Integrating website usability with the electronic ... - Semantic Scholar

Behaviour & Information Technology Vol. 30, No. 2, March–April 2011, 181–199

Integrating website usability with the electronic commerce acceptance model David T. Greena and J. Michael Pearsonb* a

Governors State University, USA; bSouthern Illinois University, USA (Received 1 May 2009; final version received 16 March 2010)

This paper analyses the role of website usability in a B2C electronic commerce environment. The authors identify dimensions of website usability that have been examined in the literature and integrate those usability dimensions within an electronic commerce acceptance model using an e-commerce simulation. Structural equation modelling was used to analyse the relationship between several website usability and e-commerce variables (design credibility, content, interactivity, navigability, responsiveness, download delay, perceived usefulness, perceived ease of use, and satisfaction with design) as well as trust, perceived risk, and intention to transact. The results demonstrate that website usability does influence several outcomes that are important for businesses to attract and retain customers. Keywords: website usability; web design; B2C e-commerce acceptance; structural equation modelling (SEM)

1. Introduction Corporate websites contain a high degree of variation in their adherence to web design conventions and website usability standards (Cappel and Huang 2007). If usability and design factors are indeed proven to be tied to consumer behaviour, organisations and their web-design teams will have further evidence suggesting the importance of usability, and those organisations that do not place heavy emphasis on web design will have more reason to do so. In online consumer markets, the potential customer will ultimately make the final decision on whether to make a purchase, return to the site at a later time, or discard the site as a non-feasible alternative for making a transaction (Nielsen 2000). Although measures have been developed to evaluate specific design factors, e.g. website usability (Agarwal and Venkatesh 2002, Palmer 2002) and website quality (Loiacono et al. 2006, 2007), their inclusion in existing electronic commerce acceptance research models has generally been ignored. Using a review of related literature on website usability and e-commerce acceptance this paper takes an analytical approach to understanding the dimensions of website usability and their impact on transaction intention. Furthermore, the dimensions of website usability were included within a B2C ecommerce acceptance framework and empirically tested. The methodology, data analysis, results, and discussion are provided in the remainder of the paper.

*Corresponding author. Email: [email protected] ISSN 0144-929X print/ISSN 1362-3001 online Ó 2011 Taylor & Francis DOI: 10.1080/01449291003793785 http://www.informaworld.com

2. Literature review 2.1. Usability Usability is the most traditional concept in human computer interface (HCI) research. Usability can be defined as a measurable component of a product’s user interface that exists to some degree (Mayhew 1999). Mayhew’s definition leaves usability measurement open to a wide variety of dimensions, and therefore, it is important to examine additional views of usability and methods of testing usability. Although Mayhew (1999) provides a good starting point for understanding usability, the term usability has been applied in many different ways, making it a difficult-to-define concept. Seffah and Metzker (2004, p. 72) explain that ‘usability refers to both a set of independent quality attributes such as user performance, satisfaction, and learnability, or all at once, making it very difficult to precisely measure usability’. And without consistent terminology it is difficult to examine the concept of usability. One of the more frequently used definitions of usability is that of ISO 9241. The ISO 9241 standard defines usability as ‘the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use’ (Green and Pearson 2006, p.67). Quesenbery (2003) notes that the ISO 9241 definition of usability may have been acceptable in a context of enterprise or other work-related applications, but in the consumer world of online shopping, and information-seeking, the ISO 9241 definition does

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not provide a broad enough view of human interaction to describe the usability goals of either users or businesses. 2.2. Website usability as a valid research construct The focus of this study is usability of business-toconsumer (B2C) websites. There have been several studies that have attempted to explain or predict online customer perceptions within a B2C setting. B2C ecommerce is the ability of consumers to purchase products and services online using Internet technologies and associated infrastructure (Olson and Olson 2000). For example, McKnight et al. (2002) proposed a web-customer satisfaction model which includes several usability constructs (e.g. navigation and interactivity) that significantly influence online customer satisfaction. Szymanski and Hise (2000) also proposed an online customer satisfaction model which includes ease of navigation as a usability construct. Devaraj et al. (2002) included supportability as a part of their B2C channel satisfaction and preference model. However, these studies selected and included only a small number of website usability constructs into their models, and therefore, the full effects of website usability on online customer perceptions may not have been captured. Previous studies have found that a usable website creates a positive attitude toward online stores, increases return visits, and eventually stimulates online purchase (Becker and Mottay 2001). Browsing behaviour has also been examined but is very difficult to quantify (Tan and Wei 2006). Several studies have determined download delay to be one of the most important aspects of e-commerce quality (McKinney et al. 2002, Torkzadeh and Dhillon 2002, Pavlou and Fygenson 2006), seriously interfering with a site’s usability (Straub et al. 2002, Fui-Hoon Nah 2004). Hall and Hanna (2004) conducted an experiment that resulted in several findings for website usability: colours with greater contrast ratio generally lead to greater readability, colour combination did not significantly affect retention, preferred colours (i.e. blues and chromatic colours) led to higher ratings of aesthetic quality and intention to purchase, and ratings of aesthetic quality were significantly related to intention to purchase. 2.3.

Empirical tests of website usability

As noted earlier, the idea of website usability has been around for some time. Only recently, though, have there been attempts to develop and test website usability as a theoretical construct (Agarawal and Venkatesh 2002, Palmer 2002, Straub et al. 2002,

Tarafdar and Zhang 2005, Fang and Holsapple 2007). According to Palmer (2002), the measure of what users want in a website is an important area of study because the website is a primary user interface for net-enabled business (Straub and Watson 2001), information provision, and promotional activities (Jarvenpaa and Todd 1997, Wu et al. 2005, Harrison et al. 2006). Agarwal and Venkatesh (2002) developed an instrument that operationalises website usability into five dimensions: ease of use, made-for-the-medium, emotion, content, and promotion. Their findings suggested that the evaluation procedure, the instrument, as well as the usability metric exhibit good statistical properties. Palmer (2002) also created a metric/instrument for the study of website usability. Palmer suggested that robust metrics can be obtained from multiple sources to identify key usability elements for website design. Palmer’s study found that website usability factors (download delay, navigability, content, interactivity, and responsiveness) are important in explaining the success of websites. Both the Palmer and the Agarwal and Venkatesh website usability instruments were found to display nomological validity. Unfortunately, both instruments measure different characteristics of websites, although they each claim to measure website usability. Additional attempts at fully understanding website usability include Lee and Kozar’s (2004) study which identified 10 website usability factors with strong psychometric properties. Factors include consistency, navigability, supportability, learnability, simplicity, interactivity, telepresence, content relevance, credibility, and readability. Cappel and Huang (2007) examined 500 company websites using 11 measures, grouped into three categories: avoidance of Web design errors, adherence to Web design conventions, and inclusion of features to promote usability. They found that most websites could be improved if usability was considered in website design and ongoing development. 2.4.

E-commerce acceptance

Although it was not the original focus of the technology acceptance model (TAM), several studies have examined websites as the focus within a similar framework. A website can be viewed as an information technology (Gefen et al. 2003), thus online purchase intentions can be explained in part by the TAM (Davis 1989, Davis et al. 1989, Loiacono et al. 2006, 2007). Gefen et al. (2003) noted the TAM’s importance as a ‘parsimonious and robust model of technology acceptance behaviours in a wide variety of IT settings’. The underlying logic is that IT users (i.e. online customers of a website) react rationally when they elect to use an

Behaviour & Information Technology information technology (Gefen and Straub 2000, Gefen et al. 2003, Pavlou 2003). There have been attempts at developing an electronic commerce acceptance model based on specific parts of the TAM. Chiravuri and Nazareth (2001) combined the antecedents used by Lederer et al. (2000) and Fung and Lee (1999) to come up with a model which included ease of understanding, ease of finding, company reputation, and quality of experience. One recent TAM-based model that takes into account perceived risk was described by Featherman and Pavlou (2002), who defined perceived risk as the potential for loss in the pursuit of a desired outcome of using an e-service. E-loyalty was the focus of one study and was influenced by e-satisfaction, e-trust, and a set of e-tail quality factors (i.e. fulfilment/reliability, responsiveness, website design, and security/privacy). In particular, website design was found to positively influence e-satisfaction (Kim et al. 2009). Geffen et al. (2003) conducted research on experienced online shoppers showing that consumer trust is as important to online commerce as the widely accepted TAM antecedents, perceived usefulness and perceived ease of use. Suh and Han (2003) investigated the impact of customer perceptions of security control on e-commerce acceptance. McCloskey (2003, 2004) applied the TAM to electronic commerce participation, finding that ease of use has an impact on whether someone would buy a product online and on usefulness, while usefulness had an impact on the number of times a respondent purchased items online. Pavlou (2003) brought forth an even broader view of the online customer. Pavlou defined electronic commerce acceptance as the consumer’s engagement in electronic exchange relationships with web retailers (i.e. B2C commerce). Online transactions were viewed as instances of interactive marketing communications (Pavlou and Stewart 2000, Stewart and Pavlou 2002). Pavlou (2003) developed a research model that was tested using data from two empirical studies of online consumers. Both studies offered strong support for their proposed electronic commerce acceptance model. 3. Theoretical model The inclusion of website usability in an e-commerce acceptance model is appropriate, particularly based on the work of Konradt et al. (2003) who found usability factors as valid predictors of user intention and decision to buy from an online website. Their findings build on other studies that have also shown usability to be an important factor in purchasing from a website (Helander and Khalid 2000, Nielsen et al. 2001, Zviran et al. 2006, Joia and Oliveira 2008). In addition, the

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inclusion of website usability in an e-commerce acceptance model helps address the necessity for the consumer to actively interact with the retailer’s website by accounting for the technical factors that influence the consumer’s perceived ease of use of the website, perceived usefulness of the website, and trust in a website. The variables used in the current study’s proposed model e-commerce acceptance are based on a consolidation of a variety of empirically tested usability variables that had different names but contained the same or similar definitions and measurement items. 3.1.

Intention to transact

Intention to transact is defined as the consumer’s intent to engage in an online exchange relationship with a web retailer (Zwass 1998). The online exchange relationship can include sharing business information, maintaining business relationships, and conducting business transactions. Based on the online transaction process, B2C e-commerce acceptance necessitates that the consumer intends to use a retailer’s website to obtain and provide information and then complete a transaction by purchasing a product or service (Pavlou 2003). The theory of reasoned action (Fishbein and Azjen 1975, Azjen and Fishbein 1980, Sheppard et al. 1988) and the theory of planned behaviour (Azjen 1985, Azjen 1991) describe the positive relationship between behavioural intentions and actions. Bernadette (1996) and others (Pavlou 2003) found a consistently high correlation between intentions and actual use in TRA and TAM research. 3.2. Satisfaction Satisfaction is often defined as an ex-post evaluation of consumers’ experience with the service and is captured as a positive feeling, indifference, or a negative feeling (Anderson 1979). Satisfaction is usually not considered part of the TAM, but research demonstrates the importance of satisfaction with the website’s design and inclusion as an attitude variable in the tradition of the theory of reasoned action and theory of planned behaviour. Consumer satisfaction is addressed in Lee’s consumer satisfaction model (1998) as presented in Turban et al. (2000). The consumer satisfaction model suggests that repeat web purchase is determined by consumer satisfaction, which in turn is the result of several properties related to the web technology in general and to the individual website. Devaraj et al. (2002) examined customer satisfaction with the e-commerce channel in the setting of the TAM. Structural equation model analyses indicated that

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metrics tested through each model provided a statistically significant explanation of the variation in the EC consumers’ satisfaction and channel preference. The study found that TAM components, perceived ease of use, and usefulness are important in forming consumer attitudes and satisfaction with the electronic commerce (EC) channel. Shim et al. (2002) conducted a two-phase study that explored customer reactions to web retailers and the presentations of their products/services, attempting to identify website characteristics that contribute to customer satisfaction arising from the web-based shopping experience. Their findings suggest that two key elements in positive retail websites are convenience of site use and simplicity of site design as related to product/service characteristics and customer-service policies. The definition of satisfaction that is often used in usability research suggests being satisfied means that the user perceives that overall the system or feature is pleasant and easy to use (Faulkner 1998, Nielsen 1993). Most of the studies previously discussed addressed satisfaction as an antecedent to an intention to return to a website rather than the current intention to make a transaction. When discussing usability, we are referring to the specific design factors of the website, therefore it is appropriate to use the term design satisfaction when using satisfaction in a usability setting and as an antecedent to intention to make a transaction at a website. Therefore we present the following hypothesis: H1: Design satisfaction will positively influence intention to make a transaction at a website.

3.3. Perceived usefulness and perceived ease of use The TAM would argue that its two external variables (i.e. perceived usefulness and perceived ease of use) influence the acceptance of Internet technology (Pavlou 2003). Following Davis (1989), perceived usefulness will be defined as the degree to which consumers believe that a particular technology will facilitate the transaction process(Pavlou2003).Perceivedeaseofusewillbedefined as the degree to which a consumer believes that using a particular technology will be free of effort (Vijayasarathy 2004). Even though perceived usefulness was originally defined with respect to one’s job performance (Davis 1989), perceived usefulness refers to the performance of any generic task in non-organisational settings. This view is consistent with a number of studies such as Davis et al. (1989), Mathieson (1991), Sjazna (1994, 1996), Taylor and Todd (1995), Agarwal and Karahanna (2000), Rose and Straub (2001), and others

which measured perceived usefulness in settings other than an organisation. The TAM also posits a relationship between perceived ease of use and perceived usefulness. The general premise is that perceived usefulness directly influences intention, but perceived ease of use acts indirectly through usefulness (Davis 1989). Gefen and Straub (2000) extensively discuss this relationship, showing that in most cases perceived ease of use should affect use intentions through perceived usefulness. Based on previous research the following hypotheses are presented: H2: The perceived usefulness of an e-commerce website is positively related to design satisfaction. H3: The perceived ease of use of an e-commerce website is positively related to design satisfaction. H4: The perceived ease of use of an e-commerce website is positively related to perceived usefulness. 3.4.

Risk, trust and e-commerce acceptance

When participating in an online transaction process, consumers are concerned about the different types of risks that confront them. However, risk has been difficult to capture as an objective reality, and therefore, the literature predominantly has addressed the notion of perceived risk, which is defined as the consumer’s subjective belief of suffering a loss in pursuit of a desired outcome (Bauer 196). Online consumers have personal beliefs regarding the inherent risks involved in every transaction based on the limited information available to them (Dowling and Staelin 1994, Wang et al. 2008). The relationship between perceived risk and transaction intentions can be explained by the notion of perceived behavioural control, described in the theory of planned behaviour (Azjen, 1985, Azjen, 1991). Since attitudes typically lead to actions, reduction of perceived risk is expected to influence willingness to transact. In fact, Jarvenpaa et al. (1999) suggested that reducing the risk associated with buying from an Internet store would increase the probability of a consumer purchasing from it. Perceived risk has been also shown to negatively influence transaction intentions with web retailers (Jarvenpaa and Tractinsky 1999, Featherman and Pavlou 2002, Lopes-Nicolas and Molina-Castillo 2008). According to Pavlou (2003), the perceived risk associated with online transactions may reduce perceptions of behavioural and environmental control, and this lack of control is likely to negatively influence

Behaviour & Information Technology transaction intentions. However, consumers are likely to transact online if their risk perceptions about behavioural and environmental uncertainties are alleviated, so that they gain control over their online transactions. The theory of reasoned action predicts that consumers would be willing to transact if their risk perceptions were low (Fishbein and Azjen 1975, Azjen and Fishbein 1980). A hypothesis about risk perception is presented: H5: Perceived risk is negatively related to design satisfaction.

Trust is defined as a set of beliefs that other people will fulfil their expected commitments (Ba and Pavlou 2002). From the B2C e-commerce perspective, trust is defined as the belief or expectation that the word or promise by the online merchant can be relied on and the seller will not take advantage of the customer’s vulnerability (Geyskens et al. 1996). Recent business research has taken a comparable stand, defining trust as the expectation that other individuals or companies will behave ethically and dependably and will fulfil their expected commitments under conditions of vulnerability and interdependence (Gefen 2000). In the case of retail e-commerce, trust is particularly important. Customers cannot see the merchant, only the merchant’s website; they are unable to touch the merchandise, they can only see a representation; they cannot wander into a store and speak with employees, they can only browse the merchant’s site and communicate with employees via email, real-time chat, or phone. A customer at an online commerce site lacks concrete cues to comfortably assess the trustworthiness of the site and therefore must rely on new kinds of cues. The interpretation of these cues drives the development of customer expectations of the trustworthiness of the vendor (Resnick and Montania 2003, Chen and Barnes 2007, Greenberg et al. 2008, Jones and Leonard 2008). A certain level of uncertainty is a prerequisite for trust to exist (Koller 1998). Thus, when consumers willingly become vulnerable to a web retailer, they consider both the characteristics of the related technological infrastructure because of environmental uncertainty as well as the characteristics of the web retailer as a result of behavioural uncertainty (Tan and Thoen 2000, 2001). Following Pavlous’s (2003) finding, the following hypothesis about consumer trust was tested: H6: Consumer trust is negatively related to the perceived risk of a website.

3.5.

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Usability

Studies such as Lee and Kozar’s (2004) have attempted to develop definitions and measures of the underlying dimensions of website usability. Although these attempts have been valuable, the current environment requires a model that provides greater parsimony. Rather than having 10 or more dimensions of website usability, a review of literature has allowed the current study to condense the previous research into six separate usability specific variables. 3.5.1. Design credibility Design credibility is defined as a holistic concept that covers an online user’s perception of safety, reliability, security, and privacy during the navigation of the website (Lee and Kozar 2004). Studies have shown that the credibility of a website is one of the main challenges faced by e-commerce vendors. Nielsen (2000) noted that online consumers typically do not disclose their personal and financial information until they are convinced the website is secure. Nielsen also suggested that websites should implement multiple features such as encryption and privacy seals to assure security and privacy of online shopping. Perceived reliability is also a part of credibility. Unstable systems have been shown to frustrate customers and diminish their consumption experience (2002). One study found security features of a site as being the most valued attribute in security and privacy (Belanger 2002). As previously noted, trust and/or perceived risk have been part of several studies addressing ecommerce acceptance (Featherman and Pavlou 2002, Gefen et al. 2003, Pavlou 2003, Keats and Mohan 2004, Angriawan and Thakur 2008, Kassim and Abdullah 2008, Kim 2008). The introduction of design credibility to an electronic commerce acceptance model focuses on the design aspects that influence the user’s perception of trust, risk, and security threat. A hypothesis about design credibility is presented: H7: Design credibility is positively related to a consumer’s trust in a website.

3.5.2.

Content

Content will be viewed in a similar manner as Palmer (2002) who built on media richness theory (Daft and Lengel 1986), which suggests that the quality, accuracy, and reliability of the information exchanged across a medium are critical. Key website capabilities include comprehensiveness and completeness of information (Shapiro and Varian 1999). Content quality

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and variety have also been identified as key consumer measures when shopping on the Web (Jarvenpaa and Todd 1997, Leonard and Riemenschneider 2008, Liao et al. 2008). Palmer (2002) also noted that Bizrate (web.bizrate.com) captures information on breadth and depth of products offered, product information quantity, and quality and relevance. Content is defined as the amount, variety, and relevance of product text, graphics, and multimedia. Therefore, the following hypothesis is presented: H8: Content is positively related to the perceived usefulness of a website.

3.5.5.

Responsiveness

Customer reaction to a website provides valuable information to designers (Berry 1999). Shapiro and Varian (1999) suggested that user interface measures include feedback features and functions. Evans and Wurster (2000) suggest feedback and access to previously asked questions as important. Responsiveness is a key consumer issue when shopping on the Web (Jarvenpaa and Todd 1997). Responsiveness is defined in this study as the presence of feedback to users and the availability of response from the site managers. Thus: H11: Responsiveness is positively related to perceived ease of use of a website.

3.5.3. Interactivity The interface design of a website influences the ability of the user to manipulate and fully utilise the site. The ability to provide a personalised, customised interaction for the user allows website design that differentiates product and service offerings (Palmer and Griffith 1998). In the current study, interactivity is defined as the ability to customise the site’s look and content as well as provide interaction with the user. By customising the site’s look and content and provide this interaction, the logical goal seems to be that of making the site more useful for the user. Thus, the following hypothesis is presented: H9: Interactivity is positively related to perceived usefulness of a website.

3.5.4. Navigability Empirical studies have shown that highly navigable interfaces, such as websites, decrease error rates and learning time and increase performance and user satisfaction. Schneiderman (1998) notes that striving for consistency is the golden rule of interface design. Lee and Kozar (2004) asserted that consistent menu bars and links significantly influence online customer behaviour. The current study defines navigability as the uniformity of the design within and across the pages of a website. Navigability appears to be a more logical antecedent to ease of use because the formation of a uniform design has the primary objective of making the site easier to navigate from page to page, a form of ease of use. Thus, the following hypothesis is proposed:

3.5.6.

Galletta et al. (2004) conducted a study on download delay and found that relatively small increases in delay can have a profound impact on how users react to websites. In their study, delays ranged from 0–12 seconds, and they found significant results at the short side of this range. website designers can choose not to include slow loading elements such as longer audio or video clips, reducing initial access time (Levine 1996). For websites, response time is actually the download delay for each of these activities. That is, it is the initial request for access to the page and then each subsequent request for changing pages within the site (Rose et al. 1999, Pavlou and Fygenson 2006). This is a perception variable that is expected to result in a decreased perceived ease of use as perception of download delay increases. Therefore, a hypothesis is presented: H12: Download delay is negatively related to perceived ease of use of a website.

It should be noted that, although connection speed is an important consideration related to download delay, it was controlled in the current study. The experiment conducted measures a user’s perception of download delay rather than actual time for a site to load, which the authors believe may differ among users even when the connection speed is controlled (Figure 1). 4.

H10: Navigability is positively related to perceived ease of use of a website.

Download delay

Procedures

The literature review identified several dimensions of website usability, many of which contained similar properties, but labelled with a different name.

Behaviour & Information Technology Previous scales were adopted and modified when appropriate to ensure discriminant validity. Five individuals familiar with Web design and e-commerce

Figure 1.

Table 1.

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research evaluated the measures to provide logical validation of the measurement items for each construct (see Table 1).

Hypothesised model.

Consolidated usability constructs and measurement items.

Construct

Definition

Items

Design credibility (DC) based on Lee and Kozar (2004) Content (CN) based on Palmer (2002)

A holistic concept that covers an online user’s perception of safety, reliability, security and privacy during the navigation The amount, variety, and relevance of product text, graphics, and multimedia

Interactivity (INT) based on Lee and Kozar (2004) Palmer (2002) Sing (2004) Navigability (NAV) based on Lee and Kozar (2004)

The ability to customise the site’s look and content as well as provide interaction with the user

The website is safe. The website is reliable. The website provides security. The website provides privacy. Provides good product information. Presents a variety of products. Provided relevant product information. The content of the website was relevant to my task. The website offers customisation. Provides significant user interaction. I can customise the site’s look. I can customise the site’s content.

The sequencing of pages, well organised layout, and consistency of design protocols

Responsiveness (RES) Quesenberry (2003), Nielsen (2000), Palmer (2002)

The presence of feedback to users and the availability of response from the site managers

Download delay (DD) Rose et al. (1999), Palmer (2002)

The initial request for access to the page and then each subsequent request for changing pages within the site

The different pages of the website maintained a similar design throughout. Within each page, there was a uniformity in the page layout. The information on succeeding links from the initial page was predictable. The sequence of obtaining information was clear. The amount of information displayed on the screen was adequate. Provides information such as FAQs. Provides feedback mechanisms to questions and concerns I had. The site offers support to problems and errors that arise. The site prevented me from committing errors. The speed in which the computer provided information was fast. The rate at which the information was displayed was fast.

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A pretest was conducted to help refine wording and eliminate potential problems areas in the survey instrument (see Appendix 1). Ten doctoral level information systems students also helped to identify five B2C websites selling compact discs and books that had relatively low levels of familiarity. The study used sites with low familiarity as a method to control for brand loyalty, which is an important factor for consumers in making a purchase but not the focus of the current study. Since the purpose of this study was to test a B2C website usability e-commerce model, a separate group of 20 upper-level undergraduate business students used a rank order method to rank the five distinct retailers based on the constructs investigated in this study: design credibility, content, interactivity, navigability, responsiveness, download delay, trust, perceived risk, perceived usefulness, perceived ease of use, and satisfaction with design. Based on the grand mean of the rank ordered measures, three sites were selected, including the measures with the first (Buy.com), third (GiantDepot.com), and fifth (CDandBooks.com) mean rankings to ensure variability of the measures among the different treatment groups. Although website performance is important to several target populations, the current study focused on the online consumer in accordance with the Pavlou (2003), Palmer (2002), and Agarwal and Venkatesh (2002) studies. Our study utilised 360 undergraduate business students from a large mid-western university, which surpasses the recommended minimum case-pervariable ratio of five observations per item (Hair et al. 1998). Students that agreed to participate were randomly assigned to complete one of six combinations (i.e. treatments) of the three website/e-commerce scenarios. The scenario involved the process of searching, selecting, and inquiring about a compact discs or book of their choice that is available from the selected web retailer. By limiting the product to two possibilities, the researchers believed the variability found in product type would be constrained with both products considered low involvement products in that they are similar in price, risk, and brand loyalty (e.g. artists vs. authors) (Chang et al. 2004). The 20-minute activity that was presented to the participants of this study emulates the consumer online transaction process: information retrieval, information transfer, and product purchase (Jarvenpaa and Tractinsky 1999). Completed surveys that had more than two missing values for one construct were removed. The cases that had single items missing per construct were treated with the item mean substitution method in SPSS, an acceptable method for treating Likert-type scale missing data (Downey and King 1998). Of the three websites selected, each participant evaluated two

websites. Thus, participants were randomly assigned one of six permutations of two of the three websites. The participants did not actually purchase any products during the experiment. The participants provided their perceptions of the website and their intention to make a transaction. Following each ecommerce exercise, a questionnaire was given that focused on each web retailer they visited. The student participants were given extra credit points for their participation. With each participant evaluating two websites, the total number of usable responses totalled 688 (see Table 2). The majority of participants were male (61.0%) with 89% within the age range typical of a traditional college student (18–25). The origin of 88.1% of the participants was the North American/ USA region with 7.3% originating from Asia. The income levels were also typical of college age students with 78.2% of the participants having incomes of less than $10,000 per year. Approximately 62.5% of the participants spent one or more hours per day browsing the Web, and 81.4% had made online purchases in the past year. User demographics are presented in Tables 3 and 4. 5.

Data analysis

This study focuses on the relationships among several latent variables, tested by examining a full structural equation model (SEM). Structural equation modelling allows the researcher to accommodate multiple interrelated relationships in a single model. After developing the theoretical model and the visual representation of that model in a path diagram, the model must be specified in more formal terms, which is completed through a series of equations that define (1) the

Table 2. Order set per treatment group and number of participants by ordered set.

Number

website 1

website 2

1

Buy.com

2

Buy.com

3

GiantDepot. com GiantDepot. com Cdandbooks. com Cdandbooks. com

GiantDepot. com Cdandbooks. com Buy.com

4 5 6 Total

Cdandbooks. com Buy.com GiantDepot. com

No. of participants per ordered set 67 52 55 58 60 52 344

Behaviour & Information Technology Table 3.

Participant demographics.

Variable

Category

Gender

Male Female 18–25 26–35 36–45 445 North America/USA South America Europe Africa Asia Australia 5$1,000 $1,000– $4,999 $5,000– $9,999 $10,000– $14,999 $15,000– $19,999 $20,000– $24,999 $25,000– $29,999 4$30,000

Age

Region of origin

Income

Table 4.

Frequency (n ¼ 344)

Percent

210 134 306 28 6 4 303 3 6 7 25 0 105 91 73 46 9 6 4 10

61.0 39.0 89.0 8.1 1.7 1.2 88.1 0.9 1.7 2.0 7.3 0.0 30.5 26.5 21.2 13.4 2.6 1.7 1.2 2.9

Internet and online shopping demographics.

Variable Time spent browsing the Web

Use email

Own computer Online purchases made in the past month

Online purchases in the past year

Category

Frequency (n ¼ 344)

Percent

51 hour 1–2 hours 2–3 hours 3–4 hours 4–5 hours 45 hours Never Not very often Sometimes Quite often Yes No None 1 2 3 4 5 45 None 1 2 3 4 5 45

129 132 60 18 5 0 1 21 68 254 306 38 161 82 42 25 8 13 13 64 41 45 53 30 56 55

37.5 38.4 17.4 5.2 1.5 0.0 0.3 6.1 19.8 73.8 89.0 11.0 46.8 23.8 12.2 7.3 2.3 3.8 3.8 18.6 11.9 13.1 15.4 8.7 16.3 16.0

measurement model specifying which variables measure which constructs, (2) the structural equations linking constructs, and (3) a set of matrices indicating any hypothesised correlations among constructs or variables (see Table 5).

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This study includes 12 latent variables. It is important to test for the validity of the measurement models before testing the structural models because the latter is based on the former (Byrne 2001). For this study, both unrestricted exploratory factor analysis, using SPSS, and confirmatory factor analysis, using EQS, were used to modify the measurement models (exploratory analysis) and to validate the measurement models (confirmatory analysis). 6.

Results

6.1. Test of assumptions Outliers were detected using macros developed for SPSS by DeCarlo (1997). SPSS identified potential cases based on their contribution to the multivariate kurtosis using Mahalanobis distance measures (Hair et al. 1998, Stevens 2002). Mahalanobis distance evaluates the position of each observation compared with the centre of all observations on a set of variables (Hair et al. 1998). Cases with the highest Mahalanobis distance values are the most likely candidates to be considered outliers and should be examined. The results of the Mahalanobis distance analysis found five cases recommended for deletion, leaving a final count of 683 cases used for this study. The assumption of multivariate normality is an important consideration when using structural equation modelling. Hair et al. (1998), Byrne (2001), and Stevens (2002) have noted how the lack of multivariate normality could invalidate statistical hypothesis testing with SEM. Multivariate normality exists when each variable in a given model is normally distributed with respect to every other variable. Depending on the degree of normality violation, different estimation methods may be applied to test the statistical hypotheses. Multivariate normality is sometimes assessed by examining univariate skewness and kurtosis. Although helpful, univariate normality assessment is not sufficient for SEM (West et al. 1995). Mardia (1970) developed measures of skewness and kurtosis to assess multivariate normality. Bentler (1989) suggests that large values of the normalised estimate indicates significant positive kurtosis, while large negative values are indicative of significant negative kurtosis. Mardia’s normalised estimate was assessed through EQS. The data in the current study exhibited a value of 129.83 for the normalised estimate. The high value of this estimate indicates that the data is not normally distributed (Byrne 2001). Although the data was not normally distributed, SEM allows for analysis using corrected statistics. With non-normal data, one should not rely on the test statistics and standard errors that come from LS, GLS, or ML

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Table 5.

Structural equations.

Endogenous variable (Yj)

¼

T PU EOU PR SAT ITT

¼ ¼ ¼ ¼ ¼ ¼

Exogenous variables (Xj)

Endogenous variables (Yj)

þ

Error (ei)

b7T b8-PR þ b9PU þ b10PEOU b11SAT

þ þ þ þ þ þ

e1 e e3 e4 e5 e6

b1DC b2CN þ b3INT b4-NAV þ b5RES þ b6DD

methods that are most often used in SEM. EQS provides an alternative method to handle this situation. For example, the Satorra-Bentler scaled w2 (Satorra and Bentler 1994) adjusts downward the value of the model w2 from standard ML estimation by an amount that reflects the degree of observed kurtosis. This statistic is the generally accepted best alternative test statistic for model evaluation under nonnormality. Robust standard errors are also provided. EQS also provides fit indices such as the Bentler-Bonett Normed Fit Index (NFI), BentlerBonett Non-Normed Fit Index (NNFI), Comparative Fit Index (CFI), and Root Mean Square Error of Approximation (RMSEA). 6.2. Descriptive statistics Descriptive statistics (mean and standard deviation) of the measurement scales were examined. Each of the items (i.e. indicators or questions) were measured by a seven-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). The higher the mean score, the more agreement with the statement. The lower the score, the more the individual disagreed with the statement. 6.3.

þ

Exploratory factor analysis

Six of the proposed website usability constructs (content, download delay, design credibility, interactivity, navigability, and responsiveness) that were derived from earlier studies were examined with a principal components factor analysis using an Oblimin rotation. Items with loadings less than 0.5 were dropped. After removing four items (INT2, NAV4, NAV5, and RES4), a second factor analysis resulted in the anticipated six factors using the Kaiser eigenvalues criterion, explaining 80.38% of the variance in all items. Table 6 shows the factor loadings from the second factor analysis with the four items removed. Convergent validity is demonstrated as the indicators load strongly on their associated factors (40.50). Discriminant validity is achieved if each item loads

Table 6.

Exploratory factor analysis of usability variables. Factors

Items

CN

DD

DC

INT

NAV

RES

CN3 CN1 CN2 CN4 DD2 DD1 DD3 DC3 DC4 DC1 DC2 INT3 INT4 INT1 NAV2 NAV1 NAV3 RES2 RES3 RES1

0.939 0.897 0.886 0.882 0.390 0.431 0.293 0.483 0.465 0.505 0.601 0.342 0.362 0.600 0.335 0.208 0.358 0.478 0.423 0.507

0.395 0.368 0.358 0.411 0.950 0.943 0.923 0.358 0.382 0.422 0.399 0.123 0.204 0.271 0.419 0.404 0.396 0.396 0.416 0.321

70.520 70.560 70.487 70.542 70.419 70.426 70.356 70.939 70.916 70.911 70.870 70.291 70.340 70.457 70.349 70.304 70.367 70.418 70.474 70.429

0.380 0.435 0.348 0.377 0.172 0.189 0.146 0.305 0.312 0.311 0.370 0.937 0.934 0.724 0.172 0.168 0.198 0.360 0.381 0.361

70.301 70.254 70.291 70.358 70.416 70.430 70.414 70.318 70.331 70.327 70.326 70.167 70.198 70.151 70.885 70.884 70.755 70.300 70.339 70.304

70.533 70.507 70.455 70.532 70.413 70.425 70.357 70.451 70.436 70.434 70.482 70.377 70.390 70.449 70.303 70.264 70.492 70.871 70.844 70.820

more strongly on its associated factor than on the other factors (Hair et al. 1998). 6.4. Confirmatory factor analysis Confirmatory factor analysis using EQS 6.1 structural equation modelling software was conducted to test the reliability and validity of the six variables and subsequently the other variables from the proposed e-commerce acceptance model. For each CFA, the measurement model was first assessed in terms of overall fit of the data. The estimated loadings of the individually measured items to the overall construct were then examined for statistical significance. If any items were deemed as having unacceptable loadings or cross-loadings, the items were dropped and an adjusted CFA was run. See the indicator loadings and reliabilities of the included items as well as the CFA fit indices in Appendix 2. Table 7 shows how the composite reliability and variance extracted for all constructs exceed the recommended level of 0.70. For the variance-extracted

191

Behaviour & Information Technology measures, responsiveness (RES), with a value of 0.48, falls just short of the recommended 50% of variance explained. A decision was made to err on the side of having three items for responsiveness, rather than drop an item that is very close to the generally accepted mark for variance extracted. The other constructs exceed the acceptable variance-extracted level of 0.50. 6.5.

Structural model

Structural equation modelling (SEM) was used to test the relationships contained in the hypothesised model of the current study. In SEM, the relationships between the constructs can be identified by providing path coefficients for each hypothesis. Each estimated path can be tested for its representative significance (Hair et al. 1998, Byrne 2001). If an estimated t-value exceeds the critical value of 1.96, using an alpha of 0.05, then the null hypothesis that the parameter was equal to 0 is rejected and the hypothesised relationship was supported. As with the confirmatory factor analyses, robust methods and its related results and fit indices were examined due to multivariate nonnormality. Table 8 shows how the SEM yielded the acceptable measurement models, providing a few adjustments, including that of correlating the six endogenous latent variables (DC, CN, INT, NAV, RES, and DD). The fit indices of the hypothesised model were all acceptable with the NFI, NNFI, IFI, and CFI above the 0.90

Table 7. tracted.

Composite reliability and average variance ex-

Construct (latent variable)

Composite reliability

Variance extracted

0.89 0.92 0.87 0.94 0.84 0.82 0.87 0.87 0.79 0.71 0.73 0.86

0.72 0.72 0.70 0.58 0.64 0.61 0.62 0.62 0.66 0.55 0.48 0.67

ITT SAT PU EOU PR T DC CN INT NAV RES DD

Table 8.

7. Discussion 7.1. Hypothesis 1 Satisfaction with design was found to have a positive influence on intention to make a transaction with the website (b ¼ 0.809, p 5 0.05). This hypothesised relationship was significant, but a large part of the variance in intention to transact was not explained. This unexplained variance could be due to other product specific variables (e.g. product being examined, price of product). The results follow the pattern of the theory of reasoned action (TRA) and theory of planned behaviour (TPB), which has attitude (i.e. satisfaction with design) as an antecedent to behavioural intention. Peter et al. (1999) make a case for using satisfaction as an attitude, noting attitude as a psychological tendency that is expressed by evaluating a particular entity with some degree of favour or disfavour. This evaluative aspect is emphasised in TRA/TPB. In the setting of website usability, the entity in question is the usability of the site’s design. An extension to the research that may provide insight involves use of a parametric measure for measuring the probability intended purchasers switching their intention to purchase state after the survey is given (Bemmaor 1995). 7.2.

Hypothesis 2

Perceived usefulness was found to be a significant and positive predictor of satisfaction with the design of the site (b ¼ 0.267, p 5 0.05). Perceived usefulness is the degree to which consumers believe that a particular technology will facilitate the transaction process

Hypothesised structural model fit indices.

Model Hypothesised model a

threshold. The chi-square (w2 (780) ¼ 23365.14, p 5 0.00) and Satorra-Bentler scaled chi-square (S-B w2(713) ¼ 2302.61, p 5 0.00) were both significant at 0.01. Figure 2 provides the standardised path coefficients of the structural model. All of the hypothesised relationships were significant at the p 5 0.05 level except H5 (PR ! PU). Although significant, H12 was not supported because of the resulting positive relationship instead of the hypothesised negative relationship.

w2

Dw2

S–B w2

DS7B w2

NFI

NNFI

IFI

CFI

RMSEA

Model

23365.1

–

2302.61

–

713

0.901

0.923

0.930

0.930

0.057a

90% Confidence interval (0.055, 0.060).

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Figure 2.

Hypothesised structural model with standardised coefficients and variance explained.

(Pavlou 2003). This relationship was expected according to the original TAM (Davis 1989), which theorised perceived usefulness as an antecedent to attitude (i.e. satisfaction). 7.3. Hypothesis 3 Hypothesis 3 was supported in this study. Perceived ease of use was found to be a significant and positive predictor of design satisfaction (b ¼ 0.088, p 5 0.05). This relationship, although positive, was weaker than that of perceived usefulness and design satisfaction. The weakness of the relationships was expected, as previous studies based on the TAM explained perceived ease of use has a relationship with outcome behaviours going through perceived usefulness. Again, this relationship was expected based on the rationale listed for the previous hypothesis that sees satisfaction as an attitude variable, building on the TRA and TPB. The results show that if a site is easy to use, the user will be more satisfied with the design, an important antecedent of intention to transact. Thus, website designers can increase the user’s satisfaction with the design of the site by introducing tools (e.g. menus, fonts) that increase the perceived ease of use for the user. 7.4.

Hypothesis 4

Hypothesis 4 was supported in this study. Perceived ease of use had a significant and positive relationship with perceived usefulness (b ¼ 0.327, p 5 0.05). This finding was expected, following the findings of Pavlou’s (2003) e-commerce acceptance model. The

general premise is that perceived usefulness directly influences intention, but perceived ease of use acts indirectly through usefulness (Davis 1989). Gefen and Straub (2000) extensively discuss this relationship, showing that in most cases perceived ease of use should affect user intentions through perceived usefulness. 7.5.

Hypothesis 5

Hypothesis 5, setting perceived risk as a predictor of design satisfaction, was not supported. The relationship was not significant at the p 5 0.5 level. The Wald’s test suggested dropping the path between perceived risk and design satisfaction to improve the chi-square. It appears that an individual’s perceived risk contained in a website has no significant relationship with that individual’s satisfaction with the design of the site. Pavlou (2003) found that perceived risk was a predictor of intention to transact. Our hypothesis was built on the belief that this perception of risk would first influence an individual’s attitude (satisfaction with the design) then the intention to transact. 7.6.

Hypothesis 6

As proposed by Pavlou (2003), trust in the website was found to be a significant and negative predictor of perceived risk (b ¼ 70.450, p 5 0.05). Trust in ecommerce reduces uncertainty and other risks associated with the possibility that a web retailer might behave in a contriving manner. When people trust others, they assume that those they trust (i.e. the web retailer) will behave as expected, reducing the

Behaviour & Information Technology complexity of the interaction. Consumers often assume that a trusted web retailer will not engage in opportunistic behaviour (Gefen 2000, Pavlou 2003). The findings support previous studies that have shown how trust reduces the perceived risk (Luhmann 1979, Lewis and Weigert 1985, Mayer et al. 1995). When a web retailer can be trusted to show competence, integrity, and benevolence, there is much less risk involved in interacting with it. 7.7. Hypothesis 7 Design credibility was found to be a significant and positive predictor of trust (b ¼ 0.768, p 5 0.05). Design credibility is defined as a holistic concept that covers an online user’s perception of safety, reliability, security, and privacy during the navigation of the website (Lee and Kozar 2004). The study’s findings reiterate the importance for web designers of B2C sites to include design attributes that will offer the user a sense of safety, reliability, security, and privacy. Further research should examine which design attributes best help bring about the credibility perceptions from users. 7.8.

Hypotheses 8 and 9

Content was found to be a significant predictor of perceived usefulness (b ¼ 0.511, p 5 0.05). Hypothesis 8 is supported. Based on the findings of this study, content is an important predictor of perceived usefulness of a website. Web designers must find content that matches the intention of the user for a specific site, which can be difficult when a site offers multiple products. Interactivity is a significant predictor of perceived usefulness (b ¼ 0.218, p 5 0.05). Hypothesis 9 is supported. The significance of this relationship demonstrates the need for web designers to include attributes in a website that offer the user some type of customisation and interaction, items that make the user feel more connected to the site, and subsequently perceiving the site to be more useful for their needs. It is also possible that both content and interactivity are also antecedents of perceived ease of use. 7.9. Hypotheses 10, 11 and 12 Almost two-thirds of the variance in perceived ease of use is explained by navigability, along with responsiveness and download delay. Navigability is a significant predictor of perceived ease of use (b ¼ 0.224, p 5 0.05), thus Hypothesis 10 is supported. This hypothesis demonstrates the need for web designers to provide a consistent design throughout a website. Responsiveness has a significant and positive relationship with perceived ease of use (b ¼ 0.587,

193

p 5 0.05), thus Hypothesis 11 is supported. The relationship between responsiveness and perceived ease of use is stronger than that between navigability and perceived ease of use. The inclusion of feedback mechanisms within a website should be included by the web designers of B2C sites to increase the user’s perception of the site’s ease of use. The relationship between download delay and perceived ease of use was found to be significant (b ¼ 0.199, p 5 0.05), but there was not the anticipated negative (inverse) relationship; therefore, Hypothesis 12 is not supported. It is logical to expect that as the download delay increases the perceived ease of use decreases. The results yielded a positive, although weak, relationship between the two. This may be accounted for by the measurement of download delay as a perception, not the actual delay. Therefore, individuals may have different perceptions of what is a fast-loading page based on their prior experience browsing the Web. 8. Implications The motivation of this study was to better understand website usability and its role in an individual consumer’s acceptance of a website. The results of this study provide further evidence that website usability, as related to its design, is an important factor in the individual’s intention to make a transaction with a B2C e-commerce site. This study provided specific dimensions that should be examined by an organisation’s web designers before launching or redesigning a B2C website. This study built on the largely ambiguous e-commerce acceptance model that used the very general variables of perceived ease of use, perceived usefulness, and trust. By determining some of the antecedents for a website’s perceived ease of use, perceived usefulness, and trust, this study gives a more practical advice to web designers on the important factors that lead to the desired outcome of making a transaction with the site. Businesses continue to seek a better understanding of the factors that lead to a consumer’s online transaction; this study provides insight to this understanding. The results show that the design specific usability attributes, design credibility, content, interactivity, navigability and responsiveness play an important role in the online shopping experience. Managers who deliver B2C e-commerce services for an organisation will benefit with a diverse set of usability metrics that may be used to test for usability of existing sites or prototypes. The metrics will also be able to determine areas of weakness that may improve the likelihood that a user will make a purchase on the site. This study also has several contributions to the field of information systems. First, this study provided

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a comprehensive conceptual model of website usability and e-commerce acceptance in the B2C context. website usability has been extensively discussed in the practitioner literature as an important factor for website success, and has only seen limited empirical investigation in the academic literature. For sites with a business model that is more information driven rather than transaction driven, other outcome variables may provide more meaningful than intention to transact, such as intention to return or likelihood to make an unplanned purchase. Perceived usefulness of a site along with shopping enjoyment has been shown to predict intention to return to a website (Koufaris 2002). Second, this study represents the first broad examination of website usability and one of the first attempts at defining and identifying the dimensions of website usability. Along with simply addressing website usability in an empirical study, it is an important contribution to the field of research because it examines the specific dimensions that have been discussed in the research and came to a consolidated result of general dimensions for website usability study. Third, this study builds upon the foundation of the technology acceptance theory (Davis 1989), an important foundational theory in information systems research. The literature review revealed that website usability includes, and is an addition to the ecommerce acceptance framework, an e-commerce adaptation of the TAM. The results of the study provide a strong contribution to IS, e-commerce, and HCI research by demonstrating that website usability dimensions are antecedents of perceived usefulness and perceived ease of use. Fourth, this study lays the groundwork for further examination of the dimensions and relationships of website usability. Specifically, further examination of perceived risk, design satisfaction, and intention to transact variables should be examined to better understand how they interact. There are also limitations in this study. The use of subjects of this study was based on the assumption that students are likely customers of B2C e-commerce websites. McKnight et al. (2002) argues that students could be used as surrogates in this context because they are being placed in a similar individual decisionmaking situation and closer to the online consumer population in terms of age and education. Second, using a convenience sample is also considered a limitation in terms of representativeness of the population. Third, the design of the study was limited to a situation where customers would visit relatively unfamiliar websites that were given to them and not visited on their own. In most cases, before accessing a B2C website, one usually has some previous information about the site, such as a reputation based on

others’ experience, the company history, hyperlink from a search engine or other related website. Fourth, each participant visited two of three different websites. There may be some learning effect from the survey of the first website to the second. A completely randomised experimental design was used to account for any differences in the order of websites. Fifth, the data was not normally distributed, and although robust structural equation modelling tests were used to adjust for non-normal distribution, the ability to generalise the findings to the larger consumer population comes into question. Finally, performing an experiment using a simulated online shopping activity without an actual transaction presents external validity questions for the research results. 9.

Conclusion

In closing, this study found several website usability dimensions that were significant antecedents to other perception outcome variables related to online acceptance of a website. As expected website usability is more than a one-dimensional measure. website usability includes multiple aspects of a user’s perception of the site, including design specific attributes. The results of this study demonstrated how website usability may be understood, defined, empirically examined, and used in both research and practice as an important tool for understanding B2C e-commerce. Future research could explore other related constructs that better predict ecommerce acceptance, calling for a more comprehensive model of e-commerce adoption. Further research could also examine the relationship of age, gender, income, and other demographic variables on the website usability e-commerce acceptance model as well as applying the model across multiple cultural groups.

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198 Appendix 1.

D.T. Green and J.M. Pearson Survey instrument.

Construct Design credibility (DC)

Content (CN)

Interactivity (INT)

Navigability (NAV)

Item 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17.

Responsiveness (RES)

18. 19. 20. 21.

Download delay (DD)

22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40.

Intention to transact (ITT) Perceived risk (PR) Trust (T) Perceived usefulness (PU)

Perceived ease of use (EOU)

The web site is safe The web site is reliable The web site provides security The web site provides privacy Provides good product information Presents a variety of products Provided relevant product information The content of the web site was relevant to my task The web site offers customisation Provides significant user interaction I can customise the site’s look I can customise the site’s content The different pages of the web site maintained a similar design throughout Within each page, there was a uniformity in the page layout. The information on succeeding links from the initial page was predictable The sequence of obtaining information was clear The amount of information displayed on the screen was adequate Provides information such as FAQs Provides feedback mechanisms to questions and concerns I had The site offers support to problems and errors that arise The site prevented me from committing errors The speed in which the computer provided information was fast The rate at which the information was displayed was fast Given the chance, I intend to use this retailer’s web site. Given the chance, I predict that I should use this retailer’s web site in the future. It is likely that I will transact with this web retailer in the near future. The decision to transact with this web retailer is risky. The decision to transact with this web retailer is a negative one. The decision to buy a product from this web retailer has the potential for loss. This web retailer is trustworthy This web retailer is one that keeps promises and commitments I trust this web retailer because they keep my best interests in mind Overall I find this retailer’s web site useful I think this retailer’s web site is valuable to me The content on this retailer’s web site is useful to me This retailer’s web site is functional My interaction with this retailer’s web site is clear and understandable Interacting with this retailer’s web site does not require a lot of mental effort I find this retailer’s web site easy to use I find it easy to locate the information that I need in this retailer’s web site.

Behaviour & Information Technology Appendix 2.

199

Indictor Loadings and Reliability.

Item/Indicator Intention to Transact ITT1 ITT2 ITT3 Item/Indicator Satisfaction with Design SAT1 SAT2 SAT3 SAT4 Item/Indicator Perceived Usefulness PU1 PU2 PU3 Item/Indicator Ease of Use EOU1 EOU2 EOU3 EOU4 Item/Indicator Perceived Risk PR1 PR2 PR3 Item/Indicator Trust T1 T2 T3

Completely Standardized Loading

Reliability

0.95 0.98 0.89 Completely Standardized Loading

0.90 0.95 0.79 Reliability

0.92 0.93 0.97 0.96 Completely Standardized Loading

0.85 0.86 0.95 0.92 Reliability

0.88 0.95 0.95 Completely Standardized Loading

0.77 0.90 0.90 Reliability

0.82 0.79 0.92 0.85 Completely Standardized Loading

0.66 0.63 0.84 0.72 Reliability

0.80 0.93 0.93 Completely Standardized Loading

0.64 0.87 0.87 Reliability

0.87 0.90 0.84

0.75 0.81 0.71

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