Web Acceptance Model (WAM): Moderating effects of user experience

Information & Management 44 (2007) 384–396 www.elsevier.com/locate/im

Web Acceptance Model (WAM): Moderating effects of user experience§ J. Alberto Castan˜eda *, Francisco Mun˜oz-Leiva, Teodoro Luque University of Granada, Spain Received 13 April 2006; received in revised form 18 November 2006; accepted 25 February 2007 Available online 18 May 2007

Abstract Our study empirically examined how Davis’s Technology Acceptance Model (TAM) helped managers predict a user’s intention to revisit a website and how this changed over time as a user gained experience of the Internet and the website. The user’s experience of the website played a moderating role. For less experienced users, perceived ease of use was found to be a more important factor in deciding to revisit the website, whereas perceived usefulness had more effect on more experienced users. Thus, web designers can identify and remove web factors that hinder user acceptance and address underlying obstacles to post-adoption usage. The novelty of the study consisted in applying TAM to a free-content website while considering the moderating effects of Internet and website experience. Significant practical implications can be derived from the results. # 2007 Elsevier B.V. All rights reserved. Keywords: Internet experience; Website experience; Website acceptance; Technology Acceptance Model; Free-content website

1. Introduction The analysis of the main objectives of most websites, which are generally considered to be its acceptance and the user’s intention of use has been somewhat neglected. Website designers need to know if a new website will be accepted. An analysis of the reasons why a system is not successful can only be achieved by rigorous research, which should identify corrective actions with a view to boosting its acceptance.

§ Study financed by research project SEC 2003-09231 of the Ministry of Science and Technology’s R&D&I National Plan and FEDER. * Corresponding author at: Department of Marketing and Market Research, University of Granada, Facultad de Ciencias Econo´micas y Empresariales, Campus Universitario la Cartuja s/n, 18071 Granada, Spain. Tel.: +34 958 240 915; fax: +34 958 240 695. E-mail address: [email protected] (J.A. Castan˜eda).

0378-7206/$ – see front matter # 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.im.2007.02.003

Our study was initiated to empirically test the ability of TAM to explain the acceptance of a specific website. It focused in particular on the moderating effect of user experience on his or her intention to use a website as discussed by Ma and Liu [42] in their meta-analysis. Although there has been some success in expanding TAM, our research was based on the original parsimonious model with usefulness and ease of use as the only antecedents of IT acceptance. Given that interaction between user and website takes place through web interfaces, the decisions to accept and continue using a website depend on these beliefs. The TAM has also been applied successfully to explain website usage (e.g. [23,38]). Gefen et al. [24] tested the moderating effect of experience by the TAM model applied to an online store. We extended their work in three directions. First, we tested TAM moderated by experience in a free-content site. Second, they considered both inexperienced and

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

experienced users, dealing with pre- and post-adopters. However, according to Bhattacherjee and Premkumar [5], the moderating effect of user experience remains significant in the post-usage stage, which we aim to test. Thirdly, they only considered the moderating effect of website experience. However, the user’s experience of the Internet itself was thought also to explain customer behavior. Thus, our study can be considered complementary to the literature focused in the moderating effect of user experience on site acceptance and use. On the basis of the meta-analyses of TAM by Lee et al. [40] and King and He [37], as well as an ad hoc search through the literature, 66 studies were found discussing Internet user acceptance (see Table 1). Of these, 18% were centred on the acceptance of the Internet as a medium, 45% on the acceptance of ecommerce and e-commerce sites, 12% on e-mail, 12% on e-learning, and 8% on other Internet-mediated services. Only the remainder (less than 5%) were centred on free-content websites. This, along with the qualitative and quantitative importance of free-content websites on the Internet, prompted our decision to work in this area. A web-based survey was conducted to obtain data. A total of 2813 Internet users responded, allowing us to analyse the acceptance of a website based on user beliefs and the moderating effects of Internet and website experience on these determinants. 2. Theoretical framework and hypotheses 2.1. The determinants of website acceptance As postulated in the Motivational Model [17], Internet user behavior will vary with the motivation for its use. In general, there are two kinds of motivation: extrinsic and intrinsic. The first occurs when a user is visiting a website with an aim other than mere surfing, focusing user evaluation of the website primarily on its

385

functional aspects. The second implies that the use of the website is an end in itself, and the user’s behavior will be mainly driven by hedonistic aspects [59]. These motivations, albeit varying with individuals and use conditions, are related to the type of website [64]. While the primary motivation for the use of an ecommerce website is extrinsic and for an entertainment site intrinsic, on an informational website both motivations will occur. Nonetheless, no clear-cut links should be presumed between a website type and a single type of motivation. Rather, one should assume the presence of different kinds of motivation [28]. Such motivations result in different user behaviors, depending on the type of website being visited. We centred on the acceptance of a free-content website by post-adopters; the use of this website category shows motivational differences compared to the use of ecommerce sites. According to Atkinson and Kydd [1], perceived usefulness is more related to extrinsic motivation while ease of use is more linked to intrinsic motivation. In keeping with this, we expected that, for e-commerce websites, perceived usefulness would be a more important factor than for free-content websites and that ease of use would take on greater importance for the latter. There is consistent evidence of the usefulness– attitude relationship from prior research [43,50]. Furthermore, TAM proposed a direct relationship between usefulness and behavioral intention. This was based on the idea that, within organizational settings, people form intentions towards behaviors they believe will increase their job performance, over and above whatever positive or negative feelings may be evoked towards the behavior per se. Ease of use has a double impact on attitude: selfefficacy and instrumentality. While efficacy is one of the main factors behind intrinsic motivation and affect directly attitude [2], improvements in ease of use can

Table 1 Classification of studies centred on Internet acceptance according to their specific focusa Category

Number of studies

Percentage (%)

Most recent references

Adoption of free-content websites E-commerce Internet services: www Internet services: e-mail E-learning Others: type of connection, telemedicine, online gambling, intranet, etc.)

3 30 12 8 8 5

4.55 45.45 18.18 12.12 12.12 7.58

[26,29,60] For example For example For example For example For example

[11,49] [50,53] [32,36] [41,47] [12,30]

Source: Elaborated as part of the study. a The list of bibliographical references for this empirical review has not been included due to reasons of space but will be made available to the reader upon request.

386

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

also contribute to increased efficiency thought its effect on usefulness. Specialist literature has consistently shown the key importance of perceived usefulness in the prediction of intended system usage. This is because most studies have tested acceptance of IS for use at work. The motivations for the use of such systems are functional and based on perceived usefulness while non-functional ones are associated with the search for new and pleasurable experiences [56]. Therefore, the Internet could be considered an instrument and the individual would be interested primarily on the outcome of the process and secondly on Web performance. The relationship between the attitude towards a given system and the behavior intention is both obvious and vital for this kind of models [10,22]. Therefore, a positive attitude towards a website will have an effect on its present and future acceptance. Finally, most of the literature focused on behavioral intention as a dependent variable. Accordingly, we focused on intention as the dependent variable for three reasons [3,31]. First, studies overwhelmingly supported a strong positive association between intention and IT acceptance and retesting this association would not serve any new purpose. Second, our subject sample consisted of individuals who had already accepted website services; lack of variance in behavior would have made the intention-behavior association meaningless. Third, individuals are aware of their decisions to accept a technology; therefore, acceptance can be explained by the underlying behavioral intention.

marketing. Venkatesh et al. [63], in their Unified Theory of Acceptance and Use of Technology (UTAUT), identified four moderators which affected effort expectancy (ease of use), including experience. But that effect was not received by performance expectancy (usefulness). This moderating effect of experience makes the relationship between ease of use and behavior stronger for users with limited experience. The arguments put forward by Koufaris et al. [39] seemed to imply that individuals with limited experience of use of a system evaluated it superficially, ease of use being a stronger determinant of future intention of use than for users with ample experience. However, experienced users evaluated a system in a more in-depth way and, consequently, they would use perceived usefulness to a greater extent than inexperienced ones. This proposition was founded on the premise of the postulates of the Heuristic-Systematic Model [14]. A customer will act with minimum effort in evaluating an element (a website). Thus, at first, the customer will process the website heuristically drawing on aspects that are easy to evaluate (ease of use). Always when the customer possesses sufficient motivation and ability (experience of use), he or she will carry out systematic processing to assess the more complex aspects of the website (usefulness). On the basis of the literature reviewed we felt that there was a moderating effect of user experience on the importance of ease of use and perceived usefulness as determinants of a future intention to use a website. This became the main hypothesis of our study.

2.2. User’s experience of the website and Internet

2.2.2. Levels of user experience of the Internet Once a need to acknowledge user experience as a moderator of the determinants of future use of a website has been justified, we shall proceed to delimit the concept of experience. For an electronic market, experience can be classified with two dimensions:

2.2.1. Moderating effect of experience User beliefs are key perceptions driving IT usage. They may change with time as users gain experience. Studies comparing new versus experienced users of IT suggested the need to refine TAM based on the extent of experience [36,58,62]. In the Internet context, user experience was considered to be one of the main factors explaining the behavior of an individual and contributing to the distinction between two different Internet surfing behaviors: goal-directed and exploratory [27]. Authors supported the claim that the more experienced users normally exhibited targeted behavior while e-novices opted for the general exploration. As Thorbjornsen et al. [61] pointed out, owing to the newness of the Internet, there are major differences in customers’ experience of the Internet, and these would play a vital role in the effectiveness of Internet

 Type of activity. Jarvenpaa et al. [33] distinguish between experience in surfing and buying. Why distinguish between these two categories of experience? For one thing, even though general Internet use is growing (in EU15 from 41% of individuals in 2002 to 56% in 2006), buying online continues at rather low levels (4.1% of commerce in EU15) [20]. That, together with the qualitative leap in making a move from surfing to buying, makes it convenient to draw a distinction between these two.  Reference level. From the most general level of experience of the medium to the most concrete level of experience of a specific website, it is possible to

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

distinguish different reference elements which the individual can have experience of. General behavior on the Internet requires a study of the experience at the highest level, that of the medium, but study of a website makes it also necessary to consider the user’s experience with that specific website. This implies that the antecedents of user behavior at a specific level are affected by the user’s experience at two levels. Jarvenpaa et al. [34] implicitly recognize that postulate in acknowledging the importance of considering experience of the Internet as part of the users perceptions and beliefs about a specific website. Consequently, we considered the impact of a user’s experience at both the Internet and specific website on his or her behavior. 2.3. Model and hypotheses We used WAM (Fig. 1) as the model in our research on predicting the ways in which individuals decide to revisit a website. It led to the following hypotheses: Hbasic. There is a user experience moderating effect on the importance of ease of use and perceived usefulness as determinants of the future intention to use a website. This hypothesis had to be divided, depending on the experience of the individual. Moreover, this moderating effect affects the relationships between both ease of use and usefulness with website acceptance, giving: H1. There is an Internet experience moderating effect on the importance of ease of use and perceived usefulness as determinants of the future intention to use a website.

387

H1A. The effect of perceived ease of use on attitude is significantly lower in website users with more Internet experience. H1B. The effect of perceived usefulness on attitude is significantly higher in website users with more Internet experience. H1C. The effect of perceived usefulness on intention of use is significantly higher in website users with more Internet experience. H2. There is a website experience moderating effect on the importance of ease of use and perceived usefulness as determinants of the future intention to use a website. H2A. The effect of perceived ease of use on attitude is significantly lower in users with more website experience. H2B. The effect of perceived usefulness on attitude is significantly higher in users with more website experience. H2C. The effect of perceived usefulness on intention of use is significantly higher in users with more website experience. 3. Methodology: sample and scales used Data was collected by a web survey located on a portal, http://www.PulevaSalud.com, offering free information on health, nutrition and general well-being. This is an established Internet reference site with over 450,000 monthly sessions in 2007. Although Internet access varies, most surveys have indicated that about half the users access health information [19]. Recent

Fig. 1. Website Acceptance Model (WAM).

388

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

Table 2 Technical specifications of the study

Table 3 Characteristics of the sample

Date of field work

May–June 2004

Categories

Percentage (%)

Target population Method of sampling

Visitors to http://www.PulevaSalud.com Non-probabilistic: self-selection by the respondent through banners on the http://www.PulevaSalud.com website and promotions on generic portals (e.g. http://msn.com) 2813 Website survey with incentive

Gender Male Female

22.8 77.2

Age group From 15 to 24 From 25 to 34 From 35 to 44 Over 44

20.9 39.7 21.9 17.5

Education level None Primary education Secondary education Higher education DK/NR

0.1 8.1 40.2 51.3 0.3

Main occupation Working Studying Other DK/NR

73.3 13.5 12.5 0.7

Marital status Single Married Other DK/NR

43.5 41.5 14.7 0.4

Area of residence Urban Rural DK/NR

87.0 12.7 0.3

Sample Method of data collection

polls in the USA and UK revealed that between 47 and 57% of Internet users used it for that purpose [15,57]. According to Siegel [54], over 25% of online information is concerned with health. The respondents were self-selected by clicking on a banner placed for that purpose in the various sections of the cooperator website and in generalist portals (e.g. http://MSN.com). During the period of availability of the survey, a total of 3238 respondents were obtained. The responses were reviewed in order to eliminate individuals replying more than once and those who had submitted obviously invalid responses; e.g. by marking the same value for all items. The result was 2813 valid cases. The technical specifications of the study are listed in Table 2. In a self-selected website-assisted survey, it is difficult to avoid non-response bias. However, an incentive was offered—hotel-stay voucher book valued at 500s, to be won by two people selected randomly from the respondents. This incentive was chosen for its broad spread of interest among different sex and age groups, as well as its desirability, given the proximity of a holiday period to the field work dates. From the demographics collected, the sample showed characteristics similar to those of general Internet users (Table 3). Perhaps the most striking difference was the preponderance of women, possibly due to the focus of the website on health, nutrition, and well-being [51]. Concerning the scales used (see Appendix A), the Internet is essentially a medium of information or communication as well as a commercial channel. However, the website could only be analysed as an information medium since it had no e-commerce option. The scale of ease of use was adapted from Davis [16] and Moore and Benbasat [46], while the scale of perceived usefulness was adapted from Davis et al. [18] and Pavlou [48].

Attitude to the website has been approached from two viewpoints. On the one hand, scales traditionally used to measure attitudes towards classic objects (brand, advertisement, etc.) were adapted (e.g. [9]). On the other, scales have been specifically created for the construct [13]. Bruner and Kumar [8] compared some of these with the one they adopted in the electronic context two years earlier. Their results achieved a better Cronbach’s alpha (0.91), more stable structure, higher explained variance in the exploratory factor analysis and better internal similarity. These results seemed to recommend our use of the Likert-type scale of Bruner and Kumar [7]. The scale for measuring the future intention to visit a website attempts to represent the future intention to use the system or website. Therefore, a Likert-type scale was constructed, composed of three items from Bhattacherjee [4] and Mathwick [45]. Finally, experience is an objective, directly accessible variable, although it has also been measured as a subjective perception by the customer,

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

389

Table 4 Exploratory factor analysis Scale

EFA

Perceived ease of use Perceived usefulness Attitude towards website Intention of use

Alpha

Explained variance (%)

Item loads

59 69 82 78

0.77; 0.88; 0.93; 0.90;

0.83; 0.88; 0.93; 0.83;

0.70 0.71 0.85 0.91

0.65 0.77 0.88 0.84

Table 5 Basic statistics and correlation coefficients Scales a

Ease of use Usefulness Attitude Intention a b

Mean

4.19 3.61 4.42 4.40

S.D.

0.62 0.77 0.61 0.64

Correlation coefficients b Ease of use

Usefulness

Attitude

Intention

1 0.44 0.46 0.38

1 0.59 0.54

1 0.66

1

Scales: 1–5. All correlation coefficients are significant at 1%.

closer in this case of the construct ‘‘perceived control’’. Starting from the view of experience as an objective construct, the log data recorded by the web server can be used to observe that experience related to a specific website, as pointed out by Sismeiro and Bucklin [55]. Goldfarb [25] defended the same standpoint conceptually and empirically by comparing the approximations of experience obtained from log data and direct inquiry of the customer, concluding that the main indicator of experience was the number of hours spent online. Accordingly, we took the number of hours of use as an indicator of the individual’s experience with the Internet in general and of the website in particular. The surfing data from the period immediately preceding the survey were recovered from the http:// www.PulevaSalud.com website server as the measure of the website experience of those taking the survey. This log data provided the number of hours the individual spent visiting the website in a given period. In order to relate the data to the respondent, users were identified by means of a permanent cookie. The same procedure, however, could not be applied to the measurement of Internet experience, for which would have required access the data of the customer’s to any Internet site. Thus, we opted for asking the customers directly about their average number of hours of Internet use per week. Experience might be confused with actual/future use, but this was avoided in our study because:

 The dependent variable (intention of use) referred to time t1, whereas experience referred to earlier usage in time t0.  Time spent on a website should not be the sole indicator of actual or future use, due to a learning effect, which means that the more times an individual visits a website, the less time they will need to carry out an information search [35]. Once the scales for measuring the variables had been established, we proceeded to assess their reliability and validity. First, we analysed the dimensionality of the different multi-item scales. The exploratory factor analysis confirmed that, in all cases, the scale measured exclusively one construct while being able to retain between 59 and 82% of the variance. In all cases Cronbach’s alpha was above 0.6, thereby demonstrating the reliability of the scales employed (Table 4). In general, the different multi-item scales were adequate for measuring the different constructs under analysis. Table 5 shows the basic statistics and correlation coefficients between the constructs. 4. Results The WAM involved a set of different but interdependent multiple regression equations; thus it was advisable to use a structural equation analysis. To complete this it was useful to take into account fulfilment of the multivariate normality condition. The corresponding test produced evidence for the rejection of the null

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

390 Table 6 Goodness of fit indices

After estimation of the structural multi-group model, we assessed the overall goodness of fit of the model (see Table 6). The indicators showed that overall fit was acceptable, all the statistics remaining within the brackets recommended in the literature. Nonetheless, the x2-value was affected by the large sample size. The Website Acceptance Model (WAM) was analysed and results are shown in Fig. 2 with standardized coefficients (with italics for low experience and with bold for high experience). The estimated coefficients for the different proposed relations turned out to be significant for a conservative level ( p < 0.01) and no modifications were needed to the structural model. The comparison between the estimated coefficients for both groups and each pair of variables (Table 7) was carried out using a measurement of the signification of the differences between coefficients using a t-test for independent samples. As can be seen, there was an experience moderation effect on the relationship between ease of use and usefulness on attitude and even on the direct effect of usefulness on the intention to revisit a website ( pvalues < 0.1). Therefore, in general terms, hypotheses H1A, H1B and H1C had empirical support in the user’s experience of the Internet.

958, d.f. 114, p < 0.01 0.073 (0.068; 0.077) 0.98 0.98 0.98 0.98 0.97 446

Chi-square RMSEA (90% RMSEA) NFI NNFI CFI IFI RFI Critical N

normality hypothesis. Considering the absence of normality from the variables, we opted for the Weighted Least Squares (WLS) estimation method, since it is less sensible to sample distribution and produces more efficient estimations provided that it is based on a large sample [6]. The software used was LISREL 8.71 and the variance–covariance matrix was used in the analysis. 4.1. Internet experience For the formation of the groups, the measure of the individual’s experience of the Internet was divided by the median. All the individuals with less than 10 h Internet use per week were thus included in group 1, while the rest were put in group 2, omitting those who had responded DK/NR.

Fig. 2. Website Acceptance Model (WAM) moderated by experience of the Internet. Table 7 Comparison of the groups based on experience of the Internet (unstandardized coefficients) Causal relationship

Group 1 (low) B

Ease of use ! usefulness Ease of use ! Attitude Usefulness ! attitude Usefulness ! intention Attitude ! intention **

Group 2 (high) S.E.

**

0.95 0.33** 0.73** 0.42** 0.42**

0.035 0.055 0.036 0.045 0.04

B

Difference

T

p-Valuea

0.06 0.11 0.08 0.11 0.05

1.19 1.34 1.51 1.51 0.78

0.117 0.091 0.067 0.066 0.218

S.E. **

0.89 0.22** 0.81** 0.53** 0.37**

0.036 0.061 0.039 0.057 0.05

p < 0.01. As the hypotheses assume the polarity of the moderation, the tests of the hypotheses are unilateral and the signification is expressed considering only one tail in T-distribution. a

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

391

Fig. 3. Website Acceptance Model (WAM) moderated by experience of the website. Table 8 Goodness of fit indices Chi-square RMSEA (90% RMSEA) NFI NNFI CFI IFI RFI Critical N

935, d.f. 114, p = 0.01 0.073 (0.069; 0.077) 0.98 0.98 0.98 0.98 0.98 440

Compared to users with low Internet experience, more experienced users were shown to be attracted in a higher extent by perceived usefulness in determining future intention to visit the website, both directly and via attitude. Furthermore, the weight of the relationship between ease of use and attitude in the case of the experienced users was substantially lowered. This suggested that this belief was not as important for experienced individuals in their future use of a website. They were sufficiently knowledgeable about the medium to prevent difficulty of use from putting limits on their future use of the system.

those who had spent a certain amount of time surfing it (group 2). Again, the global fit indices proved to be within the limits established by the literature (Table 8). All the coefficients proved to be significant at 1% except that relationship between ease of use and attitude, which, in the case of high experience, was significant at 5% (Fig. 3). Table 9 shows the t-test results for comparison of the groups based on level of website experience. Significant differences in the coefficients of ease of use and perceived usefulness affecting attitude to the website can be observed through of the experience moderation effect. Thus, hypotheses H2A and H2B obtained empirical support. Individuals with high experience of the website made more use of perceived usefulness in shaping their attitude to the website than inexperienced ones, whereas the latter focused more on ease of use. Hypothesis H2C, however, was rejected. Nonetheless, this moderation effect did take place through the indirect relation between usefulness and intention through attitude. 5. Discussion and conclusions

4.2. Experience of the website 5.1. Key findings The variable measuring website experience distinguished individuals with zero visits or zero hours of website use during the studied period (group 1) from

Our study suggests that a Website Acceptance Model (WAM) can serve as the starting point for generalization

Table 9 Comparison of the groups based on experience of the website (unstandardized coefficients) Causal relationship

Ease of use ! usefulness Ease of use ! attitude Usefulness ! attitude Usefulness ! intention Attitude ! intention ** *

p < 0.01. p < 0.05.

Group 1 (low)

Group 2 (high)

B

S.E.

B

S.E.

0.91** 0.33** 0.72** 0.46** 0.40**

0.035 0.051 0.034 0.043 0.038

0.94** 0.13* 0.86** 0.49** 0.37**

0.039 0.067 0.041 0.059 0.052

Difference

T

p-Value

0.03 0.20 0.14 0.03 0.03

0.57 2.38 2.63 0.41 0.47

0.285 0.009** 0.005** 0.341 0.320

392

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

of TAM in other contexts. The model explained almost 70% of the variance of the user’s intention to visit irrespective of the moderator and its level. This underscored the need for including the user’s experience in the explanation of website use. The modelling of the acceptance behavior of new IT is extremely useful to managers who need to assess the probability of success in their introduction. Our main objective was to extend the experience moderation effect in e-commerce sites onto the acceptance of free-content websites. A comparison between the results reached by Gefen, Karahanna and Straub (focused on e-commerce) and those obtained in this study, throws up a number of noteworthy conclusions. On the one hand, in low experience situations, perceived usefulness is apparently not a direct determinant of the intention to buy, though it does have a significant effect on the intention to visit. In such situations, trust constitutes the main determinant of the intention to buy, while attitude and perceived usefulness are the main determinants of the intention to visit. Even though ease of use is not moderated in its relations in an e-commerce acceptance model, the results of the present study do reveal the existence of such a moderation effect for a free-content website. These results are attributable to the different motivations that drive the behavior of an e-commerce site user and an information site user and to the differences in the determining variables (e.g. trust). Last but by no means least, the effect of ease of use on the perception of usefulness is the strongest relationship in Gefen et al.’s model, and one of the strongest ones in WAM. The results obtained demonstrate that it is crucial to take note of the determinants of the acceptance of web intermediaries in website design and the provision of services on the Internet. Consistent with other TAM empirical validations, the results show an important direct effect of perceived usefulness on the intention to revisit a website as well as an indirect effect through the attitude towards the website. Therefore, it has to be admitted that the intention to revisit is determined mainly by perceived usefulness. The explanation of this finding is founded on the fact that the principal motivations for the use of the website are clearly extrinsic. The coefficients of the relationships between ease of use and usefulness, and the latter and attitude are consistently the highest ( p < 0.05), regardless of the user’s experience. These results imply that greater perceived usefulness due to time savings in an interactive and well-structured website use is the surest way of attracting a future visit by the user. Moreover,

perceived usefulness offers two comparably important ways (a direct one and one through attitude) of determining intention of use. The proposed models of behavior show that in the process of shaping the attitude towards a website and the intention to revisit the website there are substantial differences due to the differing levels of experience of the users. More specifically, the results are as follows:  Perceived usefulness is the main determinant of the intention to continue visiting a website, irrespective of the level of experience of the user, its direct influence being greater in the frequent users of the Internet.  In users with high experience of the Internet or a website, the influence of perceived usefulness on the process of forming the attitude to the website is substantially greater than in users with low experience.  In users with high experience of the Internet or a website, the influence of perceived ease of use on the attitude towards the website is substantially smaller than in users with low experience. By the same token, in a high experience situation, the attitude is conditioned primarily by usefulness, the direct effect of ease of use being practically non-existent, corroborating the results of the original TAM. The reason for these results lies in the fact that different individuals evaluate a website from different perspectives. The experienced users are more interested in the outcome of the search (extrinsic motivation) than those visiting the site for the first time. The latter evaluate the website in a more superficial manner focusing, in the main, on the novelty of the site and on other instrumental beliefs (intrinsic motivation). The moderation effect of the website experience variable is more evident than the moderation effect of general Internet experience. Different levels of experience will produce markedly different results in different modelling perspectives. Naturally, a more general reference level (Internet experience) has a low effect on WAM relations while a more specific reference level (website experience) has a high moderation effect. Nonetheless, it is useful to consider both reference levels since this makes it possible to identify the difference between the moderation effects on the direct relationship between usefulness and intention of use. The moderation effect of Internet experience on the relationship between usefulness and intention of use is significant, which is not the case with website experience. As the literature suggests as a

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

justification of the proposed direct effect of usefulness on intention to use, this relationship captures the impact of performance considerations on one’s intentions when attitude is not fully activated. After grouping the users according to their level of Internet experience, in each group there should be users with both high and low specific website experience. Nevertheless, when users are divided according to their level of website experience, it is necessary to consider a source of bias—those users with high website experience will have a more enduring, accessible and clear attitude [21]. Thus, different levels of attitude activation could be conditioning the website experience moderation effect. A comparison of the coefficients obtained for the different relationships in same-experience situations (low Internet experience versus low website experience; high Internet experience versus high website experience) reveals no significant differences. These results show the coefficient estimations to be very robust. In general, the value of both Internet experience and website experience in the analysis of user’s free-content website acceptance has been demonstrated. This implies that the nomological network of antecedents of user behavior at a specific level is affected not only by the user’s experience at a given level but also by the experience acquired at other more general levels. 5.2. Limitations of the study There were several limitations of our study:  The survey had to be short as it was carried out through the Internet. For the same reason, the measures were kept to a minimum, using three items for each variable of WAM. This may have affected the validity and the reliability of the scales.  User’s Internet experience cannot be measured through the same procedure as website experience. To assess it from log data, it was necessary to access the data on the customer’s visits to any Internet site, which is only available to the Internet Service Provider or a panel of Internet users. Therefore, we decided to ask this question directly to the customers. The difference in the process of measurement could have biased comparison of experience.  The results only refer to a single context ‘‘freecontent websites’’. Thus, caution must be taken in generalizing the conclusions.  We used behavioral intention as the dependent variable but as Mathieson [44] suggested this may not be a serious limitation.

393

5.3. Practical implications In an analysis of an e-commerce website acceptance, Shang et al. [52] concluded that perceived usefulness had no significant effect on the intention to buy, and that it was ease of use that determines the behavior. This conclusion was qualified by Gefen, Karahanna and Straub who showed that the effect of perceived usefulness on the intention to buy was significant for individuals with high experience. We found that for a free-content website, the web designer or the information manager of an organization should spare the Internet user both the connection costs and the waste of time necessary to ‘‘learn’’ how to use a difficult website thus permitting him or her to allocate those valuable resources to other tasks. It is worth noting that, perceived usefulness was the most important determinant of the intention to visit, regardless of the user’s level of experience. Nonetheless, this should not be taken as advising that free-content websites focus only on improving the system for the sake of the user; according to the Heuristic-Systematic Model, a user acts on the principle of minimum effort. Thus, the user considers a website heuristically, focusing on those aspects that are easy to process and evaluate (ease of use). When the customer has sufficient motivation and experience and heuristic processing has not led them to abandon a site, the user will change to systematic processing, where they will evaluate the more complex aspects of the site (its perceived usefulness). This implies that a website has to provide a minimum level of ease of use to make it possible for a user to evaluate its usefulness; ease of use is a necessary but not sufficient condition for the acceptance and use of a free-content website. In the case of the more proficient Internet users who exhibit guided behavior and a more in-depth evaluation of the website, web designers should devote more attention to the perceived usefulness of the website. With regard to that, it is possible to shape the factors within the control of the organization, such as offering services or making available information of value. Users with high experience may prefer a more difficult interface if it enables them to achieve their objectives. Nonetheless, novice users opt for the search for new experiences and focus on the novelty of a website, which is why organizations should develop designs focused on the user, in permanent contact with the user as distinct from merely focusing on technical aspects. At the same time, for this group of users, one must not lose sight of the perceived usefulness of the web.

394

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

Last, it is worth noting that the users’ opinions about a specific website are of great importance in explaining user behavior, though not of the same significance as other factors such as perceived usefulness. In keeping with these conclusions, research into Internet users, their attitudes, online behavior, and use of the Net enables web managers to adapt the Internet medium to their needs. Similarly, identifying groups of Internet users on the basis of shared characteristics relative to their surfing behavior permits the development of strategies tailored for their needs. 5.4. Contributions to research Our study contributed to the body of knowledge in the field of IT acceptance and, more specifically, Website Acceptance Models. The main contributions were:  We focused on free-content websites. Considering that a large percentage of Internet sites offer freecontent, this is a useful complement to the existing literature.  To the best of our knowledge, our study, together with Gefen, Karahanna and Straub were the only ones to consider user website acceptance moderated by experience as a mean of explaining online behavior. A user’s experience of the website was found to be a significant moderator of the relations in the WAM. Our study also showed the importance of Internet experience in explaining user behavior.  Our study tested the WAM and the experience moderation effect on post-adoption usage, showing the validity of the model in the post-adoption phase. The meta-analyses of TAM recently published drew attention to one of the main limitations of studies—they drew heavily on students rather than on the population in general. It is worth emphasizing that our results were supported by real data from a large sample (2813 cases). Appendix A. Scales used  Measure of ease of use:  The website is complicated–simple.  The website processing is slow–fast.  The website is non-interactive–interactive.  Measure of perceived usefulness:  Searching for information in this website is an efficient way to manage my time.  Using this website makes my life easier.  The website is competent and efficient.

 Measure of attitude towards a website:  I like the website.  I consider it a good website.  I think it is a nice website.  Measure of the future intention to visit a website:  I intend to continue visiting the website in the future.  My intention is to continue using this website rather than an alternative one.  I want to continue using this website rather than stop using it.  Measure of experience of the Internet: In an average week, how much time would you say you spend connected to the Internet (for any kind of service and counting all the possible sessions over the week)?  Less than 1 h.  Between 1 and 4 h.  Between 4 and 10 h.  Between 10 and 30 h.  Between 30 and 60 h.  More than 60 h.  DK/NR.  Measure of website experience: The number of hours the respondent had dedicated to visiting the website during the period immediately preceding the survey. This information is obtained from the surfing data recorded by the website server. Each individual is identified by means of a permanent cookie in a way that enables the surfing data to be linked to the data obtained from the survey. References [1] M.A. Atkinson, C. Kydd, Individual characteristics associated with World Wide Web use: an empirical study of playfulness and motivation, The DATA BASE for Advances in Information Systems 28 (2), 1997, pp. 53–61. [2] A. Bandura, Self-efficacy mechanism in human agency, American Psychologist 37, 1982, pp. 122–147. [3] A. Bhattacherjee, Adoption of IS services: the case of electronic brokerages, IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans 30 (4), 2000, pp. 411– 420. [4] A. Bhattacherjee, An empirical analysis of the antecedents of electronic commerce service continuance, Decision Support Systems 32 (2), 2001, pp. 201–214. [5] A. Bhattacherjee, G.P. Premkumar, Understanding changes in belief and attitude toward Information Technology usage: a theoretical model and longitudinal test, MIS Quarterly 28 (2), 2004, pp. 229–254. [6] A. Boomsma, J.J. Hoogland, The robustness of LISREL modeling revisited, in: R. Jo¨reskog, S. Cudeck, S. Toit, D. So¨rbom (Eds.), Structural Equation Models: Present and Future, A Festschrift in Honor of Karl, Scientific Software International,

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

[7]

[8]

[9]

[10]

[11]

[12]

[13] [14]

[15]

[16]

[17]

[18]

[19]

[20]

[21]

[22]

[23]

[24]

Chicago, 2001, pp. 139–168 (online), available in: http:// www.ppsw.rug.nl/boomsma/ssi.pdf. G.C. Bruner II, A. Kumar, Web commercials and advertising hierarchy-of-effects, Journal of Advertising Research 40 (1/2), 2000, pp. 35–42. G.C. Bruner II, A. Kumar, Similarity analysis of three attitudetoward-the-website scales, Quarterly Journal of Electronic Commerce 3 (2), 2002, pp. 163–172. K.S. Burns, Branding in cyberspace: using the congruity of consumer and website personality to unravel online user satisfaction, in: M.A. Shaver (Ed.), in: Proceedings of the American Academy of Advertising, East Lansing, MI, 2000, pp. 9–18. J.A. Castan˜eda, M.A. Rodrı´guez, T. Luque, Identifying the hierarchy of effects operative in an Internet attitude model applied to e-loyalty, in: Proceedings of the 33rd EMAC, European Marketing Academy Conference, New Technologies and e-marketing VI, 2004, pp. 18–21. S.C. Chan, M.T. Lu, Understanding Internet banking adoption and use behavior: a Hong Kong perspective, Journal of Global Information Management 12 (3), 2004, pp. 21–43. P.Y.K. Chau, P.J.H. Hu, Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories, Information & Management 39 (4), 2002, pp. 297–311. Q. Chen, W.D. Wells, Attitude toward the site, Journal of Advertising Research 39 (5), 1999, pp. 27–37. S. Chen, S. Chaiken, The Heuristic-Systematic Model in its broader context, in: S. Chaiken, Y. Trope (Eds.), Dual-process Theories in Social Psychology, The Guilford Press, Nueva York, 1999. Datamonitor, Who is looking for health information online?—A segmentation analysis of the online consumer, Datamonitor, 2002 (online), available in: http://www.datamonitor.com. F.D. Davis, Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly 13 (3), 1989, pp. 319–340. F.D. Davis, R.P. Bagozzi, P.R. Warshaw, Extrinsic and intrinsic motivation to use computers in the workplace, Journal of Applied Social Psychology 22 (14), 1992, pp. 1111–1132. F.D. Davis, R.P. Bagozzi, P.R. Warshaw, User acceptance of computer technology: a comparison of two theoretical models, Management Science 35 (8), 1989, pp. 982–1003. G.R. Dolan, R.W. Iredale, J. Ameen, Consumer use of the Internet for health information: a survey of primary care patients, International Journal of Consumer Studies 28 (2), 2004, pp. 147– 153. EUROSTAT, Information society statistics: individuals-Internet use; e-commerce, science and technology, European Communities, 2006. R.H. Fazio, J. Chen, E.C. McDonel, S.J. Sherman, Attitude accessibility, attitude-behavior consistency, and the strength of the object-evaluation association, Journal of Experimental Social Psychology 18 (4), 1982, pp. 339–357. D. Gefen, D.W. Straub, Gender differences in the perception and use of e-mail: an extension to the Technology Acceptance Model, MIS Quarterly 21 (4), 1997, pp. 389–400. D. Gefen, E. Karahanna, D. Straub, Trust and TAM in online shoppings: an integrated model, MIS Quarterly 27 (1), 2003, pp. 51–90. D. Gefen, E. Karahanna, D. Straub, Inexperience and experience with online stores: the importance of TAM and trust, IEEE Transactions on Engineering Management 50 (3), 2003, pp. 1–15.

395

[25] A. Goldfarb, Interpreting Internet clickstream data, 2002 (online), available in: http://www.rotman.utoronto.ca/agoldfarb/surveypaper.pdf. [26] H. van der Heijden, Factors influencing the usage of websites: the case of a generic Portal in the Netherlands, Information & Management 40 (6), 2003, pp. 541–549. [27] D.L. Hoffman, T.P. Novak, Marketing in hypermedia computermediated environments: conceptual foundations, Journal of Marketing 60 (3), 1996, pp. 50–68. [28] D.L. Hoffman, T.P. Novak, A. Duhachek, The influence of goaldirected and experiential activities on on-line flow experiences, Journal of Consumer Psychology 13 (1/2), 2003, pp. 3–16. [29] W.Y. Hong, J.Y.L. Thong, W.M. Wong, K.Y. Tam, Determinants of user acceptance of digital libraries: an empirical examination of individual differences and system characteristics, Journal of Management Information Systems 18 (3), 2001, pp. 97–124. [30] C.L. Hsu, H.P. Lu, Why do people play on-line games? An extended TAM with social influences and flow experience Information & Management 41 (7), 2004, pp. 853–868. [31] P.J. Hu, T.H.K. Clark, W.W. Ma, Examining technology acceptance by school teachers: a longitudinal study, Information & Management 41 (2), 2003, pp. 227–241. [32] L.J. Huang, M.T. Lu, B.K. Wong, The impact of power distance on e-mail acceptance: evidence from the PRC, Journal of Computer Information Systems 44 (1), 2003, pp. 93–101. [33] S.L. Jarvenpaa, N. Tractinsky, L. Saarinen, M. Vitale, Consumer trust in an Internet store: a cross-cultural validation, Journal of Computer-Mediated Communication 5 (2), 1999, (online), available in: http://www.ascusc.org/jcmc/vol5/issue2/jarvenpaa.html. [34] S.L. Jarvenpaa, N. Tractinsky, M. Vitale, Consumer trust in an Internet store, Information Technology and Management 1 (1/2), 2000, pp. 45–71. [35] E.J. Johnson, S. Bellman, G.L. Lohse, Cognitive lock-in and the power law of practice, Journal of Marketing 67 (2), 2003, pp. 62– 75. [36] E. Karahanna, D.W. Straub, N.L. Chervany, Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs, MIS Quarterly 23 (2), 1999, pp. 183–213. [37] W.R. King, J. He, A meta-analysis of the technology acceptance model, Information & Management 43, 2006, pp. 740–755. [38] M. Koufaris, Applying the Technology Acceptance Model and flow theory to online consumer behavior, Information Systems Research 13 (2), 2002, pp. 205–223. [39] M. Koufaris, A. Kambil, P.A. LaBarbera, Consumer behavior in web-based commerce: an empirical study, International Journal of Electronic Commerce 6 (2), 2002, pp. 115–138. [40] Y. Lee, K.A. Kozar, K.R.T. Larsen, The Technology Acceptance Model: past, present, and future, Communications of the Association for Information Systems 12, 2003, pp. 752–780. [41] D.H. Li, J. Day, H. Lou, G. Coombs, The effect of affiliation motivation on the intention to use groupware in an MBA program, Journal of Computer Information Systems 44 (3), 2004, pp. 1–8. [42] Q. Ma, L. Liu, The Technology Acceptance Model: a metaanalysis of empirical findings, Journal of Organizational and End User Computing 16 (1), 2004, pp. 59–72. [43] Y. Malhotra, D.F. Galletta, Extending the Technology Acceptance Model to account for social influence: theoretical bases and empirical validation, in: Proceedings of the 32nd Hawaii International Conference on System Science, 1999, pp. 1–14.

396

J.A. Castan˜eda et al. / Information & Management 44 (2007) 384–396

[44] K. Mathieson, Predicting user intentions: comparing the Technology Acceptance Model with the Theory of Planned Behavior, Information Systems Research 2 (3), 1991, pp. 173–191. [45] C. Mathwick, Understanding the online consumer: a typology of online relational norms and behavior, Journal of Interactive Marketing 16 (1), 2002, pp. 40–55. [46] G.C. Moore, I. Benbasat, Development of an instrument to measure the perceptions of adopting an Information Technology innovation, Information Systems Research 2 (3), 1991, pp. 192– 222. [47] C.S. Ong, J.Y. Lai, Y.S. Wang, Factors affecting engineers’ acceptance of asynchronous e-learning systems in high-tech companies, Information & Management 41 (6), 2004, pp. 795–804. [48] P.A. Pavlou, Consumer acceptance of electronic commerce: integrating trust and risk with the Technology Acceptance Model, International Journal of Electronic Commerce 7 (3), 2003, pp. 69–103. [49] P.A. Pavlou, M. Fygenson, Understanding and predicting electronic commerce adoption: an extension of the Theory of Planned Behavior, MIS Quarterly 30 (1), 2005, pp. 115–143. [50] M.J. Sa´nchez, J.L. Ronda´n, Web acceptance and usage model: a comparison between goal-directed and experiential Web users, Internet Research 15 (1), 2005, pp. 21–48. [51] A. Scalise, Reputation, ease of use fuel web health site success, Drug Store News 22 (15), 2000, pp. 29–30. [52] E. Shang, Y. Chen, L. Shen, Extrinsic versus intrinsic motivations for consumers to shop on-line, Information & Management 42, 2005, pp. 401–413. [53] H.P. Shih, Extended technology acceptance model of Internet utilization behavior, Information & Management 41 (6), 2004, pp. 719–729. [54] L. Siegel, DTC advertising: bane . . . or blessing? Pharmaceutical Executive 20 (10), 2000, pp. 140–147. [55] C. Sismeiro, R.E. Bucklin, Modeling purchase behavior at an ecommerce web site: a task-completion approach, Journal of Marketing Research 41, 2004, pp. 306–323, (online) available in: http://www.anderson.ucla.edu/faculty/randy.bucklin/papers/ SismeiroandBucklin2002.pdf.. [56] M. Solomon, Consumer Behavior. Buying, Having and Being, Prentice Hall, New York, 1998. [57] H. Taylor, Cyberchondriacs continue to grow in America: 110 million people sometimes look for health information online, up from 97 million a year ago, Health Care News 2, 2002, (online), available in: http://www.harrisinteractive.com/harris_poll/ index.asp?PID=299. [58] S. Taylor, P.A. Todd, Understanding information technology usage: a test of competing models, Information Systems Research 6 (2), 1995, pp. 144–176. [59] T.S.H. Teo, K.G.L. Vivien, Y.C.L. Raye, Intrinsic and extrinsic motivation in Internet usage, Omega, International Journal of Management Science 27 (2), 1999, pp. 25–37. [60] J.Y.L. Thong, W.Y. Hong, K.Y. Tam, Understanding user acceptance of digital libraries: what are the roles of interface characteristics, organizational context, and individual differences? International Journal of Human-Computer Studies 57 (3), 2002, pp. 215–242.

[61] H. Thorbjornsen, M. Supphellen, H. Nysveen, P.E. Pedersen, Building brand relationships online: a comparison of two interactive applications, Journal of Interactive Marketing 16 (3), 2002, pp. 17–34. [62] V. Venkatesh, F.D. Davis, A theoretical extension of the Technology Acceptance Model: four longitudinal field studies, Management Science 46 (2), 2000, pp. 186–204. [63] V. Venkatesh, M.G. Morris, G.B. Davis, F.D. Davis, User acceptance of information technology: toward a unified view, MIS Quarterly 27 (3), 2003, pp. 425–478. [64] M. Wolfinbarger, M.C. Gilly, Shopping online for freedom, control, and fun, California Management Review 43 (2), 2001, pp. 34–55. J. Alberto Castan˜eda is associate professor in marketing and market research, and holds a PhD in business sciences from the University of Granada (Spain). His current specialization and research interests are focused on online consumer behavior. His recent works have been published in The Service Industries Journal, Information & Management, Online Information Review, Electronic Commerce Research, International Journal of Internet Marketing & Advertising, Tourism Management, among others. Francisco Mun˜oz-Leiva is associate professor in marketing and market research at the University of Granada (Spain). Although his main research interest is Internet consumer behavior and Internet acceptance, he has also published papers on other topics. His recent works have appeared in Cities, Quality & Quantity, The Service Industries Journal, International Journal of Internet Marketing & Advertising, and communications in international conferences. Teodoro Luque is professor of Marketing Department at University of Granada (Spain). His main interests are marketing research, consumer behavior, strategic marketing (city and university), electronic marketing and macromarketing. He has published several books and articles in Revista Espan˜ola de Investigacio´n de Marketing, Revista Europea de Direccio´n y Economı´a de la Empresa, Quality and Quantity, Cities, Journal of Consumer Marketing, The Service Industries Journal and others. He has contributed approximately 50 papers to conference proceeding (EMAC, AMS, ENCUENTRO DE PROFESORES DE MARKETING, AEDEM, AEDEMO, etc.). He has developed research projects with diverse companies and public administrations.