Beyond gender differences: Self-concept orientation and relationship-building applications on the Internet

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1 Journal of Business Research 60 (2007) Beyond gender differences: Self-concept orientation and relationship-building applications on the Internet Maureen E. Hupfer, Brian Detlor 1 DeGroote School of Business, McMaster University, 1280 Main Street West, Hamilton, ON, Canada L8S 4M4 Received 1 October 2005; received in revised form 1 April 2006; accepted 1 June 2006 Abstract Research concerning gender differences in Internet usage suggests greater interest among females in applications with relationship-building implications, and commonly refers to agentic and communal gender roles to explain such behaviors. However, a regression analysis of Web-based survey data collected from 386 respondents concerning their use of such Internet applications found that usage was better predicted when agentic (Self-Orientation) and communal (Other-Orientation) self-concept characteristics were measured rather than assumed from biological sex. With the exception of instant messaging, Other-Orientation was a positive predictor of usage rates for relational applications including , greeting cards, and finding new friends or relationships. Furthermore, Other-Orientation either added to or superseded the prediction afforded by biological sex Elsevier Inc. All rights reserved. Keywords: Gender; Sex; Self-concept; Internet usage 1. Introduction Sex differences in Internet usage have attracted considerable interest among researchers in psychology, marketing and electronic commerce. Compared with men, women are more likely than men to value the Internet as tool for maintaining social bonds (e.g., Boneva et al., 2001; Garbarino and Strahilevitz, 2004; Jackson et al., 2001; Krantz, 2000; Macklem, 2000; Marsh, 2001; Morahan-Martin, 1998; Mosley-Matchett, 1998; Weiser, 2000; Smith and Whitlark, 2001). More so than men, women use to communicate with friends and family. They post supportive messages to discussion groups, strongly value online purchase recommendations from friends, and are attracted to Internet communities. Typical female usage situations reflect relational concerns such as making friends, fighting for causes, exchanging ideas, and searching for information that is important not just to themselves but also to close others. Corresponding author. Tel.: x addresses: hupferm@mcmaster.ca (M.E. Hupfer), detlorb@mcmaster.ca (B. Detlor). 1 Tel.: x These observed sex differences in Internet behaviors commonly are attributed to traditional gender role distinctions (e.g., Morahan-Martin, 1998; Smith and Whitlark, 2001) that are consistent with the agentic-communal conceptualization first proposed by Bakan (1966). The male or agentic gender role is distinguished by personality characteristics such as independence, autonomy and self-sufficiency; male self-concepts evidence concern for the self and are defined by separation from others. In contrast, typical female or communal characteristics consist of interdependence, nurture, and concern for others as well as the self (e.g., Chodorow, 1978; Cross and Markus, 1993; Gilligan, 1982; Markus and Oyersman, 1989). In a similar fashion, gender role interpretations also have been proposed to account for observed sex differences in response to marketing communication (e.g., Brunel and Nelson, 2000; Meyers-Levy, 1988). Men are persuaded by agentic messages that articulate self-interest in a manner consistent with the male self-concept, but they do not respond to communal appeals that address concern for others. On the other hand, women either respond positively to both types of appeals (Meyers-Levy, 1988) or react more favorably to a message that encourages them to help others (Brunel and Nelson, 2000). Importantly, the gender theorizing described above assumes a direct relationship between biological sex and the personality /$ - see front matter 2006 Elsevier Inc. All rights reserved. doi: /j.jbusres

2 614 M.E. Hupfer, B. Detlor / Journal of Business Research 60 (2007) characteristics or aspects of self-concept that relate to gender identity. In contrast, this study contends that agentic and communal characteristics should be treated as individual differences that are not dependent on biological sex. Many women score higher on measures of agency than on those which tap communion; similarly, men also have been shown to score in the opposite direction of what the gender role stereotype would predict (Bem, 1974; Hupfer, 2001). Rather than being fixed, relationships between biological sex and gender identity vary over time, across class, and between cultures (Markus and Kitayama, 1991). This evidence suggests that individualdifference explanations of attraction to the Internet's social networking potential may augment or supersede interpretations that equate gender and sex. Furthermore, if stereotypic role distinctions become less pronounced with successive generations (Nelson, 1994), theoretical frameworks that investigate gender from an individual differences standpoint will become increasingly important. 2. The self-concept orientation model As an alternative to the commonly assumed equivalence of sex and gender, the present study proposes a self-concept orientation framework to explain usage rates for Internet applications with relational implications. This approach specifies the measurement of gender-related aspects of self-concept known as Self- and Other-Orientation (Hupfer, 2001). Briefly described, Self-Orientation is a five-item scale that assesses agency (self-sufficient, make my own choices, am my own person, self-reliant and independent). Communal characteristics (nurturing, understanding, compassionate, sympathetic, and sensitive to the needs of others) are tapped with Other- Orientation. Respondents use a 9-point scale anchored by never true of me (1) and always true of me (9) to respond to all 10 items. The two scale scores are calculated as the averages of their respective items. Research addressing the discriminant and convergent validity of the scales (Hupfer, 2001) finds latent construct correlations between Self-Orientation and the PAQ Masculinity scale (.675) as a related measure of agency (Spence et al., 1975), and between Self-Orientation and the Triandis (1995) measure of Horizontal Individualism (.546). Other-Orientation is correlated (.887) with PAQ Femininity, which assesses communal characteristics, and Triandis' Horizontal Collectivism (.703). Furthermore, Self-Orientation is unrelated to Femininity and Collectivism, while Other-Orientation is uncorrelated with Masculinity and Individualism. Rather than being bi-polar, Self-Orientation and Other-Orientation are theoretically independent. Stochastically, small correlations (.25) exist between the two scales (Hupfer, 2001). 3. Research hypotheses In adapting the agentic-communal role distinction described above to an individual differences framework, Other-Orientation was expected to account for usage differences that until now have been attributed to the female communal role. That is, Other-Orientation should be positively associated with respondents' self-reports of how often they use applications with social networking possibilities. Because past research shows that scales which measure agentic (or masculine) and communal (or feminine) characteristics are independent rather than bipolar (Bem, 1974; Hupfer, 2001), Self-Orientation should be unrelated to usage frequency. H 1. Other-Orientation will predict how often instant messaging or chat applications are used. H 2. Other-Orientation will predict how often is used for communication directed toward close others. H 3. Other-Orientation will predict how often is used to communicate with those who are casual personal acquaintances. H 4. Other-Orientation will predict how often greeting card applications are used. H 5. Other-Orientation will predict how often the Web is used to find friends or new relationships. 4. Research design 4.1. Data collection All current students, recent graduates, faculty and staff in the business school received an message to invite their participation in an online survey concerning their use of Web applications with relationship-building implications. Participants were entered in a draw for a number of $100 gift certificates to a local shopping mall. Of the 422 surveys that were received, usable data were obtained from 155 male and 231 female respondents Measures Dependent measures: Respondents were asked to consider their behavior over the last six months and indicate how often they had used to a) communicate with people with whom they had close personal relationships (e.g., a good friend, partner/spouse, family member) and b) to keep in touch with more casual personal acquaintances. Also with respect to the last six months, they indicated how often they had sent or received instant messages or participated in online chat sessions, used the Web to find new friends or potential relationships, and had sent a greeting card. All responses were collected with a nine-point scale that ranged from not at all (1) to more than once a day (9). Predictor variables: As specified in the self-concept orientation model, the focal predictor variables were Self- and Other-Orientation (Hupfer, 2001). Participants also supplied information about their sex, university status (current student, graduate, faculty or staff) and age category (up to 24 years old, and in five-year increments thereafter). To control for more general Internet application use, respondents were asked how often they used the Internet to search for information concerning products and services, and how often they purchased over the

3 M.E. Hupfer, B. Detlor / Journal of Business Research 60 (2007) Internet. Both of these were assessed with 9-point scales that ranged from 1 ( not at all ) to9( more than once a day ). Finally, cultural background was assessed by asking respondents to identify the language(s) spoken by their fathers Data analysis Past research has found interactions between Self- and Other-Orientation, in addition to evidence of non-linear relationships between the scales and dependent measures (Hupfer and Detlor, 2006). Therefore, regression models were specified with all terms for the full quadratic polynomial mean function (Cook and Weisberg, 1999). These included the linear main effect parameters for Self-Orientation and Other-Orientation, the cross-product interaction and the squared Self- and Other-Orientation terms. The two scale scores were standardized before the higher-order parameters were computed (Aiken and West, 1991). To allow for the possibility of differential response from the sample's mix of students in this study, alumni, faculty and staff, a university status variable was created (1 = current students, 2 = graduate and 3 = all others). The age categories were collapsed into three levels (1 = 18 24, 2 = 25 29, 3 = 30 and over). Next, cultural background was coded according to low and high levels of Individualism using Hofstede's (2001) reported values for 53 countries. All respondents whose fathers spoke only English or English and French were assumed to be acculturated Canadians and they were coded as having a high level of Individualism. Those whose fathers spoke languages other than English and French were assumed to identify more closely with the cultural background associated with the languages they indicated. All languages linked with countries having Individualism values below 48 (approximately the midpoint in Hofstedes' range of 6 to 91) were coded as low Individualism. All those exceeding this point were coded as high Individualism. No predictions were made concerning biological sex because the primary interest was testing theory pertaining to the predictive power of Other-Orientation. However, in order to build a managerial case for collecting self-concept orientation data, when information about user sex is so readily available, two additional sets of analyses examined relationships among sex, self-concept orientation and usage rates. The first set of these models included sex along with the age, status, search, purchase and individualism variables. If the sex was significant, the significant self-concept variables identified in the initial analysis were added to sex and the other predictors. Next, the significance of the difference between the R 2 values for the two models was calculated to determine whether practitioners would be better able to predict user response if self-concept parameters were included. 5. Results 5.1. Self- and Other-Orientation Self-Orientation scores ranged from 4.2 to 9.0 with a mean of 7.63, while Other-Orientation ranged from 3.4 to 9.0 with a mean of Cronbach's alphas were.85 and.88 respectively. As expected (Hupfer, 2001), no sex difference was found in Self-Orientation (M female =7.65, M male =7.60; t 384 =.541, ns) but females were significantly higher on Other-Orientation (M female =7.49, M male =6.81; t 384 = 6.143, p b.01). Cross- Table 1 Regression model summaries for predicting usage frequency of five types of relationship-building Internet applications, based on different predictor sets including sex and self-concept orientation Variable {and range of possible values on the respective variable} Messaging a Close b Casual c Cards d Friends e Model 1 Age {1 to 3} Status {1 to 3} Search {1 to 9} Purchase {1 to 9} Individualism {1 to 2} Self {1 to 9} Other {1 to 9} Self Other Self Other R 2 (all pb.01) Model 2 Age Status Search Purchase Individualism Sex R 2 (all pb.01) Model 3 Age Status Search Purchase Individualism Sex Self Other Self Other Self 2.13 Other 2 R 2 (all pb.01) = pb.10. = pb.05. = pb.01. Note: All dependent variables had possible values that ranged from 1 to 9. As per Aiken and West's (1991) recommendation, unstandardized s have been reported because the Self-Orientation and Other-Orientation variables were standardized before creating the cross-product and interaction terms. The standardized Self-Orientation scores ranged from 3.48 to 1.40; the standardized Other-Orientation scores ranged from 3.47 to a Instant messaging. b ing close others. c ing casual personal acquaintances. d Using greeting card applications. e Finding friends or new relationships.

4 616 M.E. Hupfer, B. Detlor / Journal of Business Research 60 (2007) Table 2 Dependent variable means by predictor category Dependent variable Predictor N Mean S.D. Instant messaging/ chat for close relationships for casual relationships Age Status Student Graduate Faculty/staff Individualism Low High All Sex Male Female All Sex Male Female All Greeting cards Sex Male Female All Finding new friends or relationships Status Student Graduate Faculty/staff Individualism Low High All tabulation of individual-level differences between the two scales indicated that males conformed more closely to stereotypic prescriptions. Most (75.5%) had Self-Orientation scores that were greater than or equal to their Other-Orientation scores. Females, on the other hand, were much more likely than males to have scores in the opposite direction of the gender stereotype. Half (49.8%) of the women surveyed had Self- Orientation scores that were greater than their Other-Orientation scores. Self- and Other-Orientation scores also differed with culture. Respondents from High-Individualism countries scored higher on Self-Orientation than those from Low-Individualism cultures (M high =7.74, M low =7.35; t 384 = 3.587, pb.01). Their Other- Orientation scores also were significantly different, with higher scores being found among those with Low-Individualism cultural background (M low =7.40, M high =7.15; t 384 =2.039, pb.05). University status and age were unrelated to Self- and Other- Orientation. Non-significant results were obtained in one-way ANOVAs with university status for both Self- (F 2, 383 =2.365) and Other-Orientation (F 2, 383 =1.080). Similarly, age had no effect on either Self- (F 2, 383 =.055) or Other-Orientation (F 2, 383 =.394). Finally, cross-tabulations of sex, status and age found that males and females were equally distributed across the three university status categories (χ 2 2 =.057, ns) and the three age categories (χ 2 2 =2.056, ns). Before proceeding with the first regression, the correlation matrix was inspected for evidence of problematic multicollinearity but all correlations between the predictor variables were below the.60 threshold. The strongest relationship, at.551, was between the age and status predictors Instant messaging and chat The first regression analysis with the self-concept parameters found a non-significant for Other-Orientation and therefore failed to confirm H1 (see Table 1 for all analyses). Significant predictors of instant messaging or chat use included age, university status, use of the Internet for searching and purchasing (marginal), and Individualism. Respondents were more likely to use instant messaging or chat if they were younger (see Table 2 for means pertaining to all analyses), students, frequent users of the Internet for searching and purchasing goods or services, and were from a cultural background that is more collectivist (i.e., low level of Individualism). The second analysis found a non-significant for sex, and no further analysis was conducted ing close personal acquaintances Other-Orientation emerged as a positive predictor of ing frequency, confirming H2. Using the Internet for both information search and purchasing also were positively related to ing frequency. Next, sex was a significant predictor of how often respondents ed those with whom they had close relationships, with women using this form of communication more often than men. The final analysis sought to determine whether a model that included Other-Orientation, in addition to sex, would afford better prediction than that obtained with sex alone. The F test for the R 2 difference between the two models confirmed that the addition of Other- Fig. 1. Predicted use frequency of greeting card applications at low, moderate, and high levels of Self- and Other-Orientation.

5 M.E. Hupfer, B. Detlor / Journal of Business Research 60 (2007) Orientation significantly improved prediction (F 1, 377 =6.892, pb.01) ing casual personal acquaintances Consistent with the H3 prediction, Other-Orientation emerged as a significant predictor of how often was used to keep in touch with more casual acquaintances. Similar to the results obtained with the use of to communicate with close others, Internet searching and purchasing also were positively related to casual acquaintance ing frequency. The second model found that sex explained frequency, with women communicating with casual acquaintances more often than men. However, the third model demonstrated that Other-Orientation best explained the casual dependent variable. When Other-Orientation was added to sex and the other predictors, the model explained significantly more variance (F 1, 377 =10.538, pb.01) and the sex became non-significant Greeting card use Confirming H4, Other-Orientation was positively associated with usage rates for greeting card applications. Internet searching and purchasing also were significant predictors. Unexpectedly, however, the squared Self-Orientation term also was significant, indicating a non-linear relationship between Self-Orientation and the use of greeting card applications. To better interpret these results, point estimates of predicted Fig. 3. Predicted use frequency for friend or relationship finding applications (other by self) at low, moderate, and high levels of Self- and Other-Orientation. frequency were computed by solving the regression equation at all nine possible combinations of low, moderate and high levels of both Self- and Other-Orientation. Following Cohen and Cohen (1983), these levels were assigned values of 1 (low = one standard deviation below the mean for z-scores), 0 (moderate = mean) and 1 (high = one standard deviation above the mean). Values of 1 were substituted for all other variables. Then, a two-way plot of predicted greeting card use frequency at low, moderate and high values of both Self- and Other- Orientation was generated (Fig. 1). This plot reveals U-shaped relationships between Self-Orientation and greeting card use at all three levels of Other-Orientation, with respondents using greeting card applications less often if they are at a Moderate level of Self-Orientation. Finally, the third analysis found that both Other-Orientation and the squared Self-Orientation term added to prediction even when the sex was present (F 2, 375 =11.993, pb.01). In this case, the sex parameter was retained although it became a less important predictor of online greeting card use Finding new friends/relationships Fig. 2. Predicted use frequency for friend or relationship finding applications (self by other) at low, moderate, and high levels of Self- and Other-Orientation. These results were the most complex among those observed. In addition to the predicted (H5) positive parameter for Other- Orientation, significant squared Other-Orientation and interaction terms were found. Contrary to expectations, a negative parameter for Self-Orientation also emerged. Other significant predictors included university status, with current students being the most likely to use the Web to find a new friend or

6 618 M.E. Hupfer, B. Detlor / Journal of Business Research 60 (2007) relationship; the Internet search and purchase variables; and Individualism, with respondents being more inclined to use the Web to find new friends or relationships if they came from a more collectivist cultural background. Because sex was unrelated to using the Web in this manner, no further analysis was conducted. Two-way plots of the predicted application use were produced using the same graphical method described above. The first of these, with Self-Orientation on the horizontal access (Fig. 2) illustrates clearly the Other-Orientation term, the interaction, and the negative parameter for Self-Orientation. When an individual is highly Other-Oriented, the level of Self- Orientation is of little importance. However, at moderate and lower levels of Other-Orientation, the negative relationship between Self-Orientation and usage frequency is stronger, such that respondents who are low in Other-Orientation and high in Self-Orientation report the lowest degree of interest in finding a friendship or relationship online. The squared Other-Orientation term is most easily observed if the horizontal and vertical axes are reversed (Fig. 3). At every level of Self-Orientation, the relationship between Other-Orientation and use frequency is stronger between the moderate and high levels of Other- Orientation than it is between the low and moderate levels. 6. Discussion It appears that past researchers are at least partly correct in attributing female interest in relationship building Internet applications to their presumed communal role. With the exception of instant messaging or chat, Other-Orientation was a positive predictor of how often respondents reported using Internet applications with relational implications. The failure to find any sex or self-concept differences in instant messaging or chat is consistent with results reported by Shaw and Gant (2002). Shaw and Gant proposed that their results reflected a lesser gender gap among younger generations, but Other- Orientation's positive prediction of usage frequency for other applications suggests that technology acceptance and familiarity, and perhaps cultural background may be more important than gender considerations where messaging and chat are concerned. Collectivist cultural background also added to the prediction of friend-finding on the Internet, another application that sex failed to predict. Notably, this research demonstrates the managerial relevance of Other-Orientation data collection. Sex data is much more easily acquired, but there are distinct advantages associated with Other-Orientation. Messaging aside, in every case Other- Orientation was a significant predictor of respondents' tendency to engage with applications that have relational implications. Where to close others and greeting card use were concerned, Other-Orientation added to the prediction afforded by sex. In the case of to casual acquaintances, Other- Orientation superseded sex as a predictor of communication frequency. Finally, Other-Orientation was a positive predictor of using the Internet to find friends or relationships whereas sex was unrelated to this behavior. The results were more complex and indicate that Self-Orientation data should be collected in conjunction with the Other-Orientation scale. To further explore these possibilities, additional investigation with Self- and Other- Orientation, sex, and their interaction is recommended. The relationship of Self- and Other-Orientation with other individual differences that have shown to be related to Internet usage behaviors also should be explored (e.g., Tuten and Bosnjak, 2001). This study found associations between a very rough indicator of individualist versus collectivist cultural background and the use of instant messaging and relationshipfinding sites. Future investigation should consider a broader array of variables related to cultural difference and ideally should measure these variables rather than assume them from secondary indicators. Like all research that takes advantage of a student sample, this investigation is limited in its generalizability. Convenience samples are appropriate starting points for theory testing (Calder et al., 1981). However, the self-concept orientation framework should be further examined among a more representative sample of Internet users. In age, education and Internet experience, this study's sample was comparable to the Canadian high-usage profile (Dryburgh, 2001), but this profile can be expected to shift as older users continue to come online. The small or negligible sex differences reported here may become more important among an older cohort that conforms more closely to traditional gender distinctions. Certainly a more balanced representation across age, sex, types of education or employment, and cultural background will be an important consideration for future investigation. The sample was dominated by young female students and by those who describe themselves as acculturated Canadians with attendant high Individualism scores. Finally, results may have been affected by having collected survey data from the students, professors and staff of a single university faculty, and one which might well be characterized by higher levels of Self-Orientation than found in other programs. The business faculty implications may be stronger for women; half the females in the sample had Self- Orientation scores higher than their Other-Orientation scores but the males were much more likely to conform to the gender role prescription. Despite its preliminary stage of investigation, the selfconcept orientation model has useful managerial implications. Like e-commerce sites that have used personality quizzes to tailor their product recommendations (Lee, 2000), practitioners promoting the use of applications that enhance social networking may want to administer the Self- and Other- Orientation scales to their targets. Those with high Other- Orientation scores will be particularly attractive prospects. Vendors that offer a suite of applications with relational potential should be able to use the self-concept orientation information to cross-sell and to encourage current customers to use a friend buttons to further increase their exposure. Most importantly, the self-concept orientation framework makes an important contribution by conceptualizing gender on an individual differences basis. Rather than assuming a direct link between gender and sex, the model can accommodate those with levels of agentic and communal characteristics that differ from those prescribed by traditional gender stereotypes.

7 M.E. Hupfer, B. Detlor / Journal of Business Research 60 (2007) Consequently, Other-Orientation outperformed biological sex in predicting the frequency with which users took advantage of Internet applications that enhance social connection. If practitioners are correct in their belief that gender role distinctions will continue to erode (Nelson, 1994), individual differences frameworks such as the self-concept orientation model will become increasingly important explanations of Internet usage behaviors that until now have been accounted for by a simple male female distinction. References Aiken LS, West Stephen G. Multiple regression: testing and interpreting interactions. Newbury Park, CA: Sage; Bakan D. The duality of human existence. Chicago: Rand McNally; Bem SL. The measurement of psychological androgyny. Journal of Consulting and Clinical Psychology 1974;42(2): Boneva B, Kraut R, Frolich D. Using for personal relationships: the difference gender makes. The American Behavioral Scientist 2001;45 (3): Brunel FF, Nelson MR. Explaining gendered responses to help-self and helpothers charity ad appeals: the mediating role of world-views. Journal of Advertising 2000;29:15 28 [Fall]. Calder BJ, Phillips LW, Tybout Alice M. Designing research for application. Journal of Consumer Research 1981;8(2): Chodorow NJ. The reproduction of mothering: psychoanalysis and the sociology of gender. Berkeley: University of California Press; Cohen J, Cohen P. Applied multiple regression/correlation analysis for the behavioural sciences. 2nd ed. London: Erlbaum Associates; Cook RD, Weisberg Sanford. Applied regression including computing and graphics. New York: John Wiley and Sons; Cross SE, Markus HR. Gender in thought, belief, and action: a cognitive approach. In: Beall AE, Sternberg RJ, editors. The psychology of gender. New York: Guilford Press; p Dryburgh H. Changing our ways: Why and how Canadians use the Internet. Statistics Canada, Catalog No. 56F0006XIE Retrieved May 7, 2005, from Garbarino E, Strahilevitz M. Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation. Journal of Business Research 2004;57: Gilligan C. In a different voice: psychological theory and women's development. Cambridge, MA: Harvard University Press; Hofstede G. Culture's consequences: comparing values, behaviors, institutions and organizations across nations. 2nd ed. Thousand Oaks: Sage; Hupfer ME. Self-concept Orientation and Response to Agentic and Communal Advertising Messages. Unpublished Doctoral Thesis, University of Alberta, Edmonton, Hupfer ME, Detlor B. Gender and Web information seeking: a self-concept orientation model. Journal of the American Society for Information Science and Technology 2006;57(8): Jackson LA, Ervin KS, Gardner PD, Schmitt N. Gender and the Internet: women communicating and men searching. Sex Roles 2001;44(5/6): Krantz M. The great online makeover. Time 2000:64 5 [January 31]. Lee G. Cybershoppers: a moving target. Women's wear daily Internet supplement 2000; (August): Retrieved May 7, 2005, from Lexis- Nexis database. Macklem K. Women to lead new digital gold rush. Financial Post 2000:C1 [March 30]. Marsh H. Why women are taking to the net. Marketing 2001:33 4 [June 21]. Markus HR, Kitayama Shinobu. Culture and the self: implications for cognition, emotion and motivation. Psychological Review 1991;98: [April]. Markus H, Oyersman D. Gender and thought: the role of self-concept. In: Crawford M, Gentry M, editors. Gender and thought: psychological perspectives. New York: Springer-Verlag; p Meyers-Levy J. The influence of sex roles on judgment. Journal of Consumer Research 1988;14: [March]. Morahan-Martin J. Males, females, and the Internet. In: Gackenbach J, editor. Psychology and the Internet: intrapersonal, interpersonal, and transpersonal implications. San Diego: Academic Press; p Mosley-Matchett JD. Marketers: there's a feminine side to the Web. Marketing News 1998;32:6 [February 16]. Nelson C. Women's market handbook: understanding and reaching today's most powerful consumer group. Detroit, MI: Gale Research; Shaw LH, Gant LM. Users divided? Exploring the gender gap in Internet use. Cyberpsychology and Behavior 2002;5(6): Smith SM, Whitlark DB. Men and women online: what makes them click? Marketing Research 2001;13(2):20 5. Spence JT, Helmreich R, Stapp J. Ratings of self and peers on sex role attributes and their relation to self-esteem and conceptions of masculinity and femininity. Journal of Personality and Social Psychology 1975;32(1): Triandis HC. Individualism and collectivism. Boulder: Westview Press; Tuten TL, Bosnjak M. Understanding differences in Web usage: the role of need for cognition and the five factor model of personality. Social Behavior and Personality 2001;29(4): Weiser EB. Gender differences in Internet use patterns and Internet application preferences: a two-sample comparison. Cyberpsychology and Behavior 2000;3: [April].

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