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Gender Differences in Perceptions of Web-Based Shopping


Despite the dot-com collapse, online retail sales continue to grow. According to the U.S. Department of Commerce, online retail sales increased over 19% from 2000 to 2001. With the continual rise in Web-based shopping, one obvious question becomes whether men and women are equally as likely to use the Web for their shopping experiences.

The New York Times (July 12, 1999) argued the Internet gender gap is disappearing. However, empirical evidence indicates that although men and women are equally likely to use the Internet for business and personal purposes, men are more likely than women to purchase products and/or services from the Web [9]. In other words, women may be visiting Internet sites, but men are more likely to purchase from these sites.

Advertisers and retailers view women as one of the fastest growing population segments using the Web. However, if women are less likely than men to use the Web to make purchases [9], it may be more profitable for organizations to focus sites on products and services that attract male shoppers. In contrast, if the business community is equipped with an understanding of what motivates, encourages, and/or discourages the female consumer from purchasing online, steps may be taken to meet these expectations and reach this growing segment of Web users.

This article explores gender differences with respect to Web-based shopping. We investigate whether gender is a significant predictor of intention to purchase on the Web. We also examine the impact of gender on perceptions of the characteristics of Web-based shopping. The literature in two broad areas, gender and innovation adoption, serves as the basis for this research.

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Gender and IT

Men have long been associated with technology while women have often been depicted as somewhat passive users. Starting as early as high school, female students seem to be noticeably less interested in technology and are underrepresented in computer application courses. Moreover, evidence suggests this trend may continue in the workplace. According to a study reported in the Los Angeles Times (Aug. 25, 1998), the proportion of women among U.S. computer professionals fell in the 1990s from 35.4% to 29.1%.

Interestingly, mounting evidence suggests that contrary to popular beliefs, women do not shun computers. For example, women make up nearly 40% of home-based email users. Women also seem to be joining the Internet quicker than ever. As a result, we see Web sites specifically geared toward the female consumer (for example, Women.com, iVillage.com, Oxygen.com). While gender has generally been ignored in the IT adoption literature [6], there are a number of notable exceptions. Gefen and Straub [6] examined how women and men differed in their perceptions and use of email. While they found only an indirect influence of gender on email use, they conclude their results "more than justify future research into gender effects on information technology perceptions and outcomes."

Differences in how genders are portrayed with respect to information technologies offer interesting insight into how men and women might differ in their perceptions of Web technologies. A study of advertisements for high-technology products in business and technology magazines demonstrated that depictions of males and females in these advertisements were largely stereotypic [2]. Men were portrayed as deep thinkers who are connected to the future. In contrast, the advertisements used women to convey the notion of simplicity of use. Gender differences in computer-related attitudes and behavior have also been demonstrated in a number of studies [12]. For example, individuals' attitudes toward computers can be classified according to gender [5]. A meta-analysis of the literature on gender differences related to computers indicates there are significant gender differences in overall attitudes toward computers and in behaviors related to computers [12]. In addition, men and women differ in their perceptions of the usefulness and ease of information technologies [11].

Consumer behavior research indicates women truly enjoy the shopping experience compared to their male counterparts. Women who enjoy going to the mall outnumber men who enjoy going to the mall by a factor of 1-1/2. Further, 60% of all shopping addicts are women [1]. An important question for the online shopping industry is whether women are willing to relinquish the traditional shopping trip (during which time items can be carefully examined) for the virtual reality version.

A recent study [9] implies that women may not be quite ready or willing to depart with the conventional shopping experience. The study finds that gender is a significant predictor of the respondents' overall and personal/business Web usage. In addition, the study finds that gender is a significant predictor of the respondents' history of Web-based purchases, with male respondents more likely to have purchased a product or service on the Web.

If gender is a significant predictor of intention to shop on the Web, it may be useful to understand why this is so. Diffusion of Innovation theory is concerned with how the use of innovations spreads through social systems. One aspect of this theory argues that perceptions of certain characteristics of an innovation influence its adoption. Three of these—relative advantage, complexity, and compatibility—are the most widely supported. Other perceptions that influence adoption have also been proposed, including result demonstrability, visibility, and image [10]. The following summarizes Diffusion of Innovation theory constructs of interest to this study:

  • Relative advantage. The degree to which an innovation is seen as being superior to its predecessor.
  • Complexity. The degree to which an innovation is seen by the potential adopter as being relatively difficult to use and understand.
  • Compatibility. The degree to which an innovation is seen to be compatible with existing values, beliefs, experiences, and needs of adopters.
  • Result demonstrability. The degree to which the results of using an innovation are perceived as tangible.
  • Visibility. The perception of the actual visibility of the innovation itself as opposed to the visibility of outputs.
  • Image. The degree to which the use of the innovation is seen as enhancing an individual's image or social status.

In addition, empirical evidence indicates that trust is important in the context of Internet-based retail commerce [8]. Since Web shopping occurs at a distance rather than face-to-face, uncertainty, vulnerability, and dependence are all high relative to traditional shopping. This leads to trust being more important than in many conventional transactions. In this study, trust is the "trustor's expectations about the motives and behaviors of a trustee" [3].

Since there is significant evidence that potential adopters' perceptions of an innovation influence their adoption decisions [10], understanding how these perceptions of Web shopping differ between men and women may provide insights into differences in use intentions.

Our study was conducted to test whether gender is a significant predictor of intention to shop on the Web, and how perceptions of Web shopping differ according to gender. The measurement scales included in the survey were validated using data from a pilot study, and all scales exhibited acceptable psychometric properties, except for the visibility scale, which had low reliability and was dropped from further analyses. The instrument was then administered to 511 subjects who ranged in age from 17 to 48 years old.

bullet.gif Analysis Stage 1. Is gender a predictor?

A regression analysis was performed to determine whether gender is a significant predictor of intention to shop on the Web. The results of this analysis are shown in Table 1.

Gender is a significant predictor of an individual's intention to make purchases over the Web. Our male participants were more likely (mean use intention = 4.64) than our female participants (mean use intention = 3.85) to purchase products and/or services via the Web. Also significant are computer use (years), email use, prior Web use, and access to a credit card. The first three of these items tell us that previous computer use does in some sense matter to intentions to shop via the Web. Participants who are more likely to purchase from the Web are those with a greater number of years of computer experience, who use email more than once per week, and who have previously used the Web. Not surprisingly, our results also indicate that having access to a credit card is a significant predictor of whether individuals are more likely to purchase from the Web.

bullet.gif Analysis Stage 2. Do perceptions differ?

To test the relationship between gender and the perceived innovation characteristics we performed multivariate analysis of covariance (MANCOVA), which shows whether at least one of the perceived characteristics differs by gender. Table 2 shows the results of this analysis. Results indicate that overall levels of the perceived innovation characteristics differ by gender (p < 0.001). Further, perceptions of complexity, compatibility, relative advantage, result demonstrability, and trust significantly differ by gender, while perceptions of image did not. In each case, men perceived Web shopping more positively than women.

Based on the results of this research we can state that men are more likely to intend to use the Web for making purchases, and men's perceptions of the characteristics of Web shopping are more favorable than women's. Specifically, men rate the compatibility, relative advantage, result demonstrability, and trustworthiness of Web shopping higher, and its complexity lower than do women.

These conclusions verify earlier findings that indicate men are more likely to intend to shop on the Web. More importantly, the findings establish significant differences in how women and men perceive Web shopping.

Understanding why there are differences in intentions to shop on the Web may help eliminate the gender gap. Broadly speaking, two factors may provide plausible explanations for the differences in perceptions—shopping practices and preferences, and attitudes toward IT. While additional research is necessary to investigate the validity of these influences, they provide a starting point for discussion.

Surprisingly, there is limited research into how males and females differ in their shopping behavior [4]. However, it has been established that women tend to be more rational catalog shoppers [4]. It may be that for many product categories (for example, clothing) it is more difficult to make rational, informed decisions when shopping online. With many products, it may be difficult to judge the quality or fashion of a product on a Web site. For example, two different pairs of shoes may look identical on a Web site. These same two pairs, however, may be quite different in the quality of materials and workmanship—differences that may be hidden on the Web.


If the business community is equipped with an understanding of what motivates, encourages, and/or discourages the female consumer from purchasing online, steps may be taken to meet these expectations and reach this growing segment of Web users.


In general, women view some forms of shopping as more of a social activity than do men. Although some merchants attempt to build a sense of community by allowing limited interaction among customers (for example, Amazon's customer reviews), online shopping remains a solitary activity. In fact, early proponents of online shopping touted the ability to avoid mall crowds, pushy salespeople, and so on. Some consumers may view this as a benefit, while others may enjoy the interaction involved with traditional shopping. If women tend to gain benefit from the social aspects of traditional shopping, Web-based shopping may be viewed less favorably, thus affecting women's perceptions of the relative advantage and compatibility of Web-based shopping.

The types of products available online may also impact perceptions. In the early days of Web-based shopping, computer hardware and software, consumer electronics, and product categories typically associated with men, were among the most popular products online. By mid-2000, online computer hardware and software sales were much higher than online sales of more female-oriented product categories such as apparel and home decor (Forrester Online Retail Index, www.forrester.com/NRF/). If products typically purchased by men dominate the Web landscape, women may view online shopping online as less advantageous and less compatible. In addition, if female-oriented products are less available online, women are not as likely to have online purchases to show their friends, resulting in lower result demonstrability. As the popularity of Web-based shopping increases, product offerings may continue to expand into products more oriented toward women.

However, it is important to note that perceptions are primarily based on past experience. Since male-oriented products dominate the relatively short history of Web shopping, it is not surprising that women have a less favorable view. In addition, past socialization of women away from technology may also be to blame. Early on, experiences with technology tend to be oriented toward males rather than girls. For example, there are very few video or computer games designed to appeal to girls [7]. This socialization away from technology may lead to a feeling that "computers are for boys," resulting in lower levels of computer experience by women. This lack of experience may translate into increased perceptions of Web shopping complexity.

Finally, traditional gender-role stereotypes tend to portray females as less technology oriented, which may degrade women's attitude toward computers. This less favorable attitude may extend to Web shopping, impacting perceptions of compatibility and complexity.

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Managerial Recommendations

This study demonstrates that women view Web-based shopping less favorably than men. However, there are some steps organizations can take that may improve women's perceptions of Web-based shopping.


Web merchants may find it useful to use technology to increase a sense of community and create a social forum for their customers.


Web merchants may find it useful to use technology to increase a sense of community and create a social forum for their customers. Since women enjoy the social aspect of shopping, merchants may wish to consider such features as chat rooms and threaded discussions to build a shopping community and reduce the solitary nature of online shopping. This will not only improve the social nature of Web-based shopping, thus improving its compatibility, but serve to enhance the trustworthiness of the innovation.

Since women tend to be more rational shoppers, providing accurate descriptions and quality pictures may increase Web-based compatibility and enhance perceptions of trustworthiness of the vendor and the related product. Although it is not possible to touch fabric or feel the quality of products online, new technologies such as virtual mannequins and high-quality visuals (if properly applied) might appeal to female shopping preferences.

A key to improving women's perceptions of the relative advantage of Web shopping is to reduce the risk involved in purchasing online. Very liberal return policies, which have long been used in catalog shopping, lower the risk associated with making sight-unseen purchases. If shoppers know there will be little cost or inconvenience in returning products that do not fit or whose fabric is not up to expectations, they may see Web-based shopping as more beneficial and less risky. Computer hardware retailers have long used policies such as the "30-day, money-back guarantee" to overcome online shopping hesitation. Retailers of other types of products may find that following this lead increases the success of their online merchandising efforts.

Online merchants should consider making special offers to new customers. For example, giving generous discounts to new customers, or allowing them to order inexpensive, useful products at no cost may induce more women to use online shopping. Through experience, women will become more accustomed to Web-shopping, which should improve perceptions of compatibility and complexity.

In a larger sense, it is critical to reverse the past tendency to socialize girls away from technology. As IT becomes an increasingly central tool in our lives, socializing over half our population to be even slightly uncomfortable with technology is intolerable. As IT practitioners and researchers, we must redouble our efforts to make Web and other technologies extremely familiar to women and girls.

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References

1. Arthur, C. Fifteen million Americans are shopping addicts. American Demographics 14 (1992), 14–15.

2. Dilevko, J. and Harris, R. Information technology and social relations: Portrayals of gender roles in high tech product advertisements. J. Amer. Society for Info. Science 48, 8 (Aug. 1997), 718–727.

3. Doney, P. and Canon, J. An examination of the nature of trust in buyer-seller relationships. J. Marketing 61, 2 (Apr. 1997), 35–51.

4. Eastlick, M. and Feinberg, R. Gender differences in mail-catalog patronage motives. J. Direct Marketing 8, 2 (Apr. 1997), 37–44.

5. Gattiker U. and Hlavka, A.. Computer attitudes and learning performance: Issues for management education and training. J. Organizational Behavior 13, 1, (Jan. 1992) 89–102.

6. Gefen, D. and Straub, D. Gender differences in the perception and use of e-mail: An extension to the Technology Acceptance Model. MIS Q. 21, 4 (Dec. 1997), 389–400.

7. Gorriz, C. and Medina, C. Engaging girls with computers through software games. Commun. ACM 43, 1 (Jan. 2000), 42–49.

8. Jarvenpaa, S.L., Tractinsky, N., and Vitale, M. Consumer trust in an Internet store. IT and Management 1, 1 (Jan. 2000), 45–71.

9. Korgaonkar, P. and Wolin, L. A multivariate analysis of Web usage. J. Advertising Research 39, 2 (Apr. 1999), 53–68.

10. Moore, G.C. and Benbasat, I. Development of an instrument to measure the perceptions of adopting an information technology innovation. IS Research 2, 3 (Sept. 1991), 192–222.

11. Venkatesh, V. and Morris, M. Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Q. 24, 1 (Mar. 2000), 115–139.

12. Whitley, B. Gender differences in computer-related attitudes and behavior: A meta-analysis. Computers in Human Behavior 12, 1 (Jan. 1997), 1–22.

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Authors

Craig Van Slyke (craig.vanslyke@bus.ucf.edu) is an assistant professor in the department of Management Information Systems at the University of Central Florida, Orlando.

Christie L. Comunale (comunale@liu.edu) is an assistant professor in the School of Professional Accountancy, Long Island University—C.W. Post Campus, Brookville, NY.

France Belanger (belanger@vt.edu) is an associate professor in the Pamplin College of Business at Virginia Polytechnic Institute and State University, Blacksburg, VA.

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Tables

T1Table 1. Regression analysis.

T2Table 2. MANCOVA results.

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