In this chapter, I present the researches that have been done in the area of user acceptance of technology in the context of Internet banking, as well as adoption of Internet banking. First there is a brief overview of the field in general. After that I discuss about the relevant empirical studies done about Technology Acceptance Model and Internet banking, as well as other research about adoption of Internet banking. To complete the theoretical background, studies using Technology Acceptance Model with other information systems are included. As a summary of the reviewed literature, state of the art of the research this far is analyzed. Finally I discuss the major findings relevant to this study, and research limitations necessary to take into consideration.
Overview of the field
It is widely agreed that internet banking provides banks with a competitive advantage, by improving the quality of customer services and reducing the operational costs (Jourdan and Katz, 1999; Furst et al., 2000a). That is a fact, the number of banks that recognized the benefits of internet banking are increased every day all around the world.
A large number of empirical studies have also been conducted with respect to the customer perception and acceptance of internet banking services.
In this regard, , Joseph and Stone (2003) investigated the customer perception of the impact of technology on service delivery in the banking sector.
According to the findings of this research ". . . high scores on the ability to deliver service via technology appears to be correlated with high satisfaction with services deemed most important to customers" (Joseph and Stone, 2003, p. 200). Hence, availability of internet banking services appears to be very important for banks for customer satisfaction and retention. However, availability of internet banking services itself is not a sufficient factor to increase customer
satisfaction. User friendliness of the internet banking services appears to be an
important factor for customers to use these services. In a similar study, Lang and
Colgate (2003) found that customers who do not have IT gap, find it easier to use
internet banking services therefore they have higher-satisfaction levels than the ones who do not have IT skills. The empirical study by Broderick and Vachirapornpuk (2002) also show that the level and nature of customer participation in using internet banking services has the greatest impact on the perception of service quality.
Similar to above studies, there is a large number of empirical research indicating a
positive correlation between the availability of internet banking services and the
customer perception of bank service quality (Mols, 2000; Jun and Cai, 2001; Polatoglu
and Ekin, 2001; Shih and Fang, 2004). Hence, we expect to see that banks which are
concerned about their customer satisfaction in bank service quality are more likely to
adopt internet banking services. There are however some other factors such as
technological development and the cost of offering internet banking services that may
also have an influence on the diffusion of internet banking services. Mols (1998) argues
that the acceptance of internet banking is influenced by technological development, as
well as by the perceptions of bank customers and bank managers. If the technological
advancements make banking services cheaper and more user friendly we expect to see
more customers using the internet to obtain the banking services they desire.
User acceptance of technology has been studied repeatedly over the decades from various perspectives. The more important technology becomes as a part of our daily lives, the more companies expect their customers, suppliers and employees to be willing and able to utilize technology in various ways. It is understandable that at the same time research done in and around this subject has become more and more important. Several models describing and predicting the reasons for users accepting or rejecting a piece of technology have been created and evolved during the years.
However, most of them are very much alike, and based on same pioneering findings made decades ago.
Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB) and
Technology Acceptance Model (TAM) are probably the most used theories for Modeling user adoption of new technology. TRA and TPB are mostly used in the studies of social psychology to study the behavior of people. Researchers of system usage and information technology adoption have also extensively adopted them. TRA is in fact the ancestor of both TPB and TAM.
Technology Acceptance Model is an information systems theory, which is adapted from TRA. It is widely used for the purpose of predicting, explaining and enhancing common understanding of user acceptance of information technology in various areas.
This research uses the findings based on TAM as the basis for the theoretical model: Also because TAM has been used in many similar studies earlier. Several extensions of
TAM have been proposed and empirically validated also in studies conducted in the area of Internet banking - especially on the retail side of it. Overall, Internet banking, e-commerce and other information technology and information system adoption have been increasingly popular topics among researchers. This has been the trend over the last decade. In addition to Technology Acceptance Model, other theoretical approaches have been used to increase general understanding. As mentioned before, the theories remind very much each other. Regardless of the theory used, the researches support each other in terms of factors and determinants identified.
Technology Acceptance model is introduced in more detail in the following sections in order to explain the foundation for this research.
Technology Acceptance Model
Technology Acceptance Model (TAM) was initially suggested by Fred Davis 1989. It is one of the most studied and used models in the investigations of user acceptance of information technology. The model is adapted from Theory of Reasoned Action (TRA), which was originally proposed by Fishbein and Ajzen in 1975. Technology Acceptance Model is an information system theory, which purpose is simply to predict and explain the user acceptance of information technology. The model addresses the reasons why users either accept or reject particular piece of information technology. The revised model by Davis et al. (1989) is constructed from external variables (external stimulus), perceived usefulness and perceived ease of use (cognitive response), behavioral intention, and actual usage (behavior). (Davis et al. 1996)
Figure 1 Original Technology Acceptance Model
This figure is a description of the original TAM by Davis
The fundamental idea of the theory is that perceived usefulness and perceived ease of use influence the users' intention to use information technology either directly or mediating via attitude towards the behaviour, leading to actual usage of the system. Attitude Towards (AT) and Behavioural Intention (BI) are common with the Theory of Reasoned Action. Perceived ease of use (PEOU) has a strong influence on AT through perceived usefulness, but also directly. Perceived Usefulness (PU) has a strong direct influence via both AT and BI.
PU was defined as "the degree to which a person believes that using a particular system would enhance his or hers job performance". "A system high in perceived usefulness, in turn, is one for which a user believes in the existence of a positive use-performance relationship". PEOU was described as "the degree to which a person believes that using a particular system would be free from effort". (Davis, 1989). The original TAM was revised by leaving attitude from the model, as empirical validation proved that intention to use is only partly mediated by attitude (Davis and Venkatesh. 19961).
Figure 2 Revised Technology Acceptance Model
This figure is a description of the revised TAM by Davis and Venkatesh
Although TAM has been found to be very good in explaining user acceptance of technology, it has been further developed. In 2000, Davis and Venkatesh extended the theory and created TAM2. "TAM2 incorporates additional theoretical constructs spanning social influence processes (subjective norm, voluntariness, and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use)." (Davis et al., 2000). Furthermore Venkatesh et al. (2003) created a unified model called Unified Theory of Acceptance and Use of Technology (UTAUT). They compared eight models, developed and empirically validated UTAUT, which proved to outperform all the existing models from the past.
Szajna (1996) empirically tested TAM by measuring both self-reported and actual usage in pre- and post-implementation. She found the model to be successful in predicting both. Legris et al. (2003) critically reviewed TAM by using 22 articles from 1980 to 2001. The articles were empirical studies using TAM respecting its integrity. Only few studies used all of the original variables, mainly they left out AT, which is in coherence with the revised TAM.
The limitations of the reviewed researches were related to frequent use of students as the empirical sample, examining office automation software or systems development applications, and self-reported usage. The conclusion of the critical review was that TAM is a useful theoretical model, but it should be integrated to a model including variables from human and social change processes, as well as innovation adoption model. TAM explains normally about 40 percent of the variance in intention to use and usage behaviour, which further supports the perception of TAM's suitability in this type of research (Legris et al 2003, Pikkarainen et al. 2004).
Technology Acceptance Model and Internet banking
Quite a few researchers have applied TAM when studying acceptance of Internet banking. Lai et al. (2001) even made an invariance analysis concluding that TAM is a well suitable instrument for evaluating Internet banking acceptance, but also that the suitability is independent of the respondent characteristics such as gender, age and information technology competence. The current research done about Internet banking and Technology Acceptance Model are reviewed next, presenting the major findings of them and the empirical environment.
Sudarraj et al. (2003) used deconstructed TAM to measure the importance of usefulness and ease of use in online and telephone banking. They successfully validated the model with Canadian university students. Karjaluoto et al. (2002) built a model based on TRA and TAM, which was empirically tested with private Finnish retail bank customers. Their conclusion is, that "prior computer experience, prior technology experience, personal banking experience, reference group, and computer attitudes strongly affect attitude and behaviour towards online banking." (Karjaluoto et al. 2002)
Supporting findings were those of Lassar et al. (2005) who studied online banking adoption in the United States in the light of TAM. They concluded that the intensity of Internet usage is significantly influencing individuals' adoption of Internet banking. These findings suggest that the more experienced the consumers are in using the computers and the Internet, the more likely it is that they will start using Internet banking.
Another Finnish study investigated consumers' acceptance of online banking:
Pikkarainen et al. (2004) added perceived enjoyment, information on online banking, security and privacy and quality of Internet connection to the model. Surprisingly, they found only PU and information of online banking significantly affecting use of Internet banking services in Finland. Hong Kong students were used to empirically test another modification of TAM; in this study Chau and Lai (2004) also discovered that PU could be the only major factor directly influencing the attitude towards online banking. PEOU influenced also directly, but mainly via PU. Other measured factors like alliance services, personalization and task familiarity influenced through PU, and accessibility through PEOU.
Suh and Han (2002) added trust to the original TAM model. They studied their model by empirically evaluating responses from personal customers of five major banks in South Korea and discovered trust to be a very significant determinant of user acceptance of Internet banking. Eriksson et al. (2004) made the same conclusion while studying the meaning of trust with Estonian private customers. Trust had a significant positive effect on both PEOU and PU, out of which PU appeared to be stronger in predicting the intention to use Internet banking.
Trust was handled also by Wang et al. (2003). Their research aimed on recognizing the determinants of user acceptance of Internet banking. In this research they introduced perceived credibility as a new factor to TAM, in addition to self-efficacy, perceived usefulness and perceived ease of use. The model was empirically tested by phone interviews with Taiwanese consumers. Surprising results were found: perceived ease of use and perceived credibility were more significant than perceived usefulness in predicting the behavioural intention to use Internet banking. The surprising factor in this way, that majority of TAM related research has concluded that PU is the ruling factor over PEOU. Self-efficacy again was found to have significant effect through the three abovementioned factors.
Adoption of Internet banking
Factors familiar from TAM have been used in studies based on other theories and theoretical frameworks. The research methods and results resemble each other very much. Liao and Cheung (2002) empirically measured perceived usefulness and its attributes with retail customers in Singapore. They found out that "individual expectations regarding accuracy, security, transactions speed, user friendliness, user involvement, and convenience were the most important quality attributes in the perceived usefulness of Internet based e-retail banking".
Supporting some of the findings in Singapore, ease of use, Internet accessibility, awareness, trust and security concerns, convenience and attitude towards change were identified as main factors that affect the adoption of Internet bank services in Malaysia (Sohail and Shanmugham, 2003). Rotchanakitumnuai and Speece (2003) made a qualitative research among Thai corporate customers, which revealed that for corporations trust and security concerns were major barriers together with lack of organizational support (lack of IT resources, knowledge, management support, and training).
Akinci et al. 2004 compared users and non-users in the process of trying to identify the factors influencing adoption among sophisticated consumer segments in Turkey. They stated that non-users were not aware of all the benefits of Internet banking and did not believe in receiving adequate help for problem solving when using Internet services. The non-users preferred traditional channels because of lacking in confidence in using Internet banking and worrying about making incorrect transactions, where as the users believed quite the opposite. These problems were identified already by Sathye (1996) in Australia almost 10 years ago: difficulty in use, resistance to change, lack of awareness, and benefits of Internet banking were standing out as the obstacles for beginning to use the online services. The research results suggest that the problem of difficulty to use could be addresses by banks giving better education to the customer.
According to Sathye, Customers also expect the banks to give comprehensive information on the benefits before adopting the service.
Research on Technology Acceptance Model
Igbaria and Iivari (1995) extended Technology Acceptance Model in research about the effect of self-efficacy on computer usage in Finnish companies. Their TAM incorporates self-efficacy and the determinants of it (experience and organizational support) as the factors having an impact on computer anxiety, perceived ease of use and perceived usefulness and finally the actual use of computer technology. Selfefficacy, computer experience and organizational support were proven to have significant direct effect on perceived ease of use. The results imply that "perceived ease of use plays very important role in mediating the relationships between experience, anxiety and self-efficacy and perceived usefulness." Furthermore, "self efficacy, computer anxiety, perceived ease of use and usefulness partially mediate the effect of experience and organizational support on self-reported usage behaviour" (Igbaria and Iivari, 1995).
In line with the findings of the studies in Internet banking, Igbaria and Iivari, also stated that perceived usefulness had the biggest direct effect on actual system usage. Davis and Venkatesh (19962) then again modelled the antecedents of perceived ease of use, concluding that one of the most important variables influencing perceived ease of use was self-efficacy.
Deriving from Iivari and others, McFarland and Hamilton (2004) studied computer anxiety, system quality, prior experience, others' use, organizational support and task structure and their influence on computer-efficacy, perceived usefulness, and perceived ease of use and system usage. They discovered that system usage is significantly influenced by all of the abovementioned factors. They empirically tested the model with answers from users in US companies.
Yi and Hwang (2003) again studied self-efficacy, enjoyment, and learning goal orientation also in the context of TAM with university students. They used web-based class management system as the piece of technology examined. Self-efficacy appeared to directly influence the use, whereas enjoyment and learning goal orientation mediated through self-efficacy, usefulness and ease of use. Usefulness and ease of use in turn influenced the decision to use through behavioural intention.
There are many similarities between adopting other e-commerce activities and Internet banking. In many ways the reasons for adoption or rejection are alike. Eastin (2002) examined four different e-commerce activities (shopping, banking, investing and online services) and their diffusion in the United States. The outcome was that selfefficacy, amount of internet use, perceived convenience, perceived economic advantage, and overall adoption of similar innovation positively have positive influence to the overall adoption of e-commerce. According to them, perceived risk has a negative impact, and therefore it works as a barrier to adoption of any kind of ecommerce.
Jiang et al. (2000) utilized TAM in their empirical study about user behaviour and ecommerce.
Their model had five constructs: utilization of the Internet, near term consequences, facilitating conditions and experience with the Internet. They found out that the most important driving factor influencing the utilization of the Internet is prior experience. Another significant positive relationship was found between facilitating conditions and utilization of the Internet. This implies that the more familiar the users are with the Internet, and the better they feel they can get information from the sites, the more likely they are to use the Internet service in question.
Summary
Technology Acceptance Model was chosen as a basis for this study. The reason for choosing it is, that the model has been successfully used in several previous researches related to retail bank customers. Additionally, similar determinants can be acknowledged to influence the user acceptance and adoption of Internet banking, whether or not these studies have been using Technology Acceptance Model as the framework.
The following seven items have been identified as common determinants of predicting the adoption of Internet banking and other type of e-commerce or information systems, and therefore selected for closer investigation in this research:
Perceived
Usefulness
"The degree to which a person believes that using a particular system would enhance his or hers job performance" (Davis,
1989)
Perceived Ease
of Use
"The degree to which a person believes that using a particular
system would be free from effort". (Davis, 1989)
Self Efficacy
A person's estimate of his/her ability to cope with using a particular system.
Previous Experience
Prior experience with similar technology.
Organizational
Support
The importance of support the customer receives from his own organisation.
Bank Support
The importance of support the customer receives from the
vendor, in this case a bank.
Awareness
The level of awareness about the particular system and using
It.
