INTERNET BANKING USING INTENTION: A MODEL MODIFICATION BASED ON QUALITY AND RISK CHARACTERISTICS Mujilan

  Airlangga Accounting International Conference & Doctoral Colloquium 2012

   

  

INTERNET BANKING USING INTENTION: A MODEL MODIFICATION BASED ON

QUALITY AND RISK CHARACTERISTICS

Mujilan

¹

  and

  Sumiyana ² Abstract

  This study modifies the Internet Banking (IB) Using Intention Model based on quality and risk. This study also gives the alternative model by dimension modification especially in the quality. The result of this study indicates the two types of quality impact to the intention. If we apply 11 dimensions of quality, there is a strong direct effect of the IB service quality to the intention. But if we apply the general perception of quality, the effect of IB service quality to the intention will be indirect via the mediating of user satisfactions. Risk has a low negative impact to the intention if the users recognize the IB service quality and satisfy which the services. It means that quality and satisfaction plays an important role to reduce perceived risk and build intention in the internet banking context. This modified model can be used to explain the characteristics of users in their perception of internet banking.

  

Keywords:internet banking, service quality, perceived risk, user

  satisfaction, intention to use, internet users, quality dimensions, general perceived quality.

  INTRODUCTION

  The internet banking using has grown as a consequence of internet and technology growth in the world. The success model of internet banking (IB) had the own characteristics that difference in some way from others technology success models like web portals or e-commerce (Bauer et al., 2005). Consequently, there is a need to develop an internet banking success model to explain the IB characteristics.

  Researchers still focused on internet banking quality (eq. Bauer et al., 2005; Ma et al., 2011) and some studies focused on internet banking risk (eq. Wong et al., 2009; Aslam et al., 2011). In their studied, Ma et al. (2011) suggested that the internet banking service quality should be extended to how user’s perception of internet banking service quality affected the satisfaction and intention behavioral. This study modifies the internet banking model to extend Ma’s internet banking service quality and to integrate which                                                              ₁ Mujilan is an education staff in Accounting Department, Faculty of Economics, Widya Mandala

  Madiun University; email: agus_muji@yahoo.com ₂ Sumiyana is accounting professor in Faculty of Economics and Business, Gadjah Mada University, Yogyakarta; email: sumiyana@ugm.ac.id Airlangga Accounting International Conference & Doctoral Colloquium 2012

    DeLone & McLean technology success model validated by Wang (2008). We also investigate perceived risk on using internet banking (Aslam et al., 2011) to complete the internet banking model.

  To modify the model, we approach from the human’s rational judgment in the decision making process. Two basic factors are considered as cost and benefit. Consequently, the model will include this two factors called internet banking quality and risk. Operationally, we use Internet Banking Service Quality (Ma et al. 2011) and Perceived Risk (Aslam et al., 2011). The SEM by Amos 18 is applied to test the model.

  This study focuses on integrating four factors to modify the model. The factors are quality, satisfaction, risk, and intention. The path directions are investigated and explained. We collect instrument to measure this four factors from some literatures and simplify the item numbers to reduce the response bias. We hope this study will contribute to the information system literature by support the intention of using internet banking model and understanding of how the effect direction of each factors. Also, we hope to give the simplified instrument related to the model.

  This study is a general view of the internet banking model. A specific characteristic (eq. respondents, IB providers) may need in the future study. The context of this study is individual perception (not a company) and be done in the developing country. This study has assumptions, first, the respondents use rational consideration in decision making to use internet banking. Second, individuals use their IB to operate their saving account.

  

Third, this IB is used in developing country or in the early phase of internet using

  (Gounaris and Dimitriadis, 2003). Forth, the distance from the user’s home to the conventional banking office doesn’t affect the decision in using IB.

  LITERATURE REVIEW Internet Banking Service Quality

  Service quality is become the great differentiator, the most powerful competitive weapon most service organization possess (Berry et al., 1988; Jayawardhena, 2004). Quality from customer’s view is conformance to specification (Berry et al., 1988). The customer’s retention and interest is very depended on services quality delivered (Hamadi, 2010).

  Quality has been viewed by Garvin (1987) as a product quality. In the information systems there was service quality (SERVQUAL) which five dimensions (Parasuraman et al., 1991; Kettiger & Lee, 1997). The context of service quality was used by Gounaris & Dimitriadis (2003) to evaluate web-portal. Bauer et al. (2005) viewed quality in the context Airlangga Accounting International Conference & Doctoral Colloquium 2012

    of e-banking. Jayawardhena (2004) studied in internet banking quality measurement. Yaya et al. (2011) used E-S-QUAL (modification from SERVQUAL by Parasuraman et al., 2005) to evaluate online banking.

  Ma et al. (2011) tried to identify the internet banking quality dimensions from former literatures. They used 11 quality dimensions. They applied the dimensions as variables in the regression. The dimensions were: reliability, convenience, efficiency, comfort,

  

serviceability, security, privacy, assurance, reputation, product differentiation and

customization, and customer service.

  Reliability: if it delivers the services as it’s promised (Ma et al., 2011). Reliability is

  the ability to perform the desired service dependably, accurately, and consistently (Berry et al., 1988; Parasuraman et al., 1985; McKinney et al., 2002; Kenova & Jonasson, 2006).

  

Convenience: if it enables customers to access banking at all times and places (Ma et

  al., 2011). Wolfinbarger & Gilly (2001) used convenience in the context of saving time and effort, including physical and mental effort.

  Efficiency: Ma et al. (2011) used efficiency in the context of speed download and

  response time. Efficiency also be used as the site is simple to use, structured properly, requires minimum of information to be input by the customer (Kenova & Jonasson, 2006; Parasuraman et al., 2005). Then, efficiency is described as ease and speed of accessing and using the site (Parasuraman et al., 2005). Comfort: Hong et al. (2011) referred to psychology that comfort was a feeling at ease. Operationally, the comfort if the user feel comfort with the change in upgrade system. Ma et al. (2011) used this context to cap that the user comfort with internet banking.

  Serviceability: is innovation ability to confirm the users need (Ma et al., 2011).

  Garvin (1987) defined serviceability as speed, courtesy, competence, and easy of repair.

  

Security: is defined as financial security, refer to the fact that user has perception if their

bank information is secure and no one else can access their account (Hamadi, 2010).

Privacy: is the user level perceptions that their personal information is protected (Hamadi,

  2010). In other word privacy is the state level if the site safe and protecting the user information (Parasuraman et al., 2005). Privacy is related to the secure of private and secret information (Ma et al., 2011).

  Assurance: can be understood as the employee knowledge, courteous, and the

  ability to make users feel confidence (Kettinger & Lee, 1997). It can be related to the clearance and trustfully of the information (Kenova & Jonasson, 2006). Reputation: Ma et al. (2011) took a marketing context that reputation was associated which brand equity, or organization credibility. This reputation was resulted by a long history of organization

  Airlangga Accounting International Conference & Doctoral Colloquium 2012

    relations in their function. Credibility was obtained from trustworthiness, believability, and honesty (Parasuraman et al., 1985).

  Product differentiation and customization: Ma et al. (2011) used it as the

  adoption of website to the better setting according to individual user requirements. Swaid & Wigant (2009) used it as a user perception of the individualized attention and differentiated services that were tailored to meet individual’s need and preferences. Cruz & Gallego (2004) said that the personalization systems could be categorized as customization (user personalization) and based on user profile (adaptive and proactive configuration). Customer services: The online customer service may hide from users. This will be a relation to the emotion and feeling of the users because no human interaction. Parasuraman et al. (2005) used contact dimensions to explain the assistance via telephone or online representatives.

  User Satisfaction

  Satisfied customers may pass on positive comments about the firm and its offering and recommend the company to others (Zeng et al., 2009). In the online shopping context, McKinney et al. (2002) define satisfaction as an affective state representing an emotional- reaction to the entire web site search experience. Based on McKinney et al. (2002) we define user satisfaction of internet banking as an affective state representing an emotional reaction to the internet banking site experience.

  Perceived Risk

  Wong et al. (2009) in the online shopping context defined perceived risk as customer perceptions to the risk of internet transaction. This study uses operational definition of perceived risk in internet banking as user perceptions of the risk when adopting internet banking.

  There are some barriers in internet banking adoption perceived by the active internet users, especially in the developing countries (Aslam et al., 2011). This barrier can reduce the intention to adopt the internet banking. In their studied, Aslam et al. (2011) categorized two major barriers: psychological barriers, and technical barriers. In the psychological barriers there were low perceived value and high perceived risk. This perceived risk included economic risk, functional risk, social risk, and psychological risk. The second major barrier was technical barrier included lack of security and privacy, lack of knowledge, and access to internet.

  In this study, we adopt perceived risk from Aslam’s high perceived risk. So there will be economic risk, functional risk, social risk, and psychological risk. Economic risk concerns for financial loss during online transaction. Functional risk is about perceived Airlangga Accounting International Conference & Doctoral Colloquium 2012

    operating difficulty and chances of incomplete transactions due to internet speed failure. Social risk is related to the culture that in the developing countries have soft and collectivist culture where concern for social value. Unlike traditional banking, using online banking is perceived to hinder the social relationship during the transaction based on interpersonal interaction at the physical services. Psychological risk is about psychological inconvenience while switching from conventional banking habits to the online banking system and to learn new technology impedes the adoption process.

  Intention to Use

  Wang (2008) applied Intention to Reuse when modify DeLone & MacLean Model (2003). DeLone & McLean (2003) suggested that Intention to Use may be a worthwhile alternative measure in intention to reuse context. Based on the marketing literature, Wang (2008) defined Intention to Reuse as the favorable attitude of the customer toward an e- commerce system that results in repeat used/purchased behavior. Based on Wang (2008), we raise an operational definition of internet banking Intention to Use as favorable attitude of the internet user towards an internet banking system that result in use behavior.

  This concept can be applied when we investigate the IB users or potential users.

  Variable Relationships

  Wang (2008) indicated that quality in the information system had positive direct effect to the user satisfaction. Zeng et al. (2009) gave the same indication; they said that fulfillment/reliability had direct effect to the overall satisfaction. This fulfillment variable is a part of the quality dimension, and overall satisfaction is close to the user satisfaction. In the internet banking context the quality will have a positive impact to the user satisfaction. This is alike direction in the other web context. It’s predicted if internet banking can provide the quality which match to the user’s expectation, they will feel that their need is complied, further they will be satisfied with the internet banking services.

  In the e-commerce and online shopping context, user satisfaction had an effect to the intention (Wang, 2008; Zeng et al., 2009). We think internet banking characteristic is closely to e-commerce context. Satisfaction is a symbol that user expectation complied and they feel comfort in using internet banking. This satisfaction affect emotionally than users will not reluctant to use internet banking. Implicitly this says that quality has impact to the intention via user satisfaction.

  If Wang’s and Zeng’s research show the indirect effect from quality to the intention, Hamadi (2010) gave the evidence in the internet banking context that perceived quality had stronger direct effect to the commitment than via mediation of satisfaction. We think commitment is closely to intention to use in this study, that commitment is customer Airlangga Accounting International Conference & Doctoral Colloquium 2012

    intention to revisit the bank site. The explanation of this direction is customers do business via bank website if they think internet banking has good quality although they do not be satisfied at all components.

  Wong et al. (2009) found that perceived risk had negative direct effect to the willingness to use e-banking. In other way Zeng et al. (2009) said that variable security/privacy which indicators of risk perceptions on using online transactions had effect to the repurchase intention. The willingness to use e-banking or repurchase intention are closely to the intention to use in this study. It seems clear that perceived risk has negative impact to the intention. Ones who perceive higher risk in the internet banking will lower the intention to use. May they choose to visit the physic bank or use the other usual facilities used.

  Other evidence related to the risk is that risk can be reduced by raise some quality in dimensions (Chen & Chang, 2005; Lee et al., 2010). Chen & Chang (2005) gave the explanation, “Theoretically, if service quality cues in an advertisement indicate the service will be performed at a high level, the associated risk should be reduced. If customers feel a service firm is reliable (for example, possessing adequate and up-to-date equipment), responsive to their particular requests, reassuring, and empathic in caring for them as an individual, then the risk of patronizing that service should be reduced.” This explanation indicated that quality has negative direct effect to the perceived risk.

  Because quality has direct impact to the satisfaction and perceived risk, so that will be an implicit hypothesis that satisfaction give a negative direct effect to the perceived risk. This direction is an implication from the indirect effect of quality to the perceived risk via user satisfaction.

  H1: Internet Banking Service Quality has a positive impact to the user satisfaction. H2: User satisfaction has a positive impact to the Intention to Use H3: Internet Banking Service Quality has a positive impact to the Intention to Use.

  H4: Perceived Risk has a negative impact to the Intention to Use H5: Internet Banking Service Quality has a negative impact to the Perceived Risk. H6. Internet Banking Service Quality has a negative impact to the Perceived Risk.

  RESEARCH METHOD Sampling and data collection

  The respondents were internet users in Indonesia conducted by paper and online media. First, post mails were sent to 15 Catholic Universities (island of Java, Sumatra, Kalimantan, Sulawesi, Nusa Tenggara), be distributed by secretariat of accounting Airlangga Accounting International Conference & Doctoral Colloquium 2012

    department to the lectures in scope. The questioners are also sent to accounting department of 10 companies in Java. Second, the online survey was conducted to fulfill the questioner on the web. Post’s mail invitations were sent to 16 companies in Java. Online invitations were sent privately via e-mail, facebook, and tokobagus. Overall 1831 paper and online questioners were sent. Responses were 429 (23.4%) questioners back or fulfilled. The data was checked and found 2 double IP, 6 un-complete, 14 un-seriously. Used data is 407 (22%).

  Instruments

  Questioner in 7 point Likert-scale was applied. The variable indicators were collected from some literatures which 73 items available. We used 44 items (see appendix) to reduce response bias because of so many questions. The items reducing were based on judgment: properly to the internet banking, same dimensions, clearly statement specification. Confirmatory factor analysis was applied by SPSS-dimension reduction and scale reliability. Loading factor were in range of 0.60 - 0.95. Sixth indicator of perceived risk (ris06) was dropped because consist in cross loading. Cronbach’s alpha for variables and quality dimensions were in range 0.72 – 0.93. So the instruments were valid and reliable according to the data characteristic in this study.

  Data and Model Testing

  The models were tested by SEM which Amos 18 software. Measurement model for confirmatory factor analysis, normality, and outliers were accessed to understanding the data and model characteristic. Model fit is accessed by Goodness-of-Fit Index (GOF Index) included absolute measures, incremental fit measures, and parsimony measures (Hair et al., 2010: p. 716).

  RESULT, ANALYSIS, and DISCUSSION Demography

  The demography data is shown in the table 1. Using frequencies indicate the prediction of IB using every month. The dominant users are in the level 1 (1 till 5 times). The purpose of IB using is dominant for private need. The respondent is dominant from employee in the universities or companies. The respondents were male 57% and female 43%. Airlangga Accounting International Conference & Doctoral Colloquium 2012

   

  Table 1: demography Using  Frequencies (in a month)

  Categories N 1  (1‐5)

  2  (6 ‐ 10)

3  (> 10)

Using  Frequencies 96 211               

  28 72      407 Using  Purpose ₂₃₅ 1 ‐Private 190

  15 30 58% ₇₆ 2 ‐office/business

  21

  13 42 19% Job  status ₃₃₄

  1 ‐Employee 74 175

  23 62 82% ₃₅

  2

  3

  17

  5 10 9% ‐Entepreneur ₃₈ 3 ‐High student 19

19 9%

  Gender ₂₃₁ 1 ‐Male 59 102

  21 49 57% ₁₇₆ 2 ‐Female 37 109

  7 23 43% Data Examining

  Normality test for the data model shows t value out of range + 2.58. It significance <0.5 or indicated non-normal distributed. There is explanation about the normality on Likert-scale. Clason & Dormody said it was difficult to see how normally distributed data can arise in a single Likert-type item. The data will frequently be skewed. Further, Norman (2010) said that parametric statistics could be used with Likert data, with small sample size, with unequal variance, and with non-normal distributions, with no fear of coming to the wrong conclusion. Another consideration on Likert-type was a large sample size could be assumed had a normal distribution. For sample sizes of 200 or more, the effect of non-normality may be negligible; the researcher could be less concerned about nonnormal variables (Hair et al., 2010: 71).

  Measurement models are applied in the two categorizes: first, measuring the quality which it’s dimensions. Second, is measuring the satisfaction, perceived risk, and intention. Quality measurement model indicated that loading factor is greater than 0.5. Measurement model for satisfaction, risk, and intention resulted loading factor was greater than 0.6. This value indicates a good convergent validity. The discriminant validity is accessed from correlation matrices. All indicators show higher correlation values to the own variable compared to other variables. It indicates good discriminant validity.

  In these measurement models there are a correlation or affection among error term or indicators suggested by Amos modification model. Not all of these suggestion were used because insignificant or to avoid a more complex path models. Example, the intention to visit website (int01) reduced risk of computer cost (ris01) but arise the perception of other expenses risk like internet expenses (ris02). Another suggested path Airlangga Accounting International Conference & Doctoral Colloquium 2012

    was intention to increase the using IB in the future (int03) would reduce the risk of difficulty to learn the interface (ris07).

  Structural Equation Model (A) ₂ Fit indices of Model A can be seen at table 2. The Model A has χ value 3353.130 _{2 2} sig 0.000. It significance of χ indicates not a good fit model, but we can see the ratio χ /df

  (3353.130/721 = 4.651), ratio < 5 indicated that model is fit. RMSEA also support this fit which mediocre category, value 0.095. Furthermore, GFI (0.726), AGFI (0.672) and PGFI (0.608), it values are greater than 0.6 or indicate a good fit. CFI (0.816) is near to 0.9. Generally can be concluded that model is good but hasn’t perfected.

  Comparison Model (B)

  In the instrument we have two indicators that measure the internet banking service quality in general. The indicators were used by Ma et al. (2011) to test the antecedent of quality variable. Model B or Model Alternative uses the way which this two quality indicators to replace 11 dimensions of quality. The result of Model B can be seen at table ₂ 2 column B. Although the Model B show better fit which less χ ratio, less RMSEA, greater

  GFI, and greater CFI, but we recommend the Model A to used in the future because it has a complete or detail specification of internet banking quality.

  Airlangga Accounting International Conference & Doctoral Colloquium 2012

   

  Figure 1: Testing Models for intention to use internet banking

  Model A: which 11 IB quality dimensions Model B: which general IB perceived quality

  Table 2: Comparison of GOF Models GOF Standard Mod. Mod.

   Index  A  B (alt) N 407 407 Absolut  Fit Indices ₂

  3353.130 312.420  Chi‐Square (X )

721.000 82.000

Degree  of freedom

  

.000 .000

Probability P  > 0.05 ₂ < 4.651 3.810  2 ; 5 Rasio  X /df

  RMSEA <  0.05; 0.08; 0.1 .095 .083 GFI >0.6 .726 .915 AGFI >0.6 .672 .860

.608 .552

PGFI >0.6 RMR <0.08 .089 .065 Incremental  / Relative Fit Indices  NFI >  0.9 .778 .940 NNFI  / TLI ‐‐>1 .791 .934 RFI >0.9 .748 .912

.817 .955

  IFI >0.9 CFI >0.9 .816 .955  **

  Parsimony  Fit Indices PRATIO .879 .683 PNFI  – 1 .684 .642 PCFI  – 1 .718 .652 Airlangga Accounting International Conference & Doctoral Colloquium 2012

   

  Table 3: Comparison of Standardized regression weight Variables Mod  A Model  B (alt) Hyphotheses/  

  Endogen Exogen Coeff. CR Sig. Coeff. CR Sig.

  Predictions Satisfaction < ‐‐‐ + Quality H1 .840 13.508 *** .858 18.757 *** Intention < ‐‐‐ + satisfaction H2 .242 3.242 *** .419 4.518 ***

• Intention < ‐‐‐ Quality H3 .551 6.793 *** .333 3.608 *** Intention < ‐‐‐ Risk H4 ‐ ‐.081 ‐2.005 ** ‐.077 ‐1.793 * Risk < ‐‐‐ Quality H5 ‐ .101 .958 .120 .995 Risk < ‐‐‐ satisfaction H6 ‐ ‐.452 ‐4.253 *** ‐.468 ‐3.889 ***  sig. 1%; ** sig. 5%; * sig. 10% ***

  The score of standardized regression weight in table 3 were drawn in the path diagram as shown in figure 2. This comparison data from the table or the figure will be used to conclude the hypotheses. The main consideration is result from the Model A.

  Table 3 indicates only one hypothesis unsupported, it is H5 which predict a negative impact from the quality to the risk. We can see that the result is positive insignificance (coeff. 0.101; CR = 0.958).

  Hypothesis 1 predicts that IB service quality has a positive impact to the user satisfaction. Model A show coefficient 0.840 sig 1%.. So it can be concluded that hypothesis 1 is supported. Hypothesis 2 predicts that user satisfaction has a positive impact to the intention to use. The coefficient of this link in Model A is 0.242 at significance level 1%. So, the hypothesis 2 is supported. Airlangga Accounting International Conference & Doctoral Colloquium 2012

   

  Figure 2: standardized regression weight (compared model A, B)

  Hypothesis 3 predicts that quality has a direct positive impact to the intention. The result shows that all models have a positive direct impact from quality to the intention (0.551; 0.333) sig. 1%. So, hypothesis 3 is supported. Hypothesis 4 predicts that perceived risk has a negative impact to the intention to use. The result supports this hypothesis. The impact values are -0.081, -0.077. Hypothesis 6 predicts that user satisfaction had a negative or reducing perceived risk. The result of all model indicate a negative impact (-0.452; -0.468), the hypothesis 6 is supported.

  Discussion The link between quality and risk shows in-significance result and contra prediction.

  The hypothesis predicts that quality will reduce risk, but the result shows the quality hasn’t power to reduce the perceived risk. In this case we can see the role of user satisfaction in reducing risk. When the quality has no power to reduce risk, the user satisfaction does. User satisfaction play an important role by mediates the link between quality and risk. Users reduce their risk perception only if the quality makes them be satisfied. Other researches (eq. Chen & Chang, 2005; Lee et al., 2010) saw the direct effect of quality to the risk haven’t included the user satisfaction

  Airlangga Accounting International Conference & Doctoral Colloquium 2012

    Even though risk has a negative impact or reduce the intention, but this impact is lower than impact of quality or satisfaction. This indicates that in the user’s perception of quality and satisfaction is more important than the risk.

  The impact of quality to the intention has a differ value by Model A and B. Model A shows higher value than B in the direct effect of quality to intention. But, when there is a mediating of user satisfaction, Model B shows higher value of the path user satisfaction to the intention. This can be explained that when users know the specification of quality (by 11 quality dimensions) that will be direct impact to the intention. But if users only be asked by the general perception of quality (2 quality indicators), they need satisfy first so the intention will arise. The mediating effect of satisfaction has an important role when users only know the general perception of quality.

CONCLUSSIONS AND LIMITATIONS

  The model of internet banking using intention is modified by the rational consideration in decision making approach which in this study uses the quality and risk. The model has four variables: internet banking service quality, user satisfaction, perceived risk, and intention to use. The model which eleven dimensions of quality was applied in model A. Then, model B used the general perception of quality by two items of indicator. The two models have a good fit, but have a little different in the effect of quality to the intention. Users who know the specific quality feel the direct impact to the intention, but if users only know the general perception of quality that the satisfaction will have an important role. Perceived risk has a negative impact to the intention, but this impact is lower power than the quality and satisfaction. Perceived risk can be reduced by raising the quality, but if users feel be satisfied first by the quality offered. So, there is a mediating effect of user satisfaction.

  The decisions by the result of this study must be considered by the limitations. First, this study is individual perceptions by self reporting from a survey and dominant from an employee. Second, the internet users are in the category of earlier level of adoption. Future researches can be done in the context of another user area, specific IB provider, user using frequencies characteristics, and IB using for companies adoption. Researcher can investigate deeper to the dimensions of quality. We suggest that the instrument in this study can be considered to be applied because more simple by the item size. We suggest to that model which 11 quality dimensions can be replicated. Airlangga Accounting International Conference & Doctoral Colloquium 2012

   

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  Consumer’s Dilemma with E-Banking, Journal of Internet Business. Issue 6, pp. 1- 27. Yaya, L.H.P., Marimon, F. and Casadesus, M. (2011), Customer’s loyalty and perception of ISO 9001 in online banking, Industrial Management & Data Systems, Vol. 111,

  No. 8, pp. 1194-1213. Yee, B.Y. and Faziharudean (2010), Factor Affecting Customer Loyalty of Using Internet Banking in Malaysia, Journal of Electronic Banking System, Vol. 2010, pp. 1-21.

  Zeng, F., Hu, Z., Chen, R. and Yang, Z. (2009), Determinants of Online Service Satisfaction and Their Impacts on Behavioral Intentions, Total Quality Management, Vol. 20, No. 9, Sept., pp. 953-969.

  Airlangga Accounting International Conference & Doctoral Colloquium 2012

  1 I think my internet banking companies keep customers information private and confidential.

  2 The structure of menus and buttons are attractive, easy to find, easy to use, and functionally good.

  Service Leelapongprasut et al. (2005)

  3 If there were a trouble, the banking officer gives assistance quickly to solve the problems.

  Repair Leelapongprasut et al. (2005) SECURITY (6)

  1 I feel safe in my online transaction and secure in providing sensitive information for my online transaction.

  Feel secure Ma et al. (2011)

  2 My bank communicates its security policies on its website Financial security

  Ma et al. (2011) PRIVACY (7)

  Information safety Ma et al. (2011)

  1 Internet banking has search function that make easy to find information.

  2 I trust that my bank website protect and didn’t used the personal information inappropriately.

  Information protected Kettinger & Lee (1997)

  ASSURANCE (8)

  1 I have confidence in the bank’s services confidence Kenova & Jonnasson (2006); Kettinger & Lee (1997)

  2 I think, internet banking has courteous in deliver services and information. courteous Kettinger & Lee (1997)

  3 Bank officer has knowledge about internet banking so can give good explanation about internet banking.

  Have the knowledge Kettinger & Lee (1997)

  REPUTATION (9)

  Service Leelapongprasut et al. (2005)

  SERVICEABILITY (5)

   

  Consistence Zeng et al. (2009) CONVENIENCE (2)

  

Appendix: Instrument of this Study

No State items Dimensions References

  RELIABILITY (1)

  1 Internet banking (IB) provides accurate information and continuously recorded my financial data.

  Accurate Ma et al. (2011)

  2 Internet Banking performs the service correctly since the first time of using.

  Rely on Zeng et al. (2011)

  

3 Internet Banking transaction are always accurate Accurate Zeng et al. (2011)

  4 Internet Banking delivered the process/transaction within the time promised.

  1 I think I can access IB anytime and anywhere, and save time as compared to conventional banking.

  Consistency with user knowledge Hong et al. (2011)

  Anywhere anytime Ma et al. (2011)

  2 Internet banking is having the time saving of not having to go to the bank office.

  Saving time Wolfinbarger & Gilly (2001) EFFICIENCY (3)

  1 It’s quick to make transaction on my bank website. Quick transaction Hamadi (2010)

  2 I earn a lot time using my bank website Ease and quick Hamadi (2010)

  COMFORT (4)

  1 I feel comfortable with the changes resulting from the upgrades of the systems.

  Comfort with change Hong et al. (2011)

  2 In the upgrades, the use ob buttons, radio buttons, and combo boxes is consistent with my understanding.

  

1 The internet banking has a reputation for delivering Offering Yee & Fazihaudean

  Airlangga Accounting International Conference & Doctoral Colloquium 2012

CUSTOMER SERVICE (11)

ONLINE BANKING QUALITY

USER SATISFACTION

  Economic risk Aslam et al. (2011)

  Economic risk Aslam et al. (2011)

  2 I think that using internet banking make extra associated cost (eq. internet cost, etc).

  Economic risk Aslam et al. (2011)

  3 I fear of loss personal service and one-to-one relationship with banker if I use internet banking.

  Social risk Aslam et al. (2011)

  4 I fear of incomplete transaction when I use internet banking Functional risk Aslam et al. (2011)

  5 I think, using internet banking to make transaction is high financial risk.

  Aslam et al. (2011)

  6 I feel inconvenience of adopting new technology Psychological risk Aslam et al. (2011)

  7 It is time taking and difficult to learn internet banking interface Psychological risk

  Service satisfaction Zeng et al. (2009)

  1 I will visit internet banking website if I need banking services.

  Intention to visit Wang (2008)

  2 I will use internet banking to make baking transaction in the future Intention to do business

  Wang (2008)

  3 I will use internet banking services more frequently in the future.

  Increasing business Wang (2008)

  1 Exactly to use internet banking need computer cost, so make me unwilling to use it.

  5 I am very satisfied with the internet banking service delivered by bank.

   

  Swaid & Wigand (2009)

  good services. services (2010)

  2 Internet banking has a reputation for being fair in its relationship with its users.

  Relationship with users Yee & Fazihaudean (2010)

  PRODUCT DIFFERENTIATION & CUSTOMIZATION (10)

  1 IB website gives a personal attention for personal or private setting.

  Personal attention Swaid & Wigand (2009)

  2 IB website enables me to order the service in a way that meets my needs.

  Order specific needs Swaid & Wigand (2009)

  3 IB website understands my specific needs. Understand specific needs.

  1 The site provides ways to contact and advisor at the bank Provide the way to contact

  4 I feel be satisfied with internet based transaction Transaction satisfaction Zeng et al. (2009)

  Hamadi (2010) 2 I can communicate with someone from the bank (eq. by e-mail) if I have problems with my account.

  Interactivity Hamadi (2010)

  1 I believe that my internet banking service provide good quality.

  Quality perception Ma et al. (2011)

  2 The internet banking service quality matches with my expectation.

  Matches expectation Kenova & Jonasson (2006)

  1 I feel be satisfied with internet banking systems. System satisfaction Wang (2008)

  2 I think that internet banking is of high quality Quality satisfaction Wang (2008)

  3 I feel satisfied with the bank because implementing internet banking.

  Satisfaction with company Zeng et al. (2009)