An Empirical Investigation into the Factors Influencing the Use of E ...

Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010

An Empirical Investigation into the Factors Influencing the Use of E-Banking Services Seung Hye Jin Sogang University [email protected]

Abstract This study proposes and empirically investigates a research model regarding the use of electronic financial services based on the e-service acceptance model. The current study categorizes electronic financial services provided by banks into transactionoriented services (TOS) and communication-oriented services (COS) to emphasize the co-value creation phenomenon through customer participation. We assume that the antecedent variables studied in the previous studies may exert differential effects on the use behavior of electronic services. The proposed model includes self-efficacy, ease of use, perceived usefulness, and perceived risk as the antecedents to the use of e-banking services. The proposed research model was tested against the data collected through the survey method with company respondents. The key result is that the use behavior of the different types of e-banking services is affected by different sets of factors: the use of both COS and TOS is found to be affected by finance specific self-efficacy, finance specific ease of use, and perceived usefulness, whereas the use of TOS is affected by general Internet self efficacy. The methodology, results, and implications are further discussed.

1. Introduction As the importance of electronic business increases, a number of studies have investigated the questions including why people shop through Internet websites [2,3,8,25,27,28,29], what is the major reason people use a website [3,8,27], and what are the key factors to make a website usable [2,28,29]. The core finding of the previous studies is that people intend to use a technology when it is easy to use and useful [8,18,24,25,26]. Previous studies well explain why people accept a technology. However, they regard ebusiness as a single enterprise which is represented by a website. We see a website as a focal point which consists of a variety of activities to support transaction and communication. Transaction support is for the interaction between customers and a company, comprised of product and service catalog, shopping cart, payment options, FAQs, and instant messaging

Yong Jin Kim Sogang university [email protected] support for customers. Communication support is for the interaction among customers to help them acquire knowledge and information about how to use the product and service. These two types of activities or technology use behaviors can be affected by a different set of factors. Previous studies have been ignorant about this issue so far. In particular, considering the very nature of service of which value is created through the interaction between companies and customers and where the role of customer is critical for value creation [1,4,6,7], it is very important to understand what factors affect more on transaction service use and what factors influence communication service use. Through this understanding, we can motivate customers to more participate in the interaction with websites and/or companies so that both customers and companies can co-create value together [1,4,6,7]. With regard to the role of information technology in offering services and creating values, it enables a lot of players or participants including service providers and users to get together and be connected in some way to work together [1]. Hence, the acceptance or use of the technology is critical for the realization of value proposed by service providers. The purpose of this study is to identify the type of e-banking services from a customer perspective and investigate what kind of factors affect each type of ebanking services. This study contributes to the literature by two ways. First, this study identifies the type of e-banking services based on the characteristics each service may carry so that it can provide a basis for future study on services. Second, this study investigates the differential effects of the antecedents on the use of e-services. With the results, we can easily identify which factors need to be focused to promote customer participation in service provision.

2. Literature Review 2.1. Technology Acceptance Technology Acceptance Model (TAM) theorizes to explain individuals’ acceptance behavior of information technology based on the Theory of

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Reasoned Action [18]. The Theory of Reasoned Action explains that user behavior is directly determined by behavioral intention which is in turn determined by individual belief and attitude toward a behavior. [18,19]. TAM posits that perceived usefulness and perceived ease of use are relevant to computer use behaviors [18,19]. Davis [18] defines perceived usefulness as “the prospective user's subjective probability that using a specific application system will increase his or her job performance within an organizational context,” and Perceived ease of use (EOU) as “the degree to which the prospective user expects the target system to be free of effort". According to TAM, ease of use and perceived usefulness are the fundamental and distinct determinants of the actual system use. TAM has been widely studied and verified by previous studies that examine individual technology acceptance behavior in various technology use contexts [18,20,21]. There are also many studies which investigate the technology acceptance behavior in the e-business area. These studies insist that TAM need to be extended to include more factors relevant to the technology acceptance behavior in the e-business area. To our understanding, most Internet-related technologies can be categorized as self-servicing technology which requires strong self-efficacy to be accepted and actually used [8,27,31]. Moreover, previous studies on technology acceptance considered technology as a monolithic entity. However, information technologies, in particular, e-service technologies, can have two totally different dimensions: one for supporting transaction, the other for communication. We need to deal with this issue in the model to explain the use behavior with e-services.

2.2. e-Service Technology Acceptance Model Hsu and Chiu [8] suggested a model of e-service acceptance (Figure 1) that describes the acceptance pattern and the role of Internet self-efficacy in the eservice adoption. Their research extends the Theory of Planned Behavior (TPB) and Technology Acceptance Model [18, 19, 20, 21] to the Internet service (filing income tax) context [8]. Hsu and Chiu separated selfefficacy construct into two distinct constructs: General internet self-efficacy and Web-specific self-efficacy. General Internet self-efficacy is defined as “an individual’s judgment of efficacy across multiple Internet application domains”, and Web-specific selfefficacy is defined as “an individual’s perception of efficacy in using a specific WWW application (service) within the domain of general Internet computing” [8,22].

The findings of the study indicate that perceived usefulness, perceives playfulness, perceived risk, general Internet self efficacy have significant effects on attitude and intention toward e-service usage. The result also indicates that Web specific self efficacy has direct effect on e-service usage. General internet self efficacy has indirect effect on e-service usage through Web specific self efficacy and attitude [8].

Figure 1. e-Service Acceptance Model Hsu and Chiu [8] in their study focus more on behavioral control because the services delivered through the Internet are typically self-servicing which requires competence on the use of the technology. This model very well explains the nature of e-service acceptance by giving a special attention to self-efficacy as the major mechanism to facilitate e-services. However, Hsu and Chiu [8] study also regards eservice as a single entity just like in other studies of technology acceptance. We argue that e-services have at least two dimensions: one for transaction between customers and companies, the other for communication among customers. These two dimensions are necessary when considering the fact that customers’ and customer community’s participation is critical for value creation. Accordingly we split e-service usage into transactional e-service usage and communicational e-service usage so that we can examine the differential effects of factors on different e-service usage.

2.3. e-Banking Services in Practice Basole and Rouse [1] suggest a conceptual model of service ecosystems that is the network of both products and services (Figure 2). They use nodes and arcs to describe the service value network where arcs represent interactions or relationships and nods represent participants including individuals or organizations in the service network [1,9]. In their model, a service network consists of five types of actors: service providers, service consumers, tier 1 and

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tier 2 enablers, and auxiliary enablers within four contexts: political, economic, technology, and social where the structure is determined [1].

Figure 2. The Conceptual Model of Service Value Networks Consumers are the users of services to realize the proposed values. To acquire the service needed, consumers first contact service providers [1]. Service providers deliver various services such as education, hospitality, wholesale, transportation and logistics, utilities, financial service, information technology (IT), telecommunications, health care, and so on. In this network of service provision, values are co-produced through the interaction between service providers and consumers [1,10,11]. Tier 1 and Tier 2 enablers support service providers to produce and supply the service. Auxiliary enablers are providing the entire system with necessary infrastructure and not limited to a specific industry. The entire service system operates within the context of society, culture, economy, and politics [1]. Information and communication technology (ICT) help coordinate value creation activities and deliver value throughout the service value network. That is, ICT supports the linkage among service providers, customers, and enablers in the service value network regardless of the relationship type: business-tobusiness (B2B), business-to-consumer (B2C), or consumer-to-consumer (C2C) [1,12]. B2B relationship is formed between business entities, i.e., service provider and enablers. For business entities, ICT helps improve cost efficiency and productivity, and enables to integrate business processes between business entities. B2B relationship also gives better information visibility, and consequently greater flexibility, agility, and responsiveness [1,13,14,15,16]. ICT provides significant benefits to consumers by enabling customers to be direct involved in value creation processes. For example, through the technologies like the Internet, mobile technology, and

telecommunications technology, consumers can express their needs directly to providers and sometimes join decision making processes [1,12]. Individual users can also share their experience with the service and service provider and value preference through customer communities, blogs, online forums and other platforms [1,17]. The primary benefit of the network approach to services ecosystems is to better understand the complexity and the necessity of cooperation among the participants in the network where actors contribute to the value creation process by focusing on their core competence and cooperating with other actors on the network [1,5]. In this study, we try to figure out e-banking service network (Figure 3). To identify how the e-banking service in practice is structured, we examined services provided through Internet banking web sites of 6 major banks in Korea. The target Internet banking websites contain most of general banking service functions provided off-line including balance checking and money transfer, and some extended financial services such as credit card service, insurance, foreign exchange, investment, stock exchange, and financial counseling. These services constitute the major part of transaction-oriented services between a bank and a customer which also incorporate various pieces of information related to transactions. With regard to the transactional service provision, the bank becomes a focal point to access diverse financial services, which in turn dramatically reduces the sheer amount of complexity to a single interface for the sake of customer convenience [1]. Customers can enjoy a variety of services in a seamless and efficient manner. In Figure 3, the left hand side of bank represents the transactional e-banking services. Despite the complexity of B2B relationships in this network, consumers do not have to contact each company in charge of each financial service. Internet banking provides an effective and efficient user interface through which consumers can conduct a whole set of investment activities such as financial planning, advising, investment decision making, and stock trading. The interface also allows service providers to better focus on the reach to individual consumers with exact suggestions and better outcomes, which will lead to both cost reduction and sales increase. The right hand side of Figure 3 illustrates consumer communities as another important constituent of the ebanking service network. We in this paper define consumer activities related to consumer communities as communication oriented e-service use. Consumers are primarily concerned about how to manage their properties and how to maximize their wealth. The information about these types of questions can be

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obtained either through the employees of a bank or customers who have actually performed some activities regarding property management. In many cases, customers prefer information and knowledge related to financial activities and financial issues obtained from peer customers. Customers want to listen to experienced customers and information providers though blogs, on-line communities, and forums that function as platforms and windows [23,32,33]. Hence, the network of customers is likely to be a key resource which customers refer to when they make decisions. Supporting the community type activities is very important because it might be a major source of customer decision making, which in turn creates value. Throughout the service value network, the value that is determined by customers is the most fundamental and drives the entire value network [1]. This kind of support can be defined as communicational e-banking service.

extension of the e-service acceptance model [8]. In this model, we focus on the effect of general belief and domain specific belief including self-efficacy and perceived ease of use on different usage behaviors. We also have usage behaviors instead of intention to use a technology, because it is believed that the use behavior is a better indicator of information system performance [8,18,20,25,26,27,31]. The usage behaviors as the dependent variables are categorized into transaction-oriented e-service (TOS) and communication-oriented e-service through which we focus on the consumer behaviors rather than businessto-business activities. Figure 4 illustrated hypothesized relationship between constructs. Previous studies have confirmed that the factors such as self-efficacy, ease of use, usefulness, and perceived risk affect behavioral intention and subsequently usage behaviors [1,8,19,21,24,25]. However, we do not know this is true in the case of e-banking services which are networked services and where customer competence is a key component for effective service delivery and value creation.

3.1. Finance-specific self-efficacy and General internet self-efficacy

Figure 3. e-Banking Service Value Network In sum, e-banking service can be categorized into transaction-oriented services (TOS) through which customers and companies interact together and communication-oriented services (COS) to help customers talk each other to get information and knowledge about financial transactions. For both cases, ICT provides service platforms, e-banking websites, to allow customers to access necessary e-banking services and banks and partners to deliver diverse services. Service providers with using the service platforms can reduce cost for service provision and increase relevance of service provision to individual customers. Customers can also enjoy more information on providers' performance and financial knowledge from peer customers as well as a variety of financial services.

3. Research Model and hypothesis As discussed in the earlier sections, e-banking service consists of two distinguishable dimensions of transaction-oriented and communication-oriented. The proposed research model (Figure 4) in this study is an

The social cognitive theory defines self-efficacy as an individual’s belief about capabilities to perform specific behavior. Previous studies on technology adoption verify the linkage between self-efficacy and individual behaviors of technology adoption [8,24, 25,31]. In particular, Hsu and Chiu [8] note that Within social cognitive theory, self-efficacy is a form of self-evaluation that influences decisions about what behaviors to undertake, the amount of effort and persistence put forth when faced with obstacles, and finally, the mastery of the behavior. Thus, people who have low selfefficacy should be less likely to perform related behavior in the future, in this case, adopt and use the e-service, than those with high degree of selfefficacy. Self-efficacy beliefs are argued to be separated based on targeted performance and domain of interest. While most of previous studies indicate that selfefficacy have positive effect on system usage and service acceptance, some studies insist that only taskspecific self-efficacy has a distinctive effect on use behavior [8,22,27]. Eastin and LaRose [27] examine that general Internet self-efficacy is positively related to Internet usage in the context of digital divide. Eastin

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[22] suggests that task specific self-efficacy needs to be considered to better explain technology and service adoptions. Hsu and Chiu [8] insist that e-service usage and Web specific self-efficacy are directly related since users are more likely to behave when they feel capable of performing task specific behaviors. Considering the characteristics of self-efficacy, in this study, we employ the similar approach to testing self-efficacy. We identify two types of self-efficacy: general Internet self-efficacy and finance specific self– efficacy. Finance specific self-efficacy may exert a strong influence on both of the e-services use behavior, just like general self-efficacy about the practical ability to use the Internet as a vehicle to achieve the value creation activities affects the use behavior of both ebanking services. Based on the above discussion, we hypothesize the relationship as follows. Hypothesis 1–a: Finance specific self-efficacy has a positive effect on communication-oriented e-service usage. Hypothesis 1–b: Finance specific self-efficacy has a positive effect on transaction-oriented e-service usage. Hypothesis 2–a: General internet self-efficacy has a positive effect on communication-oriented e-service usage. Hypothesis 2–b: General internet self-efficacy has a positive effect on transaction-oriented e-service usage.

3.2. Finance-specific easy of uses and General internet ease of use

Perceived ease of use is defined as “the degree to which the prospective user expects the target system to be free of effort” [18,24]. While previous studies provide strong evidence about the effect of perceived ease of use on technology adoption, most of them regard perceived ease of use as a single construct [8,18,24,25,26]. Regarding the financial service network, however, there are two types of perceived ease of use, just like in the case of self-efficacy. Financial activities require at least the ability to analyze interpret, and evaluate data and factors. For stock investments and derivative securities trading, users need set up specific software. The software requires consumers to learn how to deal with the programs and how to perform secure transactions. Therefore, users’ perceptions about the software for the financial activities and general Internet use are not equal. Therefore, we propose two types of ease of use in the context of e-banking service use. Finance specific ease of use is an individual’s perception regarding the ease of financial applications, while general Internet ease of use is about general Internet use related to ebanking services. Accordingly, following hypothesis are proposed Hypothesis 3–a: Finance specific ease of use has a positive effect on communication-oriented e-service usage. Hypothesis 3–b: Finance specific ease of use has a positive effect on transaction-oriented e-service usage. Hypothesis 4–a: General internet ease of use has a positive effect on communication-oriented e-service usage.

Figure 4. Research Model

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Hypothesis 4–b: General internet ease of use has a positive effect on transaction-oriented e-service usage.

3.3. Perceived usefulness and Perceived risk Perceived usefulness is defined as “the degree to which a person believes that using a particular system would enhance his or her job performance” [18,24]. Perceived risk relates to customers’ perception about performance failure which refers to the possibility of wasting time caused by unsuccessful accomplishment and potential monetary loss due to e-banking service usage. Prior research shows that perceived usefulness influences usage positively [8,18,24,25] and perceived risk influences negatively [8]. Hsu and Chiu [8] explain that economic factors affect the attitude toward using e-services. Accordingly, in this study, we argue that perceived usefulness as the user's expectation to get better outcome positively affects e-banking service use, but perceived risk as the user’s awareness about the failure possibilities and security risk of e-service usage negatively affects e-banking service use behavior. So, we hypothesize the relationships as the following. Hypothesis 5–a: Perceived usefulness has a positive effect on communication-oriented e-service usage. Hypothesis 5–b: Perceived usefulness has a positive effect on transaction-oriented e-service usage. Hypothesis 6–a: Perceived risk has a negative effect on communication-oriented e-service usage. Hypothesis 6–b: Perceived risk has a negative effect on transaction-oriented e-service usage.

4. Research Method 4.1. Sampling The proposed research model was tested against the data collected through the survey method. Sample frame is e-banking users and analysis unit is the individual user of e-banking services. Sample consists of 334 graduate students and office workers. Graduate students were majoring business administration. About 600 surveys are distributed via e-mail or directly delivered to respondents, 347 questionnaires were returned. Among the returned questionnaires, the number of useable responses was 334. Table 1 summarizes the demographic profile of the informants.

4.2. Operationalization of research variables As shown in Table 2, the instrument was operationalized based on the previous studies on technology adoption and e-service usage. Measurement items used in previous studies were directly used or adapted for the current study. The 4 measures of perceived usefulness are from Davis’s TAM studies. The 9 measures of perceived ease of use are from both of Davis’s TAM and Hsu and Chiu’s e-service acceptance model. The 9 measures of self-efficacy and the 4measures of perceived risk are mainly from eservice acceptance model and previous studies on selfefficacy. The each set of 3 measures for transactionoriented and communication-oriented e-service usages are modified by adopting usage measures from prior IS research. For all measurement items, 5 point Likert scale was used, with anchors ranging from strongly disagree (1) to strongly agree (5). Table 1. Demographics (n=334) Occupation

Graduate student

141

42.2%

Office workers

193

57.8%

Age

20’s

118

35.3%

30’s

154

46.1%

More than 40

62

18.6%

Table 2. Summary of Instruments Finance-specific self efficacy (FinSE) I feel confident completing the banking service through e-banking website

[8,21,22]

I feel confident finding information in the ebanking web site. I feel confident analyzing a and interpreting financial data and information I feel confident navigating e-banking web site by my necessity I feel confident performing investment activities in a e-banking web site

General Internet self efficacy (GISE) I feel confident visiting a Web site by URL in the browser.

[8,21,22]

I feel confident finding information using search engine. I feel confident receiving and sending e-mail I feel confident installing an application or software

Finance-specific Ease of Use (FinEOU) Financial planning would be easy for me, in the e-banking web site

[8,21,22]

I would find that it is easy to do financial activities in the e-banking web site

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It would be easy to become skillful at doing what I want to in the e-banking web site My activities about banking and investment would be clear and understandable. It would be easy to me to become skillful at investment activities

General Internet Ease of Use (GIEOU) Overall, e-banking web site is easy interface to use

[8,21,22, 24,26]

Learning to operating software and applications is easy for me I would find the system to be flexible to interact with My activities with the e-banking web site would be clear and understandable.

Perceived Usefulness (PU) e-banking if effective interface to improve my profitability in the financial activities

[8,21,22, 24,26]

was assessed by computing Cronbach’s alpha values. Alpha coefficients were ranged from 0.73(perceived risk) to 0.85(finance specific self-efficacy), which are greater than the cut-off values [30]. Average variance extracted (AVE) measures the variance that a construct captures from its indicators relative to the variance contained in the measurement error [2]. Convergent validity is adequate when construct have at least 0.5 value of AVE. Table 3 shows AVE values with the correlation of latent variables. AVE values need to be greater than the square of correlation among construct. As shown in Table 3, all AVE values are greater than 0.5 and each of square root of AVE is greater than diagonal correlation values, which indicates the measurement model has a sound convergent and discriminant validity. Table 3. AVE and Correlations of Constructs

e-banking if effective interface to make ease to do financial activities for me.

Fin SE

e-banking if effective interface to save time for accomplish task I would find the e-banking service useful in my financial planning

Perceived RISK (RISK) There is possibility of the wasting time when making unsuccessful financial activities.

[8]

There is possibility of delivery failure the service ordering in the e-banking web site. It could cause the malfunctioning.

GI EOU

PU

RISK

COS

FinSE

(.779)

GISE

.196

(.817)

FinEOU

.428

.307

GIEOU

.181

.482

.332

(.732)

PU

.274

.260

.456

.285

(.752)

RISK

.166

.157

.090

.150

.086

(.738)

COS

.331

-.010

.205

.127

.199

.049

(.743)

TOS

.249

.220

.267

.152

.184

.043

.195

TOS

(.742)

(.739)

5.2. Assessment of the structural model

There might be potential risk relate to security issues.

Communication-Oriented e-Service Usage(COS) [1,8,21,26]

How many hours do you use online communities (related to financial issues) every week. I’m interested in diverse financial issues and sharing information.

Transaction-Oriented e-Service Usage (TOS) I connect to e-banking web sites frequently.

Fin EOU

The number parentheses is the squared root of AVE

There might be potential monetary risk with ebanking service usage

I connect to online communities (related to financial issues) frequently.

GI SE

[1,8,21,26]

How many hours do you use e-banking web sites every week. I would use diverse financial services that ebanking sites provide

5. Analysis and results 5.1. Reliability and validity tests

The hypothesized relationships were tested using AMOS, which is a structural equation modeling method. Figure 5 represent the results of the structural model test. Structural model Model Fit indices were computed. ( χ 2= 981.928, d.f.=422, GFI=0.838, CFI=0.838). Hypothesis 1-a through 6-a examined the relationship between the antecedents and communication-oriented e-services. Hypothesis 1-a, 3a, and 5-a appear to be statistically significant. The result indicates that finance specific self-efficacy, finance specific ease of use, and perceived usefulness have a significant influence on communicationoriented e-services. Hypothesis 1-b through 6-b examined the relationship between the antecedents and transactionoriented e-services usage. Hypothesis 1-b, 2-b, 3-b and 5-b appear to be statistically significant. The results

Reliability and discriminant validity tests are conducted using SPSS and AMOS. Internal reliability

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indicate that finance specific self-efficacy, general Internet self-efficacy, finance specific ease of use, and perceived usefulness have positive effects on transaction-oriented e-services usage. Table 4 summarizes the results of the hypothesis test. Table 4. Results of Hypothesis Test Hypothesis

Support

H1-a

Finance specific self efficacy

COS Usage

YES

H2-a

General internet self efficacy

COS Usage

NO

H3-a

Finance specific ease of use

COS Usage

YES

H4-a

General internet ease of use

COS Usage

NO

H5-a

Perceived usefulness

COS Usage

YES

H6-a

Perceived risk

COS Usage

NO

H1-b

Finance specific self efficacy

TOS Usage

YES

H2-b

General internet self efficacy

TOS Usage

YES

H3-b

Finance specific ease of use

TOS Usage

YES

H4-b

General internet ease of use

TOS Usage

NO

H5-b

Perceived usefulness

TOS Usage

YES

H6-b

Perceived risk

TOS Usage

NO

Significant level p < .05

6. Discussion and conclusion We in this study set out to investigate the effect of antecedent variables (self-efficacy, perceived ease of use, perceived usefulness and perceived risk) on two different types of e-banking services. In so doing, we distinguished communication-oriented e-banking service use from transaction-oriented e-banking service use, finance-specific self efficacy from general Internet self efficacy, and finance-specific ease of use from general Internet ease of use. This is primarily because we assume that task specific self-efficacy may have differential effects on e-banking service usage. As expected, the key variables (perceived usefulness, finance specific self-efficacy and finance specific ease of use) affect both of COS use and TOS use behaviors. Unexpectedly, general Internet self-efficacy and perceived risk were found to have no effect on both of e-banking service use behavior, and general Internet ease of use has effect only on TOS use behaviors. The results are in line with the findings of Hue and Chiu and other previous studies on technology acceptance [8,18,20,21,25,26] where usefulness affects attitude toward use of e-services and web specific selfefficacy affects behavioral intention to use e-services. The results of this study, however, bring quite interesting issues to our attention. The order and magnitude of the antecedent variables in explaining the use of e-banking services vary according to the services. TOS use behavior is affected by finance specific self-efficacy, usefulness, general Internet selfefficacy, and general Internet ease of use in its order, while COS use behavior is influenced by usefulness, finance specific self-efficacy, and finance specific ease of use in its order. General Internet self-efficacy affects

Figure 5. Result of Research Model

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TOS use behavior, but not COS use behavior. The results may stem from the different characteristics of eservices. To perform financial transactions requires customers to have skills and knowledge about the transactions of which outcomes customers are responsible for. For this reason, customers who feel capable to use the systems or e-banking services use more e-banking services. In this case, usefulness is the second issue to consider, because customers already know using the e-banking service will give them several benefits such as time saving and money saving due to low fees for online transactions. However, when customers feel that it is useful for them to join customer communities to obtain knowledge and information about financial transactions and other related knowledge, they may use the e-banking service more. Of course, in the case of COS use, customers need to have enough self-efficacy to deal with ebanking services. Future study needs to investigate this phenomenon in a more detailed manner to verify the finding of this study by developing an instrument incorporating the above discussion. With regard to the effect of general Internet selfefficacy on the e-service use behavior, customers may have different perceptions. Performing financial transactions requires knowledge and skills about the Internet technologies as well as finance specific applications to make sure the transaction is safely done as a customer expects. However, when it comes to joining and utilizing customer communities, customers may not worry about the outcome quality unlike in the case of financial transactions. Even though they don’t have knowledge and skill to use the Internet technologies, they join the community and acquire knowledge other customers posted. This issue is also subject to further study to check whether customers feel the way we argue in this study. Finally, the fact that perceived risk does not affect either TOS use behavior or COS use behavior may be explained by considering the technological and regulatory environment of Korea. In Korea, financial service users need to install a variety of security tools required by banks or the government. The security measures deployed by banks we studied or the general system of security for e-banking services imposed to use by regulations may make customers feel safe. This is also subject to further study. This result may come from cultural differences in security beliefs. Future study needs to identify what the real cause of the difference. This study is expected to contribute to the literature in two ways. First, this study investigates the use behavior of e-banking services that requires service users' active interaction with service providers to create value. In this study, we specify the type of services

according to the nature of e-banking services, which will provide a basis for future study on e-services. Second, we separate general beliefs and task specific beliefs such as finance-specific self efficacy and finance-specific ease of use to closely examine the effect of antecedents on different e-banking services. The findings indicate that task specific self efficacy and ease of use beliefs would have strong impact on use behaviors. Future research needs to rigorously test the task specific vs general belief hypothesis. This study also provides practical implications. First, this study gives some insight into the fact that different services need different factors to promote the use of the services. Practitioners need to understand what kinds of e-services are affected by what kind of factors. Then they may come up with proper measures to promote the use of e-services they provide and understand how to design their e-services

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