glitches over the last three eras; the amount of these difficulties is because aviation is very vibrant, and its rules and regulations are standard globally. According to Rahim (2016), in the late 70’s and early 80’s the air travel industry in Africa was faced with problems. Some of these problems were mishandling of national airlines, political interference, high working expenses and using out-of-date tools. Optimistic policies were necessary to stop the failure of African national carriers. In October 1988, African ministers accountable for civil air travel met in Yamoussoukro, to decide on how airlines should be utilised as a significant mechanism to grow socially and economically in Africa and to open up African skies. The Airline industry policy is changing from regulation to deregulation and so on (Ssamula, 2008). Due to these changes, many airlines are failing; these include the Nigerian state carrier in 2002.

5.2.1 The importance of airline industry in Africa Flights travel moving to, from and within South Africa generate economic footprint, measured by its input to jobs, tax revenues and GDP. The links made amongst capitals and countries symbolize an imperative infrastructure strength that produces profits through allowing foreign direct investment. Developments in connectivity feeds to the act of the country’s economy of the wider economy through improving its total level of production. Improved connectivity contributes South African- based business big access to foreign markets (Ssamula 2008).

5.3 THE KENYA CASE

Kenya is home to 46.6 million people, situated strategically within the East African Community of countries (EAC) between Tanzania, Uganda, Ethiopia and Rwanda.

5.3.1 Historical background of Kenya’s airline industry economy Air transport in Kenya, especially for passenger transportation, has been previously seen as expensive and for the elite – far-to-reach for ordinary folk. However, that has changed in the recent past due to the challenges in regard to population growth and inadequate land transportation, which have been used as advantages for the industry in question. Advances in aviation have also created a space for the country’s airline industry to grow substantially in the recent past, spanning from the first aircraft to take to the skies in 1929 (Irandu and Rhoades, 2006).

The first domestic air travel service in Kenya was a private one, established in 1929. The company was called Wilson Airways, and it was headquartered in Mombasa. In 1932, the transport company offered inter-regional flights between Nairobi and Dar es Salaam via Zanzibar and Tanga. This allowed for flight links to other routes flying from Cairo to Cape Town. Further domestic routes were created across other Kenyan cities such Kisumu, and also Jinja along with Nakuru, creating an East African regional flight network. The unfortunate advent of World War II in 1939 resulted in the liquidation of Wilson Airways, and soon afterwards it was replaced by a larger regional conglomerate, East African Airways Corporation (EAAC) in the first calendar month of 1946. This company was operated by three countries, i.e. Tanzania, Kenya, and Uganda, operating until 1977 when the EAC (East African Community) ceased to exist, and independent national airlines were formed by the separate countries.

On January 22nd of that year, Kenya Airways as headquartered in Embakasi, Nairobi, was opened as wholly owned by the government; and commenced operations on February 4th. By 1980, the national carrier employed 2 100 staff, with routes operating between some cities in East, Southern, and North Africa; Europe, the near and Middle East. Between 1982 and 1990, further expansion was seen into Burundi, Rwanda, Tanzania, Zanzibar, Malawi, and Ethiopia. One of the notable events during this period is the governmental discussions on possible privatisation of the carrier in 1986, and a Kisumu crash during a failed landing in 1988. The former was informed by the opinion that its performance and revenues could be improved by doing so. When the carrier began negotiations

73 with South African Airlines (SAA) to have flights commence between Johannesburg and Nairobi from January 1991, the privatisation talks were still on-going (Guttery, 1998). The International Finance Corporation (IFC) was appointed as advisor to the privatisation process by the government. Privatisation of the national carrier then commenced in 1995, awarded to KLM Royal Dutch Airlines after several interests by itself, SAA, British Airways (BA), and Lufthansa. Out of these, it was only KLM and SAA which made financial offers, and this resulted in the latter being chosen due to its long history of flights to Kenya. Furthermore, it edged SAA in regard financial valuation ($100 million vs $89 million) (IFC, 2012). The following staking of the shares was followed: KLM – 26%, Kenyan government – 23% and the remaining 51% was owned by the public. This was followed by an immediate listing on the Kenyan Stock Exchange (Guttery, 2001).

From then, the airline grew steadily, posting stable profits over the years. There was an unfortunate occurrence in January of year 2000 where the flight Kenyan Airways Flight 431 crashed into the sea. This accident took place soon after taking off in Abidjan, Ivory Coast, killing 169 of the 179 civilians on board (Bureau Enquites Accidents D’Aviation Cote D’Ivoire –BEA, 2001). At this time the carrier employed 2 780 staff, operating further routes from JKIA to more cities in the continents and regions as previously mentioned. Between 2012 and 2017, the company expanded operations by acquiring more aircraft such large Boeing 777s, in addition to the 787s and 777s purchased in 2005 and 2006. The following year was also marked by yet another terrible crash in Douala, Cameroon where all 114 on board perished mainly due to pilot error whilst on Flight 507 (Cameroon Civil Aviation Authority – CCAA, 2007). The company had learned from these occurrences, and in 2012, the government became the largest shareholder by furthering through a purchase of further shares to total 29.8%. The following year, the carrier grew by investing in the formation of a low-cost airline and cargo handling services (Air Transport World, 2013). The recent period of 2015 and 2016 was a difficult time for the country’s economy, and the airline was not exempt from the effects. The airline recorded significant losses where fingers were also pointed at KLM due to contractual agreements which seemed to affect the operations and viability of the carrier. As a direct result of cash flow problems, two aircraft were sold and some airliners sub-leased to salvage its financial standing and avoid going insolvent. These and further financial interventions proved fruitful as in 2017, profit margins were significantly improved, and good value added towards the transport and storage economic sector. Most recently, in 2018, the carrier launched its maiden flight to the U.S. (USA Today, 2018).

5.3.2 Kenyan economy The economy of this country is determined by various anthropogenic activities such as the tourism sectors, education, transport, manufacturing, natural resources textiles, agriculture, energy,

74 information and communication technology (ICT), and building and construction, among other sectors. The combined effects of these sectors feed the macroeconomic indicators of national economic growth as reported by the National Bureau of Statistics (KNBS, 2017).

The impact of these sectors has resulted in the Kenyan economy faring weaker in 2017 at 4.9% when compared to the prior protracted growth of 5.9%. This was so attributed to political instability and severe weather which affected both trade and economic productivity, respectively. This then affected food price inflation, increasing it from 6.3 to 8.0% in just one year as a domino effect from the increased oil and commodities prices. The economic growth of 4.9% is albeit better than the global average of 3.6 and 3.1% in the same duration period. In terms of regional economic growth, Kenya was closely followed by Uganda, and only surpassed by Tanzania at 6.5% where internationally China eclipsed the latter by 0.3%.

5.3.3 Economic performance by sector Some of the several sectors contributing to the economy have been previously highlighted. The most performing sectors in the economy are tabulated below in Table 5.1. The stellar performance of these markets can be attributed to the increased demand for the related products or services, together with increased governmental investment into the sectors. The top five performing sectors shall be discussed since they provided the most financial income during the year 2017.

Table 5.1: The top ten 10 performing economic sectors in Kenya for the year 2017.

Sector % growth in 2017 Accommodation and food services 14.7 Information & communication 11.0 Construction 8.6 Transport and storage 7.3 Electricity 6.9 Mining sector, real estate sector; and education 6.1 (all three were tied) sectors Human health and social work 6.0

• Accommodation and food services. This sector showed better year-on-year growth of 1.4% between 2016 and 2017 (13.3 to 14.7%). This sector could have been otherwise expected to post negative results as compared to the previous year of 2016 as a direct consequence of political uncertainties around the delayed national elections. This caused several countries to issue travel warnings to the country, but despite these, earnings related

to this sector were improved by about 20.1% (to KSh 119.9 billion). These positive tourism and related earnings were as a result of intensive efforts by government towards aggressive marketing strategies so that the country is seen as a tourism destination of choice. Further positive yields were seen by this sector international traveller numbers increased by 8.1% year-on-year, translating to 1.449 million in total number; and as hotels (and other accommodation) recorded an increase in bed-nights habitation to 7.714 million from 1.266 million less the previous year of 2016. Given these outstanding numbers, this sector was the best performing of all economic sectors in the country.

• Information and communication technology (ICT). The consumption of information in Kenya has been increasing fast in the recent past. This has increased the need for more sophisticated technologies and the betterment of communication methods. Such technologies that drove the growth as recorded in 2017 (11.0%) over 2016 (9.7%) are mobile telephony, e-commerce, tax administration, social media, and online trading, among many. The main driver in this sector was telecommunications, increasing by 12.7% in 2017, and this was informed by the massive consumption of telephonic voice traffic amounting to 44.1 billion (2.2 billion more than the previous year). Mobile money transfers (such as M-Pesa services), short message services (SMSs), and increase mobile broadband data usage/bandwidth, all had significant input in the financial revenues as greatly contributed to the economy by the ICT sector.

• Construction. Although construction as a sector saw decreased contribution to the Kenyan economy for two consecutive years in 2017, to 8.6%, it still maintained better performance than transport and storage, electricity, and mining, among others as presented in Table 1. The country recorded a deflated cement demand of 6.2 million tonnes in 2017, a decrease of 8.2% from the previous year. However, public investment resulted in increased construction of public roads, railways, and gravel roads. The construction of public roads increased by 6 100 kilometres in length year-on-year in 2017.

• Electricity supply. The demand in electricity has been soaring in the country for some time due to the rapidly growing economy as all sectors in it are energy-intensive, and as such the supply needed much demand. Kenya has heeded the call as evidenced by the value energy added to the economy in 2017 as compared to 2016. However, the economic contribution was revised for the former to 6.9 from the 9.5% of the latter year. The country largely depends of hydro-generated power but the long durations with sparse rains in 2016 resulted in low

energy generation of 2.78 GWh, a tragic decline of 29.9%. Other sources of energy were then used, which have high input costs, with such options including thermal sources. Other cheaper and renewable sources were also explored such as wind and geothermal energy generation which comprised 14.8% of the supply to the national power grid in 2017. • Transport and storage. This sector also reported dampened economic growth of 7.3% in 2017 from 7.6% in 2016. The main casualty in this sector was land transport, more specifically in the freight sub-sector. The sub-sector in question contributed significantly to the poor numbers as its growth was 1.9% as compared to the 5.9% posted in 2016 – a severely negative result due to deficiencies in demand for railway and freight services. Road transport using trucks and other heavy vehicles also recorded negative growth by 22.5% from 2016, and this was also hampered by the high fuel and oil prices. Air transport, on the other hand has consistently reported positive growth in the recent past. Since air transport was an anomaly in this sector, it shall be discussed further below to unpack what made it flourish when the rest of the sector performed dismally. • Air transport. The demand of air travel services grew as a direct result of technological advances in aviation as embraced by the country, and enhanced capacity handling due to governmental investment. This enabled good growth within the transport and storage sector after the disappointing 2014/15 period where extremely poor gross domestic product (GDP) contributions were recorded (0.0 – 0.3). The highly improved results in 2016/17 were attributed to the increased demand for air transportation where the revenues escalated by 14.7% to 183.1 billion as compared to 2016. The number of air travellers had increased by 3.5% during the said period, to 10.1 million passengers, where 39.5% of this number flew domestically and the rest internationally. These volumes of passengers injected high amounts of money to the growth of this sub-sector and hence that of transport and storage as a whole. Governmental investment in this sub-sector has seen several fully efficient air- strips being built in each county to ensure air-interconnectivity and ease of travel or transportation. The air strips that were being built in 2017 include Suneka, Tseikuru, Kabunde, Ikanga, and Nanyuki. In the same time period, the country was granted an international flight certification by the United States of America (U.S) due to improved safety and security protocol and implementation. The certification – Federal American Administration (FAA) – Inter Air Security Association (IASA) allowed for direct flights between the two counterparts. Further negotiations have taken part so as to allow airlines designated by the country to fly between the two countries through Mombasa International Airport (MIA) and Jomo Kenyatta International Airport (JKIA). These two international airports recorded

annual handlings of 1.7 and 7.3 million passengers in 2017, respectively, where others reported a total of 1.2 million.

5.3.4 Kenya’s airline and market The Kenyan national carrier has grown significantly since inception; having surpassed SAA as the best airline in Africa in 2016, it continues to do well in the continental market. This success has been attributed to the quality of service, and increased demand of the country as a tourism destination. International travellers extensively tour the country, increasing the number of domestic flights with notable destinations including, but not limited to Nairobi, Mt. Kenya, Mombasa, Maasai Mara, Kisumu, Lokichogio, and Eldoret. The airports and air strips in Kenya have also recorded increasing numbers of departures since 1999 as a result of tourism activity, and by 2000, the traffic had almost doubled in some cases. By this time, South Africa was receiving the majority of international visitors, growing from 5.19 million to 6.0 million. In the same period, international arrivals to Kenya grew from 1.0 million to 1.037 million. These numbers, due to the annual growth rate, are expected to reach 20 million by the year 2020, making the country one of the big tourism destinations in Africa (Irandu and Rhoades, 2006). Another reason for increased air traffic is the poor state of land transport in the country, further driven higher by the lack of accessibility of the remote areas by road. The transportation of perishable goods also contributes to increased domestic travel due to the inability to use roads due to the tender nature of the commodities. Air-freight such as the former and heavy precious cargo is also of great importance to be transported within Kenya. As a result, as much as 183 000 tonnes of cargo is moved between JKIA and other destinations in the country. This shows how important this segment is in the market (Irandu, 2008). Given the importance of passenger transport and freight by air, it is equally imperative for the country’s airline industry to position itself cautiously so as to benefit by enhancing market share and visibility. This will improve organisational performance and hence revenues and have meaningful economic contribution to the sector and the greater economy.

5.3.4.1 Market positioning Market positioning requires extensive internal and external understanding for effective service provision. Therefore, marketing as a philosophy, is important to achieve organisational needs and industrial demands – carving a niche segment in the market, and thus being easily identifiable as a superior service to current and potential competitors. It is therefore vital for organisations to know

78 exactly what services are required and how best to address and provide these services. Branding, pricing, advertising, promotions, location availability, credit terms, and personal sales assistance, among others comprise a good marketing mix (Irandu, 2008).

Irandu (2008) carried out a market positioning case study for Kenya Airways and made recommendations in this regard. It was highlighted that in order for the national carrier to favourably position itself in its market, it needed a proper plan in place towards a suitable marketing mix in regard to the product, product services, branding, and packaging as desired by the consumer. Quality of service is another important factor that was recommended so as form a competitive edge over other service providers whilst closely following competitors’ market trends and evolving as required, ensuring enhanced market presence and growth (Irandu, 2008).

Bearing the recommendations as noted above, the Kenyan airline industry needs to take full advantage of the growing tourism sector, as highlighted in a SWOT analysis by Njoya (2016). It was pointed out in the study that the country possesses various tourist attractions, a good reputation to hospitality, good tourist infrastructure/conferencing facilities/airline interconnectivity, and highly trained staff. Key weaknesses in the tourism sector which demand attention include policy and legal frame working, poor tourism research, insufficient security agent capacity, inadequate accreditation guidelines in tourism, and poor general infrastructure, among others. The key areas for exploitation were inclusive of E-business, water/soil transportation, emerging markets, conference/domestic tourism, and others. The key threats included, among many; appalling publicity by the media, cultural value degradation, high cost of business, and increasing regional tourism competition (Njoya, 2016). These are very important factors that contribute towards the success or failures in tourism and can be potentially disastrous if not taken into consideration by the country’s airline industry in terms of its market positioning strategy.

5.3.5 Factors affecting Kenyan airline market Below are the key economic sectors contributing to the Kenyan economy:

• Tourism. Tourism plays a huge role in job creation and economic movement and is therefore vital for associated companies to improve the country’s economy in which they function (Mhlanga & Steyn, 2017). Tourism largely depends on aviation and transportation; thus airline industry and the leisure industry are interlinked with significant interdependences (Mhlanga & Steyn, 2017); (Campbell, 2004). According to Mhlanga and Steyn (2016) when airlines dismiss their services due to various challenges, arranged holidays and air travel bookings are interrupted, resulting to many complications for travellers. If tourists arrive at their destinations faster and at a cheaper price, they are likely to travel more often (Eze,

2016). Thus Heinz & O’Connell (2013) asserted that, the dependability and reliability of airline is significant to the leisure industry Kenya Airways history goes back to 1946 with the creation of the East African Airways Corporation. In January 1977, it was announced as a business entirely owned by the Kenyan government. It was recognized as the national flag carrier of Kenya and attained some assets and staff of Est African Airways. It is usually called the Pride of Africa. Kenya Airways, (2011) shows that Kenya Airways is the leading operator on domestic routes. Kenya Airways runs sixty-seven flights a week to four local destinations: Nairobi, Kisumu, Mbombassa and Malindi. Internationally, it runs arranged passenger and cargo service to Twenty-four destinations with 45 flights a week (Kenya Airways, 2011). • Technology. The influence of technology on the airline industry can be studied from the heavy use of technology in aviation (Irungu, 2012). Technology is about the promptness, accessibility, convenience and security (Irungu, 2012). The role of air technology is vital, for both the safety of passengers or air traffic (Truxal, 2013). Technology creates a great platform of advertising through the internet, and other technologies allow a quick design of these advertisements (Irungu, 2012). More air companies are using of technology to service travellers, for example, social media has made it easier to communicate and interact with customers (Irungu, 2012)

5.4 THE NIGERIAN CASE

Nigeria is among the highest populated countries in Africa, numbering above 170 million persons. It is allocated in the West Africa sub-region. It is bounded in the east by Cameroon and Chad, in the west by Benin Republic, by Atlantic Ocean in the South and by Niger Republic in the Niger. This country has nine international airports. Murtala Muhammad Airport, Abuja, Nndamdi Azikwe Airport, Kano, Malam Aminu Kano Airport are the major airports in Nigeria (Emmanuel, 2015). He further added that Murtala Muhammed Airport is the main hub and the busiest country’s airport that accounts for about 80% of the total air travel operation services.

Table 5.2: Location of the international airport in Nigeria: (Nigerian Civil Aviation Authority, 2011). Airport Municipality Region

Ilorin International Airport Kwara North-Central

Jos International Airport Jos North-East

Maiduguri International Airport Borno North-East

MalamAminu Kano International Airport Kano North-East

Margaret Ekpo International Airport Cross River South- South

MurtalaMuhammed International Lagos South-West

Airport

NnamdiAzikiwe International Airport Abuja North-Central

Port Harcourt InternationalAirport Rivers South-South

SadiqAbubakar International Airport Sokoto North-East

The country possesses affluent and profitable investments; and a huge land mass of 923,768 km2 (Ismaila, 2013). As a result, Nigeria is the 32nd largest country in earth, with the ability to substantially affect the world’s international air transport industry (AFCAA, 2008). Nigeria vaunts twenty-three airports, four of them are international airports, Lagos being the main hub for West Africa. The country’s development is estimated to go up by 2.5% in 2018, and 2.8% for the 2019/20 period.

In 1988, the country’s air travel industry attempted deregulation when three privately owned airlines began programmed local air services in a form of controlled competition with the national carrier of that era (Akpoghomeh, 1999). Before the domestic deregulation, air amenities in Nigeria were described as unreliable and ineffective. Instantaneously following deregulation, the air services followed a new traffic growth path (Oluwakoya, 2011). Furthermore, an improvement in the number of private airlines from three (3) to fourteen (14) was observed. Passenger numbers also enhanced competition, prices, and service quality.

5.4.1 Historical background of the Nigerian airline industry The Nigerian airline industry dates back to 1925, this is when the initial flight landed in Kano. Since then, Air travel became an important part of the Nigerian’s socio-economic life (Emmanuel, 2015). He further states that the formal expansion of airline began during the Second World War in 1946

81 with headquarters in Lagos. In 1970, the industry received federal government special treatment. Nigeria’s airline sector is split into: Federal Airports Authority of Nigeria (FAAN), Nigerian Airspace Management Agency (NAMA) and Nigeria Civil Aviation Authority (NCAA). Nigeria has a total number of international airports and twenty-two domestic airlines, this excludes country’s military and private landing locations (Emmanuel, 2015).

The first effort at deregulation in the country’s air industry was in 1988, when entrance boundaries were removed; permitting three private carriers to start programmed domestic air services (Ismaila 2013). This presented two aviation policies, limiting the main routes to the national carrier and just one private airline. Competition on the grounds of prices and routes was excluded, and the competition between air companies was only on the level of services provided (Akpoghomeh, 1999). The focal aim of this remediation was to expand the competition amid the carriers and permit quick reaction from airline managements to fluctuating market atmospheres. Also, the African Union (AU) retorted to international liberalisation interventions and approved the YD as a new African Civil Air travel policy in October 1988. The YD called for the liberalisation and integration of air amenities, to pave the way for Nigeria to be strongly involved in the globalisation exercise and provincial progression. Ismaila (2013) noted that state policy was directed to liberalisation and steered deregulation of the air dub-segment. This brought about to the reformation of the state bodies where of some were commercialised and denationalised. This was a tough period in the country’s air sub- segment; where airports reported poor passenger numbers as a response to skyrocketing fares, poor administration, and inauspicious investment atmosphere with high risk because of political volatility (Akpoghomeh, 1999).

5.4.2 Nigeria’s economy According to Suberu et al., (2015), Nigeria is the biggest oil trading nation in Africa and has a fast developing economy. Nigeria’s economy has improved in 2017 by 0.9% growth from -1.6% in 2016. Therefore, the country’s contribution to GDP improved in 2017 from 18.5% recorded in 2016 to 22.6%, African Economic Outlook 2018. They further mentioned that even though it has improved, it is still lower than the average growth of Africa and that of Western African region. According to the African Economic Outlook 2018, Nigerian’s economic growth is expected to increase to 2.1% and 2.0% in 2018 and 2019 in that order. The service sector in Nigeria is the main sector that contributes more to the GDP. The service sector dropped its performance in 2017, from 60.4% recorded in 216 to 56.4%, however it still remained the biggest contributor to the country’s GDP (African Economic Outlook, 2018).

The degree of development in evolving countries like Nigeria has not stretched to the optimal level of airport capability, Ismaila 2013. Some international airports in Nigeria suffer from underutilisation of their capacity. Ozoka (2009) noted that only Lagos airport has a reasonable self-sustaining traffic, the other four are in dire necessity of surplus traffic so as to expand profits. Statistics have shown that the revenue of the air travel industry offers jobs for millions of people, Ismaila 2013. Certainly, this industry can never be overlooked, and has to be immaculately scrutinized for growth using extensive research and development approaches which can result in advances in efficiency. While this industry contributes below 1% towards the GDP, as recorded in a CBN (2010) report, pragmatic proof showed that air industry is among important drivers for the growth of other economic segments which contribute immensely to the country’s GDP (CBN, 2010).

Figures have presented that the income from international air travel industry runs into trillions of dollars, creating work prospects for millions of individuals. Annual numbers of 2.3 billion travellers and an income of US$564 billion from passenger traffic in 2009 have been reported (Boeing 2010). Consequently, this industry should never be disregarded, so it has to be closely observed for development using thorough research. Ismaila (2013) emphasised that the industry is merely contributes under 1% of the country’s GDP. The CBN (2010) report showed experiential evidence that the air travel industry is one of the foremost drivers for the enhancement of other commercial sub-sectors such as tourism and trade, and these have a momentous impact to the country’s GDP. Hence it is fitting to cultivate its growth towards the development of other segments, which can be attained by origination and workable research development (CBN, 2010).

Nigeria was encouraged to take a more liberal policy towards its worldwide Air Service Agreements (ASA) by the influence of air industry liberalisation recommended by economic principle and globalisation. The policy combines the application of the Yamoussoukro Declaration with various African states, an Open Skies Agreement with the U.S, and the expedition of a level of market admittance protocols with other nations (Ssamula, 2008). Conversely (Doganis, 2010) proclaims that the airline business is known to be extremely flimsy with awfully low turnover as compared to other sectors in numerous nations. Furthermore, industry corporate policy is ever-changing, with regulation/deregulation occurring consistently. As a direct result, airlines dwindle; the Nigerian national airline is not immune as was witnessed in 2002. Nevertheless, only comprehensive and competent sectorial administration can maintain its progression and development, which is achievable through research that is able to accurately project forthcoming market behaviour (Ismaila, 2013).

Table 5.3: GDP by sector (percentage) (CBN, 2010). Sector Year 2011 2013 2016 2017 Agriculture 22.3 21.0 21.2 21.1 Of which fishing 0.5 0.5 0.5 0.5 Transportation, storage and communication 11.4 11.7 12.8 10.5 Finance, real estate and commercial services 13.1 15.0 16.2 16.7 Public admin and defence 3.9 3.0 2.7 2.6 Construction 3.0 3.3 3.5 3.8 Services 49.4 53.0 60.4 56.4 Wholesale and trade, repair of cars, domestic products, 16.8 17.9 21.3 19.8 restaurants and hotels 0.4 0.8 0.9 0.9 Of which restaurants and hotels Electricity, gas and water 0.5 0.7 0.7 0.7 Manufacturing 7.2 9.0 8.8 8.8 Industry 28.3 26.0 18.5 22.8 Mining and quarrying 17.6 13.0 5.5 9.2 Of which oil 17.5 12.9 5.3 9.1 Other services (including education, health and social work) 4.1 5.3 7.3 6.8

The performing top sectors are disused in more detail below: • Agriculture. According to NIJA 3, agriculture plays a big part in the Nigeria’s economy; it accounted for 23.1% of GDP in 2015 and hired 38% employees. This include the following sectors: crop production, livestock, fishing and forestry. The policy objectives are to: ➢ Upturn agriculture GDP from N16 trillion to N21.0 trillion by 2020 at an average yearly increase proportion of 6.92%. ➢ Minimise the importation of food and be a net exporter of key agricultural goods. ➢ Be independent in tomato paste in 2017, rice in 2019 and wheat in 2019-2020. However, the agriculture sector is facing the following challenges:

➢ Restricted access of agricultural outputs to the national and international markets and security threats to agricultural investment. ➢ Majority of farmers find it difficult to get financial assistance to advance or expand their farmers. ➢ Rural farmers are limited by the poor infrastructure to national and international markets.

• Manufacturing. Manufacturing sector account for 9.5% of the country GDP in 2015. The manufacturing sector of Nigeria is small compared to other countries like South Africa, Mexico, Indonesia and Morocco. The largest part of manufacturing in Nigeria are comprising food, agro-processing. Beverages and tobacco. In 2010, manufacturing sector hired 5.3 million Nigerians, mainly in agro-processing and textiles. • Solid minerals. One of the most promising growth segments in Nigeria is solid minerals. The sector’s GDP doubles in 2010 from N52 billion to N103 billion in 2015. There are 44 known types of minerals in Nigeria. The solid minerals industry has the ability to expand the economy; however, it is moving slow due to constrained from other factors like: ➢ Blockade to investment because of lack of geoscience evidence ➢ Insufficient funding to complete the required level of technical work ➢ Difficulties in enforcing regulations due to shortage of skilled manpower and

5.4.3 Nigerian airline industry and market The domestic air network arrangement linked only state capitals even though not all were interconnected by air by then. The travel demand is the foremost factor that governs the sum of routes connecting airports (Stephens and Ukpere, 2011). Stephens and Ukpere (2011) categorised the airports as two kinds: airports that have a multiple of routes lower than the average of 8 routes (low grading) and airports with greater than average routes (high grading). Lagos airport is the principal air hub as shown by the swarming routes. Abuja, Kano, and Port Harcourt Lagos, and Calabar airports are other sub-hubs, and are all international airports (Stephens and Ukpere, 2011).

5.4.3.1 Traffic rights and route entry regulation The Civil Aviation Authority (CAA) Act (2004) proclaims that Nigerian domestic routes are allowed to fly any route with no singular permit given that they provide notification of their flight schedules to the Nigerian Civil Aviation Authority (NCAA), the Federal Airports Authority Nigeria (FAAN) and the Nigerian Air Space Management Agency (NAMA). But then again in regard to privileges by Nigerian carriers to run worldwide routes, a request is sent to the Minister of Air travel for the depiction of an airline as flag carrier to work a worldwide route subject to an air agreement among Nigeria and the other country. The aspirant has to obey the designated guidelines. The submission is directed from the Minister to NCAA which carries out technical assessment. If a positive report is allotted, the minister may use his discretion to designate the airline as flag carrier to work the route in question.

For foreign carriers to function in Nigeria, after description of the airline by the contracting nation within the air service covenant, the notification of designation is sent to the Foreign Affairs Ministry which relays the message to the Minister of Air travel (Ismaila 2013). This is a critical stage for international circulation, and this forms a noteworthy portion of any country’s Airborne Separation Assurance systems (ASAs). In terms of carrier access, the CAA Act of 2004 proclaims that the protocol on the air business pertaining to domestic carriers is safeguarded on capitalism, and airlines may use any routes within the country. However, foreign carriers are restricted to the airport of arrival indicated in the applicable air traffic authorisation, and not permitted to work domestic routes. This consequently excludes any cabotage flights, which are viewed as some of the important liberal traffic privileges permitted to foreign airlines in ASAs.

5.4.4 Economic performance of the Nigerian airline industry The airline sub-sector is among the principal service industries that expressively contribute to the developed and developing economies (Rahim, 2016). Wensveen (2007) labels the aviation segment as an economic movement of transporting individuals and cargo by air from point A to point B. Generally, the airline industry is separated into domestic and international air traffic with the latter constituting 64% and the former, 36%. Datamonitor (2011) reported that the segment could generate a possible $713.6 billion in the nearest future. As noted by the ATAG (2014), the air industry maintains 1.1 million employees and creates $34.5 billion in the continent (the latter equivalent to 1.7% GDP). The country’s air industry, as per Amba and Jonathan (2013), comprises four main rudiments: travellers’ traffic, freight, mail, and airplanes traffics/movements.

Rahim (2016) declared that the country’s air segment is among the key pillars of the economy, as 8.3 million passengers and above 181,000 tons of cargo were despatched locally. Hence this industry is extensive, stable and most vital as never seen before. Deprived of the air industry, transnational transport of means of production, materials, and services would be severely underprivileged (Doganis, 2006). Furthermore, the air industry offers work prospects to thousands (Data Monitor, 2009). Ahmad and Khan (2011) believe that the tourism sub-sector with diners, hotels and resorts are indebted to the airline industry.

5.4.5 Competitiveness of Nigerian airline industry The NCAA (2011) stressed that a short while back Nigeria achieved US FAA accreditation for category one in relation to protection values, providing its carriers straight entry to the US market. This was attained after a hefty investment in contemporary directional aid that improves the

86 prosperity of the country’s carriers. According to Nigeria’s Ministry of Budget and National Planning report 2017, Nigeria’s young population, large market, natural resources make the country an eye- catching destination for private sector investment. However, due to complications in getting finance, incompetent bureaucracy, vague and erratic regulation, people consider it a challenging place for businesses. The survey done by World Bank Enterprise in 2014 with over 2000 small businesses revealed that the major challenges facing the businesses were poor infrastructure, corruption and limited access to finance. Below is a detailed graph showing the challenges faced by Nigerian businesses.

30 30 27 25

15 13

10 6 6 4 3 5 4 2 2 0

Figure 5.1: Obstacles faced by the Nigerian businesses (World Bank Enterprise, 2014).

5.4.6 Factors affecting the Nigerian airline market The country’s air travel segment has a number of challenges, including a low traffic when compared to countries like Morocco, Kenya, South Africa and Egypt (Ismaila, 2013). According to work reported by the NCAA (2011), this resulted in air infrastructure underutilization, where just 2.7 million international travellers in 2010 were recorded. As a direct consequence, the profits as produced were terribly hampered, placing in jeopardy the Nigeria’s air transportation system sustainability. Additionally, regardless of the Nigeria signing Bilateral Air Service Agreements (BASAs) with more than 50 nations, permitting international traffic, these treaties are still generally limited to the standard of tariff barriers (FMOA, 2010). As a result, according to the evidence of the influence of liberalisation in other nations, it could occur that these BASAs are hampering the country’s economic opportunities

87 that can come through foreign investment, consumer prosperity, and a great quality that result from services offered through healthy competition.

Additionally, the current guidelines only protect independent airlines that are just currently able to handle around 20% of the worldwide air market. Hence, the restricted numbers of foreign airlines benefit more while passengers are denied competitive benefits (Ismaila, 2013).

Nigeria has effected some liberalisation developments with various countries, counting an Open Skies treaty with the US, and the YD with a few African nations. However, negatively, Nigeria lacked carrier numbers to provide a bulk of the routes looted to the country’s airlines within these agreements (Ismaila, 2013). Yet, recently a stable increase in traffic demand in Nigeria has been observed, which could be attributed to a number of issues along with the liberalisation policy. According to Bowen, 2010, after the end of the former national carrier Nigerian Airways in 2003 of the big debt and lack of good management, diverse start-up airlines came on board and tried to fill the vacuum. Therefore, foreign airlines ruled global traffic (Ismaila, 2013).

5.5 Chapter Summary Around 1970s to 1980s, the airline industry in Africa was faced with great difficulties. Some of these challenges were misgovernment of national carriers, political meddling, high operational costs and the use of obsolete tools. The air industry in Africa has always been rather small as compared to the international industry.

Nevertheless, just like in other continents, the airline industry in Africa is a primary service segment that provides support to other fundamental economic segments like tourism, industrial, worldwide trade and commerce, and contributing to GDP. The air travel sector has presented a huge growth in the recent past because of the upward world economy, globalization, cutting-edge technology, and deregulation. The air transport industry is one of the principal services segments, playing a significant part in developed and developing economies. The demand of air transport has grown because of technological improvements in aviation as welcomed by the Nigeria, and increased capacity handling as a result of governmental intervention. From the current work, it is evident that the aviation industry in Kenya is greatly impacted by many factors that explain such an extraordinary rate of impediments that require tending to relative to other sectors. Governments should desist from excusing state intervention in the aviation industry – the excuse that state-owned carriers are of strategic significance. Easily competing independent carriers deliver superior services at a lesser fee, so what is it that is so strategic about a government-owned airline?

5.6 Lesson Learnt There are various factors influencing the airline industry negatively and positively. These include factors such as Environmental, Economic, Social, technology and tourism. It is crucial for every airline firm to be aware about the factors directly or indirectly impacting its function and profitability. Sustainability is also another serious issue to be considered with the current climate changes, which are believed to be the result of human activities, industrialization and burning of fossil fuels. The airline industry is also believed to contribute on the pollution. Sustainability seems to be considered in Kenya, but more effort is still needed from the country and particularly the airline industry.

CHAPTER 6: SOUTH AFRICAN AIRLINE INDUSTRY

6.1 Introduction This chapter covers the South African viewpoint, emphasising on South Africa’s Airline industry and its impact to the country. We will discuss in detail the importance of airline industry in South Africa and how the airline impacts on South African economic growth. The historical background of the South African airline industry is also explored.

6.2 Overview of the South African airline industry The airline industry has made a positive impact in the world and recognized for being one of the fastest growing sectors worldwide, Scholtz, 1998. SA is listed among top developed nations in the world, known for fascinating tourists, business people, scholars and persons from all works of life, Luke RJ, 2015. SA has various airports catering for both international and domestic airlines, allocated in several cities. These airports are responsible for a vital part in the economy of the country. OR Tambo is a primary airport in South Africa for International and domestic travel located in the city of Johannesburg. It is a South African airport offering non-stop flights to over 20 South African destinations and to six continents globally.

South African Airways was the first carrier to provide air transport services in South Africa since 1934, followed by British / Comair in 1946. These airlines have been in operation since then and this demonstrates that there are various factors that drive air transport demand in South Africa. The legacy carriers offer air services that significantly differ from those offered by LCCs. The South African Airline group is a fully state owned company and the SA flag carrier, established when the South African Government took over Union Airways.

South Africa has an immense number of aircrafts that fly between its enormous urban communities, and littler ones, with rates that range from top notch to cut-value economy. The airline environment in SA was lightly regulated from 1934. During World War2, the domestic airlines were offered by overseas airlines at affordable charges. This stopped when South African Airways (SAA) took over local services and increased all rates by more than 25%. The reduction of rates was quickly enforced upon SAA. In 1993 the South African international air policy was liberalised, as also witnessed by Scholtz, 1998. This resulted to a change in South African air transport environment. Among these changes, the country started experiencing an increase of international carriers flying to and from South Africa and more airlines started competing on the domestic market. These are the changes

90 that were not previously experienced and which in turn, they placed further pressure on the South African airlines to increase the service quality and minimize costs (Scholtz, 1998). Lean methodology is implemented because it ensures a smooth, quick flow of resources or materials (Vermeulen et al., 2014). This research introduces impacts of implementation and knowledge framework to enable service organisations to implement lean processes towards sustainable performance and excellence.

6.2.1 Historical background of the South African airline industry Ssamula (2014) reveals that the airline industry in South African began in 1929, just about 26 years after the Wright brother’s first flight in 1903. When the aviation practice began, it started as an airmail operation and was founded as Union Airways in 1929. Before the beginning of the aviation, there were already several types of transportation in South Africa (Bennett & George, 2004). Initially, the air transport system was for rich individuals and wasn’t meant for carriage of goods like the railways. In today’s world, the airline industry is responsible an imperative part in leisure industry and contributes largely to the South Africa’s GDP (Mhlanga and Steyn, 2016).

Union Airways was established by Major Allister Miller in 1929 in Port Elizabeth, after it was given a government agreement to transport mail between Cape Town and the main centre of South Africa, Pirie 2006. They were disclosed on 24 July 1929 and commenced the operations on 26 August 1929. The airline began to fly passengers on 26 August 1929 (Mhlanga and Steyn, 2016). Due to the increase in mail and passenger traffic, Miller added three more airlines on 29 May 1930. Unfortunately, two of the airlines crashed in 1931 and they were written off. In 1933, another union airline crashed and just after this tragic event, Miller had to ask the government to run the operations, Ssamula, 2014. On 1 February 1934, the South African government officially commenced the possessions and accountabilities of the Union Airways. The carrier was therefore named South African Airways (SAA) and was under the supervision of South African Railways and Harbours administration. Comair, a new privately owned carrier was established and began operations in 1946 (Ndlovu, 2001).

The airline industry was globally regulated with extensive government influence in 1970s (Hanlon, 2007). The deregulation of the airline industry started in the United States of America with the Airline Deregulation Act of 1978. The Act permitted the gradual removal of the restrictions on domestic services and the complete removal of the restriction happened in 1981 (Wells, 1994). The intention of the deregulation was to remove government control of ticket prices, routes and market entry, Hanlon 2007. The industry has experienced many structural changes, including the entrance of

LCCs into the market, increased competition and flexibility of carrier rates. In 1991 the LCCs market started with the deregulation of the industry in South Africa.

The apartheid era

In 1949, the domestic air services were delimited through the Air Services Act (Act No.51 of 1949). For over 40 years, the South African flag carrier, South African Airways was protected from competition (Luke & Walters, 2013). Link Airways, later identified as SA Airlink was established in 1978 followed by Bop Airline in 1979 later well known as Sun Air. South African Airways experienced rates pressures between 1978 and 1984 as airports and airlines became part of a political plan to cripple authorities of the last minority white rules states in SA (Gavin, 2013). For this period the country was isolated due to apartheid policies and countries economic views and projections were not so good (Gali, 1997). As a result of international criticism of the apartheid regime around 1980s, South African Airways was encountered with resentment, as its out of the country offices were attached and badly damaged (Gali, 1997). In 1986 and 1987, South African airlines, including South African Airway were banned to New York and Australia by US comprehensive Anti-Apartheid Act of 1986 (Mhlanga and Steyn, 2016). The country improved from 1990 when its last minority government ended statutory apartheid. As a result, the South Africa’s political isolation were ended, and the international diplomatic, cultural, commercial and sporting links were continued. 1990 was a year of political change that included removal of bans on cross-border air travel among South Africa, continental fellow citizens and several countries (Mhlanga and Steyn, 2016). In 1991 the country’s domestic air travel market was deregulated, promoting the competition for airlines (Ndlovu and Ricover, 2009).

In South Africa, the domestic airline market was deregulated in 1991 (Mhlanga 2017 & Scholtz, 1998). They further state that this provided the airlines an opportunity to compete with the SA carrier, SA Airways. This deregulation resulted to free entry into the market and promoted competition (Mhlanga 2017 & Scholtz, 1998).

Harris (2001); Mhlanga (2017); Mhlanga & Steyn (2016); Scholtz (1998) mentioned that Flitestar was the first airline to enter the market in October 1991 just after the deregulation. Flitestar showed bravery when they challenged SAA on its home ground by and targeting the SAA’s market and making their fares similar to those of SAA. On the other hand, Comair decided to hold back and only operate on the trunk routes, and this decision made the Flitestar to be the only airline competing with SAA (Bennett, 2005; Mhlanga, 2017; Scholtz, 1998; Luke, 2015).

However, according to Ssamula (2008); Bennett (2005), SA Airways was rescued from this situation due to its time-honoured power in airline industry, the solid association with airports and suppliers plus its relationship with government. And for this reason SA Airways was able to carry on intimidating private carriers. SAA carried on controlling airports and assigned landing slots to other airlines and this made it hard for new airlines to enter the market (Mhlanga, 2017). Ssamula (2014) further states that the access to the SA aviation infrastructure and other related services was only an advantage to SA Airways and this was due to its long-standing position in the domestic market. Bennett (2005) further adds that SA Airways was the only carrier that had a warrant to make use of the luggage conveyer belts at SA airports. Therefore, Flitestar would not be able to process their luggage quicker than SAA.

As a result, Flitestar made a number of accusations against SAA for unfair pricing (Mhlanga, 2017. When Flitestar joined the domestic market, South African Airways was the only carrier accredited to perform the ground management facilities at airports. New carriers like Flitestar were forced to come into a contract with SA Airways for the ramp control of all its A320 trips. And for this reason, the SAA overpriced these facilities to other carriers to increase the operating charges. Flitestar stopped its operations in April 1994, and this was because of high expenses because of weakening exchange rate as the airliner lease contract was settled in US dollars (Federico, 2013).

Mhlanga (2017) further adds that, just after the disappearance of Flitestar and SA Airlink, the country was blessed with four new carriers, i.e. SA Express, Sun Air, Phoenix Airways and Nationwide Airlines which commenced its operations in April, November and December 1994 and December 1995, in that order. In 1996 the Competition Board received another complaint from Sun Air, Phoenix Airways and Nationwide Airlines alleging greedy behaviour of SAA, Mhlanga 2017. Moreover, SAA was accused by these carriers that on the Johannesburg-Durban route, it added the number of aircrafts by 50% and its charges were too low such that they could not even cover its costs.

Phoenix Airways operated in this industry for not more than a year and Atlantic Airways took over in August 1995, Bennett 2005. Ndhlovu & Ricover, 2009 revealed that Atlantic Airways operated only for few months and stopped its operations due to high fuel rates. The Airport Company of South Africa (ACSA) was introduced in 1993 to control air transport infrastructure and related services, after SAA was again accused in 1992 of unfair advantage over its competitors (Ssamula, 2014). At this time only Comair and Nationwide were the surviving airlines to compete with SAA (Ndlovu and Ricover, 2009).

The entry of low-cost airlines in SA airline industry and Growth of SA Airline industry

The first privately owned airline that joined the domestic market was Flitestar, this was immediately after the deregulation that took place in 1991. It started working in October 1991 with freshly leased Airbus 320s. The Flitestar stopped its operations in April 1994 due to high expenditures, Smith 1998.

BA/Comair established the first low cost carrier named Kulula.com and this was the first LCC to enter the market in August 2001 (Ndhlovu and Ricover, 2009). In 2006, kulula.com started to provide airline services from Lanseria airport, a subordinate airport in Gauteng, to Western Cape and Kwa- Zulu Natal. Sun Air decided to come back in 2002 and operate again. Sun Air was liquidated in 2004 and this is when 1Time started its operations.

On the other side, CemAir started operations in March 2006 and SAA launched their LCC in October 2006 named Mango airlines (Bennett and George, 2004). While more airlines were entering the industry, it wasn’t the case with Nationwide, as they were forced to stop all flight operations in April 2008, (Shaw, 2011). Velvet sky joined the industry in March 2011; however, they were liquidated very soon after their entrance in February 2002, (Shaw-Smith, 2012).

Fly Go Air commenced to operate in February 2012, while on the other hand 1Time collapsed in November 2012 due, tough competition, high fuel and weak demand (Makalang, 2016). In October 2014 the industry was blessed with another airline named FlySafair, followed by Skywise and Fly Blue Crane in March and September 2015 in that order. Skywise did not last longer in the industry, they ceased operations in December 2015 (Young, 2015). Of all the seventeen airlines that entered the industry between 1991 and 2016, only eight are still operating (Steyn & Mhlanga, 2016). The below table demonstrates the airline history of the SA domestic market and their timeline

Table 6.1: SA Airline history (Steyn & Mhlanga, 2016). Number Carrier Operational period Start date End date 1 Union Airways Ltd August 1929 February 1934 2 SAA February 1934 Still operating 3 Comair February 1946 Still operating 4 Link Airways April 1978 May 1992 5 Bop Air July 1979 September 1992

6 Flitestar October 1991 April 1994 7 SA Airlink March 1992 Still operating 8 SA Express April 1994 Still operating 9 Sun Air November 1994 August 1999 10 Phoenix Airways December 1994 August 1995 11 Atlantic Airways August 1995 October 1995 12 Nationwide December 1995 April 2008 Airways 13 Kulula.com August 2001 Still operating 14 1Time February 2004 November 2012 15 CemAir March 2006 Still operating 16 Mango October 2006 Still operating 17 Velvet Sky March 2011 February 2012 18 Fly Go Air February 2012 Still operating 19 FlySafair October 2014 Still operating 20 Skywise March 2015 December 2015 21 Fly Blue Crane September 2015 Still operating

Other airlines like Nationwide (1995-2008), Velvet Sky (2011-2012) and 1Time (2004-2012) stopped its operations even though they were in the market for a long time, Mncebe (2014). South African Airways had also encountered losses over the past years and required several government bailouts; this includes one in January 2015 and the other one in September 2016.

6.2.2 South African airline industry strategic policy objectives The airline has to clearly specify its purpose, identify its customers and know the type of service the customers can expect from the airline. The setting of objectives and application of procedures in order to attain these objectives amounts to the development of a details plan of action. When different missions and goals are considered in combination with the size, ownership and operations of the airline, a clear picture emerges as to how an endorsement or impediment could be placed on an airline by its external environment and how this in turn could influence the internal environment and thus creditworthiness of the airline (Scholtz, 1998).

The following are the strategic objectives of the South African aviation, received from the department of transport report, 2017:

➢ To encourage and improve safety, security and environmental compliance civil aviation in all angles of the airline. ➢ To encourage the National interest of SA and promote the increase in tourism and trade. ➢ To encourage the improvement of an effective and productive airline industry that has the potential to compete locally and international ➢ To make sure that airline industry makes a meaningful contribution to the development of the resources that are useful to people. ➢ To keep a suitable and cost-effective governing structure, warranting safe, pleasant environment and trustworthy air travel services and be able to respond to moving conditions. ➢ To be able to meet the needs and requirements of all airline customers ➢ To allow preservation of airline heritage ➢ To be economically and ecologically sustainable ➢ To encourage sound links with other countries and other abroad organisations ➢ To give sufficient review meetings in well-defines communication organizations.

6.2.2.1 Flight Tariff Regulation The CAA Act 2004 does not control any flight charges; and thus carriers may bill anything estimated as suitable for services. To avoid avaricious rating, the NCAA, within its overall jurisdiction to control, executes economic reviews on carriers providing very low air facilities fares as may seem insufficient to cover their expenses. This may execute applicable agreements or issue directives where an audit divulges greedy ratings (NCAA, 2006). This as a result recommends an imperative endowment of ASAs, which shows that the nation could permit free provision for pricing except when the other country declines.

6.2.3 The impact of airline industry on the South African economic growth The air transport industry contributes R74 billion to South Africa’s yearly GDP and offers about 230 000 occupations across the overall value chain in the nation (Styan, 2013). This makes air travel an important sector in the economy. South African Airways and Comair are the best two airlines by revenue, customers carried and aircraft in South Africa. They created low-cost airlines in order to decrease costs. This is similar to the European trend where full-service carriers have created low- cost subsidiaries (Harvey and Turnbull, 2010). Both Comair and SAA have the same objective of supplying sustainable profits and growing market share. Comair held about 39% of the domestic market, while South African Airways held the remaining 61% in 2013 (Centre for Aviation, 2013).

Airline industry is important for manufactures trade, especially trade in components which is the main part of cross border trade today. It is anticipated that the value of global trade transported by air in 2018 will be $6.9 trillion. Travellers using air transport in 2018 are projected to spend $794 billion. Many economic activities like manufacturing, financial services and agriculture are dependent on reliable airline air transport services. The economic activity is likely to improve when the airline system serves these industries efficiently. There are several jobs created directly by the South African airport, these include airport restaurants, car rental organizations, airport taxicab services etc. Airline travel industry is responsible for a significant role in travel and leisure industry. The tourism industry contains other sectors such as hospitality, recreation, cultural and heritage as well as crafts production (WTTC, 2015). Tourism is largely dependent on the ability of tourists to reach the destination which creates a strong link between growth in air travel and growth in the tourism industry (ATAG, 2005).

6.2.5 The South African economy The economy in South Africa increased by 1.3% in 2017 from 0.6% recorded in 2016. This improvement was due to improved performance in agriculture and mining. The other sectors that made a positive contribution were transport and finance sectors, Key Trends 2018. These sectors are discussed in detail in the following subheadings under sector performance.

1. Employment South Africans are experiencing a high unemployment rate. In the third quarter of 2017, the unemployment rate reached 27.7%. This is the uppermost unemployment proportion since September 2003. According to the Quarterly Labour Force Survey, South Africa recorded 26.7% in unemployment rate in the fourth quarter of 2017 compared to 26.5% documented for the fourth quarter of 2016. The country has approximately 5.9 million of individuals who are currently unemployed according to the official definition of unemployment, of which under the expanded definition, the figures are increasing to 9.2 million.

The labour force, officially defined, grew by 0.9 per cent (201 573) over the year, exceeding the growth in the number of people employed (0.6 per cent – 102 414), resulting in an increase in the unemployment rate. There was however a huge rise in the number of discouraged job-seekers, which increased by 10.7 per cent over the year, its largest increase since 2011. The large increase in discouraged job-seekers underscores the importance of considering the broad definition of unemployment, as it counts discouraged job-seekers as part of the unemployed. The broad unemployment rate increased by 0.7 per cent over the last 12 months to 36.3 per cent. Broadly

97 defined, the number of people unemployed increased by about 316 574. Youth unemployment remained close to its all-time high level in the fourth quarter. Youth unemployment, officially defined, increased by 1.1 per cent over the year to 38.2 per cent. Broadly measured, the youth unemployment rate is 49.1 per cent.

2. Exchange rate After weakening of SA Rand against the US dollar in the second quarter of 2017 following the cabinet reshuffle and a credit ratings downgrade, the rand traded in a narrow band until the third quarter of 2017. The rand has strengthened significantly from the fourth quarter of 2017, along with other emerging market currencies as the dollar weakened against most major currencies. The rand strengthened by 18 per cent against the US dollar between November 2017 and January 2018, and reached its strongest level against the US dollar in February in ten months, following the change in the president. Externally, a stronger global growth outlook and higher commodity prices have supported the strengthening of the rand. Domestically, a narrower current account deficit, and recent domestic political developments, including the change in the president, has also contributed to a stronger rand.

3. Sector performance The economy of South Africa is determined by several anthropogenic events such as the tourism sectors, education, transport, manufacturing, natural resources textiles, agriculture, energy, information and communication technology (ICT), and building and construction, among other sectors. The combined effects of these sectors feed the macroeconomic indicators of national economic growth as reported by the National Bureau of Statistics (KNBS, 2017). The sectors are briefly discussed below according to the information received from 2018 Budget Review:

o Agriculture This sector is divided into four segments, namely: crop production, livestock, fishing and forestry. Agriculture witnessed an improvement in the first three quarters in 2017 compared to 2016. Fishing and forestry increased by 21.9% and contributed 0.5% to overall GDP. There was also a recovery in crop production after a severe drought in 2-15 – 2016. Maize and Soybean productions are expected to improve in 2017 and 2018 after the good summer rainfall. The on-going draught in the Western Cape remains a concern for the industry, because Western Cape contributes around 22% of agricultural products and it is the principal producer of wheat, horticultural products and wine.

o Mining 2017 was the challenging year in the mining sector, however still better than 2016. After the reduction in 2016, this sector is improving and was able to contribute more to the country GDP compared to 2016. The increased demand has improved iron ore, manganese and chromium production. Sales in minerals increased by 9.4% in the first nine months of 2017 comparing to the same period in 2016. The overall mining production improved by 4% in 2017.

o Manufacturing The poor demand of SA manufactured products, increasing operations rates, apprehensions over the political land, weighed on activity levels in the manufacturing sector in 2017. However, on the other side, the positive developments in some of South Africa’s main external markets supported production in export-oriented industries. The country experienced a decline of 0.4% in physical volume of manufactured goods, even though the sector GDP increased by 0.2% in real terms. Subdivisions like chemicals, paper and wood recorder lower amounts of production in 2017.

6.2.5 Major trends in the South African airline industry Deregulation in air travel sector has had big worldwide effects on the domestic airline markets, of which SA has also experienced the same effects. Deregulation of the airline sector has the ability to impact the structure of the airline, the flow of travellers, passenger numbers, the prices and the extent of competition. South Africa experienced a huge impact immediately after the deregulation, these include the entry and exits of airlines. The structure of the markets has been completely amended, after the entry of the first low-cost carrier in 2001. This also resulted to the increased use of the Lanseria airport in Johannesburg North.

6.2.6 Sustainability performance measurement in the South African airline Safety continues to be the first and principal priority in aviation management. As such, to ensure safety in South Africa. According to SAA 2018 report, South African Airways has already invested in ways to cut its carbon footprint by using biofuel. They added that in July 2017 South African Airways and Mango were the first flights between Johannesburg and Cape Town to fly using sustainable biofuel produced from locally grown tobacco plants. The flying machines or engines do not require any modification because the biofuel can be combined with conventional fossil jet fuel and be utilised as a ‘drop in’ fuel. The SAA and Mango airlines transported 300 travellers from Gauteng to Western Cape on Boeing 737-800s power-driven by a fuel blend made up of 30% air travel biofuel and 70% fossil fuel. South Africa’s economy presented contradictory results for the airline and leisure sectors. ATNS estimates its returns based on estimated growth in air traffic movements, with the latter receiving an increased connection to GDP at around 80%. ATNS did not up the prices in 2016, which

99 put pressure on the organisations financial capital performance. But, a 2% rise in total air traffic actions assisted to mitigate the negative effect of the zero-charge increase.

6.3 Chapter Summary South Africa is recognised as one of the top established countries in the world, known for captivating travelers, scholars, business people and individuals from all works of life, boosting with OR Tambo being the main airport offering non-stop flights to over 20 South African destinations and to six continents globally. South African Airways was the first airline to offer airline services in South Africa since 1934, followed by British / Comair in 1946. These airline companies have been operating since then and this proves that there are a lot of factors that drive air transport demand in South Africa. The legacy carriers offer air services that significantly differ from those offered by LCCs. The South African Airline group is a fully state owned company and the SA flag carrier, established when the South African Government took over Union Airways. The rate of unemployment remains a big concern in South Africa. The country has approximately 5.9 million people without jobs according to the official definition of unemployment, of which under the expanded definition, the figures are increasing to 9.2 million. This means that the country has a hug number of young individuals with no jobs and this might affect the country negatively in a long run.

6.4 Lesson Learnt The chapter revealed that the airline industry is making a positive impact in the country’s economy and this is because this industry is responsible for a significant role in tourism and leisure industry. Tourism covers subdivisions like cultural, heritage, hospitality and recreation as well as crafts production. The leisure industry is mainly dependent on the ability of tourists to reach the destination, which creates a strong link between growth in air travel and growth in the tourism industry. The connections between tourism and air travel industry are clear because a large number of tourists, especial on long distance trips, make use of airlines to travel to and from their destination.

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CHAPTER 7: RESEARCH METHODOLOGY

7.1 Introduction To date, the research aim of this study is to assess the impact of lean manufacturing in the South African airline industry requires a robust research approach, which is resolutely entrenched in both critical assessment of previous studies and quantitative research methodology. This is essential to guarantee that the study provides significant contribution to the ever-growing body of knowledge on lean phenomena. In light of this, the present chapter explains the methods used by the researcher to collect primary data for the study as well as the techniques used to analyse the data and to draw reliable findings from the data collected. The chapter begins by differentiating between quantitative and quantitative research method. The reasons for selecting qualitative research method for data collection are also outlined. The data collection instrument selected and the reason for selecting this instrument is discussed in detail. As we are aiming to answer the research questions, we need to select a proper method that will assist us to get the desired results

7.2 Research Design Research design can be defined as a roadmap for any scientific research study, offering the general scaffold for gathering data (Maxwell, 2012). Whilst, Mouton (2001) state research design is a framework for deciding on themes, research sites, and data gathering activities in order to meet the research objectives. Furthermore, he points out that the aim of a sound research design is to offer outcomes that are evaluated to be trustworthy. Hence, in the same vain, this study defines research design as a strategic roadmap for measures that are used as a link concerning research objectives and research questions, or execution of the research strategy. The research design is essential and imperative for implementing the methodology (Maxwell, 2012). Additionally, according to Mouton (2001) the kind of research undertaken to deliver suitable solutions to the research problem. To conduct this study, the researcher had the option to use either quantitative or qualitative research methods or a combination of these methods. Quantitative research involves making use of numerical or statistical data to conduct an analysis. These research methods help to draw generalised conclusions when assessing the relationship between measurable variables. On the other side, the qualitative research methods involve in-depth analysis of relatively few subjects for which a rich set of data is collected and organised (Denzil and Lincoln, 2005).

About the present study, the researcher used a quantitative method, descriptive in nature. The researcher used the survey method as means of obtaining the information. Two types of surveys were created: 1. the online and 2. Hard copy word document surveys. The online surveys were

101 created for the purpose of reaching a great volume of participant with different background. The hardcopy surveys were also distributed to, university of Johannesburg student, engineering and manufacturing companies.

The researcher made two different survey questionnaires for two different targets. The first survey was for lean manufacturing. This survey is more about the implementation of lean and the researcher wanted individual’s experience or opinions on lean implementation. The second survey was meant for airline customers. The aim of this survey was to gather people’s opinions about the service offered by the airline industry. This is supported by Mugenda & Mugenda 1999 that a survey method seeks to gather information from participants of a population and defines current phenomena by questioning individuals about their own opinions, perception and experience. And again it discovers the present standing of two or more variables at that time. This method was chosen because the primary data collected is more reliable and up to date

7.3 Quantitative Research Methodology The overall aim of Quantitative research methodology is to test the related literature theories, determine evidences, demonstrate correlation among variables, and predict results. Generally, quantitative research employs approach as of the natural sciences which are planned to guarantee impartiality, generalizability and reliability (Weinreich, 2009). Most often, the methods employed within quantitative research methodology consist of arbitrary assortment of research respondents as of the study populace within a balanced means, the standardized survey research and statistical techniques employed to assess programmed theories concerning the correlation among detailed variables.

7.4 Research Methods This is study used a two-fold approach. Firstly the study conducted a critical appraisal of existing literature regarding the growing body of knowledge on lean phenomena in order to identify gaps, and secondly the study used research survey questionnaires based on quantitative method to gather data.

7.4.1 Literature review The present research work focused on variables associated with the impact of lean implementation within the airline industry, using South Africa as case study. Considering this, a wide and appropriate literature survey was performed with the aim of providing a theoretical framework for the research project. The critical appraisal of the existing literature offered scientific justifications for the research objectives as well as research question and assisted me to validate my research results. In accordance with Neuman (1997), a literature survey is generally the assumption that knowledge

102 acquired and learned from, and built upon, what others did in the past. Hence, literature survey may be done within different aspects such as background, antique, theoretical, and methodological. Each type of review has a precise aim. Additionally, Neuman (1997) pointed out that literature survey aims at indicating the researcher‘s understanding with an existing body of knowledge concerning the research area and creating the trustworthiness of such knowledge; displaying the route of previous study and in what way the present research project is related to existing studies. Hence, the present research scientific work, in the same vain as Neuman‘s (1997) aforementioned aims, employed previous literature to identify the gaps concerning the application of lean within different business organisations of different size. The results of critical assessment revealed that the adoption and implementation of lean in the airline industry is far behind than manufacturing companies.

7.4.2 Questionnaires A questionnaire can be defined as a form comprising an array of questionnaires, exclusively concentrated on a statistically important number of themes, and is a manner of collecting data for a survey. Generally, it is employed to gather statistical data or views concerning individuals. The Oxford Advanced Learner‘s Dictionary (1997) describes a questionnaire as a recorded or reproduced set of questions to be responded by an amount of respondents, exclusively as part of an investigation. Concerning the overall aim of the present study, the questionnaire formed my primary data gathering approach and its content was steered by means of the literature reviewed. Support from the Statistics Department at the University of Johannesburg was required, mainly to get guidance regarding the rationality of items for statistical aims. The research survey questionnaire was handed out to the 206 respondents in the Gauteng Province.

7.4.3 Distribution and collection of the questionnaires As mentioned in the sample and sampling procedures described below, my target sample was the three business organisations within the city of Johannesburg of the Gauteng Province. The overall aim of the designed research survey questionnaire was to assess the impact of lean implementation in the airline industry, using South Africa as case study. The subsequent approaches were employed to distribute and gather the research survey questionnaires. The questionnaires were uploaded on an online system in order to reach as much as lean experts and handed manually to three business organisations as well as distributed manually to the international Oliver Tambo airport in Johannesburg.

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7.4.4 Population and sample of the study This research was carried out in the Republic of South Africa. The target population of the study was the Airline customers, Lean experts, Engineering and Manufacturing companies. The questionnaires were sent and distributed to all four targets.

7.4.5 Sampling Sampling is a technique considered by a researcher to make sure that the sample used is representing the field of study concerned. According to Vos et al. (2011), there are two different types of techniques that can be used; these are probability sampling and non-probability sampling. This research adopted the probability sampling.

7.4.6 Data collection This study used the primary data collected using online surveys, and the hardcopies were distributed to the targeted population. Both survey questions that were used to collect the data are included at the end of the thesis as appendix 11.

7.4.8 Exploratory Factor Analysis In order to identify crucial variables impacting on the lean manufacturing adoption and implementation within the airline industry, specifically in the South African airline sector. The collected data used in this study were also analysed by means of Exploratory Factor Analysis (EFA). It should be pointed out that EFA operates on the notion that measurable and observable variables can be reduced to fewer latent variables that share a common variance and are unobservable, which is known as reducing dimensionality (Bartholomew, Knott, & Moustaki, 2011). These unobservable factors are not directly measured but are essentially hypothetical constructs that are used to represent variables (Cattell, 1973). For example, scores on an oral presentation and an interview exam could be placed under a factor called ‘communication ability’; in this case, the latter can be inferred from the former but is not directly measured itself. EFA is used when a researcher wants to discover the number of factors influencing variables and to analyse which variables ‘go together’ (DeCoster, 1998). A basic hypothesis of EFA is that there are m common ‘latent’ factors to be discovered in the dataset, and the goal is to find the smallest number of common factors that will account for the correlations (McDonald, 1985). Another way to look at factor analysis is to call the dependent variables ‘surface attributes’ and the underlying structures (factors) ‘internal attributes' (Tucker & MacCallum, 1997).

7.4.9 Importance of using Exploratory Factor Analysis The significance behind the employment of EFA is due to the fact that large datasets that consist of several variables can be reduced by observing ‘groups’ of variables (i.e., factors) – that is, factor

104 analysis assembles common variables into descriptive categories. Factor analysis is useful for studies that involve a few or hundreds of variables, items from questionnaires, or a battery of tests which can be reduced to a smaller set, to get at an underlying concept, and to facilitate interpretations (Rummel, 1970). It is easier to focus on some key factors rather than having to consider too many variables that may be trivial, and so factor analysis is useful for placing variables into meaningful categories. Many other uses of factor analysis include data transformation, hypothesis-testing, mapping, and scaling (Rummel, 1970).

7.4.10 Requirements for Exploratory Factor Analysis To perform a factor analysis, there has to be univariate and multivariate normality within the data (Child, 2006). It is also important that there is an absence of univariate and multivariate outliers (Field, 2009). Also, a determining factor is based on the assumption that there is a linear relationship between the factors and the variables when computing the correlations (Gorsuch, 1983). For something to be labelled as a factor it should have at least 3 variables, although this depends on the design of the study (Tabachnick & Fidell, 2007). As a general guide, rotated factors that have 2 or fewer variables should be interpreted with caution. A factor with 2 variables is only considered reliable when the variables are highly correlated with each another (r > .70) but fairly uncorrelated with other variables. The recommended sample size is at least 300 participants, and the variables that are subjected to factor analysis each should have at least 5 to 10 observations (Comrey & Lee, 1992). It is normally say that the ratio of respondents to variables should be at least 10:1 and that the factors are considered to be stable and to cross-validate with a ratio of 30:1. A larger sample size will diminish the error in your data and so EFA generally works better with larger sample sizes. However, Guadagnoli and Velicer (1988) proposed that if the dataset has several high factor loading scores (> .80), then a smaller small size (n > 150) should be sufficient. A factor loading for a variable is a measure of how much the variable contributes to the factor. Factor loading scores indicate that the dimensions of the factors are better accounted for by the variables. Next, the correlation r must be .30 or greater since anything lower would suggest a really weak relationship between the variables (Tabachnick & Fidell, 2007). It is also recommended that a heterogeneous sample is used rather than a homogeneous sample as homogeneous samples lower the variance and factor loadings (Kline, 1994).

7.4.11 Ethical Considerations Clough and Nutbrown (2002) comment as follows with regard to ethics in research: with the aim of understanding, investigators should be more than technically knowledgeable. They should step into prattled understandings, open themselves to their research themes‟. They should challenge the dichotomy of characterized and knowledgeable concurrently, both conflicted, both real....” hence, for

105 the purpose of this study, we considered the protection of the emotional state, well-being, and rights of the respondents. In accordance with the instructions and rules of the University of Johannesburg concerning research that involves contribution, the subsequent ethical considerations were observed throughout the period of the research conducted in this study.

7.4.12 Confidentiality and Privacy Confidentiality is defined as a process of treating the data regarding the participants within a private way. All participants were guaranteed that their identities as well as of business organisations would not be revealed to the public and dealt with within the firmest confidence. This component comprises the rule of trust in which we guaranteed the respondents that their trust will not be subjugated for own advantage or benefit, by misleading or betraying them in the research way or its published

7.4.13 Reliability As the present work involves the use of quantitative research evidence, the concept employed to demonstrate reliability is wider than the one usually related to quantitative research. Whilst dealing with quantitative data, the notion of honesty, trustworthiness, transferability, and integrity are also employed. In accordance with MacMillan and Schumacher (2001), reliability is the extent to which the results of the study do not dependent on unintended situations. It is meticulously associated with guaranteeing the quality of field notes and assuring the respondents access to the process of the publication of the research findings. To this end, Joppe (2001) describes reliability as the degree to which research findings are unswerving over time and are an exact picture of the whole populace under investigation. In case the research findings would be replicated under a parallel policy, then the instrument is viewed to be reliable. With the aim of ensuring the validity and reliability of this study, the designed questionnaires were revised by the official statisticians from the Department of Statistics at the University of Johannesburg.

7.4.14 Chapter Conclusion This chapter has focused on the research design and methodology that underpin this study. Detailed information regarding the mixed methods design, its origins, its relevance to this study and its general characteristics, were explored in this chapter. The following chapters build on from the methodological propositions made in this chapter by employing the proposed data presentation and analysis approaches to analyse the quantitative and qualitative data. The above discussion describes the methods and the approaches used to collect primary data for the study. After the collection of the data, the results were transferred to an excel sheet for analysis. The research findings are thus discussed on the following chapter.

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CHAPTER 8: DATA ANALYSIS AND INTERPRETATION

8.1 Introduction This section presents the results and covers interpretations on the research and practical features that were observed during the research process. The researcher made two different survey questionnaires for two different target populations. The first survey was for airline customers/passengers. The aim of this survey was to gather people’s opinions about the service offered by the airline industry. The second survey is about lean assessment. This survey is more about the implementation of lean and the researcher wanted individuals experience or opinions on lean implementation.

8.2 Section A: Biographical data analysis for airline customers The biographical data analysis for airline customers is presented in this chapter; this includes sex, race, age, qualification and travelling frequency.

8.2.1 Distribution of sample according to age of customers/passengers

The majority of individuals who participated in the survey were between the ages of 26–35. This age group contributed about 89.3% of the results, with both 20-25 and 36-45 at 5.4%.These results are illustrated in Figure 8.1 below.

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100.00% 89.30% 90.00%

80.00%

70.00%

60.00%

50.00%

40.00%

30.00%

20.00%

10.00% 5.40% 5.40%

0.00% 20-25 26-35 36-45

Figure 8.1: Customer demographics per age group.

8.2.2 Distribution of sample according to customers/passenger’s gender

The distribution of sample according to gender of the customers reveals that 61% of the respondents were females and 39% was for males. This is shown in Figure 8.2

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Male Female

39%

61%

Figure 8.2: Customers/passengers demographic in terms of gender.

8.2.3 Distribution of sample according to customer’s formal qualifications

Figure 8.3 below represents the formal qualification of airline passengers. According to the results of this study, 35.7% of the airline passengers have bachelor’s degrees, which is the majority of people who travel by aircrafts in the selected population.

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Other 2.7

PhD Degree 2.7

Masters Degree 15.3

Honours Degree 17.1

Bachelor Degree 35.7

Diploma 19.6

Certificate 3.6

Grade 12 2.7

0 5 10 15 20 25 30 35 40

Figure 8.3: Customers/passengers grouped according to qualification

8.2.4 Distribution of sample according to travelling frequency

The researcher wanted to know how often the participants travel with aircrafts to link their flying experience to their flying rate. The results revealed that 38.4% of the population fly more than three times in a year and this is the group with the highest number of respondents as shown in Figure 8.4 below.

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40 38.4

30 26.8 25

20 18.8 16.1 15

0 0-1 times a year Once a year Twice a year More than a 3 times a year

Figure 8.4: Passengers travelling frequency. 8.3 Section B: Biographical data analysis for workforce The biographical data analysis for workforce is presented in this chapter; this includes sex, race, age, qualification and work experience with lean.

8.3.1 Distribution of sample according to sector/department of the personnel

Figure 8.5 revealed that the majority of people who participated in the survey are in the production, manufacturing or operations department, representing 46.4%, followed by engineering or Technical department by 21.4%. The rest of other departments represented less than 10% each department.

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Other 9.5 Governmental Organisation 2.4 Information Technology 4.8 Human health and social work 1.2 Finance / Administration 2.4 Banking and insurance 1.2 Marketing / Sales 1.2 Engineering / Technical / Maintenance 21.4 Logistics/ Distribution / Procurement 8.3 Human Resources / Training / University 1.2 Production / Manufacturing / Operations 46.4

0 10 20 30 40 50

Figure 8.5: Sector or department of workforce.

8.3.2 Distribution of sample according the number of years of practical experience/involvement with Lean

The majority of people who participated in the survey have less than two years of work involvement with Lean as an improvement tool. They represented 31%, followed by the group with 2-5 years of work experience at 27.4%, and lastly above five years represented 25% as shown in Figure 8.6 below.

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27.4 25

16.7

None <2 years 2-5 years >5 years

Figure 8.6: Years of work experience with Lean

8.3.3 Distribution of sample according to workforce work title/ specialist

Figure 8.7 reveals that 48.8% of personnel who participated in the lean assessment survey are non- management employees, 21% are working as outside consultants, 19.18% are managers and the lowest percentage is for internal facilitators.

As outside consultant As internal facilitator Manager – all levels of management Non-management employee

21.4, 20%

48.8, 46% 16.6, 16%

19, 18%

Figure 8.7: Workforce demographic per title.

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8.3.4 Distribution of sample according to workforce age group

Figure 8.8 below shows that 56.56% of the lean assessment population is between 26-35 years of age and this the majority of people who participated in the survey. 22.6% and 14.3% was for ages 20-25 and 36-45 respectively. Age groups 46-55 and 56-65 were the smallest groups who participated in the survey with 4.8% and 2.4% respectively.

56-65 2.40%

46-55 4.80%

36-45 14.30%

26-35 56%

20-25 22.60%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00%

Figure 8.8 Workforce demographic per age group.

8.3.5 Distribution of sample according to the gender of the workforce

The distribution of sample according to gender of the lean assessment population reveals that 52.4% of the respondents were females and 47.6% was for males. This is shown in figure 8.9

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47.6, 48% Male 52.4, 52% Female

Figure 8.9 Workforce demographic per gender

8.3.6 Distribution of sample according to the workforce qualification

Figure 8.10 below represents the formal qualification of lean assessment population. According to the results of this study, 39.3% of the lean assessment population have bachelor’s degrees, 29.8% have diplomas, followed by 15.5% with honours degree, 9.5% with master’s degree, then 7.1% with grade 12 and lastly 2.4% with formal certificates.

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39.3 40

35 29.8 30

20 15.5 15 9.5 10 7.1

5 2.4

0 Grade 12 Certificate Diploma Bachelor degreeHonours degree Masters degre

Figure 8.10: Workforce grouped according to qualification.

8.4 Section C: Descriptive statistics for lean assessment This section presents the lean assessment of the research questionnaires, which focuses on the implementation of lean in the South African airline industry. The following items are presented: descriptive analysis for lean benefits; improvement areas; company performance; lean assessment, factors contributing to the successful implementation of lean and lean implementation barriers. The descriptive test discloses the position of the factors from the uppermost to the lowest.

8.4.1 Descriptive statistics for Benefits of lean The below table 8.1 shows the results pertaining to the descriptive statistics for the possible benefits that could be generated through the implementation of lean within the airline industry. Hence, it can be observed from Table 8.1 below that “to improve the quality service” has the highest mean value of about 3.18 with a standard deviation of 0.808, followed by “to improve performance” with a mean of 3.11 and standard deviation of 0.871; “to improve the organisation competitiveness” represented by a mean of 3.07 and standard deviation of 0.833. “To decrease costs” is represented by a mean of 3.03 and a standard deviation of 0.826, “to improve customer satisfaction” represented by a mean of 3.03 and a standard deviation of 0.886. The benefits with the lowest mean are “to engage people” with 2.57 mean and a standard deviation of 0.975, followed by “to develop people” with a mean of 2.70 and a standard deviation of 0.979 and “to create culture of quality” represented by a mean of 2.85 and standard deviation of 1.020.

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Table 8.1: Descriptive statistics for benefits of lean. N Mean Std.

Deviation

To improve the quality of service 80 3.18 0.808

To improve performance 80 3.11 0.871

(process/working system)

To improve the organisation 81 3.07 0.833

competitiveness

To decrease costs 80 3.03 0.826

To improve customer satisfaction 80 3.03 0.886

To improve the financial performance 78 2.92 0.964

To create a culture of quality 78 2.85 1.020

To develop people 79 2.70 0.979

To engage people 75 2.57 0.975

8.4.2 Descriptive statistics for Lean improvement areas Table 8.2 below represents the descriptive statistics for improvement areas after the implementation of lean. The improvement areas with the highest mean are the areas that the respondents agreed on the most. These include the efficiency of processes with a mean of 3.90 and standard deviation of 1.188. The ability to achieve team targets with a mean of 3.88 and a standard deviation of 3.88. Recognition of good performance with 3.77 and a standard deviation of 3.77; the ability to highlight poor performance and quality of work, both with a mean of 3.73 with standard deviation of 1.123 and 1.206 respectively, followed by reduction of backlogs with 3.70 with a standard deviation of 1.10. The bottom four areas with the lowest mean are the visibility of senior staff with 3.27, followed by the improvement of working environment with 3.54. The job satisfaction and team work both with a lean of 3.56.

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Table 8.2: Descriptive statistics for improvement areas. N Mean Std.

Deviation

C3 Processes efficiency 84 3.90 1.188

C1 Achieving team targets 84 3.88 0.999

C11 Recognition of good performance 84 3.77 1.206

C2 Highlighting poor performance 84 3.73 1.123

C8 Quality of work 84 3.73 1.356

C12 Number of backlogs 84 3.70 1.190

C6 Collaborative problem solving 84 3.69 1.344

C9 Productivity 84 3.67 1.283

C10 Error rate 84 3.67 1.175

C13 Time management 84 3.65 1.256

C4 Team work 84 3.56 1.320

C5 Job satisfaction 84 3.56 1.311

C7 Working environment 84 3.54 1.312

C14 Visibility of senior staff 84 3.27 1.311

8.4.3 Descriptive statistics for Lean improvement areas in Quality Dimensions Table 8.3 below represents the descriptive statistics for quality dimensions. The quality dimensions with the highest mean are the areas that the respondents agreed on the most. These variables are arranged in the descending order, the highest mean being the increased willingness to assist with 2.54 a standard deviation of 0.594 followed by the increased safe transaction to customers with 2.50 and 0.646 SD, the ability to handle customers with 2.48 and0.617 SD, speed of service with 2.47 and 0.646 SD. The Ability to deliver service with 2.46 mean and 0.655 SD, accuracy of services with 2.44 mean and 0.659 SD, neat arranged office with the mean of 2.44 and SD of 0.66 . At number eight, it customers questions with 2.38 mean and 0.656 SD, followed at number nine by increased knowledge to answer with 2.43 mean and 0.668 SD. At number 10, it is the flexibility to service with

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2.42 mean and then provision of prompt service to customers at number eleven with a mean on 2.36 and standard deviation of 0.534. The last three quality dimensions with the lowest mean are improved visual representation with 2.18 mean and 0.683 SD, followed by Tasks completed on time without any errors with 2.28 mean and 0.624 SD and the ability to instil customer confidence with a mean of 2.31 and 0.634 SD.

Table 8.3: Descriptive statistics for quality dimensions. N Mean Std.

Deviation

D5 Increased willingness to assist 80 2.54 0.594

customers

D7 Increased safe transaction to 74 2.50 0.646

customers

D2 Ability to handle customers properly 79 2.48 0.617

from the start

D15 Speed of services 74 2.47 0.646

D1 Ability to deliver service to 80 2.46 0.655

customers

D13 Accuracy of services 77 2.44 0.659

D12 Neat and properly arranged office 75 2.44 0.663

equipment

D8 Increased knowledge to answer 72 2.43 0.668

D14 Flexibility of services 77 2.42 0.656

D9 customer’s questions 74 2.38 0.656

D4 Provision of prompt service to 80 2.36 0.534

customers

D10 Ability to pay attention to individual 74 2.32 0.760

customers

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Continuation of Table 8.3: Descriptive statistics for quality dimensions

D6 The ability to instil customer 77 2.31 0.634

confidence

D3 Tasks completed on time without 76 2.28 0.624

any errors

D11 Improved visual representation 71 2.18 0.683

8.4.4 Descriptive statistics for lean assessment on employee engagement The highest value of mean shows that most participants agree with the statement in the survey. As represented in table 8.4, statements with the highest mean are arranged in descending order. At first place is E12 with 3.08 mean and SD of 0.801, followed by E2 with 3.05 lean and 0.714 SD. At third place is E11 with 2.99 mean and 0.744 SD, followed at fourth place by E9 with 2.97 mean and 0.740 SD. At fifth place, it is E10 with 2.96 mean and 0.751 SD, followed at six places by E1 with a lean of 2.91 and SD of 0.830, then at seventh place it is E4 with a lean of 2.88 and 0.806 SD. At eight places, it is E5 with a mean of 2.81 and SD of 0.940, followed by E3 with 2.79 and 0.762. At tenth place, it is E8 with 2.74 mean and 0.839 SD, followed by E6 with 2.59 mean and 0.910 SD, then E7 with 2.47 mean and 0.883 SD.

Table 8.4: Descriptive statistics for Employment engagement. N Mean Std.

Deviation

E12 Lean business strategy has 75 3.08 0.801

enabled the department to match

resources to workload better

E2 The Lean Team provided support 79 3.05 0.714

for implementing the Lean initiative

E11 The Lean business strategy has 75 2.99 0.744

enabled the department to meet

customer requirements better

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Continuation of Table 8.4: Descriptive statistics for Employment engagement

E9 Through adoption of Lean 74 2.97 0.740 business strategy senior managers show their commitment for increasing performance

E10 As a result of Lean business 77 2.96 0.751 strategy, employees are focusing on improving the cross functional processes

E1 There is a link between the 77 2.91 0.830 company’s Lean approach and its long term strategic direction

E4 There was awareness of the 78 2.88 0.806 impact of the Lean business strategy

E5 Lean as an improvement 75 2.81 0.940 methodology is suitable for our organisation

E3 Communication about the Lean 78 2.79 0.762 business strategy has been good

E8 The implementation was more 72 2.74 0.839 problematic than it was anticipated

E6 The tools and techniques covered 73 2.59 0.910 in the Lean training were new to me

E7 The tools and techniques learnt 73 2.47 0.883 on the Lean training were used to implement the Lean initiative

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8.4.5 Descriptive statistics for factors contributing to the implementation of lean The below table 8.5 represents the descriptive statistics for factors that contribute positively to the implementation of lean. The highest value of mean from the below table represents that most participants agree with the statement in the survey. As represented below, the factors with the highest mean are, Involvement of relevant staff with 3.07 and standard deviation of 0.765, followed by the hands on approach to change with 3.07 lean and 0.806 SD, then good communication regarding the mean project with 3.04 lean and 0.895 SD. The least agreed on factors are adequate resources committed with 2.79 mean and 0.808 SD, followed by commitment of senior staff with 2.99 mean and 0.879 SD and lastly the provision of relevant training with a mean of 2.99 and a standard deviation of 0.826.

Table 8.5: Descriptive statistics for factors contributing the implementation of lean. Mean Std. N

Deviation

F1 Adequate resources committed 2.79 0.808 67

F2 Provision of relevant training 2.99 0.826 67

F3 Commitment from senior 2.99 0.879 67

management

F4 Good communication regarding 3.04 0.895 67

the Lean project

F5 Involvement of relevant staff 3.07 0.765 67

F6 Hands on approach to change 3.04 0.806 67

8.4.6 Descriptive statistics for Barriers of Lean implementation The factors that negatively affect the implementation of lean were also measured and the below table 8.6 represents the descriptive statistics for factors that affect the implementation of lean. The highest value of mean from the below table represents that most participants agree with the statement in the survey. As represented below, the factors with the highest mean are the lack of commitment by senior staff with 3.39 and standard deviation of 0.733, followed by staff resistance and lack of training, both with a mean of 3.31 and 0.773 SD. At number three, it lack of training with 3.31 and 0.889 SD, followed at fourth place by discomfort with change with a mean of 3.30 and

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0.861 SD. At fifth place is poor communication regarding change with 3.29 mean and 0.819SD, followed at sixth place by lack of accountability with 3.28 mean and 0.693 SD. The bottom three factors are, little time allowed for implementation with 3.17 mean and 0.803 SD, then culture of no change with 3.13 with 0.891 SD and lastly lack of commitment with a mean of 3.10 and standard deviation of 0.917.

Table 8.6: Descriptive statistics for Barriers to lean implementation. N Mean Std.

Deviation

G8 Lack of senior management 82 3.39 0.733

commitment

G3 Staff resistance 80 3.31 0.773

G6 Lack of training 81 3.31 0.889

G10 Discomfort with change 73 3.30 0.861

G4 Poor communication regarding 79 3.29 0.819

the project

G5 Lack of accountability 81 3.28 0.693

G9 Lack of resources 77 3.25 0.797

G7 Little time allowed for 81 3.17 0.803

implementation

G1 Culture of no change 80 3.13 0.891

G2 Lack of commitment 81 3.10 0.917

8.4.7 Descriptive statistics for Customer service quality dimensions Table 8.7 below represents the descriptive statistics for service quality dimensions. The service quality dimensions with the highest mean are the areas that the respondents agreed on the most. The top five with the highest mean being the neat staff with 4.29 and 1.062 SD, followed by detailed services with 4.18 mean and 1.033 SD , friendly staff with 4.01 mean and 1.061 SD, attractive facilities with 3.99 mean and 1.119 SD and information handled with confidentiality with 3.98 mean and 1.031 SD. The middle nine quality factors are, attentiveness to booking needs with 3.92 mean

123 and 1.067 SD, followed by prompt services with 3.91 mean and 1.127 SD. I found them to be courteous with 3.85 mean and 1.084 SD. Then ability to answer questions with 3.84 mean and 1.103 SD, followed by knowledge to answer questions with 3.83 mean and 1.081 SD. Services with speed and efficiency with 3.81 mean and 1.135 SD, then trustworthiness with 3.80 mean and 1.161 SD.

Followed by queries resolved promptly with 3.69 mean and 1.281 SD, then flexible services and products with a mean of 3.68 and a standard deviation of 1. 210. The last three quality dimensions with the lowest mean are the service as promised with 3.11 mean and 1.358 SD.

Followed by Error-free transaction with 3.20 mean and 1.464 SD and Information on change or progress of transactions with a mean of 3.24 mean and 1.409 SD.

Table 8.7: Descriptive statistics for service quality dimensions.

Mean Std. Deviation Analysis N

C15 The staff was neat and clean 4.29 1.062 112

C16 Their service products were detailed and 4.18 1.033 112

accurate – e.g. ticket information/arrival-

departure flight information

C12 They were friendly and caring 4.01 1.061 112

C14 They had attractive facilities (Appearance 3.99 1.119 112

& cleanliness)

C8 Information handled with confidentiality 3.98 1.031 112

C11 Experienced attentiveness to my booking 3.92 1.067 112

needs

C17 They offered prompt services - e.g. 3.91 1.127 112

check-in processing/ refunds/upgrade

C13 I found them to be courteous 3.85 1.084 112

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Continuation of Table 8.7: Descriptive statistics for service quality dimensions.

C7 Availability to answer questions 3.84 1.103 112

C9 Knowledge to answer questions 3.83 1.081 112

C6 Services with speed and efficiency 3.81 1.135 112

C10 Trustworthiness 3.80 1.161 112

C4 Queries handled promptly 3.69 1.281 112

C18 They offered flexible services/ products – 3.68 1.210 112

i.e. customised to suit the need

C2 Information on change or progress of 3.24 1.409 112

transactions

C3 Error-free transaction 3.20 1.464 111

C1 Service as promised (e.g. call back) 3.11 1.358 112

8.5 Section D: Exploratory factor analysis for customer service quality dimensions (CSQD) The results from the exploratory factor analysis (EFA) on the lean assessment principles are presented in table 8.10 and 8.12, where the codes and definitions are presented in below table 8.8. Before conducting the PCA, the appropriateness of the statistics data for factor analysis was considered. Examination of the correlation matrix showed the existence of coefficients of greater than 0.3. The KMO measure of sampling adequacy achieved a value of 0.940, which is higher than the recommended value of 0.6 and the Bartlett’s test of Sphericity was statistically significant < 0.05, hence supporting the factorability of the correlation matrix. Furthermore, table 8.9 is shown below representing the correlation matrix for quality service dimension, this is presented in codes as already defined in table 8.8.

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Table 8.8: Definition of identified customer service quality dimensions Codes Defination

C1 Service as promised

C2 Information on change

C3 Error-free transaction

C4 Queries handled promptly

C5 Willingness to help

C6 Services with speed and efficiency

C7 Availability to answer questions

C8 Information handled with confidentiality

C9 Knowledge to answer questions

C10 Trustworthiness

C11 Experinced attentiveness to my booking needs

C12 They were friendly and caring

C13 I found them to be courteous

C14 They had attractive facilities

C15 The staff was neat and clean

C16 Their service products were detailed and accurate

C17 They offered prompt services

C18 They offered flexible services/prodcuts

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Table 8.9: Correlation Matrix for quality service dimension

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17 C18 C1 1.000 0.631 0.350 0.532 0.552 0.592 0.529 0.439 0.546 0.488 0.479 0.518 0.482 0.510 0.459 0.429 0.553 0.493

C2 0.631 1.000 0.455 0.601 0.513 0.496 0.523 0.468 0.535 0.530 0.444 0.450 0.366 0.390 0.391 0.348 0.484 0.416

C3 0.350 0.455 1.000 0.529 0.397 0.497 0.418 0.368 0.388 0.364 0.344 0.369 0.290 0.277 0.300 0.322 0.270 0.158

C4 0.532 0.601 0.529 1.000 0.704 0.697 0.608 0.596 0.605 0.576 0.615 0.612 0.543 0.514 0.538 0.581 0.554 0.411

C5 0.552 0.513 0.397 0.704 1.000 0.764 0.588 0.674 0.638 0.601 0.600 0.678 0.591 0.672 0.718 0.678 0.625 0.492

C6 0.592 0.496 0.497 0.697 0.764 1.000 0.760 0.713 0.730 0.717 0.657 0.682 0.584 0.609 0.614 0.659 0.606 0.481

C7 0.529 0.523 0.418 0.608 0.588 0.760 1.000 0.671 0.702 0.749 0.617 0.586 0.559 0.480 0.479 0.547 0.561 0.474

C8 0.439 0.468 0.368 0.596 0.674 0.713 0.671 1.000 0.765 0.772 0.687 0.725 0.723 0.562 0.688 0.697 0.642 0.537

C9 0.546 0.535 0.388 0.605 0.638 0.730 0.702 0.765 1.000 0.806 0.715 0.700 0.654 0.542 0.663 0.657 0.630 0.557

C10 0.488 0.530 0.364 0.576 0.601 0.717 0.749 0.772 0.806 1.000 0.715 0.674 0.613 0.484 0.624 0.578 0.606 0.551

C11 0.479 0.444 0.344 0.615 0.600 0.657 0.617 0.687 0.715 0.715 1.000 0.741 0.605 0.566 0.705 0.667 0.578 0.559

C12 0.518 0.450 0.369 0.612 0.678 0.682 0.586 0.725 0.700 0.674 0.741 1.000 0.777 0.668 0.741 0.722 0.611 0.592

C13 0.482 0.366 0.290 0.543 0.591 0.584 0.559 0.723 0.654 0.613 0.605 0.777 1.000 0.638 0.673 0.660 0.601 0.595

C14 0.510 0.390 0.277 0.514 0.672 0.609 0.480 0.562 0.542 0.484 0.566 0.668 0.638 1.000 0.775 0.734 0.642 0.610

C15 0.459 0.391 0.300 0.538 0.718 0.614 0.479 0.688 0.663 0.624 0.705 0.741 0.673 0.775 1.000 0.855 0.707 0.600

C16 0.429 0.348 0.322 0.581 0.678 0.659 0.547 0.697 0.657 0.578 0.667 0.722 0.660 0.734 0.855 1.000 0.749 0.652

C17 0.553 0.484 0.270 0.554 0.625 0.606 0.561 0.642 0.630 0.606 0.578 0.611 0.601 0.642 0.707 0.749 1.000 0.738

C18 0.493 0.416 0.158 0.411 0.492 0.481 0.474 0.537 0.557 0.551 0.559 0.592 0.595 0.610 0.600 0.652 0.738 1.000

Table 8.10: KMO and Bartlett’s Test for customer service quality dimensions

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling 0.940 Adequacy.

Bartlett's Test of Sphericity Approx. 1762.143 Chi- Square Df 153

Sig. 0.000

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Table 8.11: Total variance explained for customer service quality dimensions The below table 8.11 shows the total variance explained for customer service quality dimensions which shows the number of factors and their Eigenvalues. Later on Figure 8.11 will be presented to demonstrate a Scree plot of factor analysis for customer service quality dimensions showing the Eigenvalues that are above one.

FACTOR Rotation Sums of Squared Initial Eigenvalues Extraction Sums of Squared Loadings Loadings % of Total Variance Cumulative % Total % of Variance Cumulative % Total 1 10.956 60.869 60.869 10.625 59.030 59.030 9.662 2 1.388 7.714 68.582 0.986 5.477 64.507 8.509 3 0.895 4.971 73.553 4 0.806 4.476 78.028 5 0.525 2.916 80.945 6 0.499 2.774 83.719 7 0.447 2.485 86.204 8 0.393 2.185 88.389 9 0.364 2.021 90.410 10 0.307 1.703 92.113 11 0.259 1.439 93.552 12 0.220 1.221 94.773 13 0.199 1.105 95.878 14 0.188 1.042 96.920 15 0.175 0.973 97.892 16 0.160 0.887 98.780 17 0.135 0.752 99.532 18 0.084 0.468 100.000

Principal axis factoring showed the existance of two factors with eigenvalues greater than 1 as shown in figure 8.11. Based on the evaluation of the inherent relationships between the variables under each factor, we made the following interpretations. We named factor 1 was named Customer Relations and factor two was named Organisation excellence. The two factors were named based on their connection with their variables. Below is the explanation of the two factors and how theye were derived.

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Factor 1: Customer Relations

As presented in table 8.12, the four lean assessment ideologies for Factor one were the staff was neat and clean (96.6%), their service products were detailed and accurate (94.7). They had attractive facilities (82.2%); offered flexible services/ products (75.0%). Furthermore, they offered prompt services (72.3%), and they were found to be courteous (70.3); and were friendly and caring (68.2%). Additionally, they experienced attentiveness to the booking needs (53.5%), and lastly the information was handled with great confidentiality (53.1%).

Factor 2 : Organisation excellence

The eight lean assessment ideologies for factor two were information on change or progress of transactions (74.0%), availability to answer questions (67.6%), Queries handled promptly (67.6%), Error-free transaction (66.4%), services with speed and efficiency (65.0%), trustworthiness (57.2%), service as promised (53.3) and lastly knowledge to answer questions (52.5%).

Figure 8.11: Scree plot for factor analysis for customer service quality dimensions

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Table 8.12: Pattern matrix for customer service quality dimensions

Pattern Matrix Factor 1 2 C15 The staff was neat and clean 0.966

C16 Their service products were detailed 0.947 and accurate – e.g. ticket information/arrival- departure flight information C14 They had attractive facilities 0.822 (Appearance & cleanliness) C18 They offered flexible services/ 0.750 products – i.e. customised to suit the need C17 They offered prompt services - e.g. 0.723 check-in processing/ refunds/upgrade C13 I found them to be courteous 0.703 C12 They were friendly and caring 0.682

C11 Experienced attentiveness to my 0.535 booking needs C8 Information handled with 0.531 confidentiality C2 Information on change or progress of 0.740 transactions C7 Availability to answer questions 0.717 C4 Queries handled promptly 0.676 C3 Error-free transaction 0.664 C6 Services with speed and efficiency 0.650

C10 Trustworthiness 0.572 C1 Service as promised (e.g. call back) 0.533

C9 Knowledge to answer questions 0.525

8.6 Section E: Exploratory factor analysis for benefits of lean Section E presents the factor analysis results with the aim to determine the benefits of lean that are important and applicable in the airline industry. Before conduting the PCA, the appropriatenes of the data for factor analysis was measured. The examination of the correlation matrix showed the existence of the coefficients of above 0.3 as shown in table 8.14. Table 8.15 achived a KMO value of 0.851, which is above the recommended value of 0.6. Table 8.14 also reveals that the Bartlett’s test was statistically significant with a value that is less than 0.05, hence suggesting the factorability of the correlation matrix.

To this end, the following variables were identified as important benefits of lean and the table 8.13 below presents a definition for each variable.

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Table 8.13: Definition of identified variables for benefits of lean B1 To improve the quality of service

B2 To improve the organisation competitiveness

B3 To decrease costs

B4 To improve customer satisfaction

B5 To improve performance (process/working system)

B6 To improve the financial performance

B7 To create a culture of quality

B8 To develop people

B9 To engage people

Table 8.14: Correlation matrix for factor analysis for benefits of lean

B1 B2 B3 B4 B5 B6 B7 B8 B9 B1 1.000 0.709 0.638 0.773 0.691 0.586 0.603 0.448 0.441 B2 0.709 1.000 0.642 0.760 0.706 0.606 0.466 0.524 0.493 B3 0.638 0.642 1.000 0.674 0.699 0.577 0.512 0.426 0.504 B4 0.773 0.760 0.674 1.000 0.685 0.673 0.688 0.570 0.547 B5 0.691 0.706 0.699 0.685 1.000 0.620 0.413 0.377 0.295 B6 0.586 0.606 0.577 0.673 0.620 1.000 0.744 0.642 0.561 B7 0.603 0.466 0.512 0.688 0.413 0.744 1.000 0.809 0.778 B8 0.448 0.524 0.426 0.570 0.377 0.642 0.809 1.000 0.825 B9 0.441 0.493 0.504 0.547 0.295 0.561 0.778 0.825 1.000

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Table 8.15: KMO and Bartlett’s test for benefits of lean

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling 0.851 Adequacy. Bartlett's Test of Approx. Chi-Square 544.254 Sphericity df 36 Sig. 0.000

Table 8.16: Total variance explained for benefits of lean

Rotation Sums of Squared Initial Eigenvalues Extraction Sums of Squared Loadings Loadings % of % of Component Total Variance Cumulative % Total Variance Cumulative % Total 1 5.838 64.863 64.863 5.838 64.863 64.863 5.146 2 1.285 14.274 79.137 1.285 14.274 79.137 4.465 3 0.440 4.889 84.026 4 0.416 4.620 88.646 5 0.369 4.105 92.751 6 0.237 2.631 95.382 7 0.199 2.213 97.595 0.131 1.454 99.049 8 9 0.086 0.951 100.000

Figure 8.12: Scree plot for factor analysis for benefits of lean

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Table 8.17: Pattern Matrix for benefits of lean

Factor 1 2 B5 To improve performance 0.979 (process/working system) B1 To improve the quality of 0.800 service B2 To improve the 0.797 organisation competitiveness B4 To improve customer 0.746 satisfaction B3 To decrease costs 0.735 B6 To improve the financial 0.473 performance B8 To develop people 0.918 B9 To engage people 0.891 B7 To create a culture of 0.841 quality

Figure 8.12 above revealed two factors with eigenvalue above the one. Based on the evaluation of the inherent relationships between the variables under each factor, we made the following interpretations. We named factor 1 was named Company improvement and factor two was named Employee satisfaction. The two factors were named based on their connection with their variables. Below is the explanation of the two factors and how they were derived.

Factor 1: Company improvement

The above table 8.17 reprents the following six lean assessment ideologies for factor one:

To improve performance (97.9%), to improve the quality of service (80%), to improve the organisation competitiveness (79.9%), to improve customer satisfaction (74.6%), to decrease cost (73.5%), to improve financial performance (47.3), they were friendly and caring (68.2), experienced attentiveness to my booking needs (53.5%) and lastly information handled with confidentiality (53.1).

Factor 2 : Employee satisfaction

The three lean assessment ideologies for factor two were to develop people (91.8%), to engage people (89.1%), to create culture (84.1%).

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8.7 section F: Exploratory factor analysis for lean improvement areas This section presents the factor analysis results with the aim to determine how the lean improvement areas might help airline industry to improve their services and products. Before conduting the PCA, the appropriatenes of the data for factor analysis was measured. The examination of the correlation matrix showed the existence of the coefficients of above 0.3 as shown in table 8.19. Table 8.20 achived a KMO value of 0.827, which is above the recommended value of 0.6. Table 8.20 also reveals that the Bartlett’s test was statistically significant with a value that is less than 0.05, hence suggesting the factorability of the correlation matrix. To this end, the following variables were identified as improvement areas of lean and the table 8.18 below presents a definition for each variable. In addition, table 8.22 is shown below representing the Pattern matrix for Lean improvement areas, highlighting three important factors that will be discussed later on this section.

Table 8.18: Definition of identified variables lean improvement areas (IMP)

IMP1 Achieving team targets

IMP2 Highlighting poor performance

IMP3 Processes efficiency

IMP4 Team work

IMP5 Job satisfaction

IMP6 Collaborative problem solving

IMP7 Working environment

IMP8 Quality of work

IMP9 Productivity

IMP10 Error rate

IMP11 Recognition of good performance

IMP12 Number of backlogs

IMP13 Time management

IMP14 Visibility of senior staff

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Table 8.19: Correlation matrix for factor analysis for IMP

IMP1 IMP2 IMP3 IMP4 IMP5 IMP6 IMP7 IMP8 IMP9 IMP10 IMP11 IMP12 IMP13 IMP14 1.000 0.389 0.305 0.279 0.263 0.349 0.261 0.518 0.457 0.345 0.518 0.416 0.447 0.182 IMP1 0.389 1.000 0.513 0.316 0.138 0.127 0.305 0.235 0.387 0.186 0.283 0.326 0.240 0.256 IMP2 0.305 0.513 1.000 0.326 0.367 0.245 0.242 0.223 0.271 0.305 0.271 0.329 0.268 0.195 IMP3 0.279 0.316 0.326 1.000 0.415 0.391 0.506 0.490 0.353 0.300 0.300 0.230 0.169 0.203 IMP4 0.263 0.138 0.367 0.415 1.000 0.557 0.503 0.419 0.506 0.248 0.287 0.332 0.331 0.386 IMP5 0.349 0.127 0.245 0.391 0.557 1.000 0.553 0.587 0.414 0.330 0.231 0.363 0.550 0.308 IMP6 0.261 0.305 0.242 0.506 0.503 0.553 1.000 0.537 0.422 0.195 0.352 0.528 0.421 0.264 IMP7 0.518 0.235 0.223 0.490 0.419 0.587 0.537 1.000 0.549 0.547 0.544 0.486 0.474 0.246 IMP8 0.457 0.387 0.271 0.353 0.506 0.414 0.422 0.549 1.000 0.413 0.441 0.345 0.361 0.406 IMP9 0.345 0.186 0.305 0.300 0.248 0.330 0.195 0.547 0.413 1.000 0.363 0.393 0.394 0.130 IMP10 0.518 0.283 0.271 0.300 0.287 0.231 0.352 0.544 0.441 0.363 1.000 0.607 0.385 0.223 IMP11 0.416 0.326 0.329 0.230 0.332 0.363 0.528 0.486 0.345 0.393 0.607 1.000 0.543 0.176 IMP12 0.447 0.240 0.268 0.169 0.331 0.550 0.421 0.474 0.361 0.394 0.385 0.543 1.000 0.409 IMP13 0.182 0.256 0.195 0.203 0.386 0.308 0.264 0.246 0.406 0.130 0.223 0.176 0.409 1.000 IMP14

Table 8.20: KMO and Bartlett’s test for IMP

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.827 Bartlett's Test of Sphericity Approx. Chi-Square 496.550 df 91 Sig. 0.000

Table 8.21: Total variance explained for IMP The below table 8.21 shows the total variance explained for Lean improvement areas which shows the number of factors and their Eigenvalues

Total Variance Explained

Rotation Sums of Extraction Sums of Squared Squared Initial Eigenvalues Loadings Loadings % of % of Componen Varianc Cumulativ Varianc Cumulativ t Total e e % Total e e % Total 1 5.735 40.962 40.962 5.735 40.962 40.962 4.664

2 1.305 9.323 50.285 1.305 9.323 50.285 4.316

3 1.194 8.527 58.812 1.194 8.527 58.812 2.008

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Continuation of Table 8.21: Total variance explained for IMP

4 0.995 7.106 65.918

5 0.856 6.111 72.029

6 0.791 5.651 77.680

7 0.651 4.653 82.334

8 0.607 4.335 86.669

9 0.523 3.733 90.402

10 0.333 2.379 92.780

11 0.289 2.064 94.845

12 0.266 1.903 96.748

13 0.236 1.689 98.437

14 0.219 1.563 100.000

Figure 8.13: Scree plot for factor analysis for IMP

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Table 8.22: Pattern Matrix for IMP

Factor 1 2 3 C5 Job satisfaction 0.803 C6 Collaborative problem solving 0.745

C7 Working environment 0.602

C4 Team work 0.486 C14 Visibility of senior staff 0.416

C9 Productivity 0.377 C2 Highlighting poor performance 0.865

C3 Processes efficiency 0.462 C11 Recognition of good 0.799 performance C12 Number of backlogs 0.692

C8 Quality of work 0.642 C1 Achieving team targets 0.635

C10 Error rate 0.551 C13 Time management 0.507

Figure 8.13 above revealed three factors with eigenvalue above one. Based on the evaluation of the inherent relationships between the variables under each factor, we made the following interpretations. Factor 1 was named Collaboration , factor two was named process efficiency then factor three was named Culture of Quality. The three factors were named based on their connection with their variables. Below is the explanation of the two factors and how they were derived.

Factor 1: Collaboration

The above table 8.22 reprents the following six lean assessment ideologies for factor one:

Job satisfaction (80.3%), collaborative problem solving (74.5%); working environment (760.2%); teamwork (48.6%); visibility of senior staff (41.6%); productivity (37.7%).

Factor 2 : Employee satisfaction

The two lean assessment ideologies for factor two were to highlight poor performance (86.5%) and processes efficiency (46.2%).

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Factor 3 : Culture of Quality

The six lean assessment ideologies for factor three were recognition of good performance (79.9%), number of backlogs (69.2%), quality of work (64.2%), achieving team targets (63.5%); error rate (55.1) and time management (50.7%).

8.8 Section G: Exploratory factor analysis for company performance on quality dimensions This section presents the factor analysis results for company performance on quality dimensions. Before conduting the PCA, the appropriatenes of the data for factor analysis was measured. The examination of the correlation matrix showed the existence of the coefficients of above 0.3 as shown in table 8.24. Table 8.25 achived a KMO value of 0.827, which is above the recommended value of 0.6. Table 8.25 also reveals that the Bartlett’s test was statistically significant with a value that is less than 0.05, hence suggesting the factorability of the correlation matrix. To this end, the following variables were identified as important quality dimensions to company performance and the table 8.23 below presents a definition for each variable. Furthermore Table 8.26 will be presented to demonstrate the total variance explained for quality dimensions as means of showing the number of factors and their Eigenvalues.

Table 8.23: Definition of identified variables for QD QD1 Ability to deliver service to customers QD2 Ability to handle customers properly from the start

QD3 Tasks completed on time without any errors QD4 Provision of prompt service to customers QD5 Increased willingness to assist customers QD6 The ability to instil customer confidence QD7 Increased safe transaction to customers QD8 Increased knowledge to answer customer’s questions QD9 Ability to pay attention to individual customers QD10 Ability to understand customer’s specific needs QD11 Improved visual representation QD12 Neat and properly arranged office equipment QD13 Accuracy of services QD14 Flexibility of services QD15 Speed of services

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Table 8.24: Correlation matrix for factor analysis for QD

QD1 QD2 QD3 QD4 QD5 QD6 QD7 QD8 QD9 QD10 QD11 QD12 QD13 QD14 QD15

QD1 1.000 0.572 0.495 0.257 0.200 0.503 0.175 0.381 0.162 0.369 0.372 0.080 0.100 0.109 0.189

QD2 0.572 1.000 0.433 0.169 0.447 0.278 0.334 0.525 0.348 0.488 0.371 0.205 0.431 0.226 0.388

QD3 0.495 0.433 1.000 0.263 0.115 0.488 0.385 0.347 0.239 0.441 0.271 0.239 0.207 0.342 0.232

QD4 0.257 0.169 0.263 1.000 0.314 0.565 0.304 0.366 0.188 0.169 0.356 0.266 0.068 0.183 0.381

QD5 0.200 0.447 0.115 0.314 1.000 0.223 0.478 0.381 0.471 0.370 0.400 0.471 0.485 0.461 0.438

QD6 0.503 0.278 0.488 0.565 0.223 1.000 0.398 0.352 0.334 0.384 0.337 0.302 0.139 0.195 0.320

QD7 0.175 0.334 0.385 0.304 0.478 0.398 1.000 0.290 0.360 0.302 0.143 0.173 0.104 0.308 0.355

QD8 0.381 0.525 0.347 0.366 0.381 0.352 0.290 1.000 0.337 0.415 0.467 0.367 0.347 0.290 0.316

QD9 0.162 0.348 0.239 0.188 0.471 0.334 0.360 0.337 1.000 0.643 0.455 0.396 0.500 0.567 0.561

QD10 0.369 0.488 0.441 0.169 0.370 0.384 0.302 0.415 0.643 1.000 0.653 0.488 0.449 0.511 0.528

QD11 0.372 0.371 0.271 0.356 0.400 0.337 0.143 0.467 0.455 0.653 1.000 0.602 0.462 0.462 0.559

QD12 0.080 0.205 0.239 0.266 0.471 0.302 0.173 0.367 0.396 0.488 0.602 1.000 0.469 0.594 0.578

QD13 0.100 0.431 0.207 0.068 0.485 0.139 0.104 0.347 0.500 0.449 0.462 0.469 1.000 0.515 0.558

QD14 0.109 0.226 0.342 0.183 0.461 0.195 0.308 0.290 0.567 0.511 0.462 0.594 0.515 1.000 0.649

QD15 0.189 0.388 0.232 0.381 0.438 0.320 0.355 0.316 0.561 0.528 0.559 0.578 0.558 0.649 1.0 00

Table 8.25: KMO and Bartlett’s test for QD

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.770

Bartlett's Test of Sphericity Approx. Chi-Square 458.334

df 105

Sig. 0.000

Table 8.26: Total variance explained for QD

Total Variance Explained Rotation Sums of Extraction Sums of Squared Squared Initial Eigenvalues Loadings Loadings

% of Cumulative Factor Total % of Variance Cumulative % Total Variance % Total 1 6.175 41.168 41.168 5.766 38.443 38.443 5.129 2 1.873 12.489 53.656 1.477 9.843 48.287 3.697 3 1.199 7.994 61.651 0.855 5.703 53.990 2.671 4 1.040 6.933 68.584 0.721 4.804 58.794 1.755 5 0.917 6.116 74.699 6 0.648 4.321 79.020

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Continuation of Table 8.26: Total variance explained for QD

7 0.579 3.859 82.879 8 0.534 3.562 86.441 9 0.470 3.132 89.574 10 0.401 2.676 92.250 11 0.355 2.369 94.619 12 0.294 1.959 96.578 13 0.213 1.419 97.997 14 0.170 1.134 99.132 15 0.130 0.868 100.000

The below figure represents the Scree plot of factor analysis for quality dimensions showing the

Eigenvalues that are above one.

Figure 8.14: Scree plot for factor analysis for QD

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The last table on this section is Table 8.27 which demonstrates to the reader the Pattern matrix for Quality Dimensions, underlining four important factors that will be discussed later on this section.

Table 8.27: Pattern Matrix for QD

Factor

1 2 3 4 D12 Neat and properly arranged office 0.812 equipment D14 Flexibility of services 0.806 D15 Speed of services 0.762 D13 Accuracy of services 0.753 D11 Improved visual representation 0.671

D9 customer’s questions 0.641

D10 Ability to pay attention to individual 0.568 customers D5 Increased willingness to assist 0.508 customers D2 Ability to handle customers properly 0.902 from the start

D1 Ability to deliver service to 0.778 customers D3 Tasks completed on time without 0.417 any errors D8 Increased knowledge to answer 0.380

D6 The ability to instil customer 0.742 confidence D4 Provision of prompt service to 0.626 customers D7 Increased safe transaction to 0.816 customers

Based on the evaluation of the inherent relationships between the variables under each factor, we made the following interpretations. Factor 1 was named Organisation values, factor two was named Workforce engagement, factor three was named Organisation culture, then factor four was named Partnership. The three factors were named based on their connection with their variables. Below is the explanation of the two factors and how they were derived.

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Factor 1: Organisation values

The above table 8.22 reprents the following six lean assessment ideologies for factor one:

Job satisfaction (80.3%), collaborative problem solving (74.5%); working environment (760.2%); teamwork (48.6%); visibility of senior staff (41.6%); productivity (37.7%).

Factor 2 : Workforce engagement

The two lean assessment ideologies for factor two were to highlight poor performance (86.5%) and processes efficiency (46.2%).

Factor 3 : Organisation culture

Factor 4 : Partnership

8.9 Section H: Exploratory factor analysis for factors contributing to the implementation of lean This section presents the factor analysis results for lean assessment on employee engagement. Before conduting the PCA, the appropriatenes of the data for factor analysis was measured. The examination of the correlation matrix showed the existence of the coefficients of above 0.3 as shown in table 8.29. Table 8.30 achived a KMO value of 0.826, which is above the recommended value of 0.6. Table 8.30 also reveals that the Bartlett’s test was statistically significant with a value that is less than 0.05, hence suggesting the factorability of the correlation matrix. In addition, figure 8.15 will also be presented to demosntrate the Scree plot of factor analysis for lean assessment on employee engagement showing the Eigenvalues that are above one. The factor matrix in Table 8.31 revealed one factor for lean assessment on employee engagement and this factor is discussed in detailed later on this section. The following variables were identified as crucial factors that contribute to the success of the lean implementation and the table 8.28 below presents a definition for each variable.

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Table 8.28: Definition of identified variables for factors contributing to the implementation of lean.

R 1 Adequate resources committed

R 2 Provision of relevant training

R 3 Commitment from senior management

R 4 Good communication regarding the Lean project

R 5 Involvement of relevant staff

R 6 Hands on approach to change

Table 8.29: Correlation matrix for factor analysis for R

R 1 R 1 R 1 R 1 R 1 R 1

R 1 1.000 0.574 0.646 0.468 0.684 0.565

R 1 0.574 1.000 0.781 0.780 0.671 0.530

R 1 0.646 0.781 1.000 0.662 0.777 0.535 R 1 0.468 0.780 0.662 0.610 0.654 1.000 R 1 0.684 0.671 0.777 0.610 1.000 0.708

R 1 0.565 0.530 0.535 0.654 0.708 1.000

Table 8.30: KMO and Bartlett’s test for R

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.826 Bartlett's Test of Sphericity Approx. 291.816 Chi-Square df 15 Sig. 0.000

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Figure 8.15: Scree plot for factor analysis for R :

Table 8.31: Factor matrix for R

Factor Matrix Factor 1 Involvement of relevant staff 0.872

Commitment from senior management 0.863

Provision of relevant training 0.842

Good communication regarding the Lean project 0.789

Hands on approach to change 0.730

Adequate resources committed 0.718

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The below table 8.32 reprents the following six lean assessment ideologies for this factor:

Total Variance Explained Extraction Sums of Squared Initial Eigenvalues Loadings % of Cumulative % of Cumulative

Component Total Variance % Total Variance % 1 4.225 70.414 70.414 4.225 70.414 70.414 2 0.611 10.176 80.590 3 0.540 8.997 89.586 4 0.313 5.210 94.797 5 0.162 2.702 97.499 6 0.150 2.501 100.000

Figure 8.15 above revealed one factor with eigenvalue above one. Based on the evaluation of the inherent relationships between the variables under this factor,we named this factor Proficient operations management. This factor was named based on the connection with its variables.

Factor 1: Proficient operations management

Involvement of people (87.2%), commitment from senior management (86.3%); provision of relevant training (84.2%); good communication regarding lean project (78.9%); hands on approach (73%); adequate resources (71.8%).

8.10 Section I: Exploratory factor analysis for barriers of implementation of lean This section presents the factor analysis results for lean assessment on employee engagement. Before conduting the PCA, the appropriatenes of the data for factor analysis was measured. The examination of the correlation matrix showed the existence of the coefficients of above 0.3 as shown in table 8.34. Table 8.35 achived a KMO value of 0.826, which is above the recommended value of 0.6. Table 8.35 also reveals that the Bartlett’s test was statistically significant with a value that is less than 0.05, hence suggesting the factorability of the correlation matrix. Furthermore table 8.36 will later be presented to demonstrate the total variance explained for factors affecting the implementation of lean which shows the number of factors and their Eigenvalues.

The following variables were identified as crucial factors that contribute to the success of the lean implementation and the table 8.33 below presents a definition for each variable.

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Table 8.33: Definition of identified variables for lean Barriers (F) F1 Culture of no change F2 Lack of commitment F3 Staff resistance F4 Poor communication regarding the project F5 Lack of accountability F6 Lack of training F7 Little time allowed for implementation F8 Lack of senior management commitment F9 Lack of resources F10 Discomfort with change

Table 8.34: Correlation matrix for factor analysis for F

F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F1 1.000 0.622 0.616 0.315 0.482 0.521 0.497 0.310 0.404 0.405 F2 0.622 1.000 0.617 0.619 0.650 0.781 0.475 0.534 0.442 0.563 F3 0.616 0.617 1.000 0.578 0.723 0.630 0.577 0.571 0.475 0.614 F4 0.315 0.619 0.578 1.000 0.754 0.668 0.369 0.689 0.560 0.364 F5 0.482 0.650 0.723 0.754 1.000 0.715 0.419 0.643 0.641 0.582 F6 0.521 0.781 0.630 0.668 0.715 1.000 0.453 0.594 0.726 0.663 F7 0.497 0.475 0.577 0.369 0.419 0.453 1.000 0.480 0.541 0.496 F8 0.310 0.534 0.571 0.689 0.643 0.594 0.480 1.000 0.767 0.596 F9 0.404 0.442 0.475 0.560 0.641 0.726 0.541 0.767 1.000 0.559 F10 0.405 0.563 0.614 0.364 0.582 0.663 0.496 0.596 0.559 1.000

Table 8.35: KMO and Bartlett’s test for F

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.720 Bartlett's Test of Sphericity Approx. Chi- 551.314 Square df 45 Sig. 0.000

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Figure 8.16 below is a Scree plot of factor analysis for factors affecting the implementation of lean and it shows the Eigenvalues that are above one.

Figure 8.16: Scree plot for factor analysis for F

Table 8.36: Total variance explained for F

Total Variance Explained Extraction Sums of Squared Initial Eigenvalues Loadings % of Cumulative % of Cumulative Factor Total Variance % Total Variance % 1 6.104 61.038 61.038 5.696 56.965 56.965 2 0.984 9.839 70.876 3 0.774 7.744 78.620 4 0.568 5.682 84.302 5 0.485 4.847 89.148 6 0.399 3.991 93.139 7 0.299 2.988 96.127 8 0.195 1.951 98.078 9 0.145 1.454 99.532 10 0.047 0.468 100.000

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The factor matrix in Table 8.37 below revealed one important factor for factors affecting the implementation of lean and this factor is discussed in detailed later on this section.

Table 8.37: Factor Mattrix for F

Factor Matrix Factor 1 G6 Lack of training 0.868 G5 Lack of accountability 0.846 G3 Staff resistance 0.798 G2 Lack of commitment 0.787 G8 Lack of senior management commitment 0.771 G9 Lack of resources 0.758 G4 Poor communication regarding the 0.738 project G10 Discomfort with change 0.714

G7 Little time allowed for implementation 0.619

G1 Culture of no change 0.603

Figure 8.16 above revealed one factor with eigenvalue above one. Based on the evaluation of the inherent relationships between the variables under this factor,we named this factor Company malfunctions . This factor was named based on the connection with its variables.

Factor 1: Company malfunctions

The above table 8.37 reprents the following ten lean assessment ideologies for this factor:

Lack of training (86.8%), lack of accountability (84.6%); staff resistance (79.8%); lack of commitment (78.7%); lack of senior management communication (77.1%); lack of resources (75.8%), poor communication (73.8%), discomfort with change (71.4%), little time allowed for implementation (61.9%) and culture of no change (60.3%).

8.6 RELIABILITY TEST To make a forecast about the population, the researcher tested for reliability, application of multiple regression and correlation using the collected data. The below table shows the reliability test done for calculating the Cronbach’s alpha on lean benefits, improvement areas, quality dimensions, employee engagement, factors facilitating lean and factors that affect the implementation of lean.

The results of Cronbach’s alpha for employees is listed on table 8.38 as follows: Lean benefits 0.943, the improvement areas is 0.886, quality dimensions is 0.922, employee engagement is 0.910, factors

148 facilitating the implementation of lean and factors affecting the implementation of lean is 0.920 and 0.941 respectively. The acceptable Cronbach’s value according to Tayokol and Dennick 2011 is between 0.7 and 0.9. Based on this statement, the Cronbach value is acceptable on all items tested.

Table 8.38: Reliability analysis

Cronbach's Alpha Cronbach's Alpha Based on N of Items Standardized Items Benefits 0.943 0.944 9 Improvement areas 0.886 0.886 14 Quality Dimensions 0.922 0.921 15 Employee engagement 0.910 0.911 12

Factors facilitating the 0.920 0.920 6 implementation of lean Factors affecting the 0.941 0.943 10 implementation of lean

8.7 Normality Test The normality test is carried out to determine if the sample was taken from a population that follows normal distribution (Razali & Wah 2011). This test was done on the Quality service dimensions, that is, Reliability, Responsiveness, Assurance, Empathy, Tangibles and Technical features and further represented in Table 8.39 and Figure 8.17 below.

Table 8.39 Normality table.

Kolmogorov-Smirnov Shapiro-Wilk Statistic df Sig. Statistic df Sig. Reliability 0.129 112 0.000 0.951 112 0.000 Responsiveness 0.187 112 0.000 0.881 112 0.000 Assurance 0.167 112 0.000 0.898 112 0.000 Empathy 0.183 112 0.000 0.875 112 0.000 Tangibles 0.218 112 0.000 0.809 112 0.000 Technical features 0.147 112 0.000 0.890 112 0.000

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Figure 8.17: Normality graph.

As stated on Table 8.39 above, the Kolmogorov-Smirnov test results on quality service dimensions were recorded as follows: Reliability is 0.129, Responsivenes is 0.187, Assuarnec is 0.167, Emphathy is 0.183, Tangibles is 0.218 and lastly Technical features is 0.147. The normal distributition is indicated by a p-value that is greater than 0.05, (Ghasemi and Zahediasi, 2012). All the p-values presented in table 8.14 are higher than 0.05 and this suggests a normal distribution as stated by (Ghasemi and Zahediasi, 2012).

Shapiro-Wilk test results on quality service dimensions presented on table 8.14 above were recorded as follows: Reliability is 0.951, Responsivenes is 0.881, Assuarnec is 0.898, Emphathy is 0.875, Tangibles is 0.809 and lastly Technical features is 0.890. The normal distributition is indicated by a p-value that is greater than 0.05, (Ghasemi and Zahediasi, 2012). According to Razali and Wah 2011, the normal distribution figures must range between 0 and 1. The values presented in Table for 8.14 for Shapiro-Wilk test are all between 0 and 1 and this suggests normal distribution.

8.8 Chapter Summary This chapter presented the findings of the results; these results were demonstrated in tables and graphs. They will be discussed in detail in the next chapter.

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CHAPTER 9: DISCUSSION OF FINDINGS

9.1 Introduction The purpose of this chapter is to discuss the results of the research, aligning them with the research questions, also taking into account the literature review discussed in the previous chapters. The study utilised a number of techniques with reference to Chapter Eight and these include: Descriptive statistics of biographical data, reliability analysis of the data using Cronbach’s alpha coefficient, factor analysis and normality test. The structure of the discussions is based on the two types of survey questionnaires used.

9.2 Discussion of customer’s biographic profile The discussion of customer’s biographic profile focuses on the customer’s age, gender, level of education, regular use of airlines.

1. Age As shown in Chapter Eight, the participants that took part in this study by answering to different questions contained in the survey were in between the ages 20-25 with 5.4%, 26-35 with 89.3% and lastly 36-45 with 5.4%. The middle age (26-35) is the age group that participated the most on the customer survey, leading with 89.3%.

2. Gender

Out of 112 survey respondents, 60.7% of them were females and 39.3% of them were males. Therefore, a large number of people who participated in the survey were females.

3. Highest level of qualification

The group with the highest percentage of education is the group with a Bachelor’s degree, represented by 36%, equivalent to 40 frequency. Followed by people with Diplomas at 19.8%, equivalent to 22 frequency. The third category is honours degree presented by 19 frequency at 17.1%, followed by a category with Masters Qualification, represented by 17 frequency at 15.3%, then people with grade 12 represented by 3 frequency with 2.7%. The PhDs, Certificates and other, are the bottom three qualifications with the same frequency of three and same percentage of 2.7%. This shows that most people who make use of the airline services are people with degrees. This information is important to the service providers to know the type of people they are servicing so that they can align their services and products with their market.

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4. How often do they use airline services? The question was categories into four groups and this is how they responded: customers who fly more than three times a year had a frequency of 43 with 38.4%, followed by customer who fly between 0-1 times after 2 years with 30 frequency and 26.8%. Customers who fly twice a year recorded a frequency of 21 and 18.8% and lastly people who fly once a year presented a frequency of 18 and 16.1%. Therefore, from the data collected, the people who fly the most were the highest number of people who completed the survey and recorded the highest frequency of 43.

9.3 Discussion of workforce biographic profile The discussion of workforce biographic profile focuses on the workforce age, gender, level of education, type of organisation they work for and years of experience with lean.

1. Age Out of 84 participants, 47 of them were between the ages 26-35 and the presented 56% of the sample, followed by the ages 20-25 with 22.6% and ages 36-45 recorded a frequency of 12 with 14.3%. The bottom 2 age-categories with the lowest percentage are 46-55 with a frequency of 4 at 4.8% and lastly ages 56-65 recorded a frequency of 2 with 2.4%.

2. Gender Out of 84 survey respondents, 52.4% of them were females and 47.6% of them were males. Therefore, a large number of people who participated in the survey were females.

3. Highest level of qualification The group with the highest percentage of education is the group with a Bachelor’s degree, represented by 39.3%, equivalent to 33 frequency. Followed by people with Diplomas at 29.8 equivalent to 25 frequency. The third category is Honours qualification presented by 13 frequency at 15.5%, followed by a category with Masters Qualification, represented by 8 frequency at 9.5%, then people with grade 12 represented by 6 frequency with 7.1% and lastly people with certificates recorded a frequency of 2 with 2.4%.

4. The number of years of practical experience with lean The question was categories into four groups. This is how the respondents responded: the group with experience less than 2 years recorded 31% with frequency of 26. Followed by 2-5 of work experience with lean, represented by 27.4% with a frequency of 23, then people with above 5 years of work experience with lean were represented by 25% with a frequency of 21 and the last group with the lowest percentage, is the group with no experience represented by a frequency of 14 and 16.7%.

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5. Sector/department represented by the respondents Out of 84 people who participated in the survey, 39 of them were in the production/manufacturing sector and they are the most people who participated in the survey with 46.4% as the highest percentage. The second group recorded a frequency of 18 with 21.4% and this is the engineering/technical and maintenance workers. The third group is other departments with a frequency of 8 and 9.5%. The forth group recorded a frequency of 7 and 8.3% and this is logistics/distribution and procurement, followed at fifth place by Information technology with a frequency of 4 and 4.8%. Finance/administration and Governmental organisations both recorded a frequency of 2 and 2.4%. The last groups recorded a frequency of one and represented by 1.2%, and these are Human Resources/University/Training, Sales/Marketing, Bank/Insurance, Human health/ Social work.

9.4 Service Quality Dimensions Research question: In your flying experience how often, have you experienced the following at check-ins?

The results from descriptive and exploratory factor analysis were used to answer this research question. The majority of people who completed the survey agreed that the staff at the airport is always neat, this is shown by the highest mean of 4.29 and standard deviation of 1.062. The also agreed that their services / products are detailed and accurate, this is shown by the second highest mean 4.18 and a standard deviation of 1.033.

9.5 LEAN This chapter will mostly assist us in getting answers to the research questions. This study aims at assessing the impact of lean manufacturing in airline industry and the following questions are used as guidelines to getting answers:

1. What benefits have been evident from Lean? 2. How can lean support to advance effectiveness of company processes? 3. What are the factors that contribute to the implementation of Lean? 4. What are the barriers of lean implementation? 5. What are the guidelines of successful implementation and sustainability of lean?

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9.5.1 Research Question 1 RQ1: What benefits have been evident from Lean?

We used the results from descriptive and exploratory factor analysis to answer the research questions. The results from the descriptive analysis revealed how the survey participants responded and their results were used to interpret and rank the benefits of lean based on the feedback received from the participants. From the above research question, “To improve the quality service” was ranked as the most important benefit of lean with the highest mean value of about 3.18 and a standard deviation of 0.808, followed by “to improve performance” with a mean of 3.11 and standard deviation of 0.871. These two benefits were ranked and recognised as the most important benefits of lean.

9.5.2 Research question 2 RQ2: How can lean support to advance effectiveness of company processes? The results from descriptive and exploratory factor analysis were used again to answer this research question. The results from the descriptive analysis revealed that the survey participants ranked the following factors as the most important factors that can assist to answer the above research question. The efficiency of processes was ranked the most important factor with a mean of 3.90 and standard deviation of 1.188 and to achieve team targets with a mean of 3.88 and a standard deviation of 3.88.

9.5.3 Research question 3 RQ 3: What are the factors that contribute to the implementation of Lean? A number of factors that contribute to the implementation of lean were presented in Chapter 8. Out of six factors presented, the survey participants felt that Involvement of relevant staff and hands-on approach to change were the two most important factors. These is seen by the highest standard deviation of 0.765 for Involvement of relevant staff and 0.806 for the hands-on approach to change.

9.5.4 Research question 4 RQ 4: What are the barriers of lean implementation?

The factors that negatively affect the implementation of lean were also measured and presented in Chapter 8. The highest value of mean represents that most participants agree with the statement in the survey. As represented in Chapter 8, the factors with the highest mean are the lack of commitment by senior staff with 3.39 and standard deviation of 0.733, followed by staff resistance with a mean of 3.31 and 0.773 SD. This means that the lack of commitment from senior management and staff resistance are considered the most important factors that can affect the implementation negatively if not addressed appropriately.

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CHAPTER 10: CONCLUSION AND RECOMMENDATIONS

10.1 Introduction In the past ten years the concept of Lean manufacturing has brought in an innovative management method for various business organisations, exclusively multinational firms that were previously organised and administered by means of conventional push systems. Enhancement outcomes could be dramatic with regard to quality, cycle times, and consumer’s responsiveness that is more than a set of apparatuses and techniques and have been largely implemented by various manufacturing firms. Although, lean manufacturing has gained so much attention within the manufacturing sector, however, literature presented in the present study clearly shows that there is a dearth of studies concerning lean implementation within the airline service industry. Over the last ten years, the airline sector has been growing and expanding at a fast speed, especially in the African continent. Hence, decision makers within this industry have been facing various challenges associated with creating a balance between long-run strategies with short-term solutions. One possible explanation to this is because consumer’s satisfaction is becoming more and more considerably imperative for airline operations and consequently service quality is gaining utmost significance within this industry. Hence, this study aimed at filling this gap by assessing the impact of lean manufacturing in the airline industry, using South Africa as case study. To this end, this chapter presents the summary of the findings of the research in relations to the research objectives. Then the overall research conclusion will be presented, in line with all the research objectives.

10.2 Conclusion The research objectives are listed below and will be further explained on how they were met, further to that will be an explanation of how they facilitated in achieving the research aim.

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10.2.1 Conclusion on Research Objective one o To acknowledge and understand the benefits of implementing lean as an improvement model

The first objective of this research sought to explore the benefits of implementing lean as an improvement tool. Lean is discussed in the literature review as set of ideas and methods that result in continuous improvement of the products by improving the necessary process steps while reducing the ones that do not put in value. It is becoming popular because of its ability to continuously improve the company’s performance and productivity, while it intensely reduces errors.

Findings from the survey questionnaire revealed that the top five benefits of lean are, to improve the quality service, to improve performance, to improve the organisation competitiveness, to decrease costs and lastly to improve customer satisfaction.

Therefore, the companies that implement lean as their improvement tool are mostly likely to benefit from the above listed benefits.

10.2.2 Conclusion on Research Objective two o To understand how lean can advance company processes

The literature review revealed that Lean provides answers to a number of challenges and threats that companies face in their mission of becoming worldwide competitive. Lean is a key to many companies that want to survive in the global market. This is the reason; most companies are considering implementing lean as a strategic business management preference. Lean is able to provide companies with a competitive advantage; hence, companies should have the concept of lean in place. Industrial businesses have severe issues with their office practices and processes; thus, the Lean concept was introduced. This improvement methodology allows businesses to achieve customer satisfaction, because it focuses on offering utmost value with just small resources necessary.

Findings from the survey questionnaire revealed that the top five improvement areas that can advance the company performance are efficiency, detailed and documented processes, the ability to achieve team targets, recognition of good performance, the ability to highlight poor performance and quality of work.

Therefore, organisations that align their processes with the above areas are more likely to experience process improvements.

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10.2.3 Conclusion on Research Objective three o To understand and measure factors contributing to the implementation of lean

From the literature review, we have discovered that the role of the senior management is critical and vital and can determine the success of the implementation of lean. The commitment of senior management is the foundation to the successful implementation of lean. Therefore, to successfully implement the idea of lean manufacturing, organisations should have strong management personalities. Appropriate senior management has to nurture effective skills to the employees. This approach benefits the organisations that are intending to implement the lean concept by the provision of readiness to learn, resource availability, acquire new ideas for its business competitiveness. The capacity of the company’s finance is a vital factor that determines the success and smooth implementation of lean. This is simple because the finance covers the avenues like training, consultancy, logistics etc. Therefore, lack of funds is a major barrier to the adoption and implementation of successful implementation of lean in any organisation. It is also revealed that it is vital to create a supportive company culture when intending to implement lean manufacturing. The culture of sustainable and proactive improvement is mostly noted in high performing businesses.

The factors that affect the implementation of lean from the survey results are in line with what is stated in the literature review. From the survey, we noted that the following factors were the top five factors according to the survey participants: Involvement of relevant staff, this include workforce and the management. As noted highlighted in the literature that for any successful implementation of an improvement initiative, the relevant parties must be fully committed. The second factor is good communication regarding the mean project, followed by adequate resources, commitment of senior staff and the provision of relevant training. This is in line with the literature, as already mentioned that the financial capability is important in the implementation to ensure that the required training is provided to the relevant parties involved in the project and also to ensure that the adequate resources are well taken care of.

10.2.4 Conclusion on Research Objective four o To understand and measure the barriers to the implementation of lean

The literature review has highlighted that it is vital to create a supportive company culture when intending to implement lean manufacturing. This is because the company culture is important when intending to implement an improvement project, because is includes the important factors like, company mission, ethics, goals and expectations. Therefore, the employees involved in the

157 implementation of lean should have the same focus and the same goals. The culture of sustainable and proactive improvement is mostly noted in high performing businesses.

Furthermore, it is imperative to have excellent communication skills, long-term focus and tactical team in the process of applying the new improvement models. This is because for any successful project, we need a great communicator that will be able to identify and simplify the goals of the project, responsibilities of members involved, performance and expectations from each member. If this role is overlooked, it can negatively affect the outcome of the project.

The survey results revealed the following top five barriers to lean implementation: lack of commitment from senior staff, staff resistance, lack of training, discomfort with change and poor communication. These are the barrier identified by the survey participants and in line with the factors discovered in the literature review.

10.2.1 Conclusion on Research Objective five o Guidelines and recommendation on how to implement and sustain the implementation of lean in the service industry

The main drive of this research was to assess the impact of lean manufacturing in service industry, particularly in the South Africa airline industry. This was answered by assessing the benefits of implementing lean manufacturing as an improvement too in the service industry. By assessing and evaluating factors that can advance company processes, the factors that contribute to the successful implementation of lean and the barriers to the implementation of lean. Consequently, based on the results obtained, the following conclusions were drawn from the research study:

1. It is clear that in today’s competitive world, the survival of the business depends on the satisfaction of the customers. Therefore, any type of an organisation can adopt the concept of Lean. This is because lean is well acknowledged and recognised as an improvement tool with an ability to continuously improve the company’s performance. It was also discovered that lean has the ability to improve quality service, performance, organisation competitiveness and customer satisfaction. This is rather important in the service sectors because they do not offer any tangible items but just service, therefore, any interaction with customers has to mark an outstanding experience. This concept also applies in the airline industry because they are servicing customers and any customer has their own pre-purchase expectations of how the service experience should be, therefore, the passengers will also have a range of expectations in relation to “acceptable” service encounters. Therefore, the airliners should often assess the service quality offered to their passengers in order to

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improve their service, to detect the problems quickly and to better measure customer satisfaction and this exercise should be an on-going company’s activity.

2. Lean can be used as a solution by companies who are faced by challenges in their mission of becoming worldwide competitive. Many companies have already considered the idea of lean because of Lean’s ability to provide organisations with a competitive advantage. Airline industry caters for all types of customers from all corners of the world and this is because many travelers, particularly on extensive distance journeys, use airlines to travel to and from their destination. This means that the airline industry is a sector that affect many lives. Therefore, on-going improvement initiatives are vital in this industry because they provide organisations with the ability to stand out from the competitors.

3. The commitment of top management is the basis to the effective implementation of lean. Therefore, to effectively implement the concept of lean manufacturing, companies should have strong management characters. The capability of the company’s finance is an important element that defines the achievement and smooth implementation of lean. This is because the finance covers the avenues like training, consultancy, logistics etc. Hence, lack of funds is a critical factor to the implementation of effective implementation of any project in any organisation.

4. It is imperative to build a supportive organisation culture when aiming to implement lean manufacturing. Because the organisation culture is vital when aiming to implement an improvement project, because it includes the central factors like, company mission, ethics, goals and expectations. Therefore, the workers involved in the implementation of lean should have the same motivation and the same objectives.

10.3 Recommendations This research has explored the role of lean manufacturing to maximise the customer satisfaction in the South African Arline industry. This is achieved by identifying the benefits of lean, factors that can advance company processes, the factors that contribute to the successful implementation of lean and the barriers to the implementation of lean. Consequently, the following recommendations were proposed to achieve this objective:

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o It is recommended to first create a company culture when intending to start a project. This should be the team with the same focus, same goal, mission, ethics, expectations and same objectives. o It is recommended that for a successful implementation of lean, companies should properly budget for any initiative project and ensure that the budget will be able to cover all the expenses, including transportation, consultancy, availability of adequate resources, training of relent parties, etc. o It is recommended to have a strong and committed top management in order to have a successful implementation of a quality improvement initiative. o Good communication is also recommended because for any successful project, we need a great communicator that will be able to identify and simplify the goals of the project, responsibilities of members involved, performance and expectations from each member. If this role is overlooked, it can negatively affect the outcome of the project.

10.4 Recommendation for a future research

o The future research can be done focusing on a large number of respondents and different geographical areas with the aim of achieving different opinions from different people. o The future study can combine both quantitative and qualitative analysis by adding the structured interview questionnaires.

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APPENDIX 1

Dear Sir/Madam,

I, Linda Malifete am undertaking a research project that aims at analysing the impact of lean implementation in the South African airline industry. I kindly request you to complete the following short questionnaire as comprehensively as possible. The purpose of this survey is to understand your experience with the airline industry and how well they met your needs and expectations. The survey consists of two questions and should take no longer than 10 minutes to complete. Please read each question carefully and tick a relevant box to indicate your answer. The information collected in this project is strictly confidential and the identity of participants will be protected. Hence, DO NOT write your surname and name on this form.

I thank you so much in advance for your time and cooperation in this matter. Should you require more information on the project do not hesitate to contact me telephonically at 081 586 5686 or e- mail me at [email protected]

Yours sincerely

Linda Malifete

174

Please answer the following questions by crossing (X) the relevant block or writing down your answer in the space provided.

EXAMPLE of how to complete this questionnaire:

Please indicate your gender.

If you are female:

Male 1

Female 2

Section A: Background information

This section of the questionnaire refers to background or biographical information. Although we are aware of the sensitivity of the questions in this section, the information will allow us to compare groups of respondents. Once again, we assure you that your response will remain anonymous. Your co-operation is appreciated.

About you

The following set of questions asks you about yourself to help us find out if there are any differences between the views of different groups of people.

1) In which age group are you?

20-25 1 26-35 2 36-45 3 46-55 4 56-65 5 66-75+ 6

175

2) Gender

Male 1 Female 2

Question B

1. How often do you fly?

0 – 1 times after 2 years 1 Once a year 2 Twice a year 3 More than 3 times a year 4

2. Please specify which of the following is the highest educational or professional qualification you have obtained (if still studying, select the highest qualification received so far).

Grade 12 1 Certificate 2 Diploma 3 Bachelor degree 4 Honours degree 5 Masters degree 6 PhD degree 7 Other (please specify) 8

Question C: Service Quality Dimensions (SQD)

1. In your flying experience how often, have you experienced the following at check-ins?

Service Quality Dimensions never rarely sometimes often always

176

Reliability

SQD1 Service as promised (e.g. 1 2 3 4 5 call back) SQD2 Information on change or 1 2 3 4 5 progress of transactions SQD3 Error-free transaction 1 2 3 4 5 SQD4 Queries handled promptly 1 2 3 4 5

Responsiveness SQD5 Willingness to help 1 2 3 5 5 SQD6 Services with speed and 1 2 3 4 5 efficiency SQD7 Availability to answer 1 2 3 4 5 questions Assurance SQD8 Information handled with 1 2 3 4 5 confidentiality SQD9 Knowledge to answer 1 2 3 4 5 questions SQD10 Trustworthiness 1 2 3 4 5

Empathy

SQD11 Experienced attentiveness 1 2 3 4 5 to my booking needs SQD12 They were friendly and 1 2 3 4 5 caring SQD13 I found them to be 1 2 3 4 5 courteous Tangibles SQD14 They had attractive 1 2 3 4 5 facilities (Appearance & cleanliness) SQD15 The staff was neat and 1 2 3 4 5 clean

177

Technical features of services

SQD16 Their service products 1 2 3 4 5 were detailed and

accurate – e.g. ticket information/arrival- departure flight information

SQD17 They offered prompt 1 2 3 4 5 services - e.g. check-in

processing/ refunds/upgrade

SQD18 They offered flexible services/ products – i.e. 1 2 3 4 5 customised to suit the

need .

Thank you very much for taking part in this survey and helping us with our research project

178

APPENDIX 2

Dear Sir/Madam,

I, Linda Malifete am undertaking a research project that aims at analysing the impact of lean implementation in the South African airline industry, with the purpose of understanding thoroughly how Lean improvement enterprises are introduced, implemented and assessed to advance the quality of airline services. I will first give a brief description of the word ‘Lean’.

Lean is a set of ideas and methods that lead companies to continually improve the products they offer by improving the necessary process steps while reducing the ones that do not add value. I therefore, kindly request that you complete the following short questionnaire as comprehensively as possible. The survey consists of 8 questions and should take no longer than 20 minutes to complete. Please read each question carefully and tick a relevant box to indicate your answer. The information collected in this project is strictly confidential and the identity of participants will be protected. Hence, DO NOT write your surname and name on this form.

I thank you so much in advance for your time and cooperation in this matter. Should you require more information on the project do not hesitate to contact me telephonically at 073 057 9257 or e- mail me at [email protected] .

Yours sincerely

Linda Malifete

179

Please answer the following questions by crossing (X) the relevant block or writing down your answer in the space provided.

EXAMPLE of how to complete this questionnaire:

Please indicate your gender.

If you are female:

Male 1

Female 2

Section A: Background information

Your work details

1) Sector/department represented by your organisation

Airline 1 Production / Manufacturing / Operations 2 Human Resources / Training / University 3 Logistics/ Distribution / Procurement 4 Engineering / Technical / Maintenance 5 Marketing / Sales 6 Banking and insurance 7 CEO/General Management 8 Finance / Administration 9 Human health and social work 10 Information Technology 11 Governmental Organisation 12 Other (Please specify) 13

180

2) Please indicate the number of years of practical experience / involvement you have with LEAN

None 1 <2 years 2 2 – 5 years 3 >5 years 4

3. Which of the following best describe your experience with lean – may tick more than one category

As outside consultant 1 As internal facilitator 2 Manager – all levels of management 3 Non-management employee 4

About you

The final set of questions asks you about yourself to help us find out if there are any differences between the views of different groups of people.

ALL THE INFORMATION YOU PROVIDE ABOUT YOURSELF WILL BE KEPT STRICTLY CONFIDENTIAL.

Section B

1) In which age group are you?

20-25 1 26-35 2 36-45 3 46-55 4 56-65 5 66-75+ 6

2) Gender

Male 1 Female 2

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3) Please specify which of the following is the highest educational or professional qualification you have obtained (if still studying, select the highest qualification received so far).

Grade 12 1 Certificate 2 Diploma 3 Bachelor degree 4 Honours degree 5 Masters degree 6 PhD degree 7 Other (please specify) 8

Section C:

Definition of lean: Lean is a set of ideas and methods that lead companies to continually improve the products they offer by improving the necessary process steps while reducing the ones that do not add value.

1. Benefits of lean (B)

Do you agree that these are the benefits of Lean Implementation?

Benefits (B) Strongly Disagree Agree Strongly Don’t disagree Agree know B1 To improve the quality of service 1 2 3 4 5

B2 To improve the organisation 1 2 3 4 5 competitiveness

B3 To decrease costs 1 2 3 4 5

B4 To improve customer 1 2 3 4 5 satisfaction

B5 To improve performance 1 2 3 4 5 (process/working system)

B6 To improve the financial 1 2 3 4 5 performance

B7 To create a culture of quality 1 2 3 4 5

B8 To develop people 1 2 3 4 5

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B9 To engage people 1 2 3 4 5

B10 Other 1 2 3 4 5

Other benefits……………………………………………………………………...

2. Lean improvement areas (IMP)

Rate the extent of improvement in the following areas after the implementation of Lean, if you have implemented Lean

Improvements (IMP) No Small Neutr Moderate Great improve improveme al improvem improveme ment nt ent nt IMP1 Achieving team targets 1 2 3 4 5 IMP2 Highlighting poor 1 2 3 4 5 performance IMP3 Processes efficiency 1 2 3 4 5 IMP4 Team work 1 2 3 4 5 IMP5 Job satisfaction 1 2 3 4 5 IMP6 Collaborative problem 1 2 3 4 5 solving IMP7 Working environment 1 2 3 4 5 IMP8 Quality of work 1 2 3 4 5 IMP9 Productivity 1 2 3 4 5 IMP1 Error rate 1 2 3 4 5 0 IMP1 Recognition of good 1 2 3 4 5 1 performance IMP1 Number of backlogs 1 2 3 4 5 2 IMP1 Time management 1 2 3 4 5 3 IMP1 Visibility of senior staff 1 2 3 4 5 4

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3. Company performance on quality service dimensions (QD)

Rate the extent to which the company performance has improved in the following dimensions (if you have implemented)

No Some Great Don’t Quality Dimensions (QD) extent extent extent know

Reliability QD1 Ability to deliver service to 1 2 3 4 customers QD2 Ability to handle customers 1 2 3 4 properly from the start QD3 Tasks completed on time without 1 2 3 4 any errors Responsiveness QD4 Provision of prompt service to 1 2 3 4 customers QD5 Increased willingness to assist 1 2 3 4 customers Assurance QD6 The ability to instil customer 1 2 3 4 confidence QD7 Increased safe transaction to 1 2 3 4 customers QD8 Increased knowledge to answer 1 2 3 4 customer’s questions

Empathy QD9 Ability to pay attention to 1 2 3 4 individual customers QD10 Ability to understand customer’s 1 2 3 4 specific needs Tangibles

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QD11 Improved visual representation 1 2 3 4

QD12 Neat and properly arranged office 1 2 3 4 equipment Technical features of services

QD13 Accuracy of services 1 2 3 4

QD14 Flexibility of services 1 2 3 4

QD15 Speed of services 1 2 3 4

4. Lean assessment on employee engagement (LA) questionnaire

The purpose of this questionnaire is to collect your views and comments on your experience on the Lean project. Please complete all questions and statements from your own individual perspective.

Please use the scale and choices provided below.

STATEMENT Strongly Disagree Agree Strongly Don’t disagree Agree know LA1 There is a link between 1 2 3 4 5 the company’s Lean approach and its long term strategic direction LA2 The Lean Team provided 1 2 3 4 5 support for implementing the Lean initiative LA3 Communication about the 1 2 3 4 5 Lean business strategy has been good LA4 There was awareness of 1 2 3 4 5 the impact of the Lean business strategy LA5 Lean as an improvement 1 2 3 4 5 methodology is suitable for our organisation

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LA6 The tools and techniques 1 2 3 4 5 covered in the Lean training were new to me LA7 The tools and techniques 1 2 3 4 5 learnt on the Lean training were used to implement the Lean initiative LA8 The implementation was 1 2 3 4 5 more problematic than it was anticipated LA9 Through adoption of Lean 1 2 3 4 5 business strategy senior managers show their commitment for increasing performance LA10 As a result of Lean 1 2 3 4 5 business strategy, employees are focusing on improving the cross functional processes LA11 The Lean business 1 2 3 4 5 strategy has enabled the department to meet customer requirements better LA12 Lean business strategy 1 2 3 4 5 has enabled the department to match resources to workload better

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5. Factors contributing to the success of lean implementation

Do you agree that the main reasons (R) for achieving success in the elements outlined in question 6 above have been………….

Reasons Strongly Disagree Agree Strongly Don’t disagree Agree know

R1 Adequate resources 1 2 3 4 5 committed R2 Provision of relevant 1 2 3 4 5 training R3 Commitment from senior 1 2 3 4 5 management R4 Good communication 1 2 3 4 5 regarding the Lean project R5 Involvement of relevant 1 2 3 4 5 staff

R6 Hands on approach to 1 2 3 4 5 change

6. Barriers of Lean implementation

Do you agree that the following factors (F) affect the implementation of Lean?

Reasons Strongly Disagree Agree Strongly Don’t disagree Agree know F1 Culture of no change 1 2 3 4 5 F2 Lack of commitment 1 2 3 4 5 F3 Staff resistance 1 2 3 4 5 F4 Poor communication 1 2 3 4 5 regarding the project F5 Lack of accountability 1 2 3 4 5

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F6 Lack of training 1 2 3 4 5 F7 Little time allowed for 1 2 3 4 5 implementation F8 Lack of senior 1 2 3 4 5 management commitment F9 Lack of resources 1 2 3 4 5 F10 Discomfort with change 1 2 3 4 5

Thank you very much for taking part in this survey and helping us with our research project.

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