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MINISTRY OF EDUCATION AND TRAINING THE STATE BANK OF VIET NAM BANKING UNIVERSITY OF HO CHI MINH CITY NGUYEN TRAN MY DUYEN THE IMPACT OF PERCEIVED RISKS AND PERCEIVED BENEFITS ON THE INTENTION TO REUSE.
MINISTRY OF EDUCATION AND TRAINING THE STATE BANK OF VIET NAM BANKING UNIVERSITY OF HO CHI MINH CITY NGUYEN TRAN MY DUYEN THE IMPACT OF PERCEIVED RISKS AND PERCEIVED BENEFITS ON THE INTENTION TO REUSE MOMO E-WALLET OF GEN Z GRADUATE THESIS MAJOR: BUSINESS ADMINISTRATION CODE: 7340101 HO CHI MINH CITY, 2022 MINISTRY OF EDUCATION AND TRAINING THE STATE BANK OF VIET NAM BANKING UNIVERSITY OF HO CHI MINH CITY NGUYEN TRAN MY DUYEN THE IMPACT OF PERCEIVED RISKS AND PERCEIVED BENEFITS ON THE INTENTION TO REUSE MOMO E-WALLET OF GEN Z GRADUATE THESIS MAJOR: BUSINESS ADMINISTRATION CODE: 7340101 SUPERVISOR Dr PHAM HUONG DIEN HO CHI MINH CITY, 2022 i DECLARATION OF AUTHORSHIP I thus declare that this thesis was written by me under the direction and supervision of a Ph.D Pham Huong Dien; and that the work and findings included therein are accurate and not breach research ethics The data and figures in this thesis were gathered for analysis, comments, and assessments from a variety of sources and have been properly recognized in the reference section I will accept full responsibility for any academic misconduct discovered in my thesis Ho Chi Minh City, 27th Apr 2022 Author Nguyen Tran My Duyen ii ACKNOWLEDGEMENT I'd want to express my gratitude to my supervisor, Dr Pham Huong Dien, for her unwavering support and direction Dr Dien was a constant source of encouragement and was always eager to help in any manner possible during the study effort Finally, many thanks to everyone who participated in the survey and made this study possible Ho Chi Minh City, 27th Apr 2022 Author Nguyen Tran My Duyen iii ABSTRACT This study aims to examine the impact of perceived risks and perceived benefits on the intention to reuse the Momo e-wallet of Gen Z in Ho Chi Minh City This study uses quantitative research methods In the quantitative study, data was collected from an online questionnaire from 358 Gen Z people who are using Momo e-wallet The analysis results show that the perceived risk of Gen Z when using the Momo ewallet is created by financial risk, security risk, time-loss risk, and operational risk, while the perceived benefit of Gen Z when using the Momo e-wallet is created by the economic benefit, seamless transaction, convenience Besides, the analysis results also show that Gen Z's intention to reuse Momo e-wallet is negatively impacted by perceived risk this will reduce Gen Z's intention to reuse Momo ewallet and is positively impacted by perceived benefit, which increased Gen Z's intention to reuse Momo wallet In which, the perceived benefit has a stronger impact than the perceived risk From the research results, a number of implications have been proposed to help promote the users’ perceived benefit when using the service, and at the same time, try hard to minimize perceived risk, thereby promoting intend to reuse e-wallets of Gen Z more and more Keywords: Perceived risk, Perceived benefit, E-wallet iv Table of Contents CHAPTER 1: INTRODUCTION 1.1 Research Statement 1.2 Research Objectives and Questions 1.2.1 Research Objectives 1.2.2 Research Questions 1.3 Research Subjects and Scope 1.4 Research Methodology 1.5 Research Significance .5 1.6 Thesis structure .5 Summary of Chapter .6 CHAPTER 2: LITERATURE REVIEW 2.1 Theoretical Foundations 2.1.1 E-wallet 2.1.2 Generation Z .9 2.1.3 Reuse Intention 2.2 Theoretical Framework 10 2.2.1 Technology Acceptance Model (TAM) 10 2.2.2 The Risk-Benefit Framework 12 2.3 Previous research 16 2.4 Research Hypotheses and Model 22 2.4.1 Research hypotheses .22 2.4.2 Research model 27 Summary of Chapter .29 CHAPTER 3: METHODOLOGY 30 v 3.1 Research process 30 3.2 Research design .31 3.3 Data collection .32 3.3.1 Sampling 32 3.3.2 Scale formulation .33 3.3.3 Survey questionnaire 34 3.4 Data analysis 34 3.4.1 Cronbach’s Alpha Analysis 34 3.4.2 Exploratory Factor Analysis (EFA) 35 3.4.3 Confirmatory Factor Analysis (CFA) 36 3.4.4 Structural Equation Modeling (SEM) Analysis .39 Summary of Chapter .40 CHAPTER 4: RESULT 41 4.1 Descriptive Statistics .41 4.2 Cronbach’s Alpha 44 4.3 Exploratory Factor Analysis 46 4.3.1 Exploratory factor analysis of factors creating perceived risk 46 4.3.2 Exploratory factor analysis of factors creating perceived benefit 47 4.3.3 Exploratory factor analysis for the scale of the intention to reuse 48 4.4 Confirmatory factor analysis .49 4.4.1 Confirmatory factor analysis for the scale of factors creating perceived risk, perceived benefit 49 4.4.2 Confirmatory factor analysis for the scales of perceived risk, perceived benefit, and intention to reuse 50 4.5 Structural equation modeling 53 Summary of Chapter .55 vi CHAPTER 5: CONCLUSION 56 5.1 Conclusion .56 5.2 Implications 58 5.3 Limitations of the study and future research directions 60 REFERENCES 62 APPENDIX 72 APPENDIX 79 APPENDIX 85 APPENDIX 88 APPENDIX 95 APPENDIX 103 APPENDIX 113 vii LIST OF FIGURES Figure 2.1 Technology Acceptance Model 12 Figure 2.2 Proposed research model 28 Figure 3.1 Research Process 31 Figure 4.1 The results of the analysis of the structural equation modeling .53 LIST OF FIGURES TABLES Table 2.1 Previous studies summary 19 Table 2.2 Factors of perceived risk and perceived benefit impact the intention to reuse an E-wallet .21 Table 2.3 Synthesize the hypothesis of the current study 27 Table 3.1 Synthesis of indicators to evaluate the goodness of fit of the model .38 Table 4.1 Descriptive Statistics 43 Table 4.2 Cronbach's Alpha coefficient analysis .44 Table 4.3 Exploratory factor analysis of factors creating perceived risk 46 Table 4.4 Exploratory factor analysis of factors creating perceived benefit 48 Table 4.5 Exploratory factor analysis for the scale of the intention to reuse 49 Table 4.6 Correlations of First-Order Perceived Risks 50 Table 4.7 Correlations of First-Order Perceived Benefits .50 Table 4.8 Reliability Convergent Validity Results 51 Table 4.9 Correlations of Latent Variables 52 Table 4.10 Model Fit Measures .52 viii LIST OF ABBREVIATIONS AMOS Analysis of Moment Structures CFA Confirmatory Factor Analysis CFI Comparative Fit Index EFA Exploratory Factor Analysis GFI Goodness of Fit Index H (1-2) Hypothesis (1-2) TAM Technology Acceptance Model TLI Tucker and Lewis Index TPR Theory of Perceived Risk RMSEA Root Mean Square Error of Approximation SEM Structural Equation Modeling SPSS Statistical Package for Social Sciences 107 CFA for Perceived Risk, Perceived Benefit, Intention to Reuse 108 Regression Weights: (Group number - Default model) Estimate S.E C.R P FR < - PR 1.000 TR < - PR 1.249 138 9.085 *** SR < - PR 1.057 142 7.452 *** POR < - PR 1.264 140 9.050 *** EB < - PB 1.000 ST < - PB 1.415 169 8.376 *** CV < - PB 1.204 146 8.246 *** FR1 < - FR 1.000 FR3 < - FR 1.179 085 13.927 *** FR6 < - FR 1.023 072 14.202 *** FR2 < - FR 1.147 081 14.182 *** FR4 < - FR 1.018 074 13.677 *** FR5 < - FR 1.186 089 13.270 *** TR3 < - TR 1.000 TR2 < - TR 921 061 15.012 *** TR4 < - TR 1.003 064 15.611 *** TR5 < - TR 1.146 080 14.285 *** TR1 < - TR 1.088 075 14.408 *** SR4 < - SR 1.000 SR1 < - SR 1.060 077 13.758 *** SR5 < - SR 793 062 12.757 *** Label 109 Estimate S.E C.R P SR6 < - SR 814 072 11.350 *** SR2 < - SR 665 060 11.172 *** POR1 < - POR 1.000 POR3 < - POR 1.037 065 15.996 *** POR2 < - POR 1.069 072 14.900 *** EB3 < - EB 1.000 EB4 < - EB 998 079 12.615 *** EB1 < - EB 876 069 12.677 *** EB2 < - EB 915 071 12.891 *** ST2 < - ST 1.000 ST1 < - ST 946 067 14.215 *** ST3 < - ST 923 065 14.303 *** CV3 < - CV 1.000 CV2 < - CV 983 071 13.899 *** CV4 < - CV 1.019 071 14.323 *** CV6 < - CV 1.050 079 13.236 *** CV5 < - CV 1.026 076 13.417 *** CV1 < - CV 1.036 079 13.104 *** ITUE3 < - ITUE 1.000 ITUE1 < - ITUE 1.156 090 12.892 *** ITUE2 < - ITUE 1.027 091 11.254 *** Label 110 Standardized Regression Weights: (Group number - Default model) Estimate FR < - PR 678 TR < - PR 836 SR < - PR 602 POR < - PR 807 EB < - PB 655 ST < - PB 812 CV < - PB 813 FR1 < - FR 756 FR3 < - FR 744 FR6 < - FR 758 FR2 < - FR 757 FR4 < - FR 732 FR5 < - FR 712 TR3 < - TR 785 TR2 < - TR 766 TR4 < - TR 792 TR5 < - TR 734 TR1 < - TR 739 SR4 < - SR 736 SR1 < - SR 798 SR5 < - SR 732 111 Estimate SR6 < - SR 648 SR2 < - SR 638 POR1 < - POR 813 POR3 < - POR 824 POR2 < - POR 766 EB3 < - EB 745 EB4 < - EB 730 EB1 < - EB 734 EB2 < - EB 748 ST2 < - ST 790 ST1 < - ST 775 ST3 < - ST 781 CV3 < - CV 742 CV2 < - CV 755 CV4 < - CV 777 CV6 < - CV 720 CV5 < - CV 729 CV1 < - CV 713 ITUE3 < - ITUE 728 ITUE1 < - ITUE 820 ITUE2 < - ITUE 670 112 Model Validity Measure CR AVE MSV MaxR(H) ITUE PR PB ITUE 0.785 0.550 0.348 0.800 0.742 PR 0.824 0.543 0.138 0.848 -0.371*** 0.807 0.584 0.348 0.823 0.590*** 0.301*** 0.764 PB Validity Concerns No validity concerns here 0.737 113 APPENDIX 114 SEM 115 Regression Weights: (Group number - Default model) Estimate S.E C.R P FR < - PR 1.000 TR < - PR 1.249 138 9.085 *** SR < - PR 1.057 142 7.452 *** POR < - PR 1.264 140 9.050 *** EB < - PB 1.000 ST < - PB 1.415 169 8.376 *** CV < - PB 1.204 146 8.246 *** ITUE < - PR -.675 094 -7.195 *** ITUE < - PB 841 110 7.621 *** FR1 < - FR 1.000 FR3 < - FR 1.179 085 13.927 *** FR6 < - FR 1.023 072 14.202 *** FR2 < - FR 1.147 081 14.182 *** FR4 < - FR 1.018 074 13.677 *** FR5 < - FR 1.186 089 13.270 *** TR3 < - TR 1.000 TR2 < - TR 921 061 15.012 *** TR4 < - TR 1.003 064 15.611 *** TR5 < - TR 1.146 080 14.285 *** TR1 < - TR 1.088 075 14.408 *** Label 116 Estimate S.E C.R P SR4 < - SR 1.000 SR1 < - SR 1.060 077 13.758 *** SR5 < - SR 793 062 12.757 *** SR6 < - SR 814 072 11.350 *** SR2 < - SR 665 060 11.172 *** POR1 < - POR 1.000 POR3 < - POR 1.037 065 15.996 *** POR2 < - POR 1.069 072 14.900 *** EB3 < - EB 1.000 EB4 < - EB 998 079 12.615 *** EB1 < - EB 876 069 12.677 *** EB2 < - EB 915 071 12.891 *** ST2 < - ST 1.000 ST1 < - ST 946 067 14.215 *** ST3 < - ST 923 065 14.303 *** CV3 < - CV 1.000 CV2 < - CV 983 071 13.899 *** CV4 < - CV 1.019 071 14.323 *** CV6 < - CV 1.050 079 13.236 *** CV5 < - CV 1.026 076 13.417 *** CV1 < - CV 1.036 079 13.104 *** Label 117 Estimate S.E C.R P ITUE3 < - ITUE 1.000 ITUE1 < - ITUE 1.156 090 12.892 *** ITUE2 < - ITUE 1.027 091 11.254 *** Label Standardized Regression Weights: (Group number - Default model) Estimate FR < - PR 678 TR < - PR 836 SR < - PR 602 POR < - PR 807 EB < - PB 655 ST < - PB 812 CV < - PB 813 ITUE < - PR -.603 ITUE < - PB 771 FR1 < - FR 756 FR3 < - FR 744 FR6 < - FR 758 FR2 < - FR 757 FR4 < - FR 732 FR5 < - FR 712 118 Estimate TR3 < - TR 785 TR2 < - TR 766 TR4 < - TR 792 TR5 < - TR 734 TR1 < - TR 739 SR4 < - SR 736 SR1 < - SR 798 SR5 < - SR 732 SR6 < - SR 648 SR2 < - SR 638 POR1 < - POR 813 POR3 < - POR 824 POR2 < - POR 766 EB3 < - EB 745 EB4 < - EB 730 EB1 < - EB 734 EB2 < - EB 748 ST2 < - ST 790 ST1 < - ST 775 ST3 < - ST 781 CV3 < - CV 742 119 Estimate CV2 < - CV 755 CV4 < - CV 777 CV6 < - CV 720 CV5 < - CV 729 CV1 < - CV 713 ITUE3 < - ITUE 728 ITUE1 < - ITUE 820 ITUE2 < - ITUE 670 Squared Multiple Correlations: (Group number - Default model) Estimate ITUE 678 CV 660 ST 662 EB 429 POR 651 SR 363 TR 698 FR 460 ITUE2 450 ITUE1 672 120 Estimate ITUE3 530 CV1 509 CV5 532 CV6 519 CV4 603 CV2 569 CV3 551 ST3 609 ST1 601 ST2 625 EB2 560 EB1 539 EB4 533 EB3 556 POR2 587 POR3 680 POR1 661 SR2 407 SR6 420 SR5 535 SR1 637 121 Estimate SR4 542 TR1 547 TR5 539 TR4 627 TR2 587 TR3 617 FR5 507 FR4 536 FR2 573 FR6 575 FR3 554 FR1 571 ... reuse Momo e- wallet? 1.3 Research Subjects and Scope The research focuses on the impact of perceived risk and perceived benefit on the intention to reuse Momo e- wallet investigated among the generation... reduce risks, and increase Gen Z' s intention to reuse Momo e- wallet 4 1.2.2 Research Questions Do perceived risks and perceived benefits affect the intention to reuse MoMo e- wallet? How are the. .. negative effect on the intention to reuse Momo ewallet 2.4.1.4 The relationship between perceived benefit and intention to reuse According to Lee et al (2013), perceived benefit is defined as the user's