Dimensions of Retail Website Effectiveness

Transcription

1 Dimensions of Retail Website Effectiveness by Edward A. Riordan and David L. Williams both of Department of Marketing School of Business Administration Wayne State University (313) Submitted for review for the 2001 Summer AMA Meetings NOTE: This is a work in progress. Do not quote without written permission of the authors.

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3 2 Dimensions of Retail Website Effectiveness More systematic research into the nature of commerce on the World Wide Web has been called for by a variety of academicians and practitioners. In this paper, the authors identify three dimensions of retail website design and empirically examine their role as drivers of overall impression of the retail website and site revisit intention. Using a structural equations model, the authors identify utility, esthetics and entertainment factors that contribute substantially to the two dependent variables. The authors also offer implications and future research suggestions based on the findings. Introduction: The absolute size and rapid growth of the Internet as a commerce tool and advertising medium has attracted much media attention recently. One estimate forecasts that 61.3 million U.S. households will have Internet access by 2002 (Iconocast, 2000). Additionally, of Internet users, 45% have reported at least one purchase (Business Week, 2000). During the 2000 holiday season, the Internet attracted over 60 million unique visitors per week, over 34 million to retail websites alone and generated total sales of over $10 billion (Media Metrix, 2001). During the same time period, the volatility of this new medium has been evidenced in a number of ways including the free fall of Internet company stocks and retail website failures. For example, popular sites such as Toysmart.com, Furniture.com, Pets.com all failed during Further, large sites such as Priceline.com, Etoys.com, and Drkoop.com are expected to fail during the first quarter of 2001 (Business Week, 2001). The growth and volatility of this medium has led to an increase in marketing practitioner and academic interest in more systematic research

4 3 into the nature of commerce on the Web. A number of authors have called for future research to assess the effectiveness of the Web as a marketing and advertising vehicle (i.e., Watson, et al, 2000). However, a review of the most cited marketing and advertising literature reveals that research in this area is still fragmented. We believe research is needed that systematically addresses a model of consumer behavior on the Internet. Several studies have provided important findings on which to build further research. Korgaonkar and Wolin (1999) studied the determinants of Web usage. They found seven factors that drove the amount of Web usage time: 1) Social escapism motivation, 2) Information motivation, and 3) Interactive control motivation, 4) Socialization motivation, 5) Transactionbased security and privacy concerns, 6) Non-transactional privacy concerns, and 7) Economic motivation. This study suggests that consumers use the Web for a wide variety of psychological and utilitarian reasons. Thus, we believe it is important to distinguish use of the Internet for product search and purchase from other applications such as socialization and exploration. Ducoffe (1996) has examined consumer s perceived value of web advertising and its role as an antecedent to overall audience attitudes. He found a strong positive effect of two factors, Informativeness and Entertainment on two dependent variables: the perceived value of advertising and subsequently, attitude toward Web advertising. Schlosser, et al (1999) found similar results concerning attitudes toward Internet advertising.

5 4 Berthon, et al (1996) have modeled the flow of Internet surfer activity. Essentially, their model is an update of the popular hierarchy of effects models of advertising used by marketers for the past 40 years. The Berthon, et al (1996) model views the effects of advertising as a multistage process beginning with surfer awareness leading to a website hit, through a series of stages to purchase and, if applicable, repurchase. Thus, the Berthon, et al model is particularly relevant to researchers interested in understanding consumer Internet usage directed at product purchase. Purpose The purpose of this paper is to examine the consumer s purchase process as it progresses from the 3 rd to the 4 th levels of the Berthon, et al (1996) model, specifically contact efficiency and conversion efficiency. That is, from the point of the initial website hit to the completion of a purchase. We are most interested in what factors increase the likelihood that a surfer will stay on a retail website and that will persuade that person to actually purchase a product. In this context, we can also examine the factors that lead to site revisit intention. Our research focuses on three basic questions: 1) What are the characteristics of a retail website that influence the potential purchaser to stay on the site? 2) From the site designer's perspective, can the numerous characteristics of a retail website be reduced to a smaller number of basic website design dimensions? 3) How do these basic website design factors drive the consumer's overall impression of the site and, in turn, his or her intention to

6 5 revisit the site? To answer these questions, the study was conducted in two phases. Method Given the exploratory nature of the study, we first asked 336 graduate and undergraduate marketing students at a large urban state university to identify websites they had recently purchased from and which they liked best, those they liked least, and the reasons that determined their preferences. The websites liked least and liked best formed the pool of sites used for evaluation in the second phase of the study. The reasons for site preference were analyzed and used as input for construction of the website evaluation questionnaire for the second (modeling) phase of the research. In the second phase, 173 graduate and undergraduate students actually accessed two retail websites in a controlled laboratory environment and completed a simulated purchase of a specific product. After each simulated purchase, they completed a website evaluation questionnaire. Lastly, they completed a set of standard demographic items. The second phase sample composition is shown in Figure 1. As would be expected from a population of students at an urban commuter university, the sample was balanced with respect to gender, but evinced a higher skew on income and Internet access. However, the sample composition is comparable to that found for Internet users nationally (Coupey, 2001:47). Figure 2 shows representative retail websites drawn from the total pool of sites liked best and liked least as identified by respondents in the

7 6 first phase of the study. A total of 152 unique websites were used in the second phase of the study, covering twelve different popular retail categories. Website evaluation items were selected from the literature (i.e., Alexander and Tate, 1999) as well as from subjects responses as found in the first phase of the study. Figure 3 illustrates the nine website evaluation items derived from this analysis. Respondents were asked to rate the websites on each of the items using a five point excellent to poor scale after performing a simulated purchase. The dependent variable items are also shown in Figure 3. Here, the respondents were asked to rate their overall impression of the website and their web site revisit intention. Ratings for overall web site impression were also recorded on a five point excellent to poor scale. Similarly, site revisit intention was measured by a five point very likely to very unlikely scale. Results Data from 173 subjects, representing 152 unique retail websites, yielded a total of 295 useable (with complete ratings) website evaluations. The data were analyzed using the Amos structural equation modeling software (Arbuckle, 1997). The first facet of the analysis explored the factor structure of the nine website evaluation items. Figure 4 shows the three factor model which best fit the data, with all nine items loading heavily on one of the three factors. It is interesting to note that the three factors incorporate the utilitarian, the esthetic, and the entertainment aspects of a website. Five of nine items loaded on the utilitarian dimension, including navigational time, understandability, clarity,

8 7 consistency, and overall ease of use. A second factor, esthetics, contained two items measuring the visual quality of the site and the quality of graphic images. The entertainment factor included two inherently related items: the sites ability to grab and hold the users attention and the sites perceived entertainment value. Figure 4 also shows that the three factors were substantially intercorrelated. The next portion of Figure 4 reveals how the three factors drive the overall impression of a website. Each of the three factors makes a significant contribution to explaining the variance in overall website impression. Moreover, the utility factor has the largest standardized regression weight compared to the other two factors. In turn, the standardized regression weight for entertainment is considerably larger than that found for the esthetics factor. The final portion of Figure 4 illustrates the relationship between the two dependent variables: overall website impression and respondents intention to revisit the website. As Figure 4 indicates, the best fitting model includes linkages from overall impression and the entertainment factor to respondents intention to revisit the website. Also in Figure 4 are the chi-square and goodness-of-fit indices for the model. The Normed Fit and Comparative Fit indices suggests that the model fits the data reasonably well, as both are above.95. The Root Mean Square of Approximation value of.079 also indicates an acceptable fit to the data. However, a significant chi-square value implies the potential for model improvement, a typical result in an exploratory study.

9 8 Discussion and Conclusions Our research objective was to understand the aspects of retail website design that drive users overall impression of the website and their revisit intention. First, we sought to identify a series of retail website characteristics that are relevant and salient to users. Based on respondents reasons for liking or disliking websites from which they had previously purchased, we designed a nine-item scale to tap key website design elements. Next, we sought to determine the dimensionality of these elements. We found a three-factor solution that offers important insights into consumers assessments of retail websites. It suggests that the utilitarian, esthetic and entertainment aspects of a retail site are all salient to potential purchasers. The prevailing wisdom has been that users do not necessarily visit retail websites for purposes of entertainment; that is, they are normally visited for an already planned purchase of a specific product. By this view, the only important website design issues are utilitarian. Although more items loaded on the utilitarian dimension in our model, the findings suggest that retail website designers should not overlook the esthetic and entertainment aspects of their sites. Consumers do appear to discriminate among retail websites on these dimensions. Our research also sought to identify the drivers of overall website impressions. Here again, our model demonstrates the importance of the utilitarian, esthetic and entertainment aspects of website deign. All three dimensions contributed significantly to respondents overall impression of the websites they evaluated.

10 9 Finally, we examined the factors that drive intention to revisit a site. Not surprisingly, overall impression of the site made the greatest contribution to explaining variance in revisit intentions. However, the fit of our model was significantly improved by including a direct path from the entertainment value of a site to revisit intention, suggesting that the entertaining aspects of a site that are not directly captured in a consumer s overall impression of the site still influence his or her intention to revisit the site. This finding further underscores the importance of a retail website s entertainment value for encouraging future visits. Our findings are subject to several limitations that suggest fruitful directions for further research. First, we measured 152 unique retail websites, most large scale retailers. While this is a broad sampling, mid- and small-size retailers were underrepresented. It can be argued that the major retail sites tend to be more uniformly well-funded, well-designed, and well-presented and operated. This tendency may have affected our results in that a different pattern of results could have been found for a broader sampling, including more sites of smaller retailers. Future research should more systematically compare websites developed by retailers of various sizes. Second, there may be other aspects of website design not assessed by our evaluation instrument. As the body of knowledge in this area develops, additional important elements of website design may be uncovered. Thus, future research should be directed at identifying other design dimensions that can contribute to a more fully explicated model. We agree with those that call for increased attention to website usability and design

11 10 quality measurement (i.e., Fellenstein and Wood, 2000: ) using an evaluation instrument such as that developed for this study.

12 11 References Alexander, J. and M. Tate (1999), Web Wisdom: How to Evaluate and Create Information Quality on the Web. Mahway, NJ: Lawrence Erlbaum Associates. Arbuckle, J. (1997), Amos Users Guide Version 3.6. Chicago: SPSS Inc. Berthon, P., Pitt L. and R. Watson (1996), The World Wide Web as an Advertising Medium: Towards an Understanding of Conversion Efficiency, Journal of Advertising Research, 36 (Jan/Feb), Business Week Harris Interactive Poll, March 2-6 (2000), It s time for Rules in Wonderland, Business Week, March 20, 96. Business Week (2001), 2000: The year of the Dot-Bomb, Business Week, January 15, 10. Coupey, E. ( 2001), Marketing and the Internet. Upper Saddle River, NJ: Prentice Hall. Ducoffe, R. (1996), Advertising Value and Advertising on the Web, Journal of Advertising Research, 36 (Sept/Oct), Fellenstein, C. and R. Wood (2000), Exploring E-commerce, Global E-business, and E-societies. Upper Saddle River, NJ: Prentice Hall PTR. Iconocast, ed. (2000), Internet at a Glance, Iconocast, Winter. Korgaonkar, P. and L. Wolin (1999), A Multivariate Analysis of Web Usage, Journal of Advertising Research, 39 (Mar/Apr), Media Metrix (2001), Results of Holiday 2000 online-shopping season, press release, January 5. Schlosser, A., Shavitt, S. and A. Kanfer (1999), Survey of Internet Users Attitudes Toward Internet Advertising, Journal of Interactive Marketing, 13, 1, (Winter), Watson, R., Berthon, P., Pitt, L. and G. Zinkhan (2000), Electronic Commerce: The Strategic Perspective. Fort Worth: Dryden Press.

13 FIGURE 1 Sample Profile (Base = 173) 12 Gender Age Male 49% Female 51% % Over 30 14% % % % Household Income Internet Access Over $75,000 $50,001 to $75,000 $25,001 to $50,000 $25,000 or less 13% 17% 26% 44% Percent Responding None 6% Home only Work 29% only 9% Both 56%

14 13 FIGURE 2 Representative Web Sites Apparel Electronics Outdoor jcrew circuitcity llbean express gatewaycountry cabelas Books Household Sports borders fingerhut nhl barnesandnoble crateandbarrell nfl Cometics Jewelry Toys avon servicemerchandise etoys clinique firstjewelry toys-r-us Department stores Music Miscellaneous target towerrecords gnc kmart amazon flowers Total = 152 unique sites

15 14 FIGURE 3 Questionnaire Items Website Evaluation Items: 1. Time required to find the information you wanted. 2. Visual quality of the site, including such factors as page design, use of colors, contrast, etc. 3. Quality of the graphics, sharpness/size of the images, pictures, designs, etc. 4. Understandability of the icons, buttons, menus, and the like. 5. Clarity of the instructions, if any. 6. Consistency of formatting and functions across pages. 7. Overall ease of use. 8. Ability to grab and keep your attention. 9. Entertainment value. Dependent Variable Items: 1. Overall impression of the site. 2. Site Revisit Intention - How likely are you to visit this site the next time you need one of the products or services it offers?

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