Factors influencing the adoption of internet banking a case study in ho chi minh city

UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business TU THI HANH FACTORS INFLUENCING THE ADOPTION OF INTERNET BANKING: A CASE STUDY IN HO CHI MINH CITY MASTER OF BUSINESS (Honours) Ho Chi Minh City – Year 2014 UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business TU THI HANH FACTORS INFLUENCING THE ADOPTION OF INTERNET BANKING: A CASE STUDY IN HO CHI MINH CITY ID: 22110018 MASTER OF BUSINESS (Honours) SUPERVISOR: PHAM QUOC HUNG Ho Chi Minh City – Year 2014 TABLE OF CONTENTS ABSTRACT……………………………………………………………………………1 CHAPTER 1: INTRODUCTION 1.1 Background to the study 1.2 The advantages of electronic banking services 1.3 Difficulties in implementing internet banking service 1.4 Problem statement 1.4.1 Potential factors can improve the development of electronic banking services 1.4.2 The reality of electronic banking using and problem statement 1.5 Research objective 1.6 Limitation 1.7 Implication 1.8 Structure of Thesis 1.9 Summary 10 CHAPTER 2: LITERATURE REVIEW AND HYPOTHESES 11 2.1 The relevant theories 11 2.1.1 The theory of reasoned action 11 2.1.2 Theory of planned behaviour 13 2.1.3 Technology acceptance model 14 2.2 Research model and hypotheses 16 2.2.1 Perceived usefulness 16 2.2.2 Perceived ease of use and perceived behavioural control 18 2.2.3 Subjective norm and attitude 19 2.2.4 The moderating role of perceived behavioral control 20 CHAPTER 3: METHODOLOGY 22 3.1 Research Design 22 3.2 Questionnaire development 23 3.2.1 Measurement scales 23 3.2.1.1 Measurement of perceived usefulness and perceived ease of use 23 3.2.1.2 Measurement of attitude 24 3.2.1.3 Measurement of subjective norm 25 3.2.1.4 Measurement of perceived behavioural control 26 3.2.1.5 Measurement of intention to use internet banking 26 3.2.2 Building questionnaire 26 3.3 Description of the pilot study 27 3.4 The sample 28 3.5 Methods of data analysis 29 3.5.1 Reliability 29 3.5.2 Exploratory factor analysis 29 3.5.3 Regression analysis 30 3.5.3.1 The Path model 30 3.5.3.2 Simple linear regression and multiple linear regression 31 3.6 Chapter summary 32 CHAPTER 4: DATA ANALYSIS AND RESULTS 33 4.1 Descriptive analysis 33 4.2 Measure scale assessment 33 4.2.1 Reliability analysis 33 4.2.1.1 Reliability analysis for perceived usefulness 33 4.2.1.2 Reliability analysis for perceived ease of use 34 4.2.1.3 Reliability analysis for attitude 34 4.2.1.4 Reliability analysis for subjective norm 34 4.2.1.5 Reliability analysis for perceived behavioural control 35 4.2.1.6 Reliability analysis for intention to use internet banking 35 4.2.2 Exploratory factor analysis 35 4.2.2.1 Condition for exploratory factor analysis 35 4.2.2.2 Results of exploratory factor analysis 36 4.3 Testing the hypothesis 37 4.3.1 Regression Model 37 4.3.2 Regression Model 38 4.3.3 Regression Model 40 4.3.4 Regression Model 40 4.3.4.1 Solving the moderator 40 4.3.4.2 Analysis result 41 CHAPTER 5: CONCLUSION 44 5.1 Overview 44 5.2 Main findings 44 5.3 Practical implications 45 5.4 Limitations 46 REFERENCES 46 APPENDIX 48 APPENDIX 54 APPENDIX 59 APPENDIX 62 APPENDIX 64 APPENDIX 65 APPENDIX 66 APPENDIX 69 APPENDIX 74 APPENDIX 78 ABSTRACT Vietnam economy and bank system had to face many difficulties in 2011 and 2012 This challenge opens a new trend for banks Electronic banking is a modern service that banks armed to gain market and improve profit Since, many financial institutions are fostering to provide many banking services to customers via the mobile phone, computers that are connected internet Financial transactions are conducted via electronic banking have lower cost and faster speed than physical transactions However, the number of people who decide to adopt and use such technologies is still low, particularly in Ho Chi Minh City Hence, there is a need to identify relevant factors that influence the adoption and usage of Internet banking in HCMC Technology Acceptance Model (TAM) and Technology of Planed Behaviour (TPB) are two basic models to investigate the adoption and usage of Internet banking This research proposes the model that comprises five variables: Perceived usefulness, Perceived ease of use, Attitude, Subjective norm and Perceived behavioural control The results reveal that Perceived usefulness, Perceived ease to use, Attitude, Subjective norm and Perceived behavioural control have a significant association with the adoption and usage of Internet banking The research result has been a finding so that based on it, leaders of commercial banks will make an effective strategy to enhance customer satisfaction and improve operational efficiency Contributions of this study are a basis for researchers, students for developing further research to practical applications Key words: Perceived usefulness, Perceived ease of use, Attitude, Subjective norm and Perceived behavioural control, Intention to use CHAPTER 1: INTRODUCTION 1.1 Background to the Study Banks are important in every country and have a significant effect in supporting economic development through efficient financial services They provide a mechanical system to group saving and convert them into investment For over a decade, banks have been affected by changes associated with globalization and financial liberalization Reacting to these changes, banks expand the choice of services offered to the customers and increase their reliance on technology (Al-Smadi and AlWabel, 2011) Banks have been significantly affected by the evaluation of technology; competition between banks has forced them to find new market to expand, and the number of financial institutions that offer electronic banking products increased Hence, banks have begun to offer electronic banking services to improve the effectiveness of distribution channels through reducing the transaction cost and increasing the speed of services The definition of electronic banking varies among researchers, because electronic banking refers to types of services through which bank customers can request information and carry out most retail banking services via computer, television or mobile phone (Daniel, 1999) Electronic banking is referred to as using of internet as delivery mode for the provision of services like opening a deposit account, electronic bill payments, and online transfers These services can either be provided by the banks having physical offices and by creating a website and providing services through that or services can be provisioned through a virtual bank as well (Sana haider sumra, 2011) Recently, electronic banking has become the way for the development of banking system, and the role of electronic banking is increasing in many countries It offers opportunities to create services processes that demand few internal resources, and therefore, lower cost As well as it provides wider availability and possibility to reach more customers From the customers' point of view, electronic banking allows customers easier access to financial services and time saving in managing their finance (Almazari and Siam, 2008; Ayrga, 2011; Tan and Teo, 2000) Indeed, the emergence of electronic banking has prompted many banks to develop marketing and information technology strategies in order to stay competitive Venkatesh, Morris, and Davis (2003) noted that the successful implementation of information systems is dependent on the extent to which such a system is used and eventually adapted by the potential users Information system implementation is not likely to be considered successful if users are unmotivated to use that type of technology, and thus it will not bring full benefits to the organization In order to motivate customers to use electronic banking, banks must make key improvements that address the customers' concerns Although Internet banking introduces many benefits for banks and customers; customers still fear from the risk of electronic banking services Some customers feel that Internet banking services could make them lose their money Hence, there are still a large group of customers who refuse to adopt such services (Kuisma, Laukkanen, and Hiltunen, 2007; Littler and Melanthiou, 2006; Natarajan, Balasubramanian, and Manickavasagam, 2010) Without understanding what motivates the customers to use Internet banking services, banks will not be able to take actions to increase the use of such services Therefore, it is necessary to understand the key factors that influence the adoption of electronic banking among the banking customers 1.2 The Advantages of Electronic Banking Services: Electronic banking services have many benefits for both banks and customers From the customers’ point of view, Aladwani (2001), found that electronic banking provide faster, easier and more reliable services to customers Payment services through Internet banking, customers can conduct banking transactions not need go to the bank, not restricted by geographical area They can sit at home to ordering, purchase a variety of goods and services quickly Those services help customer saving time and costs For banks, Internet banking is conceded a strategy weapon; help them to achieve competitive advantage and increase their market share Furthermore, using Internet services can save the cost of resources, which are needed for traditional baking services (Jayawardhena and Foley, 2000) The number of individual customers using the internet and online payment via the internet is increasing In particular, the young customers can adaptable easily the new information technology The commercial banks also save operating costs in counting and storage of cash 1.3 Difficulties in Implementing Internet Banking Service APPENDIX 9: RESULT OF MODEL: ATT = f(PU,PEOU,SN) + Variables Entered/Removedb Variables Model Variables Entered SN, PEOU, PUa Removed Method Enter a All requested variables entered b Dependent Variable: ATT Model Summary Std Error of the Model R R Square 610a Adjusted R Square 372 Estimate 364 78568 a Predictors: (Constant), SN, PEOU, PU ANOVAb Model Sum of Squares Regression df Mean Square 85.061 28.354 Residual 143.830 233 617 Total 228.891 236 F 45.932 Sig .000a a Predictors: (Constant), SN, PEOU, PU b Dependent Variable: ATT 78 Coefficientsa Standardized Unstandardized Coefficients Model B (Constant) Coefficients Std Error -.010 281 PU 374 063 PEOU 356 SN 313 Beta Collinearity Statistics t Sig Tolerance VIF -.034 973 324 5.939 000 905 1.106 070 273 5.062 000 927 1.079 064 271 4.886 000 878 1.139 a Dependent Variable: ATT 79 80 81 RESULT OF MODEL: PU, PEOU -> PBC Variables Entered/Removedb Model Variables Entered Variables Removed PEOU, PUa Method Enter a All requested variables entered b Dependent Variable: PBC Model Summary Std Error of the Model R R Square 433a 188 Adjusted R Square 181 Estimate 74526 a Predictors: (Constant), PEOU, PU 82 ANOVAb Model Sum of Squares Regression df Mean Square 30.060 15.030 Residual 129.966 234 555 Total 160.026 236 F Sig .000a 27.061 Coefficientsa Standardiz ed Unstandardized Coefficient Collinearity Coefficients s Statistics Std Model B (Consta Error 1.144 242 PU 323 058 PEOU 241 065 nt) Beta t Sig Tolerance VIF 4.728 000 335 5.603 000 968 1.033 221 3.692 000 968 1.033 a Dependent Variable: PBC 83 RESULT OF MODEL: ATT -> IT Variables Entered/Removedb Model Variables Variables Entered Removed ATTa Method Enter a All requested variables entered b Dependent Variable: IT Model Summaryb Model R R Square 420a Adjusted R Std Error of the R Square Square Estimate Change 177 173 79995 Durbin-Watson 177 1.851 a Predictors: (Constant), ATT b Dependent Variable: IT ANOVAb Model Sum of Squares Regression df Mean Square 32.243 32.243 Residual 150.381 235 640 Total 182.624 236 F 50.387 Sig .000a a Predictors: (Constant), ATT b Dependent Variable: IT 84 Coefficientsa Model B (Constant) ATT Std Error 2.224 176 375 053 Beta 420 t Sig 12.624 000 7.098 000 a Dependent Variable: IT 85 86 RESULT OF MODEL: ATT*PBC -> IT Variables Entered/Removedb Model Variables Variables Entered Removed NEW, ATTa Method Enter a All requested variables entered b Dependent Variable: IT Model Summaryb Model R R Square 423a Adjusted R Std Error of the Square Estimate 179 172 80065 a Predictors: (Constant), NEW, ATT b Dependent Variable: IT ANOVAb Model Sum of Squares Regression df Mean Square 32.621 16.310 Residual 150.003 234 641 Total 182.624 236 F 25.444 Sig .000a a Predictors: (Constant), NEW, ATT 87 ANOVAb Model Sum of Squares Regression df Mean Square F 32.621 16.310 Residual 150.003 234 641 Total 182.624 236 Sig 25.444 000a b Dependent Variable: IT Coefficientsa Standardized Unstandardized Coefficients Model B (Constant) Std Error 2.219 176 ATT 373 053 NEW 044 057 Coefficients Beta Collinearity Statistics t Sig Tolerance VIF 12.576 000 418 7.046 000 998 1.002 046 767 444 998 1.002 a Dependent Variable: IT 88 89 90 91 92 ...UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business TU THI HANH FACTORS INFLUENCING THE ADOPTION OF INTERNET BANKING: A CASE STUDY IN HO CHI MINH CITY ID:... study is to investigate and validate the factors influencing the adoption and usage of Internet banking in Ho Chi Minh City, Vietnam The study will investigate these factors by using two different... So, the result of research just can undertake in the Ho Chi Minh City market The research will assess only in the adaption and usage of Internet banking The other factors such as the priority in