Main behavioural models

Users and their perceptions are key factors in the success of newly introduced systems (Dinev et al., 2006; Hartwick & Barki, 1994; Suh & Han, 2003; Venkatesh, Morris, Davis, & Davis, 2003; Vijayasarathy, 2004; Warkentin et al., 2002). Researchers have attempted to explain the role of user perceptions in the adoption of new systems and technologies by using theories and models such as the Technology Acceptance Model (TAM) (Davis, 1989), Theory of Planned Behaviour (TPB) (Ajzen, 1991), Diffusion of Innovations Theory (Rogers, 1962) to explain the impact of different factors on users‟ intentions to use information technology. These models have also been used to predict the intention to use e-services (e.g. Brown & Buys, 2005; Carter & Belanger, 2003; Featherman & Pavlou, 2003; Horst et al., 2007; Hsu & Chiu, 2004; Lee & Rao, 2005; Nath, 2005; Sahai & Machiraju, 2001; Wu & Chen, 2005).

TAM was introduced by Davis (1986) (see Figure 3.1). It was proposed to explain users‟ intentions to use information technology solutions. The model proposes that perceived usefulness and ease of use jointly determine attitude toward using a system and this in turn influences actual level of use. Perceived usefulness was defined by Davis as "the degree to which a person believes that using a particular system would enhance his or her job performance" (Davis, 1989, p. 320). Ease of use is opposite to

complexity of use and it was defined by Davis as "the degree to which a person believes that using a particular system would be free of effort" (1989, p. 320). Davis (1993) tested the model and found that while both perceived usefulness and perceived ease of use played a role in predicting user attitudes toward using a system, the influence of perceived usefulness was 50% stronger than that of perceived ease of use.

Perceived usefulness Perceived ease of use Attitude toward using External variables Actual use Behavioural intention to use

Figure 3.1 TAM (Davis, 1986)

Venkatesh and Davis (2000) provided a theoretical extension of TAM that explains perceived usefulness and usage intention in terms of social influence and other factors as shown in Figure 3.2. In addition to representing the impact of usefulness perceptions on usage intentions, TAM2 also suggests that social influence (subjective norm,

voluntariness, and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use) significantly influence user acceptance and intention to use information technology.

Perceived usefulness Perceived ease of use Behavioural intention to use Actual system use Original TAM Subjective norm Job relevance Image Experience Voluntariness Result demonstrability Output quality

Figure 3.2 TAM2 (Venkatesh & Davis, 2000)

Venkatesh, Morris, Davis, and Davis (2003) examined and tested eight prominent information technology acceptance models and based on this proposed their Unified Theory of Acceptance and Use of Technology(UTAUT). The eight models that were tested were TAM (Davis, 1989), the Motivational Model (Davis, Bagozzi, & Warshaw, 1992), the Theory of Reasoned Action (Ajzen & Fishbein, 1980), the TPB (Ajzen, 1991), a model combining TAM and TPB (Taylor & Todd, 1995b), the Model of PC Utilization (Thompson, Higgins, & Howell, 1991), Diffusion of Innovations Theory (Rogers, 1962), and Social Cognitive Theory (Bandura, 1986). As shown in Figure 3.3, the main constructs in UTAUT that are proposed to have a significant direct role in influencing behavioural intention to use a system are performance expectancy

(perceived usefulness), effort expectancy (ease of use), social influence, and facilitating conditions. There are also four moderators of key relationships. These moderators are gender, age, experience and voluntariness of use. Venkatesh et al. (2003) argue that

proactively addressing the factors identified in UTAUT can help organizations to attract users to adopt and use new systems.

Performance expectancy Behavioural intention Use behaviour Social influence Facilitating conditions Effort expectancy Experience Voluntariness of use Age Gender

Figure 3.3 UTAUT (Venkatesh et al., 2003)

The theories and models presented above have been tested in many domains and many authors have adapted and extended them. The next section (Section 3.3.2) extends the discussion of key factors that have emerged from these models and that appear

particularly relevant to the research described in this thesis. The following sections then look specifically at research that considers e-commerce (Section 3.4) and e-government adoption (Section 3.5).

3.3.2. Key factors influencing system usage

Perceived usefulness is widely supported as a key factor that influences behavioural intention as previously shown in TAM, TAM2, UTAUT, and many other models (Carter & Belanger, 2005; Davis, 1989; Fenech, 1998; Karahanna, Straub, & Chervany,

1999; Lee, Braynov, & Rao, 2003; Saha, 2008; Venkatesh & Davis, 2000; Venkatesh et al., 2003; Vijayasarathy, 2004).

Social norms or subjective norms refer to users‟ beliefs as to whether most other people who are important to them want them to perform a behaviour (note: this study uses the term social norms). These referents include people such as supervisors, subordinates, family members and peers. Social norms has been shown to be a significant predictor of behaviour (Bagozzi, 1992; Fishbein & Ajzen, 1975; Vijayasarathy, 2004) and social norms are believed to influence behavioural intention to use information systems via their affect on perceived usefulness (Davis et al., 1992; Kim, Kim, & Shin, 2009; Lee, Lee, & Lee, 2006; Ruth, 2000; Saha, 2008; Venkatesh & Davis, 2000).

The role of previous experience on the intention to use systems has been examined by many scholars. It has been found to play an important role in influencing users‟ behaviour (Ajzen, 1991; Ajzen & Fishbein, 1980; Bagozzi, 1992; Fishbein & Ajzen, 1975; Taylor & Todd, 1995a). Ajzen and Fishbein (1980) believed that experience makes knowledge more accessible in memory. They argued that experience influences the users‟ behavioural intention and that direct experience will result in a stronger, more stable behavioural intention. In TAM2, experience moderates the relationship between subjective norm and perceived usefulness which in turn impact the intention to use. The UTAUT model proposes that prior experience indirectly impacts intention to use via perceived usefulness and subjective norm (Venkatesh et al., 2003). Taylor and Todd (1995a) examined whether the determinants of information technology usage are the same for experienced and inexperienced users of a system and found significant

3.4.

Factors impacting e-commerce services usage

Henderson, Snyder, and Byrd (2003) define e-commerce as commercial transactions between organizations and customers to sell and buy goods and services using any type of ICT. E-commerce services are one form of e-service as mentioned at the beginning of Section 3.2. This section examines previous research in order to better understand the different factors that impact on e-commerce adoption by users. Although the research described in this thesis focuses on e-government services, much of the relevant

literature relates to e-commerce. Therefore the research relating to factors that influence e-commerce service adoption will be reviewed first.

A number of studies have examined the factors that determine the adoption of e-commerce websites by users (e.g. Dinev & Hart, 2006b; Liu et al., 2005; Liu, Marchewka, & Ku, 2004; Nath, 2005; Park et al., 2004). Lee, Park, and Ahn (2001) built on TAM by incorporating the theoretical foundations of prior research in the theories of perceived risk (e.g. Bauer, 1960; Cox & Rich, 1964; Jarvenpaa, Tractinsky, & Vitale, 2000) to produce a new model called e-CAM to explain the adoption of e-commerce as shown in Figure 3.4.

Perceived risk in the context of transaction Purchasing behaviour Perceived usefulness Perceived ease of use

Perceived risk with product/service

Figure 3.4 E-CAM (Lee et al., 2001)

In particular, Lee et al. (2001) examined the impact of perceived ease of use, perceived usefulness, perceived risk with products/services, and perceived risk in the context of the online transaction on the consumer‟s purchasing behaviour. The antecedent constructs in the model were proposed to directly and/or indirectly affect consumers‟ adoption of e-commerce services. Park, Lee, and Ahn (2004) validated the e-CAM in Korea and the USA. Their study supported the generalizability of e-CAM, and they suggested that e-service providers should consider these contextual factors in order to facilitate consumers‟ adoption behaviour.

Several studies have specifically investigated the role of e-privacy concerns in adoption of e-services. Nath (2005) and Metzger (2004) studied consumers concerns about the availability of personal information on the Internet and their concerns relating to the possible abuse of personal information submitted online. Both studies found that e-privacy risk concern is a major factor that affects consumers‟ adoption of online services. Nath‟s (2005) study examined the influences on online information disclosure and found that online users‟ concerns relate to unlawful information exchanges and their fears of violation of their individual privacy rights. Nath found that online users are not

confident that their e-privacy is protected and this causes an increase in their privacy concerns. Nath added that privacy concerns also increase through exposures in the media. Nath‟s study concluded that privacy risk concerns negatively influence trust and online information disclosure. This study also investigated online information

protection awareness and Nath suggests that consumers who are knowledgeable about privacy practices and options for securing their online information should take suitable actions to protect their e-privacy.

Online privacy concerns in the e-commerce domain have also been studied by Dinev and Hart (2006b), who examined the relationships between privacy concerns related to finding online personal information and privacy concerns related to the possible abuse of such information, and intended e-services use. They found that privacy concerns impact negatively on the information exchange. They also found that privacy concerns increase as the amount and sensitivity of personal information submitted through websites increases.

Belanger et al. (2002) investigated the factors impacting online users when purchasing online goods and services. They found that trustworthiness of websites services plays an important role and suggested that when online users make the decision to provide personal information online, they rely significantly on their perceptions of

trustworthiness.

Liu, Marchewka, and Ku (2004) and Liu et al. (2005) also modelled the role of trust in the adoption of e-services. Their Privacy-Trust-Behavioural Intention Model as shown in Figure 3.5 suggests that there is a positive relationship between privacy and the degree of trust the consumer has in an e-commerce website, and that attempts to keep

data secure positively influence the customer‟s level of trust. The model also indicates that trust in a corporate website influences intentions to use the site again, and whether users would recommend it to others (Liu et al., 2005; Liu et al., 2004). The model clearly suggests the importance of trust in consumers‟ intentions to use and re-use e-services, and introduces the role of e-privacy protection by identifying security as part of privacy.

Privacy Trust Behavioural _intention

Dimensions:  Notices  Access  Choice  Security Dimensions:

 Level or degree of trust

Dimensions:

 Repeat purchase

 Visit again

 Recommend to others

 Positive remarks

Figure 3.5 Privacy-Trust-Behavioral Intention Model (Liu et al., 2005; Liu et al., 2004) As shown in Figure 3.6, Kim, Kim, and Shin (2009) integrated social norms and

electronic trust (eTrust) into their Airline B2C E-commerce Websites (AB2CEWS) acceptance model in order to determine their role in the acceptance of airline business- to-customer e-commerce websites. They hypothesized causal relationships between social norms and intention to reuse e-services, and between eTrust, and intention to reuse e-services. They found that both e-trust and social norms had a significant impact on users‟ intentions to reuse e-services.

Perceived usefulness Perceived ease of use Attitude toward use eTrust Subjective norms Intention to reuse

Figure 3.6 AB2CEWS acceptance model (Kim et al., 2009)

The importance of prior experience identified by Taylor and Todd (1995a) has been confirmed in the e-commerce domain by Suh and Han (2003) who found that users with higher levels of previous experience tend to accept more risk when using e-services. They also argued that previous experience is very important in creating and

consolidating trust among e-services users.

Malhotra, Kim and Agarwal(2004) proposed and tested a model of the relationship between Internet users' information privacy concerns and intention to release personal information at the request of a marketer (see Figure 3.7). They found that the model explained a large amount of the variance in behavioural intention and concluded that the model provides a useful tool for analysing privacy threats on the Internet in terms of trusting beliefs, risk beliefs, and types of information.

Collection

Type of information requested

 Less sensitive information

 More sensitive information

Behavioural intention Risk beliefs Trusting beliefs Internet users’ information privacy concerns Awareness Control

Figure 3.7 Malhotra, Kim and Agarwal‟s research model (2004)

Suh and Han (2003) investigated the impact of customer perceptions of security control on e-commerce acceptance. They found that perceptions of privacy protection and data integrity have indirect significant impacts on customers‟ intentions to use e-commerce through their influence on trust. Gilbert, Balestrini, and Littleboy (2004) also examined the role of trust as well as the influence of financial security and information quality on e-services adoption. They found that these factors could be barriers to adoption when users are not assured that their financial data are secure, and that e-services grant them accurate and relevant information. They therefore stressed the importance of having e-privacy protected and controlled to support the adoption of e-services provided by

Internet sites.

The research discussed above introduced perceived risk, privacy concerns, trust and previous experience as additional factors that play a role in the adoption of e-commerce services. The next section builds on this to look specifically at research in the