Airline choice for domestic flights in vietnam, application of multinomial logit model

ERASMUS UNVERSITY ROTTERDAM UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE NETHERLANDS VIETNAM 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 UNIVERSITY OF ECONOMICS HO CHI MINH CITY HO CHI MINH CITY, December 2016 INSTITUTE OF SOCIAL STUDIES THE HAGUE VIETNAM 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 ACKNOWLEDGEMENT First 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 ABBREVIATIONS RUM Random Utility Model SP Stataed Preference RP Revealed Preference VNA Vietnam Airline VJ Vietjet Air BL Jetstar Pacific LCC Low cost carrier II ABSTRACT In 2015, Vietnam witnessed the booming of airline industry The participation of low cost carriers makes the airline market more and more competitive Understanding the behavior of passengers is essential for any carriers to make their strategic policies This study employs the multinomial logit model with the data of 122 respondents to investigate the 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 income whereas the attributes of airlines consist of price, number of flights of airlines, punctuality, comfort of seat space, and quality of check in service th rd A stated preference survey is conducted online from 16 to 23 of October 2016 to collect the data of 122 respondents, who used to travel by air at least one time before They are required to finish 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 three airlines, including Vietnam Airline, Vietjet, and Jetstar The final part is hypothetical scenarios of fifteen 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 that characteristics of airlines have relationships with the ratios of probability of chosing Vietnam Airline or Vietjet over probability of chosing Jetstar, except for the satisfaction of customers about 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, a good judgment of service of an airline makes the odds ratios of that airline and the base increased In contrast, a good evaluation of the based carrier or of the other airline makes the odds ratios declined Besides that, income has positive association with probability of choice Vietnam Airline and Vietjet but negative relation with Jetstar, holding other variables constantly III TABLE OF CONTENTS Contents ACKNOWLEDGEMENT I ABSTRACT B TABLE OF CONTENTS: IV LIST OF TABLES VI LIST OF FIGURES .VII INTRODUCTION 1.1 Problem statement a Overview of airline industry b Airline industry in Vietnam 1.2 Research objectives 1.3 Research questions 1.4 Scope of the thesis 1.5 Structure of thesis LITERATURE REVIEW .5 2.1 Theoretical review a Random Utility Model (RUM) b Reveal Preference & Stated Preference survey .7 2.2 Empirical review 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 c Effect of different routes 38 CONCLUSION 41 REFERENCES i APPENDIX v V LIST 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 LIST 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 CHAPTER INTRODUCTION 1.1 Problem statement 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, the aviation 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 million passengers, approximately 28% of those who are scheduled passengers (IATA report, 2016) According to The International Air Transport Association (IATA), number of air travelers is forecasted to increase nearly double, from 3.8 billion in 2016 to 7.2 billion in 2035 IATA also announces the five fastest growing markets that have the most additional passengers per year for over the next 20 years, including China, US, India, Indonesia, and Vietnam In detail, Vietnam may have 112 million new passengers for a total of 150 million Moreover, IATA also stated that Vietnam is one of the seven countries which have fastest growth in aviation industry Besides that, Vietnam Government pays much attention to infrastructure which is one of the most critical components 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 Civil Aviation 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 of cargo In particular, transportation of domestic carriers is 31.1 million passengers, increased by 21% This positive sign with the falling of crude oil price of 30% in 2015 are stimulus for airline carriers to continue reducing fares in order to meet the demand of transportation of passengers (28) (29) (30) (31) (32) [1]seavn_ufr = [2]seavn_ufr = [3]o.seavn_ufr = [1]seavj_ufr = [2]seavj_ufr = xxxi (33) [3]o.seavj_ufr = (34) [1]seabl_ufr = (35) [2]seabl_ufr = (36) [3]o.seabl_ufr = (37) [1]chevn_ufr = (38) [2]chevn_ufr = (39) [3]o.chevn_ufr = (40) [1]chevj_ufr = (41) [2]chevj_ufr = (42) [3]o.chevj_ufr = (43) [1]chebl_ufr = (44) [2]chebl_ufr = (45) [3]o.chebl_ufr = Constraint dropped Constraint dropped Constraint dropped Constraint 12 dropped Constraint 15 dropped Constraint 18 dropped Constraint 21 dropped Constraint 24 dropped Constraint 27 dropped Constraint 30 dropped Constraint 33 dropped Constraint 36 dropped Constraint 39 dropped Constraint 42 dropped Constraint 45 dropped Regression results of model mlogit choice pricevn pricevj pricebl freqvn freqvj freqbl age male single schoolyear income job_emp ontvn_pun ontvj_pun on > tbl_pun seavn_ufr seavj_ufr seabl_ufr chevn_ufr chevj_ufr chebl_ufr ,base(3) Iteration Iteration Iteration Iteration Iteration Iteration Iteration Iteration Iteration Iteration 0: 1: 2: 3: 4: 5: 6: 7: 8: 9: Multinomial logistic regression Log likelihood = -418.6353 + | xxxii - + - + | | (base outcome) - mfx, predict(p outcome(1)) Marginal efects after mlogit y = Pr(choice==1) (predict, p outcome(1)) = 22090092 -variable | -+ pricevn | pricevj | pricebl | freqvn | freqvj | freqbl | age | male*| single*| school~r | income | on~n_pun*| se~j_ufr*| seab~ufr*| ch~n_ufr*| cheb~ufr*| -( dy/dx is for discrete change of dummy variable from to mfx, predict(p outcome(2)) xxxiii Marginal efects after mlogit y = Pr(choice==2) (predict, p outcome(2)) = 51621706 -variable | -+ pricevn | pricevj | pricebl | freqvn | freqvj | freqbl | age | male*| single*| school~r | income | job_emp*| on~n_pun*| -.2117619 on~j_pun*| on~l_pun*| -.1055995 se~n_ufr*| -.5444404 se~j_ufr*| -.3359625 seab~ufr*| ch~n_ufr*| ch~j_ufr*| cheb~ufr*| -( dy/dx is for discrete change of dummy variable from to mfx, predict(p outcome(3)) Marginal efects after mlogit y = Pr(choice==3) (predict, p outcome(3)) = 26288202 -variable | pricevn | pricevj | pricebl | freqvn | freqvj | freqbl | age | male*| single*| school~r | income | job_emp*| on~n_pun*| on~l_pun*| se~n_ufr*| se~j_ufr*| seab~ufr*| ch~n_ufr*| ch~j_ufr*| cheb~ufr*| -(*) dy/dx is for discrete change of dummy variable from to test pricevn pricevj pricebl freqvn freqvj freqbl age male single schoolyear income job_emp ontvn_pun ontvj_pun ontbl_pun s > eavn_ufr seavj_ufr seabl_ufr chevn_ufr chevj_ufr chebl_ufr ( 1) [1]pricevn = ( ( ( ( ( 2) 3) 4) 5) 6) [2]pricevn = [3]o.pricevn = [1]pricevj = [2]pricevj = [3]o.pricevj = xxxiv ( 7) ( 8) ( 9) [1]pricebl = [2]pricebl = [3]o.pricebl = (10) [1]freqvn = (11) [2]freqvn = (12) [3]o.freqvn = (13) [1]freqvj = (14) [2]freqvj = (15) [3]o.freqvj = (16) [1]freqbl = (17) [2]freqbl = (18) [3]o.freqbl = (19) [1]age = (20) [2]age = (21) [3]o.age = (22) [1]male = (23) [2]male = (24) [3]o.male = (25) [1]single = (26) [2]single = (27) [3]o.single = (28) [1]schoolyear = (29) [2]schoolyear = (30) [3]o.schoolyear = (31) [1]income = (32) [2]income = (33) [3]o.income = (34) [1]job_emp = (35) [2]job_emp = (36) [3]o.job_emp = (37) [1]ontvn_pun = (38) [2]ontvn_pun = (39) [3]o.ontvn_pun = (40) [1]ontvj_pun = (41) [2]ontvj_pun = (42) [3]o.ontvj_pun = (43) [1]ontbl_pun = (44) [2]ontbl_pun = (45) [3]o.ontbl_pun = (46) [1]seavn_ufr = (47) [2]seavn_ufr = (48) [3]o.seavn_ufr = (49) [1]seavj_ufr = (50) [2]seavj_ufr = (51) [3]o.seavj_ufr = (52) [1]seabl_ufr = (53) [2]seabl_ufr = (54) [3]o.seabl_ufr = (55) [1]chevn_ufr = (56) [2]chevn_ufr = (57) [3]o.chevn_ufr = (58) [1]chevj_ufr = (59) [2]chevj_ufr = (60) [3]o.chevj_ufr = (61) [1]chebl_ufr = (62) [2]chebl_ufr = (63) [3]o.chebl_ufr = Constraint dropped Constraint dropped Constraint dropped Constraint 12 dropped Constraint 15 dropped Constraint 18 dropped Constraint 21 dropped Constraint 24 dropped Constraint 27 dropped Constraint Constraint Constraint Constraint Constraint Constraint 30 33 36 39 42 45 dropped dropped dropped dropped dropped dropped xxxv Constraint Constraint Constraint Constraint Constraint Constraint 48 51 54 57 60 63 chi2( 42) Prob > chi2 Regression results of model mlogit choice age male single schoolyear income job_emp ontvn_pun ontvj_pun ontbl_pun seavn_ufr seavj_ufr seabl_ufr chevn_u > fr chevj_ufr chebl_ufr i.route ,base(3) Iteration Iteration Iteration Iteration Iteration Iteration Iteration Iteration Iteration Iteration 0: 1: 2: 3: 4: 5: 6: 7: 8: 9: Iteration 10: log log log log log log log log log log log likelihood likelihood likelihood likelihood likelihood likelihood likelihood likelihood likelihood likelihood likelihood = = = = = = = = = = = -622.1505 -449.69888 -433.82939 -432.25687 -431.94668 -431.86977 -431.85425 -431.85091 -431.85015 -431.84996 -431.84992 Multinomial logistic regression Log likelihood = -431.84992 -1 route 10 11 12 13 14 15 xxxvi + | | route| | | | | | | | | 10 | 11 | 12 | 13 | 14 | 15 | | + | test age male single schoolyear income job_emp ontvn_pun ontvj_pun ontbl_pun seavn_ufr seavj_ufr seabl_ufr chevn_ufr chevj_ > ufr chebl_ufr ( ( ( ( ( ( ( ( ( 1) 2) 3) 4) 5) 6) 7) 8) 9) [1]age = [2]age = [3]o.age = [1]male = [2]male = [3]o.male = [1]single = [2]single = [3]o.single = (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) [1]schoolyear = [2]schoolyear = [3]o.schoolyear = [1]income = [2]income = [3]o.income = [1]job_emp = [2]job_emp = [3]o.job_emp = [1]ontvn_pun = [2]ontvn_pun = [3]o.ontvn_pun = [1]ontvj_pun = [2]ontvj_pun = [3]o.ontvj_pun = (25) (26) (27) (28) (29) [1]ontbl_pun = [2]ontbl_pun = [3]o.ontbl_pun = [1]seavn_ufr = [2]seavn_ufr = xxxvii (30) [3]o.seavn_ufr = (31) [1]seavj_ufr = (32) [2]seavj_ufr = (33) [3]o.seavj_ufr = (34) [1]seabl_ufr = (35) [2]seabl_ufr = (36) [3]o.seabl_ufr = (37) [1]chevn_ufr = (38) [2]chevn_ufr = (39) [3]o.chevn_ufr = (40) [1]chevj_ufr = (41) [2]chevj_ufr = (42) [3]o.chevj_ufr = (43) [1]chebl_ufr = (44) [2]chebl_ufr = (45) [3]o.chebl_ufr = Constraint dropped Constraint dropped Constraint dropped Constraint 12 dropped Constraint 15 dropped Constraint 18 dropped Constraint 21 dropped Constraint 24 dropped Constraint 27 dropped Constraint 30 dropped Constraint 33 dropped Constraint 36 dropped Constraint 39 dropped Constraint 42 dropped Constraint 45 dropped xxxviii ... 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... difference of assumptions of the distribution of the error terms causes many forms of choice models According to Train (2009), the main models include logit, GEV, probit and mixed logit model First, logit. .. satisfaction 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 of price