Factors Affect Intention To Use Evn Mobile Application (Epoint) Among Generation Y And Generation Z In Hanoi.docx

NATIONAL ECONOMICS UNIVERSITY NEU BUSINESS SCHOOL LUU TRAN THUY ANH FACTORS AFFECT INTENTION TO USE EVN MOBILE APPLICATION (EPOINT) AMONG GENERATION Y AND GENERATION Z IN HANOI MASTER OF BUSINESS ADMI[.]

NATIONAL ECONOMICS UNIVERSITY NEU BUSINESS SCHOOL LUU TRAN THUY ANH FACTORS AFFECT INTENTION TO USE EVN MOBILE APPLICATION (EPOINT) AMONG GENERATION Y AND GENERATION Z IN HANOI MASTER OF BUSINESS ADMINISTRATION THESIS Hanoi – 2022 NATIONAL ECONOMICS UNIVERSITY NEU BUSINESS SCHOOL LUU TRAN THUY ANH FACTORS AFFECT INTENTION TO USE EVN MOBILE APPLICATION (EPOINT) AMONG GENERATION Y AND GENERATION Z IN HANOI MASTER OF BUSINESS ADMINISTRATION THESIS SUPERVISOR: ASSOC PROF DR LE THI MY LINH Hanoi – 2022 EXECUTIVE SUMMARY According to reports by both global empirical institution like We are social and Appota, Vietnam has huge potential for mobile e-commerce economy with more than 157% mobile connection of total population as well as the e-commerce value reaching USD 847 million respectively on the two most popular platforms Google Play and Apple App Store Mobile applications have become an integral part of Vietnamese consumers' lives and bring great profits for suppliers, especially for service providers like EVN EVN is currently the largest and exclusive electricity supplier in Vietnam, having released the EVN mobile app since 2016 to provide customers with comprehensive customer care solutions This application is available on iOS and Android operating systems, as of the end of May 2021, there are more than one million customers in the South and Central regions However, in the Northern region, the number of customers using the Epoint application to pay and manage electricity consumption is still limited, specifically this number is much less than the number of customers who have used the Epoint mobile application in the South and Central regions of Vietnam Moreover, there are currently no studies on the factors affecting the intention to use the mobile application Epoint app by EVN among Vietnamese generation Z and Y in the North part of Vietnam such as the capital city Hanoi Therefore, the objective of this study is to determine the factors affecting the intention to use Epoint mobile application Especially, the study aims to focus on potential customers who belong to generation Y (who was born from 1980-1994) and generation Z (who was born from 1995 to 2012) working and living in Hanoi and have not used Epoint app yet Because according to the report by Nielsen Vietnam, by 2025, gen Y and gen Z are predicted to be the majority of labor workforce and consumers in Vietnam, accounting for more than 45% of total population The proposed research model is based on the unified theory of technology acceptance and use and perceived risk factor i Both qualitative and quantitative methods are adopted in this study The qualitative is implemented to make literature reviews on theories and findings from previous empirical research and studies on the related topics to build a profound research model and research hypotheses From previous empirical research and studies related to the acceptance of mobile application and intention to adopt mobile application, UTAUT2 and TAM are most popularly used to build the research model Based on UTAUT2 and TAM, Venkatesh et al (2012), Kim et al (2016), Linh (2018) and Hung et al (2019), flexibility, perceived usefulness, perceived ease of use, trust, social influence, hedonic motivation and perceived risk are key elements that have influence on the intention to use mobile application Therefore, this study mainly focuses on these factors to examine how they impact on generation Y and Z’s intention to adopt Epoint apps Then the quantitative method is used to find statistical evidence to confirm research hypotheses of the study An online survey is conducted to collect data for quantitative research Data were collected from 207 responses and analyzed using a regression model The research results show that the factors affecting the intention to use Epoint application in descending order: perceived risk, perceived ease of use, flexibility, hedonic motivation, perceived usefulness, social influence and trust In which, risk perception has the opposite effect and the remaining factors have the same effect From there, the study proposes some managerial implications for EVN to drive intention to use Epoint app among Vietnamese young generation ENV should improve privacy, accuracy and security for Epoint apps to decrease perceived risk of customers Besides, it is necessary to increase perceived ease of use by designing an intuitive and appropriate interface of Epoint app Increasing flexibility and hedonic motivation for users to use Epoint by constantly creating, innovating and enriching services on Epoint app to provide customers, diversify mobile applications and payment methods is also suggested for EVN to drive the mobile app adoption among young users And finally, EVN should enhance perceived usefulness, trust and social influence to drive young generation to adopt Epoint app through social media and influencer marketing in appropriate ways ii TABLE OF CONTENT EXECUTIVE SUMMARY i TABLE OF CONTENTS .iii LIST OF TABLES v LISTS OF FIGURES vi CHAPTER 1: INTRODUCTION 1.1 Rationale 1.2 Research objectives 1.3 Research questions 1.4 Research methodology 1.4.1 Research process 1.4.2 Research approach 1.4.3 Sample size and sampling method 1.4.4 Data collection 1.4.5 Data analysis 1.5 Scope of the research 10 1.6 Thesis structure 10 CHAPTER 2: LITERATURE REVIEW 11 2.1 Customer’s intention to use the service 11 2.2 Mobile application 11 2.3 Theories and frameworks on behaviors to adopt mobile technology 13 2.3.1 Theory of Reasoned Action (TRA) .13 2.3.2 Theory of planned behavior (TPB) .14 2.3.3 Technology acceptance model (TAM) 15 2.3.4 Unified theory of acceptance and use of technology (UTAUT) 17 2.3.5 Theory of perceived risk (TPR) 19 2.4 Theoretical framework 20 2.4.1 Previous research and studies 20 iii 2.4.2 Proposed research model .24 2.4.3 Measured variables in the research model 29 CHAPTER 3: RESEARCH FINDINGS AND DISCUSSION 33 3.1 Introduction on EVN 33 3.1.1 The development history of EVN .33 3.1.2 EVN’s products and services 33 3.1.3 EVN’s organizational structure 34 3.1.4 The characteristics of human resource at EVN 37 3.1.5 EVN’s business performance 40 3.2 The characteristics of sample size .41 3.3 Reliability analysis 46 3.4 Descriptive analysis 48 3.5 EFA analysis 55 3.6 Correlation and regression analysis 61 3.7 Discussion on findings 68 CHAPTER 4: RECOMMENDATIONS 75 4.1 EVN’s directions on customer service development 75 4.2 Recommendations 76 4.2.1 Improving privacy, accuracy and security for Epoint apps to decrease perceived risk of customers 76 4.2.2 Increasing perceived ease of use 78 4.2.3 Increasing flexibility and hedonic motivation for users to use Epoint 79 4.2.4 Increasing perceived usefulness, trust and social influence to drive young generation to adopt Epoint app 81 CONCLUSIONS 84 REFERENCES 85 APPENDIX 94 LIST OF TABL iv Table 2-1: Description of measured variables in the research model .30 Table 3-1: Characteristics of human resources at EVN in 2019 37 Table 3-2: Reliability test results 47 Table 3-3: Descriptive analysis of Flexibility (FT) 48 Table 3-4: Descriptive analysis of perceived usefulness (PU) .49 Table 3-5: Descriptive analysis of perceived ease of use (PE) 50 Table 3-6: Descriptive analysis of Trust (TR) .51 Table 3-7: Descriptive analysis of Social influence (SI) 52 Table 3-8: Descriptive analysis of Hedonic motivation (HM) .53 Table 3-9: Descriptive analysis of Perceived risks (PR) 53 Table 3-10: Descriptive analysis of Intention to use Epoint app (IT) 54 Table 3-11: KMO and Bartlett's Test For Independent Variables 56 Table 3-12: Total Variance Explained For Independent Variables 57 Table 3-13: Rotated Component Matrix 59 Table 3-14: KMO and Bartlett's Test For Dependent Variables 60 Table 3-15: Total Variance Explained For Dependent Variables 61 Table 3-16: Pearson correlation analysis .62 Table 3-17: Model summary 64 Table 3-18: ANOVA test results 65 Table 3-19: Regression results .67 Table 3-20: Hypothesis testing results 68 LISTS OF FIGUR v Figure 1:1: Research process Figure 2:1: TRA model by Fishbein & Ajzen (1975) 13 Figure 2:2: TPB model by Ajzen (1991) .15 Figure 2:3: TAM by Davis (1989) 16 Figure 2:4: UTAUT by Venkatesh et al (2003) 18 Figure 2:5: UTAUT by Venkatesh et al (2012) 19 Figure 2:6: Proposed research model .29 Figure 3:1: EVN organizational structure 36 Figure 3:2: Gender of participants 42 Figure 3:4: Occupation of participants 43 Figure 3:5: Education background of participants 43 Figure 3:6: Monthly income of participants 44 Figure 3:7: Payment methods for electricity bills of participants 45 Figure 3:8: Online payment methods for electricity bills .45 Figure 3:9: Number of participants who already installed Epoint apps 46 vi