Perceived customer value of vietnam airlines online ticketing

TRƯỜNG ĐẠI HỌC MỞ TP HCM HO CHI MINH CITY OPEN UNIVERSITY Tai Lieu Chat Luong UNIVERSITE LIBRE DE BRUXELLES SOLVAY BRUSSELS SCHOOL MBAVB3 NGUYEN THE HOANG PERCEIVED CUSTOMER VALUE OF VIETNAM AIRLINES ONLINE TICKETING MASTER PROJECT MASTER IN BUSINESS ADMINISTRATION (PART-TIME) Tutor’s Name: Dr NGUYEN Duc Tri Ho Chi Minh City (2010) DECLARATION This thesis is a presentation of my original research work Wherever contributions of others are involved, every effort is made to indicate this clearly, with due reference to the literature, and acknowledgement of collaborative research and discussions The work was done under the guidance of Dr NGUYEN DUC TRI, under the framework of the the Master program in Business Management – The join Masters Program between Ho Chi Minh City Open University (Vietnam) and Solvay Brussels School (Belgium) The work was completed in December 2010, in Ho Chi Minh City Vietnam (candidate’s name and signature) NGUYEN THE HOANG In my capacity as supervisor of the candidate’s thesis, I certify that the above statements are true to the best of my knowledge (guide’s name and signature) Dr NGUYEN DUC TRI Date: …… Acknowledgement This thesis could not have been done without the contribution and encouragement from many people… First of all, I would like to express my profound gratitude and great appreciation to my supervisor Dr NGUYEN DUC TRI for his valuable guidance, advices and recommendations throughout the research study I would like to express my great appreciation to the staff of the Passenger Sales & Marketing Department, Southern Regional Office of Vietnam Airlines, who I had chance to work with during my short internship at the early stage of this study Deep appreciation and thanks are reserved to Mr HUNG – Supervisor at the Department – for his fruitful discussions as well as providing me with the necessary information Special thanks also to be sent to Mr KHANH – Head of Human Resource Department of Southern Regional Office – for facilitating all the administrative arrangement for my internship, and Mr SON – Head of the Sales and Marketing Department – for accepting me as a trainee in his Department I would like to express my sincere thanks to my classmates MBAVB3 who have shared with me their impressive knowledge and skills during the challenging courses of the MBA program I specially want to express my loving thanks to all the members in my dear group (4A+4B) who were always besides me whenever the “team work” assignments have been carried out My greatest debt of gratitude is to my wife, Thao, who was sharing with me all the difficulty occurred during this MBA study My MBA study could not be completed without her moral encouragement and support Finally, I would like to thank the members of the Examination Committee for taking time and giving valuable comments to improve this study HCM City, December 2010 NGUYEN THE HOANG ABSTRACT Facing with high costs, Airlines are attempting to shift customers from traditional ticketing channels to their direct channels such as website which is considered as a prominent marketing channel and the most cost effective for Airlines The biggest Airline in Vietnam – Vietnam Airlines – has also followed this strategy by recently launching ticket selling via its website However, the emergence of online booking can lead to significant changes in consumers’ references and behavior Therefore better understanding key factors influencing on “perceived customer value”, which has been found to be a powerful predictor of purchase intention, becomes a crucial issue for e-marketers In such context, this research follows the study of Chen and Dubinsky (2003) A more simplistic model was suggested to indentify key antecedents of perceived customer value in B-to-C online ticketing The model was empirically tested with Vietnam Airlines’ e-clientele This choice has double purposes Firstly, worthy implications deducted from the results expected can help better implement tactics for further development of Vietnam Airlines’ e-commerce Secondly, the investigation can give further empirical support to better ascertain the validation of the original model suggested by Chen and Dubinsky A quantitative research was carried out Structured questionnaire was administered to collect data from Vietnam Airlines’ e-customers by both methods: “online questionnaire” and “personally administered questionnaire” surveys The analysis techniques which include Reliability, Factor and Multiple Regression analyses were used to valid the construct measurement and test the hypotheses suggested Revision of research questions, hypotheses, and research model in the case of investigation was carried out The results obtained by the research shows that “valence of experience” and “perceived product quality” are predictors of “perceived customer value” They are positively and significantly related to the “perceived customer value” Furthermore, it is also shown that the factors, which are related to the website’s performance, including “relevant information”, “ease of use”, and “customer service” are the predictors of customers’ “valence of experience” COMMENTS OF TUTOR …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… …………………………………………………………………… 1 CHAPTER 1: INTRODUCTION 1.1 Research background Facing with high fixed costs, airlines strive to find an efficient and effective distribution strategy of tickets (Toh and Raven, 2003) Distribution through brick-andmortar travel agencies is expensive because it requires airlines to pay not only commissions to travel agencies but also transaction fees for the computerized reservation systems (Bilotkach and Pejcinovska, 2008) Working with online travel agencies (OTAs), such as Expedia and Travelocity, offers airlines a broader consumer base than if they distributed solely through their brand.com websites which can help to save airlines distribution costs Furthermore, previous studies showed that there was a contention of shares amongst the channels of airlines For example, during 2000-2001 in Taiwan, the market share data showed that, traditional tour agents have lost at least half of their customers to the ticketing websites (Shon et al., 2003) These show many challenges for sales channel management that directly affect the profits of airlines Airlines’ websites provide a distribution channel linking the Airlines more closely and directly to their potential customers Distribution through own website is generally regarded as the most cost effective for Airlines (Lubbe, 2007) To consumers, the benefits of the Internet are tremendous As an alternative channel, web shopping is convenient and time saving Consumers can compare prices and products or services’ features across suppliers by using rich and free information available Though, previous works on web-shopping, has raised the e-suppliers’ concerns about the low purchasing rate and moderate satisfaction of online shoppers (Moon and Frei, 2000) Customers now have much more bargaining power, lower switching costs, and high number of choices Thus understanding what leads to online customers’ purchase intentions has become an important research topic (Barsh et al., 2000) “Perceived customer value” has gained much attention from maketers and researchers because of its important role in predicting purchase behaviour (Cronin et al., 2000) From the standpoint of marketing strategy, creating “customer value” means meeting customers’ needs and increasing customer satisfaction (Porter, 1985) Customer value management has been used widely by firms to differentiate themselves from competitors Nguyen The Hoang – MBA VB3 Previous studies have shown that perceived customer value can change with consumption context Thus, buying on the Internet, may lead to a change in perceived customer value relative to other traditional channels Despite of its importance, a few systematic researches could be found to understanding how an online shopping context could affect perceived customer value, especially in typical service industry such as Airlines The study of Chen and Dubinsky (2003), which suggested a preliminary investigation on perceived customer value in e-commerce, got some interesting findings A conceptual model of perceived customer value, involving several influencing factors, was suggested However, as suggested by the authors that further empirical supports need to be done for future works to ascertain whether the model is posited In such a context, investigating appropriate models, to better understand which key factor affecting on perceived customer value, and correctly applying them in dynamic service industries, such as Airlines, in emerging markets, such as the one of Vietnam, will help to bring tremendous benefits for both firms and customers Several implications could be withdrawn to help the firm, such as Vietnam Airlines, to well implement for further development of its online channels, and hence increase its competitiveness over competitors 1.2 Research problem 2.1.1 Brief introduction about Vietnam Airlines Vietnam Airlines is owned by the government of Vietnam The airline is headed and overseen by a management team, members of which are selected by the Prime Minister of Vietnam The airline branches include: Southern, Central and North branches Currently the airline is headquartered in Hanoi Vietnam Airlines has an extensive network throughout East Asia, Southeast Asia, Europe and Oceania With more than 290 daily flights, the airline flies to 20 destinations domestically, and to another 28 internationally Operating the young fleet of 70 modern aircrafts (Airbus and Boeing mainly), the airline expects to further expand its fleet to 115 and 165 aircrafts by 2015 and 2020, respectively1 Vietnam Airlines is currently a member of SkyTeam and codeshares with most SkyTeam members Vietnam Airlines also has codeshares with four current Oneworld http://www.vietnamairlines.com.vn/ Nguyen The Hoang – MBA VB3 members – American Airlines, Cathay Pacific, Japan Airlines, and Qantas – and is part of Cathay Pacific's Asia Miles program Joining SkyTeam marks a favorable step toward Vietnam Airlines’ future growth It will bring passengers convenient and seamless service of international standards to a global network covering more than 850 destinations in 169 countries Vietnam Airlines holds about 40 per cent of the market share of international tourists flying to and from Vietnam This is significant because Vietnam Airlines receives two-thirds of its profits from international passengers In domestic market, Vietnam Airlines and VASCO (its subsidiary) has an 80% share of the aviation market, with the rest covered by Jetstar Pacific and the others (Vietjet Air, Mekong Air – a new carrier) In 2009, the airline's revenue was $US1.3 billion, compared to $US1.56 billion it earned the previous year Vietnam Airlines carried 9.3 million passengers during this period It is reported that Vietnam Airlines’ passenger capacity for 2010 has risen up to 30% over the same period of the previous year (Figure below) Total sales are estimated to obtain a high rate of ~18% per year from 2010 to 2015 Figure Top 30 airlines in Asia (Anna.aero, May 2010) Internal financial source of VNA (unofficial source) Nguyen The Hoang – MBA VB3 The sales resulted from the Southern branch of Vietnam Airlines, located in HoChiMinh City, hold approximately ~50% of the total of the company The remains hold by the North and Central branches The organizational charts of the corporation and of the Sales Department (passenger) are given in the Appendix 12 Vietnam Airlines has developed a multichannel sales network including both offline and online ones (Table below) Offline channels are traditional channels which still hold a large portion of total sales (~ 97% total sales, YTD 20103) The online channels, which include both B-to-C and B-to-B customers, bring only the remains of ~3% The Bto-C e-ticket selling is done via the Airline’s website The later (B-to-B) is performed with a particular web-based site developed for corporation clients, called “web portal” Some internal sources show that the company is now developing an ambitious plan to foster sales via online channels, especially on web-portal4 Table Classification of key sales channels of VietNam Airline ONLINE DIRECT INDIRECT (1) Airline’s website (B-C) (2) Web portal (B-B) *Sales estimated5: ~ 3% (Not yet participation in OTA – Online Travel Agencies such as Expedia.com, Opodo.com, Orbit.com) OFFLINE (3) CTO (City Ticketing Office) (4) ATO (Airport Ticketing Office) *Sales estimated: ~ 13% (5) Tour Agents (6) Independent sales Agents *Sales estimated: ~ 85% 2.1.2 Identification of research opportunity Vietnam achieved around 8% annual GDP growth from 1990 to 1997 and continued at around 7% from 2000 to 2005, making it one of the world's fastest growing economies The country’s GDP growths by 8, 9, and percent for the year of 2007, 2008, 2009 and 2010 respectively despite of the difficult period during the financial crisis6 The penetration of Internet user in Vietnam has been estimated to be 35% Approximately $US 6.3 billion has been estimated to inject into the internet market to meet Numbers are scaled Internal source (unofficial) Numbers are scaled http://www.indexmundi.com/vietnam/gdp_real_growth_rate.html Nguyen The Hoang – MBA VB3 the expectation in 2010 It can be seen (Table below) that for 10 years (2000-2010), the penetration of Internet users has been grown up to 27% Table Internet Usage and Population Statistics (Internet World Stats) Furthermore, some recent reports has identified that Vietnam’s air travel market is one of the most potential markets in Asia with double-digits growth rate (Figure below) Figure Top Asian air travel market (Anna.aero, May 2010) In 2009, Vietnam Airlines has officially launched the e-ticket selling via the website of the company for one year (VOA news, 2009) With such new channel, passengers can make their bookings, and buy e-tickets using credit cards or via ATM services Customers also save time by having easier access to all the information related to their flights, bookings and ticket prices To ensure the highest security for payments, Vietnam Airlines has cooperated with chartered credit card organizations to take measures to limit risks in conducting e-transaction Nguyen The Hoang – MBA VB3 75 Construct “Valence of Experience” Total Variance Explained Initial Eigenvalues Compon ent Total % of Variance Extraction Sums of Squared Loadings Cumulative % 3.366 67.329 67.329 542 10.833 78.162 475 9.503 87.664 333 6.664 94.328 284 5.672 100.000 Total % of Variance 3.366 Cumulative % 67.329 67.329 Extraction Method: Principal Component Analysis Construct “Perceived Risk” Total Variance Explained Initial Eigenvalues Compon ent Total % of Variance Extraction Sums of Squared Loadings Cumulative % 2.371 59.276 59.276 742 18.545 77.820 525 13.129 90.949 362 9.051 100.000 Total % of Variance 2.371 Cumulative % 59.276 59.276 Extraction Method: Principal Component Analysis Construct “Product Price” Total Variance Explained Initial Eigenvalues Compon ent Total % of Variance Extraction Sums of Squared Loadings Cumulative % 1.560 78.013 78.013 440 21.987 100.000 Extraction Method: Principal Component Analysis Nguyen The Hoang – MBA VB3 Total 1.560 % of Variance 78.013 Cumulative % 78.013 76 Construct “Perceived Product Quality” Total Variance Explained Initial Eigenvalues Compon ent Total % of Variance Extraction Sums of Squared Loadings Cumulative % 2.599 64.965 64.965 768 19.192 84.157 454 11.354 95.511 180 4.489 100.000 Total % of Variance 2.599 Cumulative % 64.965 64.965 Extraction Method: Principal Component Analysis Construct “Perceived Customer Value” Total Variance Explained Initial Eigenvalues Compon ent Total % of Variance Extraction Sums of Squared Loadings Cumulative % 2.534 50.688 50.688 954 19.090 69.778 695 13.899 83.677 480 9.599 93.276 336 6.724 100.000 Extraction Method: Principal Component Analysis Nguyen The Hoang – MBA VB3 Total 2.534 % of Variance 50.688 Cumulative % 50.688 77 APPENDIX 8: ASSUMPTION CHECKING FOR MULTIPLE REGRESSION ANALYSES Model (dependent variable: Valence of Experience) Nguyen The Hoang – MBA VB3 Model (dependent variable: Perceived customer value) 78 APPENDIX 9: ANALYSES OF MULTIPLE REGRESSIONS Model (dependent variable: Valence of Experience Descriptive Statistics Mean Model Summaryb Std Deviation N Adjusted R Std Error of the Square Estimate TOTva 2.8822 77291 163 Model TOTse 3.1418 76158 165 TOTre 3.5527 64841 165 a Predictors: (Constant), TOTea, TOTse, TOTre TOTea 3.3828 68183 163 b Dependent Variable: TOTva R 613a ANOVAb Model Sum of Squares df Mean Square Regression 35.918 11.973 Residual 59.665 157 380 Total 95.584 160 a Predictors: (Constant), TOTea, TOTse, TOTre b Dependent Variable: TOTva Nguyen The Hoang – MBA VB3 F 31.505 Sig .000a R Square 376 364 61647 79 Residuals Statisticsa Minimum Maximum Mean Std Deviation N Predicted Value 1.4924 3.9885 2.8886 46588 163 Std Predicted Value -2.933 2.335 014 983 163 050 282 091 033 163 1.5115 3.9985 2.8951 46481 161 -1.64860 2.73741 -.00323 61182 161 Std Residual -2.674 4.440 -.005 992 161 Stud Residual -2.899 4.532 -.008 1.012 161 -2.00930 2.85107 -.00687 63701 161 -2.970 4.845 -.007 1.026 161 Mahal Distance 068 32.420 2.942 3.664 163 Cook's Distance 000 555 011 049 161 Centered Leverage Value 000 203 018 023 163 Standard Error of Predicted Value Adjusted Predicted Value Residual Deleted Residual Stud Deleted Residual a Dependent Variable: TOTva Nguyen The Hoang – MBA VB3 80 “Model 2” - Multiple Regression Descriptive Statistics Mean Model Summaryb Std Deviation N Std Error of the TOTcva 3.2024 62781 165 Model TOTva 2.8822 77291 163 TOTrk 3.3018 88376 164 a Predictors: (Constant), TOTpro, TOTrk, TOTpri, TOTva TOTpri 3.3000 88138 165 b Dependent Variable: TOTcva TOTpro 3.6667 72695 165 ANOVAb Model Sum of Squares df Mean Square Regression 31.860 7.965 Residual 31.596 157 201 Total 63.457 161 a Predictors: (Constant), TOTpro, TOTrk, TOTpri, TOTva b Dependent Variable: TOTcva Nguyen The Hoang – MBA VB3 F 39.578 Sig .000a R R Square 709a 502 Adjusted R Square 489 Estimate 44861 81 Residuals Statisticsa Minimum Maximum Mean Std Deviation N Predicted Value 2.1950 4.4181 3.2044 44661 162 Std Predicted Value -2.265 2.733 005 1.004 162 038 160 075 024 162 2.2165 4.3941 3.2044 44631 162 -1.27038 99991 00791 43198 162 Std Residual -2.832 2.229 018 963 162 Stud Residual -2.887 2.247 018 979 162 -1.32044 1.01639 00798 44647 162 -2.957 2.277 018 985 162 Mahal Distance 140 19.361 4.007 3.496 162 Cook's Distance 000 066 006 011 162 Centered Leverage Value 001 120 025 022 162 Standard Error of Predicted Value Adjusted Predicted Value Residual Deleted Residual Stud Deleted Residual a Dependent Variable: TOTcva Nguyen The Hoang – MBA VB3 82 APPENDIX 10: FIRST PAGE OF VNA’S WEB FOR ONLINE TICKETING Nguyen The Hoang – MBA VB3 83 APPENDIX 11: RESULTS OBTAINED BY CHEN AND DUBINSKY (2003) Multiple Regression Results (Chen and Dubinsky, 2003) Nguyen The Hoang – MBA VB3 84 APPENDIX 12: ORGANIZATIONAL CHARTS OF VIETNAM AIRLINES Fig (a) Organizational structures of VNA Management Board of Vietnam Airlines Advisory Experts Group Supervisory Board Vietnam Airlines General Director General Affairs Units Offices Investment Planning Technical Deputy General Director Finance and Accounting Deputy General Director of Operation Internal Audit Commercial Deputy General Director Human Resources Independent companies VINAPCO Quality Assurance Department Standard and Flight Safety Department Technical Department Flight Monitoring and Operating Department (Noibai and Tansonnhat) Passenger Marketing Department Air design consulting Co Cargo Department Air construction company 919 Flight Division Marketing Service Department Air super plastic company Cabin Crew Division Regional offices (North South Central) Market Planning Department International rep offices Maintenance companies A75, A76 Air catering Noibai Training center Ground service companies (N,S,C) VASCO Airlines import export company Cargo Service company NB Air services company Vietnam Air Caterers VINAKO Nguyen The Hoang – MBA VB3 ABACUS Offices of Unions and Party JVs, joint stock companies Pacific Airlines Tan Son Nhat Cargo Service Co Supporting companies Trade Unions Newly-setup Co Aviation Institute Air Insurance company Air Project Depart Air Finance company Air Tourism Co Air printing company Air auto transportation company NASCO MASCO SASCO Labor supply and import export Co Hotel 27B IT 85 Fig (b) Organizational chart of VNA Sale Department (Southern branch at HCM) SALES DEPARTMENT Management units Agencies • Web Portal Agents • Sabre Agents • Website support Nguyen The Hoang – MBA VB3 Specific Customers • CA • IOM • Students • Labors Management units Price and routes • Pricing • Schedule fight • Implementation Marketing • P.R; Event • Image building • Commerce promotion Refight check • Booking • SC • CXL TABLE OF CONTENTS CHAPTER 1: INTRODUCTION 1.1 Research background 1.2 Research problem 1.2.1 Brief introduction about Vietnam Airlines 1.2.2 Identification of research opportunity 1.3 Research objectives and questions 1.3.1 Research Objectives 1.3.2 Research questions 1.4 Research model 1.5 Research methodology 10 1.6 Delimitations 10 1.7 Structure of the study 10 CHAPTER 2: LITERATURE REVIEW 12 2.1 Business environment in the airline industry 12 2.2 Airline e-commerce and multichannel development 14 2.3 Consumer behavior towards online shopping 16 2.4 Antecedents of Perceived Customer Value 18 2.4.1 Concept of Perceived Customer Value 18 2.4.2 Valence of Experience 19 2.4.3 Relevant Information 20 2.4.4 Ease of use of the website 20 2.4.5 Customer Service 20 2.4.6 Perceived Product Quality 21 2.4.7 Perceived Risk 21 2.4.8 Product Price 22 2.5 Conclusion about theoretical framework for the research 22 CHAPTER 3: RESEARCH METHODOLOGY 24 3.1 Research model 24 3.2 Research process 24 3.3 Questionnaire design 27 3.4 Measures 27 3.5 Sampling design 30 3.6 Survey method 31 3.7 Data analysis techniques 32 Nguyen The Hoang – MBA VB3 CHAPTER 4: DATA ANALYSIS AND FINDINGS 33 4.1 Profile of samples 33 4.2 Reliability analysis 33 4.3 Factor analysis 34 4.4 Regression analysis 36 4.4.1 Checking the assumptions 37 4.4.2 Evaluation of models 39 4.4.3 Evaluation of the independent variables - Assessment of hypotheses 41 4.5 Summary of findings 43 4.5.1 Antecedents of Valence of Experiences 43 4.5.2 Antecedents of Perceived Customer Value 43 4.5.3 Confirmed research models 44 CHAPTER 5: DISCUSSION AND IMPLICATION 45 5.1 Discussion 45 5.2 Rationales for unanticipated findings 49 CHAPTER 6: CONCLUSION 51 6.1 Results and contribution of the research 51 6.2 Limitation and suggestion for future research 52 REFERENCES 55 APPENDIX 1: THE QUESTIONNAIRE FOR MAIN SURVEY 58 APPENDIX 2: WEB INTERFACE OF ONLINE QUESTIONNAIRE 63 APPENDIX 3: CODE BOOK 64 APPENDIX 4: DESCRIPTIVE STATISTICS OF RESPONDENTS 65 APPENDIX 5: RELIABILITY ANALYSIS (SPSS VERSION 16) 67 APPENDIX 6: SUITABILITY ASSESSMENT FOR FACTOR ANALYSIS 72 APPENDIX 7: FACTOR EXTRACTION (FACTOR ANALYSIS) 74 APPENDIX 8: ASSUMPTION CHECKING FOR MULTIPLE REGRESSION ANALYSES 77 APPENDIX 9: ANALYSES OF MULTIPLE REGRESSIONS 78 APPENDIX 10: FIRST PAGE OF VNA’S WEB FOR ONLINE TICKETING 82 APPENDIX 11: RESULTS OBTAINED BY CHEN AND DUBINSKY (2003) 83 APPENDIX 12: ORGANIZATIONAL CHARTS OF VIETNAM AIRLINES 84 Nguyen The Hoang – MBA VB3 LIST OF FIGURES Figure Top 30 airlines in Asia (Anna.aero, May 2010) Figure Top Asian air travel market (Anna.aero, May 2010) Figure Suggested research model (simplified from Chen and Dubinsky, 2003) Figure airline industry value chain (Buhalis, 2004) 13 Figure Sales channels with alternatives that Airlines can use (Dembrower et al., 2003) 15 Figure Market share of ticketing channels in Taiwan after 18 months of ticketing website launching ( Shon et al., 2003) 16 Figure Conceptual framework of perceived customer value in an e-commerce context (Chen and Dubinsky, 2003) 18 Figure Research process of the study 26 Figure Normal Probability Plot of “Valence of Experience” (SPSS - model 1) 38 Figure 10 Normal Probability Plot of “Perceived Customer Value” (SPSS - model 2) 39 Figure 11 Confirmed research models (with standardized regression coefficients) 44 Nguyen The Hoang – MBA VB3 LIST OF TABLES Table Classification of key sales channels of VietNam Airline Table Internet Usage and Population Statistics (Internet World Stats) Table Structure by chapters of the thesis 11 Table Four-distribution channels of KLM (Royal Dutch Airlines) 15 Table Constructs and items developed for the research 28 Table Results of Reliability analysis of items (SPSS v.16) 34 Table Summary results from first step of factor analysis of items (SPSS v.16) 35 Table Definition of variables’ coded names and calculation formulas 36 Table Dependent and independent variables of models studied 37 Table 10 Indicators for multicollinearity checking (SPSS) for models 38 Table 11 Model summary and statistical significance of the result (model 1) 40 Table 12 Model summary and statistical significance of the result (model 2) 40 Table 13 Multiple regression results 41 Nguyen The Hoang – MBA VB3