An Ordinal Logistic Regression Model For Analyzing Airport Passenger Satisfaction of ITALY Airport

1. An Ordinal Logistic Regression
Model For Analyzing Airport
Passenger Satisfaction
PRESENTED BY;
Tharindu Dodanwala st120339
Navodi Peiris st120457
Nischaya Sedai st120459
Kyaw Kyaw Paing st120423
Roman Man Shrestha st120294
Sai Saing Hlaing st120567
PRESENTED TO;
Dr. Djoen San Santoso
12-11-2018

2. CONTENT
• Chapter 1: Introduction
• Chapter 2: Literature Review
• Chapter 3: Methodology
• Chapter 4: Results and Discussion
• Chapter 5: Conclusions and Recommendation
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3. CHAPTER 1
INTRODUCTION
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4. Trieste
Forli
Ancona
Brindsiri
Lamezia Terme
International
Airport
Parlermo
Cagliari
Alghero
Cuneo
Milan
Venice
Catania
Pisa
Genova
Rome
Naples
Map: Main International Airport of Italy

5. BACKGROUND
• Economic evolution has led to an increment in passenger
demand.
• An improvement of the transport infrastructures and services
leads to an economic development.
• Therefore, the transportation sector has become very dynamic
in the European countries.
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6. PROBLEM STATEMENT
• Many European countries are made up of many coastal areas
and islands which attracts tourists.
• Especially for the tourism sector transport service efficiency is
fundamental in order to have a notable development.
• Therefore, it is important to analyze the passenger satisfaction
in airports.
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7. OBJECTIVE OF THE STUDY
• To identify the critical service aspects available in Lamezia
Terme International Airport terminal.
• To develop a tool for measuring air passenger satisfaction.
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SCOPE AND LIMITATIONS
• This research is focused on Calabria, Italy.
• The data collection is done in Lamezia Terme International
Airport which is a B class airport.
• The data is collected from passengers in departure terminal.

8. CHAPTER 2
LITERATURE REVIEW
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9. GENERAL
• Since the 1980s, in the European Union countries, air traffic has
increased by 7.4 per cent, and the plane handling quintupled
(Commission of the European Communities, 2001).
• A doubling of air traffic was expected by 2010 (Commission of
the European Communities, 2001).
• Lamezia Terme airport has the most air traffic among Calabrian
airports (ENAC, 2006).
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10. CUSTOMER SATISFACTION
• Service quality is the whole of the service/product aspects and
characteristics on which complete satisfaction customer needs
depends ( Tanese et al.,2003)
• There is a strong relationship between service quality and
customer satisfaction (Hill et al., 2003).
• Customer satisfaction is a measure of company performances
according to customer needs (Hill et al., 2003).
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11. CUSTOMER SATISFACTION (CONTINUED)
• Two basic concepts of the customers satisfaction surveys are:
– The expectations, represents what customers expect from the service
– The perceptions, represents what customers receive
• Expectations are evaluated by the customers through the
indication of a level of importance.
• perceptions are evaluated by a judgement of satisfaction.
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12. CHAPTER 3
METHODOLOGY
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13. RESEARCH FRAMEWORK
Literature
Review
Developing a
Questionnaire
Pilot Survey
Making
Adjustment in the
Questionnaire
Distributing the
Questionnaire at
Departure
Terminal
Analyzing the
data
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14. HYPOTHESIS DEVELOPMENT
• H0: There is no relationship between service quality aspects and
passenger satisfaction.
• H1: There is a relationship between service quality aspects and
passenger satisfaction.
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15. QUESTIONNAIRE DEVELOPMENT
• The objectives are defined, some preliminary data and information
are collected in order to define the survey issues.
• Focus group was used in order to brainstorm the airport
passenger terminal service quality aspects (below).
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• Competence of personnel • Toilets inside the terminal
• Helpfulness of personnel • Video information inside the terminal
• Airport appearance • Air-conditioning inside the terminal
• Road condition inside the airport • Luggage trolley availability inside the airport
• Airport signposting • Availability and frequency of bus links
• Security against thefts • Public telephone availability inside the terminal
• Cleanliness inside the terminal • Car rental

16. QUESTIONNAIRE DEVELOPMENT (CONTINUED)
• A questionnaire was developed using the information gathered from the
focus group discussions.
• Ordinal scale :
• Questionnaire:
Section 1: Demographic Information
Section 2: Quality of Services Available in Passenger Terminal
Section 3: Passenger Satisfaction
• Pilot survey was conducted to check whether the questionnaire is
understandable and the time required to fill it up
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1 - Very Poor 2 - Poor
3 - Insufficient 4 - Sufficient
5 - Good 6 - Very Good

17. DATA COLLECTION
• Population during the data collection: 36,000
passengers at departure terminal
• Sample Size: 1,800 passengers at departure
terminal
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18. DATA ANALYSIS PROCEDURE
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Data Analysis Procedure
Descriptive Statistics
Ordinal Logistic
Regression

19. DESCRIPTIVE ANALYSIS PROCEDURE
• Get the frequency analysis of demographic information.
• Get the frequency of occurrence of each variable with the six
point scaler (Absolute distribution).
• Divide the value by total sample size (Relative distribution)
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Varia
ble
Very poor Poor Insufficient Sufficient Good Very good Total
Abs. Rel. Abs. Rel. Abs. Rel. Abs. Rel. Abs. Rel. Abs. Rel.
V1 10 0.10 10 0.10 15 0.15 15 0.15 30 0.30 20 0.20 100
Table 1: Sample of descriptive analysis
Note: Abs.= Absolute , Rel.= Relative

20. ORDINAL LOGISTIC REGRESSION
• A statistical technique that is used to predict behavior of ordinal
dependent variable with a set of independent variables.
• Independent variable may be categorical or continuous.
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21. ORDINAL LOGISTIC REGRESSION (CONTINUED)
• Direct quantification: changing ordinal scale into numerical
values.
• Measuring the strength of the association.
• Nagelkerke test of R2 is used (0~1).
• Represents the percentage of variance in DV that can be explained.
• The development of two models
• Extended model: All the coefficients exists.
• Reduced model: Not significant coefficients are removed.
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22. CHAPTER 4
RESULTS AND DISCUSSION
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23. Description Category Percentage (%)
Gender
Male 65
Female 35
Age
≤ 25 Years 6
26-45 Years 71
≥ 45 Years 23
Travelling
purpose
Work 55
Travelling 25
Other 20
Occupation
Businessman/ Freelancer 59
Student 14
Managers/ Officers 10
Other 17
DESCRIPTIVE ANALYSIS
Table 2: Demographic information

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DESCRIPTIVE ANALYSIS (CONTINUED)
Table 3: descriptive analysis of independent variables

25. ORDINAL LOGISTIC MODEL ANALYSIS
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Table 4: Extended and reduced model

26. ORDINAL LOGISTIC MODEL ANALYSIS (CONTINUED)
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Table 4: Extended and reduced model

27. ORDINAL LOGISTIC MODEL ANALYSIS (CONTINUED)
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Table 4: Extended and reduced model

28. DISCUSSION
• Nagelkerke test of R2
• Extended model R2 = 0.958
• Reduced model R2 = 0.948
• The compared models showed an insignificant impact of some
services aspects on the passenger overall satisfaction,
• The are airport appearance, airport signposting, toilets inside the
terminal, and availability and frequency of bus links.
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29. CHAPTER 5
CONCLUSIONS AND RECCOMMENDATION
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30. CONCLUSIONS
• The proposed model can be considered as a consumer-based
method, because it requires input data collected by an
experimental survey through a simple questionnaire.
• According to the various level of satisfaction, different customer
profiles can be determined.
• By using the coefficients of each model, the company managing
the airport services can identify the actions for improving
passenger satisfaction and then service quality.
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31. RECCOMMENDATION
• Examination of the links between measures of the performance
of the company managing the airport services and results of the
model concerning satisfaction for the air passengers.
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32. THANK YOU!
ANY QUESTIONS?
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