FACTORS AFFECTING BEHAVIORAL INTENTIONS TOWARD MOBILE BANKING USAGE A STUDY OF BANKING CUSTOMERS IN HO CHI MINH CITY

UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business Nguyen Khac Duy FACTORS AFFECTING BEHAVIORAL INTENTIONS TOWARD MOBILE BANKING USAGE: A STUDY OF BANKING CUSTOMERS IN HO CHI MINH CITY ID: 60340102 MASTER OF BUSINESS (Honours) SUPERVISOR: Dr Nguyen Thi Nguyet Que Ho Chi Minh City – Year 2012 [2] ACKNOWLEDGEMENT At the first of my thesis, I would like to thank all those people who made this thesis possible and an unforgettable experience for my studying Foremost, I would like to express my sincere gratitude to my supervisor, Dr Nguyen Thi Nguyet Que, for the continuous support of my MBUS study and research, for her patience, motivation, enthusiasm, and immense knowledge Her guidance helped me in all the time of research and writing of this thesis Besides my supervisor, I would like to thank the rest of my thesis committee: Prof Nguyen Dong Phong, Prof Nguyen Dinh Tho, and Dr Tran Ha Minh Quan, for their encouragement, insightful comments, and hard questions I thank my classmates in ISB MBUS 2010 encourage and support me complete this thesis Completing this work would have been all the most difficult were it not for the support and friendship provided by the members of University of Economics Ho Chi Minh City - International School of Business Last but not the least; I would like to thank my family I must express my gratitude to Nguyen Thi Hong Hiep, my wife, for her continued support and encouragement I also wish thank all those people who spent through their time and generous support made this thesis project a dream come true Ho Chi Minh City, December 18, 2012 NGUYEN KHAC DUY [3] ABSTRACT Mobile phones with banking technology are becoming more readily available in Vietnam Similarly, many financial institutions and mobile phone service providers are teaming up to provide several banking services to customers via the mobile phone However, the number of people who choose to adopt or use such technologies is still relatively low Therefore, there is a need to assess the acceptance of such technologies to establish factors that hinder or promote customer‟s intention to use mobile banking (MB) Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB) are the base models in order to investigate the customers‟ intention to use mobile banking services in Ho Chi Minh City (HCMC) A questionnaire with five-point Likert scale is survey to 400 target respondents This research combines the variables (1) “perceived usefulness”, (2) “perceived ease of use”, (3) “attitude”, (4) “subjective norm”, and (5) “Perceived behavioral control” in a proposed model to reflect consumer‟s intention to use mobile banking Results indicate that perceived usefulness, perceived ease of use, subjective norm, and perceived behavioral control are significant with respect to the customer‟s intention to use mobile banking services In constrast with previous studies, attitude was not significant in explaining mobile banking adoption In summary, perceived behavioral control contributes the most in explaining the factor of intention to use mobile banking The results of the data analysis contributes to the body of knowledge by demonstrating that the above factors are critical in intention to use mobile banking in a developing country context The implications of the results form a good basis for providing practical recommendations to leaders of commercial banks, and directions for further work [4] TABLE OF CONTENTS ACKNOWLEDGEMENT ABSTRACT LIST OF FIGURES LIST OF TABLES CHAPTER 1: INTRODUCTION 1.1 Research background 1.2 Overview of electronic banking market in Ho Chi Minh City 1.2.1 E-banking services 1.2.2 Advantages of e-banking services 11 1.2.3 Difficulties in implementing e-banking services 12 1.3 Problem statement 13 1.4 Research objective 14 1.5 Research scopes and limitations 15 1.6 Research implications 15 1.7 Thesis structure 16 1.8 Summary 17 CHAPTER 2: LITERATURE REVIEW 18 1.1 Theoretical background 18 1.1.1 Technology Acceptance Model 18 1.1.2 Theory of Planned Behavior 19 1.2 Research model and hypotheses 20 1.3 Summary 24 CHAPTER 3: METHODOLOGY 25 [5] 3.1 Research design 25 3.2 Development of questionnaire 26 3.2.1 Measurement scales 26 3.2.1.1 Measure of Perceived usefulness and Perceived ease of use 26 3.2.1.2 Measure of Attitude 27 3.2.1.3 Measure of Subjective norms 28 3.2.1.4 Measure of Perceived Behavioural Control 29 3.2.1.5 Measure of Intention to use mobile banking 29 3.2.2 Draft questionnaire 30 3.3 Pilot study 30 3.4 Sample method 31 3.5 Questionnaire administration 32 3.6 Data analysis methods 32 3.6.1 Reliability 32 3.6.2 Exploratory Factor Analysis (EFA) 33 3.6.3 Multiple regression analysis 33 3.7 Summary 34 CHAPTER 4: DATA ANALYSIS AND RESULTS 35 4.1 Descriptive analysis 35 4.2 Measure assessment 36 4.2.1 Reliability analysis 36 4.2.2 Exploratory Factor Analysis (EFA) 38 4.3 Hypotheses testing 41 4.4 Testing the effect of demographic variables 44 4.5 Summary 44 [6] CHAPTER 5: CONCLUSION 46 5.1 Overview 46 5.2 Main findings 46 5.3 Practical implications 47 5.4 Theoretical implications 47 5.5 Limitations 48 APPENDICES 52 APPENDIX 1: QUESTIONNAIRE 52 APPENDIX 2: DESCRIPTIVE STATISTICS 56 APPENDIX 3: CRONBACH‟S ALPHA RELIABILITY ANALYSIS 58 APPENDIX 4: INTER-ITEM CORRELATION MATRIX 61 APPENDIX 5: THE FIRST-TIME RUNNING FACTOR ANALYSIS – EIGENVALUES (FOR INDEPENDENT VARIABLES) 62 APPENDIX 6: THE FIRST TIME RUNNING – FACTOR LOADING 63 APPENDIX 7: THE SECOND TIME RUNNING – EIGENVALUES 65 APPENDIX 8: THE SECOND TIME RUNNING – FACTOR LOADING 66 APPENDIX 9: THE FIRST TIME RUNNING – EIGENVALUES AND FACTOR LOADING (FOR DEPENDENT VARIABLE) 67 APPENDIX 10: MULTIPLE REGRESSION 68 APPENDIX 11: CHARTS OF TESTING HYPOTHESES 69 APPENDIX 12: AFFECTING OF DEMOGRAPHIC VARIABLES 71 [7] LIST OF FIGURES Figure 1: Technology Acceptance Model 14 Figure 2: Theory of Planned Behaviour 16 Figure 3: The proposed research model with hypotheses 17 Figure 4: Research process 22 LIST OF TABLES Table 1: Figure of e-banking services of 15 commercial banks in HCMC 10 Table 2: Scale of Perceived usefulness and Perceived ease of use 27 Table 3: Scale of Attitude 28 Table 4: Scale of Subjective norms 29 Table 5: Scale of Perceived Behavioural Control 29 Table 6: Scale of Intention to use mobile banking 30 Table 7: Cronbach‟s alpha reliability coefficient 33 Table 8: Descriptive statistic of respondent‟s characteristics 36 Table 9: Reliability analysis for each factor 38 Table 10: Key dimensions, items 41 Table 11: R Square Value (R2) 43 Table 12: ANOVA 43 Table 13: Beta Coefficient 43 Table 14: Creating and recoding variables 45 [8] CHAPTER 1: INTRODUCTION The introduction chapter identifies the research background, present the problem statement, and introduce the research objectives as well as the scope of research Futhermore, the research implications is also outline 1.1 Research background Mobile banking is an innovative service, which has been perpetuated by the development and diffusion of the mobile communication technology Mobile banking is defineded as “the financial services delivered via mobile networks and performed on a mobile phone” (Bangens & Soderberg, 2008, p.26) This service provides much convenience and promptness to the banks‟ customers along with cost savings Many banks are interested in expanding their market through mobile services Traditionally, the most widespread method of conducting banking transactions has been through offline retail banking Mobile banking, however, is the recent trend in banking transition and holds a bright future that is promising over and above the one brought by electronic banking (e-banking) Mobile banking provides personalized, anytime - anywhere banking services thus making it the future of banking In the last several years, several commercial banks in Vietnam have introduced and diffused some mobile banking systems The world economy is going through a crisis period Consumers of today are highly sophisticated and their need for personalized service is ever increasing by the day The digital age customers now require banking services serve to them anywhere they are As an emerging technological innovation, especially in the developing countries, mobile banking is yet to gain acceptance on a wide scale and adoption level is marginally insignificant (Amin, 2007, p.31) Hence, the need to understand the factors influencing intention to use mobile banking services is indispensable [9] 1.2 Overview of electronic banking market in Ho Chi Minh City So far, all commercial banks have built core-banking system, which connects online system The commercial banks have same level of investment in technology, because the same solutions and network infrastructure Therefore, the commercial banks can launch e-banking services similar to each other 1.2.1 E-banking services Currently, the commercial banks in HCMC have developed banking services via e-banking with convenient Many new payment services and valueadded utilities was, promoted for payment services, create competitive advantage among the banks Therefore, the banks have focused on technology, infrastructure effectively to serve the best payment services via e-banking, with the expanding scope to serve businesses and individuals customer Practical figures in HCMC shows, to the end of 2011, there were 111,861 customers are businesses and individuals who use payment services through e-banking, with the number of transactions through this channel during the year 2011 reached 1,732,654 transactions, total transaction value of 49,436 billion VND (data from the State Bank of Viet Nam - Branch Ho Chi Minh City) E-banking services also vary as (1) Internet banking for businesses and individual customers (transfers in and out of the system, the inter-bank transfer through CITAD ); (2) Mobile banking: SMS Banking (account balance inquiries, automatic SMS when there is a change in account ), Mobile banking (money transfer, bill payment ); (3) Phone banking (payment of school fees, telephone payment,etc) The commercial banks is cooperating with partners in the implementation of electronic payment services in order to reduce banking transaction costs, increased competition and improve the quality of services This also helps reduce the bank‟s cost in payments via papers, making it convenient for customers Customers not need go to the bank, but can make the payment transaction at [ 10 ] home At the same time, the banks are also actively working with technology partners to provide security services, ensure the safety of customer and bank assets Table – Figure of electronic banking services of 15 commercial banks in Ho Chi Minh City (Report of the State Bank of Viet Nam - Branch Ho Chi Minh City on December 31, 2011) Number of transactions Items (items) / Value (million VND) The number of enterprise customers using 7.561 payment via internet banking services The number of individual customers are using 73.644 services paid via internet banking The number of individual customers using 17.437 payment services via mobile banking The number of customers using payment services 13.219 via other electronic banking The number of payment transactions of business 325.846 customer via internet banking Value of payment transactions of business 27.120.937 customer via internet banking The number of payment transactions individual 1.056.905 customers via internet banking Value of payment transactions individual 21.821.640 [ 58 ] APPENDIX 3: CRONBACH’S ALPHA RELIABILITY ANALYSIS Reliability Statistics Cronbach's Alpha N of Items 625 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Corrected Item- Cronbach's Alpha Item Deleted Total Correlation if Item Deleted PU01 17.07 2.941 458 533 PU02 17.34 2.726 603 459 PU03 17.78 3.433 207 652 PU04 17.12 3.067 291 622 PU05 17.70 3.051 382 570 Reliability Statistics Cronbach's Alpha N of Items 652 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Corrected Item- Cronbach's Alpha Item Deleted Total Correlation if Item Deleted PU01 13.10 2.267 396 608 PU02 13.37 1.975 614 461 PU04 13.14 2.051 403 610 PU05 13.72 2.326 342 643 Reliability Statistics Cronbach's Alpha N of Items 867 [ 59 ] Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Corrected ItemItem Deleted Total Correlation Cronbach's Alpha if Item Deleted PEU06 10.95 4.069 569 886 PEU07 11.52 3.471 779 804 PEU08 11.24 3.769 792 805 PEU09 11.46 3.353 753 817 Reliability Statistics Cronbach's Alpha N of Items 885 Item-Total Statistics Scale Scale Mean if Variance if Item Deleted Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted ATT10 7.57 2.255 740 871 ATT11 7.08 1.838 798 823 ATT12 7.32 2.012 804 813 Reliability Statistics Cronbach's Alpha N of Items 846 Item-Total Statistics Scale Mean if Item Deleted Scale Variance Corrected Item- Cronbach's Alpha if Item Deleted Total Correlation if Item Deleted SN13 16.63 7.502 701 807 SN14 16.12 7.574 824 780 SN15 15.80 8.310 573 833 SN16 16.67 9.554 473 847 SN17 16.40 8.678 715 810 SN18 16.04 8.578 530 841 [ 60 ] Reliability Statistics Cronbach's Alpha N of Items 848 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item- Cronbach's Alpha Total Correlation if Item Deleted PBC19 11.09 3.188 692 808 PBC20 10.37 3.261 582 849 PBC21 11.50 2.644 769 770 PBC22 10.95 2.770 720 793 Reliability Statistics Cronbach's Alpha N of Items 901 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected ItemTotal Correlation Cronbach's Alpha if Item Deleted INT23 6.90 2.124 771 887 INT24 7.19 1.995 856 811 INT25 7.39 2.248 787 872 [ 61 ] APPENDIX 4: INTER-ITEM CORRELATION MATRIX [ 62 ] APPENDIX 5: THE FIRST-TIME RUNNING FACTOR ANALYSIS – EIGENVALUES (FOR INDEPENDENT VARIABLES) KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity 752 Approx Chi-Square 3612.436 df 210 Sig .000 Total Variance Explained Rotation Sums of Extraction Sums of Squared Loadings Squared Loadingsa Initial Eigenvalues % of Factor Total Cumulative Variance % % of Total Cumulative Variance % Total 6.746 32.124 32.124 6.475 30.834 30.834 4.430 2.862 13.629 45.753 2.590 12.332 43.166 3.872 2.549 12.140 57.893 2.287 10.888 54.054 3.619 1.709 8.139 66.033 1.441 6.861 60.916 2.926 1.591 7.576 73.609 1.223 5.825 66.740 4.684 1.009 4.803 78.412 732 3.486 70.226 2.530 753 3.587 81.999 686 3.266 85.266 582 2.773 88.038 10 430 2.049 90.087 11 387 1.844 91.931 12 302 1.440 93.371 13 238 1.134 94.504 14 227 1.079 95.584 15 202 961 96.544 16 184 877 97.421 17 148 703 98.124 18 132 629 98.753 19 106 504 99.256 20 085 405 99.662 21 071 338 100.000 Extraction Method: Principal Axis Factoring [ 63 ] KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity 752 Approx Chi-Square 3612.436 df 210 a When factors are correlated, sums of squared loadings cannot be added to obtain a total variance APPENDIX 6: THE FIRST TIME RUNNING – FACTOR LOADING (FOR INDEPENDENT VARIABLES) Pattern Matrixa Factor PU01 PU02 -.261 239 PU04 -.313 728 206 670 248 PU05 527 PEU06 479 PEU07 880 PEU08 781 PEU09 910 -.252 562 251 281 299 -.223 328 ATT10 771 ATT11 891 ATT12 923 SN13 673 SN14 708 SN15 981 290 SN16 860 SN17 889 SN18 230 798 PBC19 PBC20 -.395 866 409 379 PBC21 794 PBC22 591 Extraction Method: Principal Axis Factoring Rotation Method: Promax with Kaiser Normalization .287 [ 64 ] Pattern Matrixa Factor PU01 PU02 -.261 239 PU04 -.313 728 206 670 248 PU05 527 PEU06 479 PEU07 880 PEU08 781 PEU09 910 -.252 562 251 281 299 -.223 328 ATT10 771 ATT11 891 ATT12 923 SN13 673 SN14 708 SN15 981 290 SN16 860 SN17 889 SN18 230 PBC19 PBC20 798 -.395 866 409 379 PBC21 794 PBC22 591 a Rotation converged in iterations .287 [ 65 ] APPENDIX 7: THE SECOND TIME RUNNING – EIGENVALUES (FOR INDEPENDENT VARIABLES) KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity Approx Chi-Square 724 2900.191 df 153 Sig .000 Total Variance Explained Rotation Sums of Extraction Sums of Squared Loadings Squared Loadingsa Initial Eigenvalues % of Factor Total Cumulative Variance % % of Total Cumulative Variance % Total 5.648 31.379 31.379 5.419 30.106 30.106 3.348 2.671 14.838 46.217 2.384 13.243 43.349 3.424 2.361 13.115 59.332 2.124 11.801 55.150 2.835 1.555 8.638 67.970 1.239 6.885 62.036 3.680 1.421 7.895 75.865 1.164 6.464 68.500 3.767 711 4.801 81.666 678 3.765 85.432 509 2.829 88.261 387 2.148 90.409 10 330 1.832 92.240 11 302 1.678 93.918 12 229 1.271 95.189 13 221 1.225 96.414 14 183 1.015 97.429 15 152 843 98.272 16 131 730 99.002 17 103 570 99.572 18 077 428 100.000 Extraction Method: Principal Axis Factoring a When factors are correlated, sums of squared loadings cannot be added to obtain a total variance [ 66 ] APPENDIX 8: THE SECOND TIME RUNNING – FACTOR LOADING (FOR INDEPENDENT VARIABLES) Pattern Matrixa Factor PU01 270 -.249 PU02 742 228 PEU07 801 PEU09 497 729 PEU08 648 221 PU04 -.390 979 ATT10 779 ATT11 894 ATT12 921 SN13 SN14 688 287 653 SN15 957 SN16 860 SN17 902 SN18 783 -.344 PBC19 958 PBC21 752 PBC22 621 Extraction Method: Principal Axis Factoring Rotation Method: Promax with Kaiser Normalization a Rotation converged in iterations .272 [ 67 ] APPENDIX 9: THE FIRST TIME RUNNING – EIGENVALUES AND FACTOR LOADING (FOR DEPENDENT VARIABLE) KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity Approx Chi-Square 728 434.931 df Sig .000 Total Variance Explained Initial Eigenvalues Factor Total % of Variance Extraction Sums of Squared Loadings Cumulative % 2.505 83.510 83.510 317 10.560 94.071 178 5.929 100.000 Extraction Method: Principal Axis Factoring Factor Matrixa Factor INT23 815 INT24 948 INT25 841 Extraction Method: Principal Axis Factoring a factors extracted 11 iterations required Total 2.271 % of Variance 75.710 Cumulative % 75.710 [ 68 ] APPENDIX 10: MULTIPLE REGRESSION Model Summaryb Adjusted R Model R 859a Square R Square Std Error of the Estimate 819 818 1.08361 a Predictors: (Constant), X5, X3, X1, X4, X2 b Dependent Variable: Intention to use mobile banking ANOVAb Model Sum of Squares Regression df Mean Square 2931.071 219 Sig 499.243 000a 1.174 3188.222 Total 586.214 257.151 Residual F 224 a Predictors: (Constant), X5, X3, X1, X4, X2 b Dependent Variable: Intention to use mobile banking Table 12: Coefficientsa Unstandardized Coefficients Model Standardized Coefficients B (Const Std Error -3.432 324 052 X2 061 X3 X4 t 817 X1 Beta Collinearity Statistics Sig Tolerance VIF -4.201 000 231 6.273 000 847 1.180 042 133 1.447 049 717 1.396 -.016 037 -.009 -.435 664 896 1.116 031 025 128 1.254 031 731 1.369 X5 832 052 577 a Dependent Variable: Intention to use mobile banking 15.345 000 598 1.672 ant) [ 69 ] APPENDIX 11: CHARTS OF TESTING HYPOTHESES Histogram [ 70 ] [ 71 ] APPENDIX 12: AFFECTING OF DEMOGRAPHIC VARIABLES c Model Summary Change Statistics R Adjusted R Std Error of R Square Square Square the Estimate Change Sig F Model R F Change df1 df2 Change 959 a 919 918 1.08361 919 499.243 219 000 960 b 921 918 1.07721 001 3.611 218 049 a Predictors: (Constant), Perceived usefulness Perceived ease of use, Attitude, Subjective norm, Perceived behavioral control b Predictors: (Constant), Perceived usefulness Perceived ease of use, Attitude, Subjective norm, Perceived behavioral control, Gender c Dependent Variable: Intention to use mobile banking c Model Summary Change Statistics R Adjusted R Std Error of R Square Square Square the Estimate Change Sig F Model R 959 a 919 918 1.08361 919 499.243 219 000 961 b 923 920 1.06391 003 9.186 218 053 F Change df1 df2 Change a Predictors: (Constant), Perceived usefulness Perceived ease of use, Attitude, Subjective norm, Perceived behavioral control b Predictors: (Constant), Perceived usefulness Perceived ease of use, Attitude, Subjective norm, Perceived behavioral control, Marital status c Dependent Variable: Intention to use mobile banking c Model Summary Change Statistics R Adjusted R Std Error of R Square Square Square the Estimate Change Sig F Model R 959 a 919 918 1.08361 919 499.243 219 000 961 b 923 920 1.06978 003 2.424 215 049 F Change df1 df2 Change a Predictors: (Constant), Perceived usefulness Perceived ease of use, Attitude, Subjective norm, Perceived behavioral control b Predictors: (Constant), Perceived usefulness Perceived ease of use, Attitude, Subjective norm, Perceived behavioral control, Age c Dependent Variable: Intention to use mobile banking [ 72 ] c Model Summary Change Statistics R Adjusted R Std Error of R Square Square Square the Estimate Change Sig F Model R F Change df1 df2 Change 959 a 919 918 1.08361 919 499.243 219 000 960 b 922 919 1.07447 002 2.247 216 084 a Predictors: (Constant), Perceived usefulness Perceived ease of use, Attitude, Subjective norm, Perceived behavioral control b Predictors: (Constant), Perceived usefulness Perceived ease of use, Attitude, Subjective norm, Perceived behavioral control, Education c Dependent Variable: Intention to use mobile banking ... statement was defined to take a closed look at using mobile banking in Viet Nam In order to narrow down the topic area, the scope of research examined the mobile banking in Ho Chi Minh City Finally,... electronic banking (e -banking) Mobile banking provides personalized, anytime - anywhere banking services thus making it the future of banking In the last several years, several commercial banks in Vietnam... via internet banking Value of payment transactions of business 27.120.937 customer via internet banking The number of payment transactions individual 1.056.905 customers via internet banking Value