Technology Acceptance Model (TAM) (Previous Studies)

TAM has been examined and tested on different contexts, samples and technologies. A wide range of these studies were reviewed and can be classified into three groups. The first group focused on how individuals (users) accept or reject such systems and what determines their behaviours. The second group applied TAM to examine customers’ behaviours towards e-vendors, why customers accept or reject online shopping and what factors affect their behaviours. The last group will provide an overview for the studies that adopt TAM in the Internet banking context, and will be discussed in the Internet banking studies section (3.11).

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In terms of technology system acceptance, a large body of literature examines TAM to investigate users’ behaviour (Adams et al., 1992, Davis, 1993, Subramanian, 1994, Keil et al., 1995, Taylor and Todd, 1995a, Taylor and Todd, 1995b, Chau, 1996, Szajna, 1996, Igbaria et al., 1997, Jackson et al., 1997, Gefen and Keil, 1998, Agarwal and Prasad, 1999, Dishaw and Strong, 1999, Lucas and Spitler, 1999, Lederer et al., 2000, Venkatesh and Morris, 2000, Venkatesh, 2000, Chau and Hu, 2001, Venkatesh et al., 2002, Lu et al., 2003). Across these studies, different models were provided to examine individuals’ behaviours, and different factors were proposed and supported that influence users’ behaviours. Different factor relationships were proposed which will be highlighted in this section.

Adams et al. (1992) examined the psychometric properties of the usefulness and ease of use scales and proposed that perceived ease of use and usefulness were the main determinant of users’ behaviours towards electronic mail, voicemail, word processing, spreadsheets and graphics systems in Canada, finding that system usage was significantly influenced by perceived ease of use and usefulness. Davis (1993) examined why users accept or reject information systems by integrating system design features as external factors influencing perceived ease of use and usefulness directly and indirectly influence users’ attitude and actual system usage across two systems (electronic mail and text editor) and found that all the relationships were supported. Subramanian (1994) applied TAM to examine users’ usage future behaviours across two systems (voice mail and customer dial-up systems) in USA, finding that perceived usefulness had significant influence on future usage, while ease of use did not. In USA also, Keil et al. (1995) proposed a Usefulness/Ease of Use Grid that would help managers and system designers to understand different scenarios under different conditions of ease of use or usefulness. Taylor and Todd (1995a) combined TAM and TPB to investigate individuals’ behaviour for inexperienced and experienced users in a computing resource centre in Canada and found some variation in the regression weights across the groups, such as the relationship between ease of use and attitude, and perceived behavioural control and behaviour. In Canada also, Taylor and Todd (1995b) examined and compared TAM, TPB and DTPB to assess and evaluate which model best helps to understand usage behaviour in a computing resource centre and found that TAM was preferable in usage prediction, while DTPB provided a full understanding of usage behaviour and intention for managers and researchers. In Hong Kong, Chau (1996) examined the factors that influence Computer-Aided Software Engineering (CASE) and proposed that the implementation gap between the old and new system and transitional support would influence system acceptance

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through ease of use, near-term usefulness and long-term consequences and found that the implementation gap had a negative influence on ease of use and near-term usefulness, and transitional support had insignificant effect on near- and long-term usefulness but had significant influence on ease of use. In the USA, Szajna (1996) carried out a longitudinal study to examine and confirm empirically the revised TAM model on the electronic mail system and found that usefulness had significant influence on intention behaviour in pre-implementation and post-pre-implementation of TAM, while ease of use did not have any significant influences in both cases. Igbaria et al. (1997) developed a model based on TAM to examine personal computing acceptance determinants in small firms in New Zealand. Igbaria et al (1997) proposed that inter-organizational (internal computing support, training and management support) and extra-organisational (external computing support and training) factors would influence personal computing acceptance via perceived ease of use and usefulness. Meanwhile Jackson et al.(1997) integrated user involvement constructs (prior use, argument for change, intrinsic involvement and situational involvement) with TAM constructs (ease of use, usefulness, attitude and behavioural intention) to examine user behaviour towards PC and network systems. Gefen and Keil (1998) investigated the influence of perceived developer responsiveness on perceived ease of use and usefulness, and from perceived ease of use and usefulness on self-reported use in the expert (CONFIG) system.

They found that all the relationships were supported with the exception of the relationship between perceived ease of use and self-reported use. Agarwal and Prasad (1999) in USA, extended TAM to examine the role of individual differences (role with regard to technology, tenure in workforce, level of education, prior, similar experience and participation in training) in influencing users’ behaviour with the old system (operating system utilized a command-line interface) and new system (a standard GUI environment), finding variations in the results from one construct to another. In USA also, Dishaw and Strong (1999) integrated the Task Technology Fit Model (TTF) and TAM, comparing all the three models (TAM, TTF and TAM/TTF) on IBM 3090 mainframes and found that TAM explained user behaviour more that TTF or TTF/TAM. Lucas and Spitler (1999) carried out a study to investigate the user behaviours towards a workstation that was designed for private-client brokers and proposed that perceived system quality will have an indirect influence on use or intent to use and on jobs’ performance via perceived usefulness, ease of use and norms. Lucas and Spitler (1999) found that the original TAM’s variables were not supported, while social norms were supported and had significant influence on use or intent to use. Lederer et al.(2000) applied TAM to examine the antecedents of World Wide Web’s ease of use and usefulness in the

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USA so that website developers and mangers could be helped to improve websites’ usability and usefulness, the results of which supported TAM. Venkatesh and Morris (2000) conducted a longitudinal study to develop a research model by integrating subjective norm, gender and experience with TAM, and found the difference between men and women did not change over time. Venkatesh (2000) attempted to identify the perceived ease of use determinants and whether their importance can be changed by increasing users’ experiences by adopting a longitudinal study across three time points and three samples, proposing that perceived ease of use would be determined by internal control (computer self-efficacy) and external control (facilitating condition), intrinsic motivation (computer playfulness), and emotion (computer anxiety) and over time; perceived ease of use would be influenced by system usability and enjoyment. Venkatesh’s (2000) model was supported. Venkatesh and Davis (2000) conducted four longitudinal field studies to develop a model (TAM2) that was an extension of the original TAM by integrating key determinates of perceived usefulness (subjective norm, image, job relevance, output quality and result demonstrability) and find out how the influence of subjective norm on perceived usefulness and intention can be changed with improved experiences and voluntariness. They found that the theoretical extension was supported across all four studies. In Hong Kong, Chau and Hu (2001) carried out a study in the context of telemedicine technology in order to compare three models (TAM, TPB and DTPB) and found several limitations of TAM and TPB in predicting technology acceptance by professionals. Venkatesh et al. (2002) developed a model to examine how users’

perceptions were impacted by pre-training and training environment (user acceptance enablers). They found that the integrated model was better in explaining users’ perceptions than previous studies (Venkatesh and Speier, 1999, Venkatesh, 1999). In USA, Lu et al.

(2003) developed a conceptual technology acceptance model for wireless Internet, via mobile devices, and proposed that technology complexity, individual differences, facilitating conditions, social influences and wireless trust environment would be the important determinates of long-and-near term usefulness and ease of use, resulting in attitude and behavioural intention.

Most of the above studies applied and tested TAM in which system usage in the organizational context. The following studies will give an overview about the studies that applied TAM in the e-commerce context. Gefen and Straub (2000) applied TAM to explain the influence of perceived ease of use on IT adoption across different tasks (intrinsic and extrinsic tasks) in the context of e-commerce (online bookstores) in the USA and found that

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perceived ease of use influenced intention to use when a website was used for an inquiry task but not for purchasing task, while perceived usefulness affected intention to use in both inquiry and purchasing tasks and the results confirmed that extrinsic motivation is more important than intrinsic motivation in IT acceptance. In the USA also, Bhattacherjee (2001) developed a model that investigated the drivers of consumers’ intention to continue using B2C services, proposing that continuance intention would be determined directly by satisfaction, perceived usefulness and loyalty incentives and indirectly by confirmation.

Bhattacherjee (2001) found that all the proposed hypotheses were supported. The trust antecedents of Gefen et al. (2003b) and the technological attributes found in TAM were integrated into a theoretical model to examine customers’ behaviours towards online book or online CD vendors in the USA and found that intention to use online vendor websites was determined by trust, perceived ease of use and perceived usefulness directly and indirectly by calculative based trust, institution-based structural assurances, institution-based situational normality, and knowledge-based familiarity. In USA, Pavlou (2003) developed a theoretical model that integrated TAM with trust and risk perceptions to examine the key drivers of consumers in online transactions. Pavlou (2003) proposed that intention to transact will be directly and indirectly influenced by perceived ease of use, perceived usefulness, and perceived risk, and three control variables (reputation, satisfaction with past transactions and frequency) were proposed to influence trust, perceived risk and intention to transact, finding that the proposed model was supported. Lee et al. (2006) carried out research to examine the influence of Image Interactivity Technology (IIT) on customer behavioural intention in the USA by applying TAM and proposed that behavioural intention will be affected directly by customers’ attitude towards online retailers and indirectly by their perceived ease of use, usefulness and enjoyment. Lee et al. (2006) also proposed utilitarian shopping orientation, hedonic shopping orientation and level of IIT would influence perceived ease of use, usefulness, and enjoyment directly and found that the proposed model was supported. In the UK, Dennis et al. (2009) developed a conceptual framework to examine concepts of e-consumer behaviour by integrating both the e-consumer and technology viewpoints, proposing that behavioural intention will be determined by consumers’ attitude, trust, past experiences and learning. In Spain, Hernandez et al. (2009) conducted a study and developed a model to examine the differences between the adoption of e-commerce by potential purchasers, and experienced e-customers who have carried out at least one purchase, by applying TAM. They proposed that perceived self-efficacy would influence customers’ intention to purchase via perceived ease of use, usefulness and attitude and found that the influence of self-efficacy

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and usefulness on behavioural intentions increased when customers gain experiences, while the influence of perceived ease of use decreased with increasing experiences. In USA, Kim and Forsythe (2009) examined online shoppers’ adoption of three visual Sensory Enabling Technologies (SET) (2D larger view and alternative views, 3D rotation views, and virtual try-on). Kim and Forsythe (2009) proposed that attitude would be influenced by perceived usefulness, ease of use, and entertainment value of SET and actual will be determined by attitude, innovativeness and technology anxiety. They found that perceived ease of use and usefulness were strong predictors for customers’ attitude in all three SET technologies, while perceived ease of use was the strong predictor for attitude in the 3D rotation views technology. In the following section, this study will provide an overview of research that explains how technology be accepted across cultures.