UNIVERSITY OF ECONOMICS UNIVERSITY OF ECONOMICS DEDICATION To my loving family and friends who support me a lot in my life, study, and work ACKNOWLEDGEMENTS Composing this master thesis is a long journey with many unexpected ups and downs; thanks to my great family, good friends, colleagues, and resourceful supervisor, I have accomplished this goal I am blessed beyond all measures, and I just want to say thank you I wish to extend special thanks to my supervisor, Dr Tran Phuong Thao, for all your time, advice, comments, and encouragement I could not have even imagined how I would have completed this thesis without your support Also, I would like to thank Dr Nguyen Dinh Tho, Dr Nguyen Thi Mai Trang, and Dr Dinh Thai Hoang, who all provide me initial foundation of research design as well as data analysis To the ISB research committee, I am thankful for your time, comments, and kind words that helped me through this process To my friends at Master of Business program ABSTRACT Vietnam TABLE OF CONTENT ACKNOWLEDGEMENTS ABSTRACT LIST OF FIGURES LIST OF TABLES ABBREVIATIONS CHAPTER - INTRODUCTION 1.1 Background of study 1.2 Research problem 1.3 Research objective and research questions 1.4 Scope of research 1.5 Research significance 1.6 Structure of the thesis CHAPTER - LITERATURE REVIEW, HYPOTHESES AND CONCEPTUAL MODEL 2.1 Foundational theories 2.1.1 Theory of Reasoned Action (TRA) 2.1.2 Theory of Planned Behavior (TPB) 2.2 Customer 3.1 Research process 21 3.2 Measurement 22 3.2.1 Measurement scale 22 3.2.2 Pilot test 25 3.3 Sampling and Data collection 26 3.3.1 Minimum sample size 26 3.3.2 Data collection 26 3.4 Data analysis 27 3.4.1 Reliability measure 27 3.4.2 Exploratory factor analysis (EFA) 28 3.4.3 Multiple regression analysis 28 3.5 Chapter summary CHAPTER 29 APPENDICES Appendix A: Questionnaire (English - Vietnamese version) Appendix B: KMO and Bartlett LIST OF FIGURES Page Figure 2.1: The Theory of Reasoned Action Figure 2.2: The Theory of Planned Behavior 10 Figure 2.3: Conceptual Model 19 Figure 3.1: Research process 22 LIST OF TABLES Page Table 3.1: Scale Items 24 Table 4.1: Profile of respondents 30 Table 4.2: Total Cronbach 53 Amin, H (2012a) Explaining intention to use the Islamic credit card: an extension of the TRA model Retrieved from http://mpra.ub.uni-muenchen.de/36957/ Amin, H (2012b) Patronage factors of malaysian local customers towards islamic credit cards Management Research Review, 35(6), 512-530 Andries, M., & Martin, C (2004) Oversight of non-cash payment schemes: objectives and implementation procedures Banque De France Financial Stability Review, 5, 91-106 Bai, F., & Chen, X (2013) Analysis on the new types and countermeasures of credit card fraud in mainland China Journal of Financial Crime, 20(3), 267-271 Barker, T., & Sekerkaya, A (1992) Globalizaton of credit card usage: the case of a developing economy International Journal of Bank Marketing, 10(6), 27-31 Baumann, C., Elliott, G., & Burton, S (2012) Modeling customer satisfaction and loyalty: survey data versus data mining Journal of Services Marketing, 26(3), 148-157 Borzekowski, R., & Kiser, E (2007) The choice at the checkout: quantifying demand across payment instruments International Journal of Industrial Organization, 26(4), 889-902 Capgemini (2014) World payment report 2014 Retrieved from https://www.worldpaymentsreport.com/ Celik, H (2011) Influence of social norms, perceived playfulness and online shopping anxiety on customers 54 Cheong, J.H., & Park, M.C (2005) Mobile internet acceptance in Korea Internet Research, 15(2), 125-140 Chiu, Y.B., Lin, C.P., & Tang, L.L (2005) Gender differs: assessing a model of online purchase intentions in e-tail service International Journal of Service Industry Management, 16(5), 416-435 Chong, A.Y.L., Ooi, K.B., Lin, B., & Tan, B.I (2010) Online banking adoption: an empirical analysis International Journal of Bank Marketing, 28(4), 267-287 Comrey, A.L., & Lee, H.B (1992) A First Course in Factor Analysis, 2nd ed., Lawrence Erlbaum Associates, Hillsdale, NJ Coyle-Camp, E M (1994) Savings in the cards Facilities, 12(8), 5-9 Davies, E., & Lea, S.E.G (1995) Student attitudes to student debt Journal of Economic Psychology, 16, 663-679 Davis, F.D (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology MIS Quarterly, 13(3), 319-340 Delener, N., Katzenstein, H (1994) Credit Card Possession and Other Payment Systems: Use Patterns among Asian and Hispanic Consumers International Journal of Bank Marketing, 12(4), 13-24 Dimov, Y (2011) Role of the banking sector in non-cash payments settlement: case of Cibank Tampere University of Applied Sciences Retrieved from https://publications.theseus.fi/bitstream/handle/10024/38242/Dimov_Yancho.pdf?sequ ence=2 Eagly, A.H., & Chaiken, S (1993) The Psychology of Attitudes, HBJ College Publishers, Orlando, FL Erdem, C (2008) Factors affecting the probability of credit card default and the intention of card use in Turkey International Research Journal of Finance and Economics, 18, 159-171 Euromonitor International (2010) Financial cards and payment 55 Fishbein, M., & Ajzen, I (1975) Belief, attitude, intention, and behavior: An introduction to theory and research Addison-Wesley, Reading, MA Foscht, T., Maloles, C III, Swoboda, B., & Chia, S.L (2010) Debit and credit card usage and satisfaction: who uses which and why 56 Kaynak, E., & Harcar, T (2001) Consumer 57 Lin, W., Wang, Y., Yang, F., & Sekarini, N S (2013) The effect of credit card on the compulsive buying behavior intention Journal of Accounting, Finance & Management Strategy, 8(2), 45-74 Luarn, P., & Lin, H.H (2005) Towards an understanding of the behavioral intention to use mobile banking Computers in Human Behavior, 21(6), 873-891 Mansor, N., & Che-Mat, A (2009) Islamic credit card: are demographic factors a good indicator Asian Social Science, 5(12), 17-26 Mathieson, K., Peacock, E., & Chin, W.W (2001) Extending the technology acceptance model: the influence of perceived user resources DATABASE for Advance in Information System, 32(3), 86-112 Nasri, W (2011) Factors influencing the adoption of internet banking in Tunisia International Journal of Business and Management, 6(8), 143-160 Nielson Finance IPG (2011) Vietnam landscape and finance trends Retrieved from http://www.nielsen.com/content/dam/corporate/t3/vietnam/reports/Nielsen_PFMPrese ntation_June2011.pdf Nga, J.K.H., Yong, L.H.L., & Sellappan, R (2011) The influence of image consciousness, materialism and compulsive spending on credit card usage intentions among youth Young consumers, 12(3), 243-253 Oxford Dictionary (n.d) Definition of materialism in English Retrieved form http://www.oxforddictionaries.com/definition/english/materialism 58 Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S (2004) Consumer acceptance of online banking: an extension of the technology acceptance model Internet Research, 14(3), 224-235 Proquest (2013, Feb 08) Debit, credit card usage boosts global growth M2 EquityBites Retrieved from http://search.proquest.com/docview/1285160654?accountid=39958 Ramayah, T., Jantan, M., Noor, M.N.M., & Ling, K.P (2003) Receptiveness internet banking by Malaysian consumers Asian Academy of Management Journal, 8(2), 1-29 Ramayah, T., & Mohd-Suki, N (2006) Intention to use mobile PC among MBA students: implications for technology integration in the learning curriculum UNITAR e-Journal, 1(2), 1-10 Rau, A (2013) E-Payments in Emerging Markets Journal of Payments Strategy and Systems, 7(4) Retrieved from http://www.henrystewartpublications.com/jpss Richins, M (2004) The Material Values Scale: Measurement Properties and Development of a Short Form Journal of Consumer Research, 31, 209-219 Richins, M., & Dawson, S (1992) A Consumer Values Orientation for Materialism and Its Measurement: Scale Development and Validation Journal of Consumer Research, 19, 303-316 Sathye, M (1999) Adoption of internet banking by Australian consumers: an empirical investigation International Journal of Bank Marketing, 17(7), 324-334 Sharpe, D.L., Yao, R., & Liao, L (2012) Correlates of credit card adoption in urban China J Fam Econ Iss, 33, 156-166 Singh, A.M (2004) Trends in South African internet banking Aslib Proceedings: New Information Perspectives, 56(3), 187-196 Sripalawat, J., Thongmak, M., & Ngramyarn, A (2011) M-banking in metropolitan Bangkok and a comparison with other countries The Journal of Computer Information Systems, 51(3), 67-76 State bank of Vietnam (2014a) Credit institution system Retrieved from http://www.sbv.gov.vn/portal/faces/en/enm/enpages_home/creditinstitutionssys/crediti nstitutions?_adf.ctrl-state=1daj6dvp2z_4&_afrLoop=3566065827126500 59 State bank of Vietnam (2014b) Number of bank cards Retrieved from http://www.sbv.gov.vn/portal/faces/en/enm/enpages_home/statistic/paymentstatistic/n umbankcard?_afrWindowId=null&_afrLoop=134082493634400&_afrWindowMode= 0&_adf.ctrlstate=12ztl826rj_4#%40%3F_afrWindowId%3Dnull%26_afrLoop%3D134082493634 400%26_afrWindowMode%3D0%26_adf.ctrl-state%3Di8ib85xf6_4 State bank of Vietnam (2014c) Personal current account as of the end of Quarter IV/2013 Retrieved from http://www.sbv.gov.vn/portal/faces/en/enm/enpages_home/statistic/paymentstatistic/ac cindividual?_adf.ctrl-state=1bucak9f9k_4&_afrLoop=7099960338480500 Sumanjeet (2009) Emergence of payment systems in the age of electronic commerce: the state of art Asia Pacific Journal of Finance and Banking Research, 3(3), 18-40 Tabachnick, B G., & Fidell, L S (2001) Using Multivariate Statistics Boston: Pearson Education Taherdoost, H., Masrom, M., & Ismail, Z (2009) Adoption model to assess the user acceptance of smart card technology Journal of US-China Public Administration, 6(3), 47-58 Taib, F M., Ramayah, T., & Razak, D A (2008) Factors influencing intention to use diminishing partnership home financing International Journal of Islamic and Middle Eastern Finance and Management, 1, 235-248 Teoh, W M., Chong, S., & Yong, S M (2013) Exploring the factors influencing credit card spending behavior among Malaysians International Journal of Bank Marketing, 31(6), 481-500 Thakur, R., & Srivastava, M (2014) Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India Internet Research, 24(3), 369-392 Tuoitrenews (2012) Vietnam 60 VCCInews (2014) Vietnam credit card market forecast to boom soon Retrieved from http://vccinews.com/news_detail.asp?news_id=3729 Venkatesh, V., & Davis, F.D (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies Management Science, 46(2), 186-204 Venkatesh, V., Morris, G B, & Davis, F D (2003) User acceptance of information technology: Towards a unified view MIS Quarterly, 27(3), 425-478 VietnamNews (2014) New decree targets reduction of cash payments Retrieved from http://vietnamnews.vn/economy/250238/new-decree-targets-reduction-of-cashpayments.html Wang, Y.S., Wang, Y.M., Lin, H.H., & Tang, T.I (2003) Determinants of user acceptance of internet banking: an empirical study International Journal of Service Industry Management, 14(5), 501-519 Watkins, J.P (2000) The corporate power and the evolution of consumer credit Journal of Economic Issues, 34(4), 909-933 White, L., & Yanamandram, V (2004) Why customers stay: reasons and consequences of inertia in financial services Managing Service Quality, 14(2/3), 183-194 World Trade Organization (2007) Viet Nam joins WTO with Director-General APPENDICES Appendix A: Questionnaire (English - Vietnamese version) A SURVEY ON CREDIT CARD USAGE INTENTION I am a Master student from The University of Economics HCMC now undertaking a survey on factors affecting Vietnamese customer intention to use credit card I would like to have your cooperation in answering the following questions The information collected will only be used for research purposes All collected information will be treated with strict confidentiality Please circle the answer that you think best describes your perceptions and attitude Part I: Screening Have you got any credit cards currently? Part 2: Materialism I admire people who own expensive homes, cars, and clothes The things I own say a lot about how well I (1) Yes (2) No Strongly Disagree Disagree Neutral Agree Strongl y Agree Part 5: Social Influence People who are important to me think that I should use 20 credit cards People who are familiar with me think that I should 21 use credit cards People who influence my behavior think that I should 22 use credit cards 23 Most people surrounding with me use credit cards People whose opinion I value think I should use credit 24 cards Part 6: Perceived Credibility I believe my information is kept confidential when 25 using credit cards I believe my transactions are secured when using 26 credit cards I believe my privacy would not be divulged when 27 using credit cards 28 I believe the banking environment is safe Part 7: Amount of information about credit card I have generally received enough basic information 29 about credit cards I received enough information about the promotion of 30 credit cards I obtained information on credit cards via the bank and 31 its management Part 8: Intention to use credit card 5 5 5 5 5 5 32 My general intention to use a credit card is very high 33 I will think about using a credit card 34 I will use a credit card in the future Part 9: Demographics information 35 36 37 38 39 What is your gender? What is your age? What is your marital status? What is your highest level of education completed? What is your monthly income? (1) Male (2) Female (1) 18 - 29 (2) 30-39 (3) (4) (1) 40 - 49 50 and above Single (2) Married (3) Separated (1) Highschool (2) University/College (3) Advanced Degree (1) Below 4.5m VND (2) From 4.5m VND to below 7.5m VND (3) From 7.5m VND to below 15m VND (4) 15m VND and above KH 22 Nh Appendix B: KMO and Bartlett Appendix C: Testing multiple regression assumptions Figure C1: Histogram of standardize residual Figure C2: Normal P-P plot of standardize residual Figure C3: Scatterplot Case Number Std Residual INTENTION Predicted Value Residual 4.209 15.00 15 -3.371 6.00 210 -3.003 7.00 a Dependent Variable: INTENTION 8.7606 6.23940 10.9978 -4.99784 11.4519 -4.45193 Table C1: Casewise Diagnostics ... correlated with credit card usage intention; while correlation between intention to use credit card and materialism as well as the correlation between intention to use credit card and perceived credibility... and factorially distinct and all items are used to measure a particular construct loaded on a single factor: Table 4.6: Summarized Factor analysis Factor Item Attitude towards using credit card. .. Vietnamese customers aware of credit card; a number of customers have not enough basic information about credit card as well as promotion ads about it This turns to be a barrier against credit card