Thai Nguyen University Socialist Republic of Vietnam Southern Luzon State University Republic of the Philippines DOCTORAL DESSERTATION (ABSTRACT) FACTORS AFFECTING THE USE OF MOBILE BANKING SERVICES IN HANOI, VIETNAM In Partial Fulfillment of The Requirements for The Degree of Doctor in Business Administration Full Name: Vu Manh Cuong English Name: Cameron Adviser Dr Nelly Mendoza (Southern Luzon State University) HANOI, 2013   Chapter I INTRODUCTION Mobile banking services have become the objective and inevitable trend during the international economic integration more and more deeper in Vietnam The development of mobile banking services has brought significant benefits to customers as a convenient, fast and accurate of the transaction At the same time it also opens up new development opportunities for the telecommunications providers, application and software developers, e-commerce merchants and bankers in Vietnam Vietnam has more than 86 million population (GSO, 2012), 120.7 million mobile subscribers, 15.5 million fixed subscribers, over 31% rate of people use the Internet regularly, 30.2 million mobile users and (MIC, 2012), 44 bankers with hightech infrastructure (SBV, 2013), and more then 400 Value added services providers (MIC, 2013) It should be a great potential market 1.1 Background of the study The study of consumer behavior is an important part of the research needs of customers To succeed in any business at all the fields, especially in fast-growing and dynamic markets as today's, entrepreneurs, marketers need to know clearly about customers such as the needs, convenience, the difficulty, suitable time, etc Numerous theoretical models have been launched and continuous improvement Most notably, Theory of Reasoned Action Models introduced Ajzen & Fishbein (1975), often referred to TRA model, and then extended into TPB model (Ajzen, 1991) Davis (1989) has applied this theory to build the Technology Acceptance Model (TAM), and then Venkatesh and Davis (2000) has built Technology Acceptance Model (TAM2) Thousands of studies have applied TAM model to explain the behavior of using integrated technology services on many different areas in many countries around the world In the technology service sector in general and mobile banking services in particular, the choice and use by customer is also comply the basic principles of psychology and behavior, but specific expression of consume behavior in these situations, conditions and environment are totally different This has made the line of research on consumer behavior continues incessantly   In recent years, mobile banking has attracted particular and get the attention of researchers, managers There are a lot of research in the world were conducted, but, in-depth studies of this field in Vietnam were very rare So far there is no research about the use of mobile banking services in Hanoi specifically and Vietnam overall Stemming from such pressing issues, this study was conducted to explore the factors influence the use of mobile banking services of customers in Hanoi The dissertation contributes to propose the policy to develop this services in the near future 1.2 Statement of the objectives - Determine the relationships of the demographic characteristics (age, gender, occupation, income and educational attainment) of the respondents and the use of mobile banking services; - Determine the differences in the purpose of the use of mobile banking services by customers in Hanoi by gender, age, education, occupation and income; - Determine the factors affecting the use of mobile banking services by consumers in Hanoi; - Analyze the level level of influence of the different factors to the use of mobile banking services in Hanoi; and - Propose solutions to improve mobile banking services to increase the number of users in Hanoi, Vietnam 1.3 Hypothesis H1: The use of mobile banking services are affected by the geographical location and demographic characteristics such as age, gender, education, area, occupation and income H2 Perceived usefulness of mobile banking services has a positive impact on the use of the services H3: Perceived of ease of use of mobile banking services has a positive impact to the use of the services H4: Perceived costs to use mobile banking services have a negative impact to use the service   H5: The trust of customers on mobile banking services has a positive impact to the use of the services H6: Perceived risks of customers for mobile banking services have a negative impact to the use of the services 1.4 Significance of the study Regarding scientific, dissertation contributed (i) reviewing the basis of the theory of consumer behavior generally and Theory of Technology Acceptance Model (TAM) in particular; (ii) providing the research model of consumer's behavior in the use of mobile banking services in Hanoi Regarding practice, dissertation contributed (i) to enrich the practical research in the field using mobile banking services in Vietnam generally and Hanoi in particular; (ii) to outline a comprehensive picture of the use of mobile banking services in Hanoi And then identify the major factors affecting the use of the services of customer in the studied area; (iii) to suggest the main recommendations of the policy for the mobile banking service providers in Hanoi, practical contribution to improving mobile banking services in Vietnam; (iv) to provide a good reference material for managers, service providers, researchers and practitioners in the management agencies, universities of Vietnam and International 1.5 Scope and Limitations The research will be conducted within Hanoi Capital The respondents were living in Hanoi and using mobile banking services (included SMS banking and Internet banking) The survey was conducted in districts: Hoan Kiem, Ba Dinh, Hai Ba Trung, Dong Da, Cau Giay, Tay Ho, Thanh Xuan, Hoang Mai, and Long Bien   Chapter II REVIEW OF RELATED LITERATURE AND STUDIES 2.1 Banks in Vietnam According to State Bank of Vietnam (SBV), at the end of 2012 in Vietnam, there are total 44 banks (excluding Vietnam Development Bank, Vietnam Bank for Social Policies, Joint-­‐venture Bank, Branches of Foreign Bank, Rep Office of Foreign Banks), including Stated owned Banks (Agribank, BIDV, Vietinbank, Vietcombank, and Mekong Housing Bank); 34 Commercial Banks (such as: ACB, Eximbank, Techcombank, MBBank, Maritime, etc.); and wholly Foreign-owned banks (HSBC, Standard Chartered, ANZ, Hong Leong, Shinhan) 2.2 Mobile Banking Services The rapid growing of mobile service in Asia has created opportunities for new and innovative mobile services The most promising is Mobile finance service including mobile banking, mobile payment and mobile commerce services Mobile banking allow end-users to get bank information via SMS such as balances, transaction history, promotion information, confirmation for direct payment (Niina M, Matti R, Virpi K.T, 2004) The cost is saved average 19% when using the mobile banking service (McKay, Claudia and Mark Pickens, 2010) The number of mobile banking users worldwide is forecasted to grow from 55 million in 2009 to 894 million in 2015, at a compound annual growth rate of 59% (Ann H., 2010) Juniper estimate the number of mobile subscribers who use mobile banking will exceed 400 million globally by 2013 Mobile banking can perform account balances and transaction history inquiries, funds transfers, and bill payments via mobile devices (Laukkanen, 2007; Turban, King, Viehland, & Lee, 2006) 2.3 Mobile Financial Services Mobile Financial Services where telecom and banking converge, using the mobile device for formal financial services, Immediate, simple and convenient access to money-related transactions Using for shopping online, pay for education, save money, buy insurances, pay bills, receive and payoff loans, buy tickets, pay for   parking, transfer airtime, purchase goods, receive salary, pay for transportation, send money home, etc (Jorge Campos, 2011) According to Niina et al., the key players of mobile financial services includes banks and other financial organizations, the telecom operators, retailers, equipment manufacturers (hand-set devices), and software vendors that enabling the services are incremental in building the infrastructure progress 2.4 Mobile Commerce Services Mobile Commerce (m-commerce) is defined as a business transaction conducted through mobile communication networks or the Internet (Siau & Shen, 2003) M-commerce can offer value to consumers through convenience and flexibility by enabling time and place independence (Kim et al., 2009; Venkatesh et al., 2003) There are challenges associated with m-commerce, and specifically mobile banking Mobile devices with a small screen size, limited screen resolution and uncooperative keypad may make it difficult for the customer (Kim et al., 2009) 2.5 Mobile banking technology Currently, mobile banking is implemented through three different technology solutions: browser-based applications, messaging-based applications and client-based applications (Kim et al., 2009; Tiwari & Buse, 2007) The browser-based application is essentially a Wireless Access Protocol (WAP)-based internet access (Kim et al., 2009) This requires a compatible mobile phone which is WAP-enabled The mobile phone is used to access banking portals through the Internet Based on assessment of mobile banking is a full-potential field in the world, many technology teams was focused in research and development of technology solutions for this type of service The solutions are continuously improved in line with the rapid development of mobile, especially the rapid growth of smartphone 2.6 Mobile Banking in Vietnam Mobile banking has been introduced in Vietnam quite late compare to other countries in the region Four commercial banks only have actually introduced in 2011   The mobile banking functions are focusing account inquire, money transactions, payment for bills and online According to while paper on Information & Communication Technology 2012 (MIC, 2013), by August 2012, Vietnam has 25.79 million smart phone subscribers, contribute to 21% of total mobile phone subscribers and representing an increase 27% compared to the end This is quite good for the development of mobile application in general and mobile banking in particular With the interest of bankers, service providers, mobile operators, merchants and combined the rapid development of technology environments including core banking, e-commerce, mobile infrastructure, and smart phone, mobile banking is a potential market in Vietnam 2.7 Consumer Behavior The consumer behavior is a research tries to understand the decision-making processes of buyers, both individually and in-group, including: problem recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior It studies characteristics of individual consumers such as demographics and behavioral variables in discovering the people's wants It also tries to assess influences on the consumer from related groups such as family, friends, and society According to Kotler and Armstrong (1996), the factors affecting the consumer behavior are cultural, social, personal, and psychological The theories and models are most commonly applied in the study and explanation of consumer behavior since the second half of the twentieth century are theories of attitude and behavior, such as Expectancy-Value Theories (Tolman, 1932; Rotter, 1954; Atkinson, 1957), Theory of Reasoned Action (Ajzen & Fishbein, 1980), Theory of Planned Behavior (Ajzen & Driver, 1992) 2.8 Expectancy-Value Theory Expectancy Value Theory (EVT) was presented by Tolman (1932), Rotter (1954) and Atkinson (1957) According to Fishbein & Ajzen (1975), people learn "expectations," i.e., briefs that a given response will be followed by some events Since these "events" could be either positive or negative "reinforcers" (i.e., could have   positive or negative valence), his argument, essentially, was that people would learn to perform (or increase their probability of performing) behavior that they "expected" to lead to positively valence events (Tolman, 1932) In the late 1970s Fishbein and Ajzen expanded expectancy-value theory into the theory of reasoned action (TRA) 2.9 The Theory of Reasoned Action The theory of reasoned action (TRA) developed by Fishbein & Ajzen (1969, 1980) This model defines the links between beliefs, attitudes, norms, intentions, and individuals behaviors The person’s behavior is determined by its behavioral intention to perform it The intention is itself determined by the person’s attitudes and his subjective norms towards the behavior TRA also claims that all other factors influence the behavior only so in an indirect way by influencing the attitude or subjective norms Fishbein & Ajzen (1975) refer to these factors as external variables 2.10 The Theory of Planned Behavior Theory of Planned Behavior (TPB) was developed from TRA (Venkatesh et al, 2003) with the aim to improve the predictive power by adding a major predictor, perceived behavioral control, to the model It is one of the most predictive persuasion theories It has been applied to studies of the relations among beliefs, attitudes, behavioral intentions and behaviors in various fields such as advertising, public relations, advertising campaigns and healthcare TPB is good in explaining individual acceptance and usage of many different technologies (Harrison et al., 1997; Mathieson, 1991; Taylor and Todd, 1995) However, Taylor and Todd (2001) reported that it did not provide a complete explanation of usage intention as compared TAM (Faziharudean & Tan, 2011) According to Gregory (2011) both TRA and TPB models have been widely used to evaluate a range of consumer behaviors 2.11 Technology Acceptance Model The Technology Acceptance Model (TAM) introduced by Davis (1989) TAM has been continuously studied and extended to TAM2 by Venkatesh & Davis (2000) and the Unified Theory of Acceptance and Use of Technology (UTAUT) by Venkatesh et al (2003) TAM3 has also proposed by Venkatesh & Bala (2008)   TAM suggests that perceived usefulness and perceived ease of use are the two most important factors in explaining individual users’ adoption intentions and actual usage (Davis, 1989) TAM has been extensively tested and validated and is a widely accepted model, which can be modified or extended using other theories or constructs (Taylor & Todd, 1995; Davis & Venkatesh, 2000; Wu & Wang, 2005; Luarn & Lin, 2005; Zhang, Gou & Cheng, 2008) Venkatesh and Davis (2000) introduced such social and organizational factors as subjective norms, impression, quality of output and work relevance into the TAM model and proposed TAM2 Luarn & Lin (2005) conducted a study with perceived usefulness, perceived ease of use, perceived credibility, self-efficacy, and perceived financial cost Lee (2009) investigated the factors influencing the adoption of Internet banking with five antecedents of perceived risk were discussed: performance risk, social risk, financial risk, time risk and security risk Perceived cost is defined as the extent to which a person believes that using mobile banking will cost money (Luarn & Lin 2005) Kim et al (2009) defined the trust as a psychological expectation The trust was defined as a feeling of security and willingness (Kim, Chung & Lee, 2010) 2.12 The conceptual framework Perceived usefulness H2 The use of Perceived ease of use Perceived Cost Trust Perceived Risk H3 H4 H5 mobile banking services H1 Demographic Characteristics (age, gender, education, area, occupation, income) H6   Chapter III RESEARCH METHODOLOGY 3.1 Research design To achieve the proposed objectives, the research process was organized into two steps including qualitative research and quantitative research The entire research process is summarized in following figure Theoretical framework and research model (theories of psychology and consumer behavior, model TRA, TPB and TAM) Study materials and questionnaire development Pilot Study (N=50) Completing the questionnaire Theoretical model Orientation Questionnaire Formal Questionnaire Fieldwork and integrated analysis Formal Study (N = 800) Descriptive Statistical Analysis Exploratory Factor Analysis (EFA) Regression Model Analysis 3.1.1 Pilot study A pilot study was conducted by interviewing 50 customers in Hanoi who are using mobile banking services to explore preliminarily the main characteristics of the use of mobile banking services The pilot study was a basis to design the survey questionnaire for the next quantitative study 3.1.2 Variable measurement There are five independent variables, specifically, "perceived usefulness", "perceived ease of use", "perceived cost", perceived risk" and "trust of service" Each   independent variable measured by three to ten questions related mobile banking services A total of 27 questions were conducted to five aspects of the use of mobile banking services The dependent variable was designed with three questions to measure the use of mobile banking services in Hanoi A five-point Likert scale was applied to measure the responses of the survey 3.2 Determination of Sample size Total population of Hanoi is 6,451,909, in which 69.1% are aged between 15 and 64 (GSO, 2010) equal to 4,458,269 According to the stratified random sampling method use Slovin’s formula with the error level at 5% showed the sample size is 400 as following formula: n= N 4,458,269 = = 399, 96 ≈ 400 1+ 4,458,269 * (0, 05)2 + Ne However, Hanoi is a big city, the second biggest city in Vietnam, thus to enhance practical significance as well as to ensure the reliability of data analysis, Authors have collected data from 800 respondents 3.3 Sampling design and techniques The samples were conducted by the method of convenience sampling surveys, but the adjustment on the surveying area and gender to ensure the sample is spread evenly over the studied region The survey was conducted in districts including: Hoan Kiem, Ba Dinh, Hai Ba Trung, Dong Da, Cau Giay, Tay Ho, Thanh Xuan, Hoang Mai, and Long Bien The number of sample was allocated as following table 3.4 Research Instrument The measurement tools used Likert scale introduced by Rennis Likert Questionnaire was used to collect primary data using five-point Likert scales The questionnaire was designed with two parts: (i) the questions related to respondents' demographic characteristics to classify the group of consumers such as living area, gender, age, occupation, income and education; (ii) the questions related to measuring the influence and dimension of factors affecting the use of mobile banking services in Hanoi 10   The results of the reliability analysis of scale showed that Alpha coefficients of all components are greater than 0.8, ranged from 0.8311 to 0.8807 The values of the corrected Item - Total Correlation of variables ranged from 0.4489 to 0.8320, greater than 0.3 That indicated the reliability of scale was satisfied 3.5 Data gathering procedure The study used both primary and secondary data to identify the factors affecting consumer behavior on the use of mobile banking service in Vietnam The primary data was used to assess the influence and level of the factors The secondary data was used to analyze the demographic characteristics of respondents, features and functions of the service model, current status and market potential of the services, the ability to meet the suppliers in the value chain of mobile banking services, and the aspects related to the research 3.5 Data processing method The collected information should be checked and revised by the review process to avoid errors and inconsistencies Then all the collected information is encrypted answers and entered data into the computer Authors used Microsoft Excel 2003 software for entering the survey data and processing of raw materials After the first phase of the basic data cleaning, data was imported into SPSS 16.0 software for filtering in second phase, and then create statistical tables and conduct the 3.6 Statistical treatment The dissertation used Cronbach's Alpha to analyze the reliability of scale, exploratory factor analysis to extract the factors, and regression analysis to analyze and test the hypothesis and factors affecting the use of mobile banking services in Hanoi ANOVA analysis was used to determine the difference between the demographic characteristics and the use of mobile banking services in Hanoi 11   Chapter IV RESULTS AND DISCUSSION 4.1 Profile of the respondents 4.1.1 Demographic characteristics The study surveyed 800 respondents in districts of Hanoi, there are 717 responses are useable for data analysis The profile of the respondents as follows Demographic Characteristics Living area Suburban Center Gender Female Male Age Less than 25 From 25 to 35 From 35 to 45 From 45 to 55 Over 55 Education Secondary High School College University Graduated Occupation Business or Self-Employed Officer or state area Un-employer Pupil or Student Housewife Retirement Income Less than Million From to 10 Million From 10 to 15 Million From 15 to 20 Million Over 20 Frequency Percent Valid Percent Cumulative Percent 208 509 29.0 71.0 29.0 71.0 29.0 100.0 373 344 52.0 48.0 52.0 48.0 52.0 100.0 255 291 116 28 27 35.6 40.6 16.2 3.9 3.8 35.6 40.6 16.2 3.9 3.8 35.6 76.2 92.3 96.2 100.0 22 63 35 526 69 3.1 8.8 4.9 73.4 9.6 3.1 8.8 4.9 73.6 9.7 3.1 11.9 16.8 90.3 100.0 244 276 30 124 16 27 34.0 38.5 4.2 17.3 2.2 3.8 34.0 38.5 4.2 17.3 2.2 3.8 34.0 72.5 76.7 94.0 96.2 100.0 192 246 96 36 37 26.8 34.3 13.4 5.0 5.2 31.6 40.5 15.8 5.9 6.1 31.6 72.2 88.0 93.9 100.0 12   4.1.2 The use of banking services Most of the customers surveyed have at least a bank account with a rate of 84.2% The customers not have the bank account is only 15.8% However, the transactions in the bank is much less convenient The results showed that 78.4% of customers took less than 15 minutes to the nearest branch of bank, while 19% from 15 to 45 minutes The rate of customer to the nearest branch over 45 minutes is only small percentage, with 2.6% This is entirely consistent with a city like Hanoi, the branch of banks has grown rapidly in recent times The percentage of customers who have not used the service but intend to use if it is convenient and safe, is quite high, with 44.6% The results showed that 46% of consumers have used mobile banking services There are only 9.3% of customers are not interested in using the service 4.2 Purpose of use mobile banking services The results showed that purpose of customers are very different including checking bank account, transfer money, pay for purchases or pay for monthly bills such as electricity, telephone, TV cable, etc Up to 448 customers equal to 77.5% use the service to check account at the bank, 346 people (59.9%) to transfer money; the purchase and monthly bills accounted respectively 257 and 221 customers, equal to 44.5% and 38.2%; the purpose of the savings is 34.6% Female use the services for the purpose of checking accounted 52% higher than male (48%) Regarding the purpose of transferring money, female accounted 45.7% and 54.3% of male The purpose of savings deposits female is higher than men, the rate respectively 53.5% and 46.5% Customers with high education level accounted the rate higher than others, such as purpose of checking account up to 88.3%, transfer money is 81.7%, pay for monthly bills is 53.3% compared with lowest ratio of others respectively is 33.3% (secondary), 34.3% (high school) and 22.2% (college) The highest income group accounted 91.7% compare with 57.5% of group has income between to 10 million The purpose of pay for monthly billd accounted 36.0% to 52.8% except 21.4% ratio of group with income from 15 to 20 million 4.3 Analysing the differences in the use of mobile banking services 4.3.1 The difference by living area To analyse the difference of the trust of customers in the use the services, research conducted analysis of variance The results showed the Levene Statistic has statistical significance levels by 0.001 (Sig.=.001) and Anova Sig.= 0.035 It can be concluded that there is no difference by living area in the use of the services 13   4.3.2 The difference by gender Results of variance analysis showed that Levene Statistic has significant level is 0.020 (Sig =0.020), the variance of customer's trust for mobile banking services between male and female is different at 5% It allowed to conclude there were not sufficient basic to confirm a difference by gender in the use of the services 4.3.3 The difference by age The results of analysis of variance showed Levene Statistic indicators are significant level of 0.425 (Sig.=.425), Sig value of 838 by ANOVA (Sig = 838) This allows the conclusion that was not enough basis to evaluate the difference between the group of age in the use of mobile banking services 4.3.4 The difference by education The results of analysis of variance showed Levene Statistic indicators are significant level of 0.106 (Sig.=.106), Sig value of 334 by ANOVA (Sig = 334) This allowed to conclude that was not enough basis to evaluate the difference between the level of education in the use of mobile banking services 4.3.5 The difference by occupation The results of analysis of variance showed Levene Statistic indicators are significant level of 0.644 (Sig.=.644), Sig value of 440 by ANOVA (Sig = 440) This allows the conclusion that was not enough basis to evaluate the difference between the type of occupation in the use of mobile banking services 4.3.6 The difference by income The results of analysis of variance showed Levene Statistic indicators are significant level of 0.261 (Sig.=.261), Sig value of 0.937 by ANOVA (Sig = 937) This allowed to conclude that was not enough basis to evaluate the difference between the level of income in the use mobile banking services 4.4 Exploratory Factor Analysis Exploratory Factor Analysis (EFA) is used to extract the factors This study used Principal component method with Variamax rotation stops when value in the eigenvalue ≥ According to Hair et al (1998), Factor loading is the norm to ensure 14   the practical significance of EFA Factor loading > 0.3 are considered to achieve the minimum level, Factor loading > 0.4 are considered important, > 0.5 are considered to have practical significance The results of exploratory factor analysis are presented in following table Variable Component RISKSE1 765 RISKSE2 722 RISKSE3 715 RISKSO1 672 RISKSO2 653 RISKTI1 511 RISKTI2 504 TRUST4 764 TRUST5 761 TRUST6 725 TRUST3 697 TRUST2 668 TRUST1 634 USEFUL2 893 USEFUL1 874 USEFUL3 840 USEFUL4 516 COSTPE1 COSTPE3 COSTPE2 EASE1 EASE3 EASE2 RISKFIN2 RISKPE2 RISKPE1 RISKFIN1 Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity 853 843 794 Approx Chi-Square df Sig .813 794 665 811 714 606 866 10476.605 351 000 Analysis of 27 observed variables combined, the result is extracted factors Analysis results showed coefficient KMO = 0.866 at significant level of Sig = 0.000 Thus the hypothesis of the overall correlation matrix is the homogenous matrix is rejected, i.e the variables are correlated with each other and satisfy the conditions in the factor analysis The analytical results have been extracted factors with the factor loading coefficients are higher than selected standards (≥ 0.5) 15   4.5 Correlation analysis The correlation analysis showed that most of these variables are strongly correlated and statistically significant at the 1% (Sig.2-tailed = 000) for variable TRUOVER except variable COSTPE USEFUL EASILY USEFUL Pearson 001 000 1.000 1.000 983 1.000 000 000 -.001 000 1.000 1.000 974 1.000 000 000 002 000 1.000 1.000 961 1.000 Pearson Correlation 001 -.001 002 001 000 -.136(**) Sig (2-tailed) 983 974 961 982 998 000 000 000 000 001 000 010 1.000 1.000 1.000 982 1.000 782 000 000 000 000 000 1.000 1.000 1.000 998 1.000 Pearson Correlation Pearson Correlation Sig (2-tailed) COSTPE Pearson Correlation Sig (2-tailed) TRUST TRUST TRUOVER 000 Sig (2-tailed) RISK2 COSTPE 000 Sig (2-tailed) RISK1 RISK2 Correlation EASILY RISK1 Pearson Correlation Sig (2-tailed) TRUOVER Pearson Correlation Sig (2-tailed) 262(**) 304(**) -.164(**) -.136(**) 000 000 000 000 000 262(**) 1.000 000 000 304(**) 1.000 000 000 -.164(**) 1.000 000 360(**) 000 010 360(**) 782 000 ** Correlation is significant at level of 0.01 (2-tailed) 4.6 Regression analysis 4.6.1 Regression model The R2 Adjusted coefficient shows the data explained 33.1% of the impact of independent variables on the dependent variable, the statistic F = 71.832 at significance level 0.000 with the assumption of multiple regression were satisfied In particular, most of the explanatory variables have expected sign as predicted and statistically significant at the 1% level, except the factor COSTPE has the 16   phenomenon of multi-collinearity With the analysis results above, the regression model is written as follows: TRUOVER = 262 USEFUL + 304 EASILY - 163 ISK1 - 136 RISK2 + 360 TRUST The regression models showed the variables marked as expected The factor USEFUL is the third impact among analysis variables, EASILY have been positively impact, RISK1 has the opposite impact, RISK2 marked as expected - negative sign, TRUST has a positive impact In factor were analysed, there are factors are actually influence to the use of mobile banking service including: Perceived usefulness of the service (USEFUL), Perceived ease of use of the service (EASILY), Perceived risk of social and safety (RISK1), Perceived risk of performance and finance (RISK2), Trust on the service (TRUST) 4.6.2 Tesing the assumptions of the regression model v Testing the assumption of a linear regression model of constant variance: The chart of standardized residuals and predicted values residuals showed random residual dispersion in the surrounding area of the original release It allowed to conclude that the assumption of a linear regression model of constant variance is satisfied v Testing the error variance in the model: The results of the test Spearman showed that assumptions about the correlation of the overall is zero is rejected This allows the conclusion that the research model variance of the error does not change v Testing the standardized distribution of residuals: From chart of residual distribution shows the average value of residuals is (Mean=0.00) and histogram of standardized residuals follow near the standardized distribution This allows conclude that the standardized distribution assumption of the regression model was not violated v Testing the independence of the error in the model: The value DurbinWatson shows D = 1.978, the value D in the acceptable range: 1< D