UNIVERSITY OF ECONOMICS ERASMUS UNVERSITY ROTTERDAMVIETNAM –THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS AIRLINE CHOICE FOR DOMESTIC FLIGHTS IN VIETNAM: APPLICATION OF MULT
Trang 1UNIVERSITY OF ECONOMICS ERASMUS UNVERSITY ROTTERDAM
VIETNAM –THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS
AIRLINE CHOICE FOR DOMESTIC FLIGHTS IN VIETNAM: APPLICATION OF MULTINOMIAL LOGIT MODEL
BY
TRAN PHUOC THO
MASTER OF ARTS IN DEVELOPMENT ECONOMICS
HO CHI MINH CITY, December 2016
Trang 2VIETNAM THE NETHERLANDS
VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS
AIRLINE CHOICE FOR DOMESTIC FLIGHTS IN VIETNAM: APPLICATION OF MULTINOMIAL LOGIT MODEL
A thesis submitted in partial fulfilment of the requirements for the degree of
MASTER OF ARTS IN DEVELOPMENT ECONOMICS
By
TRAN PHUOC THO
Academic Supervisor:
TRUONG DANG THUY
HO CHI MINH CITY, December 2016
Trang 3First of all, I would like to express my gratitude supervisor Dr Truong Dang Thuy of the Vietnam – The Netherlands Programme (VNP) at Ho Chi Minh City University of Economics for his patience, enthusiasm, and immense knowledge He not only guided me to the right direction but also continuously supported in overcoming a lot of obstabcles in my research.
Second, I would like to thank all of the respondents for spending their time to answer the questions in my survey They contribute significantly in collecting data for my study Without their participation, I am sure that the survey could not be conducted successfully.
Finally, my sincere thanks also go to my family and my friends for encouraging me throughout two years
of study as wel as throughout the process of researching and writing this thesis.
Thank you.
Tran Phuoc Tho
December, 2016
I
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Trang 5In 2015, Vietnam witnessed the booming of airline industry The participation of low costcarriers makes the airline market more and more competitive Understanding the behavior ofpassengers is essential for any carriers to make their strategic policies
This study employs the multinomial logit model with the data of 122 respondents to investigatethe impacts of characteristics of passengers as well as attributes of airlines on the airline choice.The characteristics of passengers include age, gender, marital status, education, and incomewhereas the attributes of airlines consist of price, number of flights of airlines, punctuality,comfort of seat space, and quality of check in service
A stated preference survey is conducted online from 16th to 23rd of October 2016 to collect thedata of 122 respondents, who used to travel by air at least one time before They are required tofinish three tasks The first task is providing their information, such as age, gender, marital status,education, and income The second one is evaluating about the quality of services of the threeairlines, including Vietnam Airline, Vietjet, and Jetstar The final part is hypothetical scenarios offifteen domestic routes given along with the prices of airlines for the respondents to choose one
of the three airlines
Jetstar is chosen as the base outcome, the results of multinomial logit model suggest thatcharacteristics of airlines have relationships with the ratios of probability of chosing VietnamAirline or Vietjet over probability of chosing Jetstar, except for the satisfaction of customersabout staff at the check in counter When comparing one airline and the based airline (Jetstar),the attributes of the third airline is also necessary to be taken into consideration In general, agood judgment of service of an airline makes the odds ratios of that airline and the baseincreased In contrast, a good evaluation of the based carrier or of the other airline makes theodds ratios declined Besides that, income has positive association with probability of choiceVietnam Airline and Vietjet but negative relation with Jetstar, holding other variables constantly
III
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Contents
ACKNOWLEDGEMENT I
ABSTRACT B
TABLE OF CONTENTS: IV
LIST OF TABLES VI
LIST OF FIGURES VII
INTRODUCTION 1
1.1 Problem statement 1
a Overview of airline industry 1
b Airline industry in Vietnam 1
1.2 Research objectives 3
1.3 Research questions 4
1.4 Scope of the thesis 4
1.5 Structure of thesis 4
LITERATURE REVIEW 5
2.1 Theoretical review 5
a Random Utility Model (RUM) 5
b Reveal Preference & Stated Preference survey 7
2.2 Empirical review 8
RESEARCH METHODOLOGY 13
3.1 Stated preference method 13
3.2 Questionnaire and survey process 14
3.3 Attributes of airlines 16
3.4 Model specification 18
DATA & EMPIRICAL RESULTS 23
4.1 Data 23
4.2 Empirical results 31
a Controlling variables 35
b Attributes of airline 37
IV
Trang 7c Effect of different routes 38
CONCLUSION 41
REFERENCES i
APPENDIX v
V
Trang 8LIST OF TABLES
Table 3.1 Summary of hypothetical scenarios in survey: 15
Table 3.2 Attributes of airline: 17
Table 3.3 Prices and numbers of flights by routes of carriers 20
Table 3.4 Description of variables: 21
Table 4.1 Social demographic characteristics 27
Table 4.2 Estimation results of multinomial logit model 32
VI
Trang 9LIST OF FIGURES
Figure 3.1 The screen of the online survey 16
Figure 4.1 Airline Choice for Destinations 24
Figure 4.2 Frequency Of Income 25
Figure 4.3 Willingness to pay for routes 26
Figure 4.4 Check-In Service Evaluation 28
Figure 4.5 Cabin Crew Service Evaluation 28
Figure 4.6 Food & Drink Onboard Evaluation 29
Figure 4.7 Inflight Seat Space Evaluation 29
Figure 4.8 On-time Performance Evaluation 30
Figure 4.9 Schedules Delay Evaluation 30
Figure 4.10 Predicted probability of airline choice and income 35
Figure 4.11 Predicted probability of airline choice and age 36
VII
Trang 10CHAPTER 1
INTRODUCTION
a Overview of airline industry
In 2015, the world’s aviation industry achieved the highest net profit in history, 33 billion dollars
It is nearly double when compared to a net profit of 17.4 billion dollars in 2014 Particularly, theaviation industry in Asia Pacific obtained net profit of more than 5.8 billion dollars In addition,region of Asia Pacific accounted for 31% of global passengers, while Europe and North America
is 30% and 26%, respectively It is noted that low cost carrier has transported over 950 millionpassengers, approximately 28% of those who are scheduled passengers (IATA report, 2016).According to The International Air Transport Association (IATA), number of air travelers isforecasted to increase nearly double, from 3.8 billion in 2016 to 7.2 billion in 2035 IATA alsoannounces the five fastest growing markets that have the most additional passengers per year forover the next 20 years, including China, US, India, Indonesia, and Vietnam In detail, Vietnammay have 112 million new passengers for a total of 150 million Moreover, IATA also stated thatVietnam is one of the seven countries which have fastest growth in aviation industry Besidesthat, Vietnam Government pays much attention to infrastructure which is one of the most criticalcomponents of air transport sector Vietnam’s planning is to have 26 airports by 2020;particularly Long Thanh International Airport will be ready by 2020
b Airline industry in Vietnam
The Vietnam airline industry, which was administered by Ministry of Transport and CivilAviation Authority of Vietnam, has witnessed rapid growth in 2015 compared to the figures in
2014 The whole market served 40.1 million of passengers and transported 771 thousand tons ofcargo In particular, transportation of domestic carriers is 31.1 million passengers, increased by21% This positive sign with the falling of crude oil price of 30% in 2015 are stimulus for airlinecarriers to continue reducing fares in order to meet the demand of transportation of passengers
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Trang 11It could be said that airline industry in Vietnam has a potential market due to many reasons First,population of Vietnam is more than 90 million Thus, demand of traveling is very high.Moreover, in the recent years, income of Vietnamese is increasing so that the demand of transit
of people is also higher day by day People have many options to choose means of transports notonly faster but also safer Although there are some disasters of airline in 2014 in the world, itseems that traveling by air is the safest way According to IATA Safety Report, there were 12fatal accidents in the total of 73 accidents, which caused to 641 fatalities on over the world in
2014 This is not a high proportion when comparing to about 33 billion passengers in 2014(IATA Annual Review 2015) Moreover, air travel helps people save much time For examples, ittakes about two days to transit by train from Ho Chi Minh City to Ha Noi while only two hours
by air Finally, thanks to internet, e-commerce is more and more popular People can stay athome, and buy tickets with the cheap price at the time of promotion of carriers
In 1956, the Government established the Vietnam Civil Aviation Department At that time, therewere only five aircrafts to serve some domestic flights In 1993, Vietnam Airlines was set up as anational carrier Until 1995, by gathering 20 aviation enterprises, Vietnam Airlines Corporationwas born and the airline itself is the core business Now, Vietnam Airlines is operating anextensive network of domestic and international services to Southeast and North Asia, Europeand Australia In July 2016, ANA Holding Inc became a strategic shareholder after purchasing of
an 8.77% stake Vietnam Airlines claimed that, under the restructure plan, it will keep on todivest the shareholding of state to 75% Skytrax, organization of the leading airline and airportrating of the world, certified that Vietnam Airlines is a 4-star airline
Vietjet Air, an international low cost carrier, was the first privately owned airline in Vietnam.Although Vietjet Air was approved to operate in November 2007, it launched the first flight inDecember 2011, with only 3 aircrafts Up to 2015, Vietjet had 29 aircrafts with 28 domesticroutes and 12 international routes As planning of Vietjet in 2016, it will have 42 aircrafts to meetthe demand of travel and open more 3 domestic and 5 international fleets
Another airline is Jetstar Pacific Airlines JSC This airline was founded in 1990 as PacificAirlines and commenced operations in 1991 with charter cargo services under control of VietnamAirlines Corporation In 2005, it began to operate in passenger service In 2007, Qantas AirwayLimited bought a portion of Pacific Airlines’ shares and changed it as model of low cost
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Trang 12carrier It officially became a part of Jetstar network in 2008, named Jetstar Pacific In 2012,Vietnam Airlines purchased a 70% stake, so up to now Qantas is having only 30% stake in thecompany.
Vietnam Air Services Company (VASCO) is one of a subsidiary of Vietnam AirlinesCorporation From 2004 to now, VASCO has transported passengers from Tan Son Nhat Airport
to Southern airport such as Ca Mau, Con Dao, Rach Gia, Can Tho and many other routes.Besides of service flight, VASCO also plays a role as a multi functioning airline and providingmaintenance service for private aircrafts
In summary, there are four domestic carriers are operating in Vietnam at present, includingVietnam Airlines, Vietjet, Jetstar, and VASCO In the past, there were another two airlines used
to operate: Indochina Airlines and Air Mekong Due to difficulty in finances, Indochina Airlinesclaimed to stop all of the flights after one year in operation in 2009 Similarly, because of loss inbusiness, Air Mekong had to halt commercial flights in 2013 Until January in 2015, it isofficially revoked by The Ministry of Transport
There are many literatures about the theory of customer behavior and empirical studies aboutairline choice of passengers The annual report of IATA (The International Air TransportAssociation) in 2015 shows the answers of the passengers with the question “What is the firstreason for choosing an airline?” It is found that nonstop flight (15%) and lowest fare (14%) arethe reasons why customers choose an airline while recommended by travel agent and in-flightservice is just accounted for 4% and 3%, respectively However, in Vietnam, airline industry hasjust been booming in the recent years so there are not many researches focus on this topic.Knowing the preference of passengers is necessary for both aviation firms and foreign investors
It helps not only the three carriers have policies that are suitable for Vietnamese people but alsoinvestors in evaluate the airline market to make decision in investing or not
This study uses stated preference survey and employs the multinomial logit model to identify thefactors that have impacts on airline choice of passengers These factors include thecharacteristics of both airline and air travelers This study is expected to provide information on
3
Trang 13factors affecting the choice of passengers, and thus provide information for carriers in identifyingtheir target market segments and efficiently improving their services.
1.3 Research questions
There are two questions are proposed First, what are attributes of airlines that giving impacts ontravelers in deciding which airline to fly? Second, what are demographic factors of air travelersthat have influence on their airline choice?
1.4 Scope of the thesis
Although there are four carriers in Vietnam airline market, this research examines the airlinechoice of three carriers, including Vietnam Airline (VNA), Vietjet (VJ), and Jetstar (BL).VASCO is excluded from the choice set since VASCO just operate in the Southest with shortflight, for example from Sai Gon to Ca Mau, Rach Gia, Con Dao Moreover, the main business
of VASCO is providing maintenance service for aircrafts, not transporting passengers Therefore,the market share of VASCO is very small so the elimination of VASCO is not a severe problem
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Trang 14CHAPTER 2
LITERATURE REVIEW
This chapter first introduces the economic literature of individual choice, which is the foundationfor empirical studies in analyzing choices of economic agents, including air travellers Thechapter then provides a review of empirical studies that analyzed choice of passengers amongcarriers Based on these reviews, a model is set up to analyze the choices of air travelers amongthe three airlines: Vietnam Airlines, Vietjet, and Jetstar
a Random Utility Model (RUM)
Random Utility Model is commonly used to represent individual choice behavior Thurstone(1927) first introduced a law of comparative judgment and originally developed the terms ofpsychological stimuli, which leads to the result of binary probit model now This is a model ofwhether the respondents could get the different level of stimulus The stimuli concept was furtherdeveloped as utility by Marschak (1960) The random utility model implies that the decisionmaker may know the utility of each choice alternative but the researcher may not know it fully.Therefore, it is necessary to take uncertainty into account This leads to the result that the model
of utility consists of two parts, deterministic and random components Deterministic componentscould be observed and interpreted by the analyst while random components are unknown Thereare four main causes of uncertainty that Manski (1977) identified, including measurement errors,the use of proxy variables, unobserved of attributes of the choicer and unobserved attributes ofthe alternatives
Discrete choice models are based on the random utility theory and other assumptions It isassumed that the decision-makers choose among a finite choice set, which are collectivelyexhaustive and mutually exclusive alternatives and they select the alternative that brings thehighest utility With every alternative, the deterministic factors of utility are stated as a function
of attributes, for example a linear function The probability of selecting an alternative of anindividual is the outcome of the choice model Besides that, random components are also the key
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Trang 15factors The difference of assumptions of the distribution of the error terms causes many forms ofchoice models According to Train (2009), the main models include logit, GEV, probit and mixedlogit model.
First, logit model is assumed that the error terms is iid extreme value The term of iid meansindependent, identically distributed (Train, 2009) It is assumed that the unobserved factors arenot correlated and have the same variance with alternatives This assumption, on the one hand, isrestrictive, on the other hand, makes the choice probability have a very convenient form Thisconvenience makes the logit model used popularly; however, in some situations, the assumption
of un-correlation over alternatives could be not appropriated The sequences of choices over timeare also derived under the independence assumption This means that each choice does notdepend on the others Thanks to the convenient form, most of the researchers utilize this model
to examine many aspects of air choice behavior (Escobari & Mellado (2014); Warburg (2005);Yoo & Ashford (1996))
Second, to avoid the assumption of independence in logit model, generalized extreme valuemodels or GEV which imply a generalization of the distribution of extreme value weredeveloped (Train, 2009) The generalization allows the relationship of unobserved factors andalternative It could be seen as a special case of logit model when this correlation does not exist.The less or more flexibility of the correlations depend on the kinds of GEV model For instance,
a comparatively simple GEV classifies the alternatives in many groups, called nests Theunobserved factors are assumed to have the same correlation with alternatives in the same nestbut no correlation with ones in the others nests Hess (2008) employs nested logit model toestablish model of air travel behavior Pels et al (2001) also use nested logit model to describethe passenger concerning in airports and airlines
Third, probit can deal with three limitation of logit model Train (2009) shows the restrictions oflogit model, including not representing random taste variation, IIA property and correlationbetween unobserved components and alternatives However, probit model assumes that errorsterms are normally distributed Therefore, the only limitation of probit model is that, in somecases, unobserved factors may not have normal distribution
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Trang 16Finally, mixed logit permit the unobserved factors to have any distribution In this model,unobserved factors could be divided in two parts One part includes all of the heteroskedasticityand correlation while the other part is iid extreme value It is noted that the first part could obeyany distribution, not excluding non-normal distribution Adler et al (2005) apply mixed logitmodel to develop itinerary choice model The research of Warburg (2005) employs both ofmultinomial logit model and mixed logit to understand the flight choice behavior of passengers.
In reality, there are many other discrete choice models specified for specific purposes byresearchers These models are often established by incorporate the concepts of other models Forexample, a mixed probit could be obtained by breaking down the observed components as inmixed logit, yet, the second part is normal distributed in lieu of extreme value distributed Byacknowledging the motivation and derivation of these models, researchers are able to determinethe model that is suitable for a specific situation to achieve the goals of their studies
b Reveal Preference & Stated Preference survey
There are two main kinds of surveys which are conducted to analyze the behavior of customers,including revealed preference (RP) and stated preference (SP) survey RP data provideinformation about the preferences in a real choice environment This brings the primaryadvantage of RP data, actual behavior of respondent However, it is difficult to do trade-offanalysis with RP data (Bhat & Sardesai, 2004) Moreover, for new alternatives introduced in thenew market, it could not handle the models with RP data (Whitaker et al, 2005) According toYoo and Ashford (1996), there are three practical limitations of RP data First, it is not enoughvariation for some interesting variables to calibrate a statistical model Second, researchers face
to difficulty with estimating model that reflects the trade-off ratios due to the correlations ofexplanatory variables Finally, to calibrate statistical models, it is necessary to carried out verylarge surveys to obtain enough observations Therefore, not many researchers employ thismethod of survey in modeling choice behavior of customers Carrier (2008) use RP data of abooking data so that the study does not include the non-booked travel alternatives, such asincome, purpose of travel,…Escobari and Mellado (2014) collect data from the online travelagency and use posted priced and the changes of inventory to explain the demand of flights
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Trang 17In contrast, in SP survey, the hypothetical scenarios are designed to understand the statedresponses of the interviewers Thus, SP data could reduce the limitation of RP data According toCollins et al (2012), with SP data, it is possible to reproduce the output of behavior, such aswillingness to pay In addition, by conducting SP survey, it is able to explore the choice behavior
of consumers regarding the alternatives that do not exist Nevertheless, SP data has limitationthat the respondents may be uninterested or careless in a survey, or may express their ownopinions about the context of survey rather than give information about a new product usage(Warburg, 2006) Besides that, decision making in hypothetical situation easily leads to the result
of bias because people may not do as what they say In practical, most of the researchers use SPsurvey for modeling choice behavior Adler et al (2005) do SP survey to analysis trade-offs in airitinerary choice while Collins et al (2012) use the interactive stated choice survey to investigatethe behavior of air travelers Wen and Lai (2010) and Proussaloglou and Koppelman (1999) alsouse SP data to examine air carrier choice of passengers
In general, due to the full complement of RP and SP data, there are estimation techniques to bedeveloped to combine these data sources to deal with limitation of each type of data It issuggested that the most effective way is to use both of method RP is useful for forecastingdemand or realistic purposes while SP is useful for system planning purpose (Yoo & Ashford,1996) Similarly, to present model of itinerary choice, Atasoy and Bierlaire (2012) use mixeddataset of RP and SP The mixed data enable the study to succeed in estimating elasticity of price
in demand model
2.2 Empirical review
There are several studies that examine all the different aspects of airline choice behavior Forinstances, the researches of Basar and Bhat (2004), Hess and Polak (2005), and Pathomsiri andHaghani (2005) investigate the airport choice in multi-airport regions Besides that, some papersfocus on not only airport choice but also other aspects of travel Ndoh et al (1990) study airportchoice and route choice of passengers whereas Furiuchi and Koppelman (1994) examine thepassengers’ destination choice and airport choice In addition, there are a few studies payattention to air traveler choice rather than airport choice, such as the research of Chin (2002),Algers and Beser (2001), Proussaloglou and Koppelman (1999), and Yoo and Ashford (1996)
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Trang 18The multinomial logit model of choice is utilized in most of the studies mentioned above Otherstudies, such as Ndoh et al (1990), Furiuchi and Koppelman (1994), and Pels et al (2001) usethe nested logit model to estimate the multidimensional and spatial choices of air travelers.However, the papers that attempt to consider the issues of behavior or effects in air travel choicesemploy the mixed multinomial logit model (Hess & Polak, 2005; Pathomsiri & Haghani, 2005).Moreno (2006) uses the multinomial logit model to address airline choice for domestic flights inSão Paulo There were 1,923 passengers interviewed at the departing lounges of São Paulo-Guarulhos International Airport (GRU) and São Paulo-Congonhas Airport (CGH) It is believedthat airline choice is the result of the tradeoff due passengers have to face with flight cost, flightfrequency, and performance of airline Thus, three types of variables are tested First, variablesassociated with cost are the lowest and highest fare The second type of variables is thoseassociated with flight frequency, including the existence of connections or stops, travel period,and the day of the week Finally, age of airline is used to be proxy of performance of airline Thisstudy finds that the lowest fare is the best explained variable of airline choice Besides that,senior passengers seem to pay more attention to airline age than junior passengers In the sameway, Nason (1981) conducts a stated preference survey to ask respondents to make a choice ofairline among a list of airlines By employing multinomial logit model, the research considersairline choice as a function of attributes of airline service as well as characteristics of passengers.With revealed preference survey, Prossaloglou and Koppelman (1995) examine airline choice ofpassengers who depart from Dallas and Chicago in the US In multinomial logit model,independent variables are schedule convenience, reliability, fares, city pair presence, marketpresence, and frequently flyer program of membership The results show that the attractiveness
of carriers and its market share are positively associated with program of frequently flyer.Similarly, Nako (1992) explores the choice of airlines of business travelers as a function of thefrequently flyer program of airlines It is concluded that frequently flyer programs affectpositively on demand of airline Similarly, Prossaloglou and Koppelman (1999) investigate thepassengers’ choice of airline, flight, and fare class by using logit model The authors considerthat air travelers are rational decision makers, who tend to choose the alternative brings thehighest utility The explanatory variables include fare class, fare price, presence of carriermarket, service quality, frequent flyer participation of travelers, and flight schedules Moreover,
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Trang 19the study use separate models to estimate for different groups, such as business and leisurepassengers These models are based on stated preference data, which is collected by a two-tiersurvey First, initial data involving in the characteristics of passengers, such as previous trip,purpose of trip, address, membership of frequent flyer are collected via mail survey Second, asample of mail survey respondents is chosen randomly to be interviewed by phone Thequestionnaire is designed to simulate the search of individual for air travel options and theirselection among alternatives like during a real process of booking air tickets The results suggestthat behavior of leisure and business travelers are significant different Leisure travelers are moreprice-sensitive but less time-sensitive than business travelers Furthermore, businessmen paymore attention to frequent flyer programs and they are also willing to pay more to fly with theirmost preferred airlines.
In contrast, Pels et al (2001) also use separate models for business and leisure traveler but theresults suggest that the difference between two groups is very small The authors utilize thenested logit model to examine the preferences of passengers in concerning airports and airlines
In this research, the nests defined by airports as well as the nest defined by airlines areconsidered in detail This empirical study use data of the survey in San Francisco Bay Area in
1995 Furthermore, it is implied that an airline has two types of competitors: ones operate in thesame airport and the others operate in other airports because access time to the airport aresignificant for both leisure and business travelers
Besides that, Warburg (2005) says that it is valuable to understand the passengers’ flight choicebehavior and predict air travel demand The study helps the carriers give appropriate pricingpolicy and predict air travel demand in new routes In 2001, Warburg conducted statedpreference survey which consists of 119 business and 521 non-business passengers Therespondents were passengers who reported their most recent domestic flight They had to make
10 binary choices between the actual flight and hypothesis flight, which was 10 itineraryalternatives with the same departure and arrival place Therefore, Warburg (2005) claims thatthere is not existence of universal choice set This could be explained that travelers have differentflight itineraries so there is ability of different choice set for each passenger The study employsboth multinomial logit model and mixed logit model to examine the behavior of two groups ofpassengers: business and non-business travelers Similarly to the results of Prossaloglou and
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Trang 20Koppelman (1999), in multinomial logit model, the business people seem to be more sensitive totime while non-business ones are more sensitive to fare and men are more sensitive to fare thanwomen.
Moreover, the study of Yoo and Ashford (1996) investigates the flight choice behavior ofKorean The respondents were who had long distance international air trips, which took morethan 10 hours air journey time By employing logit model for both RP and SP data, theresearchers also want to do comparative analysis of RP and SP survey Surveys were conducted
at the passenger terminal of Kimpo International Airport in Seoul, in Oct 1993 for RP Survey and
in August 1994 for SP survey Total number of samples was equal in RP and SP data Theresearch gives the result that passengers paid more for Korean airline than foreign airline andKorean residents paid more than foreign residents Likely, Escobari and Mellado (2014) estimatethe demand of international flights by using a unique dataset with information of flight choices,prices, and characteristics of non-booked flights The data collected from the online agency
“expedia.com”, consist of 317 flights from 6 carriers between 19 and 24 Dec, from New York toToronto and vice versa The prices and inventory changes for the flights departed from 19 to 24Dec, 2008 were recorded The study focuses on one way and non-stop flights The findings showthat if the price increases 10% in 100 seat aircraft, the quantity demand decrease by 7.7 seats.For revealed preference survey, Ukpere et al (2012) investigate the determinants of airlinechoice making in the Nigerian domestic air transport With the questionnaire follows Likert scale
of ranking, data are collected to obtain both socio-economic characteristics and attributes ofairline The socio-economic characteristics include sex, age, marital status whereas the airlineattributes consist of comfort, on-board service, fare, frequency, behavior of crew, and power ofmonopoly These determinants could have effects on passengers in choosing airlines at theselected airports By using the nested logit model, the findings show that all of these variablesare significant, that means they effect on making decision of customers The authors alsorecommend that airline should charge competitive fares and make their products distinct fromothers to attract more air travelers In constrast, Adler et al (2005) do stated preference survey onthe internet in 2003 to collect the detail information of about 600 individuals who have just paidfor domestic air trip The aim of this study is to understand the tradeoffs that an individual faces
to when choosing itinerary choices The characteristics of itineraries in the survey include
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Trang 21airline carrier, airport, fare, flight times, on-time performance of carrier, the time differencebetween the expected arrival time and schedule arrival time By employing mixed multinomiallogit model, it is found that the effects of these characteristics of the service are statisticallysignificant However, the limitation of the study of Adler et al (2005) is that it does not examinethe effects of characteristics of demographics and trip on the choice of individuals.
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Trang 22CHAPTER 3
RESEARCH METHODOLOGY
This chapter presents the research methods, including the identification of the airlines attributesthat may affect traveler’s choice, the data collection methods, and the analytical model
According to Whitaker et al (2005), stated preference (SP) method, a technique widely used tounderstand behavior of decision makers, plays an important role in forecasting demand ofdifferent types of airlines services Traditionally, analysis of demand employs revealedpreference (RP) data, which is choices and decision making take place in actual environment.Yet, approaching of RP has some practical limitations First, it is largely associated with costs ofsurvey Moreover, based on RP data, new alternatives, which may be proposed in the market infuture, could not be handled in the models
Wen and Lai (2010) suggest that although approaching of reveal preference collects data in realchoice, it may be inappropriate since passengers often do not consider carefully all of attributes
of all possible airlines However, the stated choice approach could analyze how individual wouldrespond to hypothetical choice situations, which are comprised a set of alternatives and attributeswith their levels Recently, this method has been applied generally in airline choice and otherchoice problems
It is said that in research of travel behavior, there are two types of stated response (Hensher,1994) First, a respondent is asked to identify his or her preferences in alternatives This taskusually aims to find out a scale of metric, which is a rating scale or a rank ordering scale Arating scale is scale designed to obtain information about both of quantitative and qualitativeattributes Likert scale and 1 to 10 rating scale are commonly used in researches However, arank ordering scale has a little bit of difference With a rating task, individuals are able to orderalternatives that listed so it could give the view of their degrees of preferences The study ofWarburg et al (2006), Adler el al (2005) are typical examples of using rank ordering scale in
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Trang 23survey of airline choice Second, a respondent is required to take one of the listed alternatives.This is named as first preference choice task It is important to address types of response strategy
at the beginning of conducting an SP survey since it defines the outputs
The survey of this study applies the first preference choice task In this task, based on the airfares
of airlines for a specific route, each respondent is required to choose one of three airlines:Vietnam Airlines (VNA), Vietjet Air (VJ), and Jetstar (BL) According to Hensher (1994), SPdata has an appealing feature that is ability to view the stated response as the counterpart ofreveal preference It is because in reality, individuals decide to select one option after considering
a set of alternatives carefully Many researchers utilize this method in their studies, such as Wen
& Lai (2010), Hong (2010) In the SP survey of Wen & Lai (2010), air travelers face to a choiceset of three carriers: China Airlines, EVA Airways, and JAA for Tapei – Tokyo route whereasfour airlines: China Airlines, EVA Airway, Cathay Pacific, and Dragon for Tapei
– Hong Kong route Similarly, Hong (2010) conducts an SP survey which the task of respondents
is select one of three airlines: British Airways, Air France, and Easyjet
3.2 Questionnaire and survey process
The questionnaire of this survey that is showed detail in the Appendix consists of three parts Thefirst section is the questions about social demographic information and primary purpose of trip
In the second part, respondents evaluate the quality of services of airlines, including attitude ofstaff at check in counter, attitude of flight attendants, in-flight food and drink, seat space, and on-time performance For carriers that they have never had experience, there is an available choicefor them “I have never used this service before” Finally, fifteen hypothetical situations arepresented Each case is a specific route that departs from Tan Son Nhat Airport to others 15domestic airports, is presented in Table 3.1 The hypothetical scenario is that if an individual hastravel by air, with the airfare as listed, which airline he or she could choose In addition,respondents also reveal their possible purpose of trip and the highest price that they willing topay for a ticket of each route However, if respondents think that they would never go to oneplace in future, they could choose option as “I will never go there” and skip the remainingquestions to move to the new situation
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Trang 24Table 3.1 Summary of hypothetical scenarios in survey:
Note: x: having at least one flight in a day
At the beginning, a pilot-test was conducted at the air ticket agency to identify the determinants
that have influence on decision of customers in purchasing air tickets There were 18 customers,
who had just bought air ticket, were asked to list all of the possible factors affect their choice
These factors consist of fare, schedules, on time performance, quality of staff service, and
comfort of seat onboard After that, this survey was proceeded online from 16th to 23rd of
October 2016 SurveyMonkey, online survey development software is employed to design the
questionnaire Figure 3.1 is the print screen of the online survey The link to access this
questionnaire is sent to air travelers via mail as well as posted public on social media network,
such as Facebook and Zalo The target respondents are those who have traveled by air before and
used to fly with at least one of airlines: VNA, VJ, and BL It is noted that they may not have
experiment with all of three airlines Because of loyalty of customers, some people tend to use
only service of their favorite airline Therefore, it is not easy to find out a person who has
chances to fly with all of three airlines
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Trang 25Figure 3.1 The screen of the online survey
3.3 Attributes of airlines
In service industry, customer satisfaction is one of the most important determinants of customer’sretention Fornell et al (1994) suggest that customer satisfaction brings benefits because it meansthat the company gets back fewer complaint, thus it make the cost of dealing with failure alsodecreased According to Zeithaml and Bitner (1996), satisfaction of customers is made up of anumber of factors, including price, term and condition, quality of products and services, andpersonal characteristics Quality of service is not the only crucial factor of customer loyalty sincecustomers usually have trend to consider trade-off relationship between costs and benefits (Lee
& Cunningham, 1996) Hence, price is also a key factor of consumer satisfaction Furthermore,the research of Athanassopoulos et al (2001) imply that customer behavior responds to customersatisfaction in one of the three ways, including staying with the existing providers, participating
in word-of-mouth communicating, or changing service providers In airline industry, beside ofprice and quality of service, there are many determinants that affect on selection of airlines,including schedule time, frequency of flights, aircraft types, number of seats
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Trang 26of airline Many researchers investigate the effects of airline attributes on carrier choice, which are summarized as in Table 3.2
Table 3.2 Attributes of airline:
Trang 273.4 Model specification
This study follows the framework of Random Utility Model of Manski (1977) since air travelersare assumed to be rational to maximize their utility Passengers tend to select the carrier thatbrings them the highest utility which has the form as below:
Where U: Utility level of passenger
V: Portion of utility (observed utility), and = + : Error terms
(unobserved utility)
X: vector of explanatory variables
i : Passenger i
n = 1, 2, 3 denoted for Vietnam Airline, Vietjet, and Jetstar, respectively
It is reasonable to assume that the actual of choosing airline n is , so:
Therefore, an air traveler i selects airline n when < − + It is clearly that if the distribution of error , the probability could be
estimated The multinomial logit model is based on the assumption that the error terms are identical, independent distributed extreme value
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Trang 28(Gumbel distribution) According to Train (2009), the function of probability could be rewritten
as below:
=
Furthermore, it could be seen that the total of probability of choosing three airline of anindividual is equal to 1 However, according to Gujarati (2011), it is unable to identify the threeprobabilities independently It is common to select one choice as the reference or base choice inmultinomial logit model The coefficients of the base choice are set to be zero If n = 3 is chosen
as the base, and set α3 = 0 and β3 = 0, the probabilities of three airlines could be obtained:
Trang 29In this model, it is noted that X is the vector of variables, including independent variables andcontrolling variables, are investigated whether they have the relationships with carrier choice ornot Independent variables are composed of price, frequency of flights, and routes These factorsare mentioned as hypothesis in the third part of the survey for respondents making decision.Controlling variables which consist of information of respondents and their evaluation of airlineservice are collected through the first and the second section of the questionnaire The list ofvariables used in this study is described in Table 3.4
Notably, the price and frequency of flights are collected online base on the real business ofairline This survey uses the price as the average price of each route of each airline in November
2016 whereas the frequency of flights is the actual number of flights that each carrier has in aday Table 3.3 is the summary of value of independent variables
Table 3.3 Prices and numbers of flights by routes of carriers
Trang 30Table 3.4 Description of variables: Type of variable
Trang 32Type of variableVariables
Trang 3322
Trang 34CHAPTER 4
DATA & EMPIRICAL RESULTS
This chapter presents the summary of data collected form the stated preference survey as well asthe regression results of multinomial logit model
The characteristics of social demography is describes in details as Table 4.1 Actually, thereare135 respondents but 13 of them did not finish the questions so they are eliminated out of thedata Each individual faces to 15 scenarios to select the airline Figure 4.1 shows the choice ofairline in every hypothesis destination in the survey It seems that Ha Noi, Da Nang, and PhuQuoc are destinations that have the highest demand of travel because more than 98 percent ofrespondents think that they will go there in future VNA has the lowest percentage of choosingairline in all of routes Notably, there is no choice of VNA for the route of Sai Gon – Tuy Hoaand Sai Gon – Chu Lai since VNA does not have any flight in reality Therefore, in this survey,scenarios of Tuy Hoa and Chu Lai, VNA is excluded In general, VJ has the highest percentage
of choosing airline in most of scenarios Especially, for the route of Sai Gon to Ha Noi, and DaNang, more than 60 percent of respondents select VJ However, in some cases such as Da Latand Hue, BL is the airline that has the highest percentage of choice
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Trang 35-DADHANPQCCXR DII HUI BMV UIH VII TBB VCL PXU HPHVDH THD
Airline Choice for Destinations - Depart from Sai Gon
BL
VJ
VNA
NO DEMAND
Figure 4.1 Airline Choice for Destinations
(Notes: HAN: Ha Noi, DAD: Da Nang, VII: Vinh, CXR: Nha Trang, DII: Da Lat, HUI: Hue, THD: Thanh Hoa, BMV: Buon Me Thuot, PXU: Pleiku, PQC: Phu Quoc, HPH: Hai Phong, TBB: Phu Yen, UIH: Quy Nhon, VDH: Dong Hoi, VCL: Chu Lai)
There are 122 respondents in the data includes 84 females (68.85%) and 38 males (31.15%)(Table 4.1) Most of them are single, approximately 70% Besides that, this survey is conductedonline so the respondents are young people who have ability to access internet easily Thus, themedium age of them is around 27 while the youngest is 20 and the oldest is 46 It is also notedthat there are two people not reveal their age in this survey In addition, 83 respondents (68%)graduate from university and 32 (26.23%) have a master degree whereas only one personfinished high school Moreover, it could be seen that a number of people in this survey areemployees who are working for companies (83 respondents, about 68%) In contrast, just oneperson is freelancer or self-employee For the purpose of trip, more than 40 percent of them saidthat they usually travel by air for both of leisure and business Furthermore, the level of incomethat seems most of respondents reach in the period of survey is from 8 to 10 million per month(Figure 4.2)
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Trang 362 5 7 9 11 13 15 17 19 22.527.5 35 45 55
Income (Mill VND/month)
Figure 4.2 Frequency Of Income
In the survey, people are asked to evaluate the quality of service of airlines, including check-inservice, attitudes of cabin crew, quality of food and drink onboard (Figure 4.4 to 4.7) Theseservices are rated with three scales: not good, good enough, and very good In addition, to judgethe delay of schedules of flights, the respondents are asked two questions First, their previousflights of three airlines they ever traveled are punctual or not (Figure 4.8) Second, it is whetherthey can accept the on time performance of airlines (Figure 4.9) However, for those who havenever used the services of any airline, there is an option for them: “I have not used the servicebefore”
In general, approximately 36 percent of people in this survey said that they have not flied withJetstar Pacific before, the highest rate among of three airlines This contrasts with VietnamAirlines Besides that, most of people appraise that the quality of service of Vietnam Airlines isgood and very good Specially, very few people judge that check-in and cabin crew service ofVietnam Airlines are unfriendly (just 1.64% and 0.82%, respectively) About punctuality, itseems that almost respondents agree that flights of Vietnam Airlines depart on time (about 60%)and around 74% think that the rate of delayed flights of Vietnam Airlines is acceptable Yet,Vietjet Air has the highest number of unpunctual flights (up to 62%) and more than 30% saysthat it is unacceptable for schedule changes of Vietjet Air
In addition, this survey also inquires the respondents to reveal how much they are willing to payfor an air ticket of each route, for example from Sai Gon to Ha Noi Figure 4.8 presents the mean
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Trang 37of willingness to pay for routes of the respondents It is clearly that people are pleased to paymore for long distance trips (Ho Chi Minh to Ha Noi, Hai Phong) and pay less for short distancetrip (Ho Chi Minh to Nha Trang).
-HAN DAD VII CXR DII HUI THD BMV PXU PQC HPH TBB UIH VDH VCL
Destinations - Departure from Saigon
Figure 4.3 Willingness to pay for routes
(Notes: HAN: Ha Noi, DAD: Da Nang, VII: Vinh, CXR: Nha Trang, DII: Da Lat, HUI: Hue, THD: Thanh Hoa, BMV: Buon Me Thuot, PXU: Pleiku, PQC: Phu Quoc, HPH: Hai Phong, TBB: Phu Yen, UIH: Quy Nhon, VDH: Dong Hoi, VCL: Chu Lai)
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Trang 38Table 4.1 Social demographic characteristics
Trang 3920
10 -
25 20 15 10 5 -
Trang 40VJ 20
BL 10
30
20