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Labovitz School of Business & Economics, University of Minnesota Duluth, 11 E. Superior Street, Suite 210, Duluth, MN 55802 Sd Gender Conference 2 - Womens Images of Guns.Pdf
Fredrica Rudell, lona College [to cite]:
Fredrica Rudell (1991) ,"Sd Gender Conference 2 - Womens Images of Guns.Pdf", in GCB - Gender and Consumer Behavior
Volume 1, eds. Dr. Janeen Arnold Costa, Salt Lake City, UT : Association for Consumer Research, Pages: 187-198.
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http://www.acrwebsite.org/volumes/15525/gender/v01/GCB-01
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This work is copyrighted by The Association for Consumer Research. For permission to copy or use this work in whole or in part,
please contact the Copyright Clearance Center at http://www.copyright.com/.
Boys' Toys and Girls' Tools?: An Exploration of Gender Differences
in Consumer Decision-making for High-tech Products
Fredrica Rudell, lona College
i Gender differences in relations to technology are traced to differences in socialization, involvement, values, problem solving style, and personal efficacy. Hypotheses are generated regarding probable differences in perceived need for high-tech products. Literature and exploratory research results point to a toyItool distinction.
INTRODUCTION
Current interest in the causes, nature and role of gender differences not only is retlected in the popular press, e.g., "Subtle but Intriguing Differences Found In the Brain Anatomy of Men and Women" (Goleman, 1989), but has become an area of intense scholarly interest. We are assured by some scholars that women speak "In a Different Voice" (Gilligan 1982) or have their own "Ways of Knowing," (Belenky et aI., 1986). Others are equally convinced that gender differences are "Deceptive Distinctions" (Epstein 1988).
More than twenty years after landing on the moon, science and technology also earn their share of public attention. While scientists debate the future of cold fusion, superconductivity, and genetic engineering, our lives have been transformed by personal computers, n1icrowave ovens and vcr's. Gender and technology collide in headlines: "Computingin America: A Masculine Mystique" (Markoff 1989). Is technology affecting everyone the same way?
Marketers, adept by now at segmentation, are used to selling soap, soda and sedans differently to men and women, appealing to their different needs and tastes, offering different benefits and models. But what about products and services for which the consumer must undergo extensive problem solving and con1plex decision making, i.e., technological innovations? Do differences in cognitive functioning, learning styles and judgment criteria result in gender differences in consumer decision making for such products? The question to be addressed is: Are there differences between
male and female consumers in their attitudes toward and decision making for high technology goods and services?
With respect to the stages of consumer decision making, these differences might include:
1. Need recognition. Do males and females differ in their perceptions of need for new technology, or perceptions of what is appropriate for a given task?
2. Information processing. Are there gender differences in amounts and types of information used to learn about new technology?
3. Brand evaluation. Do males and females look for different attributes when evaluating high-tech products and forming their attitudes?
4. Purchase. Are there differences in the way new technology is purchased, e.g., tin1ing of purchase, type of store?
5. Post-purchase evaluation. Do males and females differ in usage of and satisfaction with new technology?
The scope of this paper will be limited to the first stage of the decision making process, i.e., perceptions of need for high technology products, while ongoing research addresses gender differences in some of the later stages. Because of the important role that high-tech products have in our lives, the findings should have implications for the design and diffusion of new technology which will be useful to n1arketers, consumer educators and public policy makers.
CONSUMER RESEARCH
Consumer behavior researchers recognize the importance of diffusion of innovation, especially consumer adoption of new technology. Many studies have been done to investigate the
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personal, situational and product characteristics that foster or inhibit consumer acceptance of innovations. (See for instance Rogers and Shoemaker 1971; Gatignon and Robertson 1985; Ram and Sheth 1989. For a brief review of the literature, see Rudell 1989). Most experiments or surveys for these studies made use of all male or all female samples, and where mixed samples were used, data were seldom analyzed by gender.
For example, Danko and MacLachlan (1983) did not have enough female adopters of personal computers in their sample, so they only analyzed the male responses (but made suggestions about encouraging "support"from women by positioning the product in an educational, rather than business context). Dickerson and Gentry (1983) used computer club members (notoriously male-dominated) and subscribers to Psychology Today to represent adopters and nonadopters of personal computers respectively, but did not record or report on sex of respondents. In Venkatesh and Vitalari's (1984) study of household decision making for home computers, 95% of the respondents were male.
Thus we see that little or no attention has been paid in these studies to the possible role of gender differences in attitudes toward technology, or to adoption of new technologies. The findings of differences between adopters and nonadopters may in part reflect gender differences, and conclusions drawn fronl research on all male or all female samples may not be applicable to consumers of the opposite sex. The only study to combine gender differences and innovation appears to be that of Gentry et al. (1989), which investigated gender differences in technical vs. symbolic product preferences, and found variations across five cultures (U.S., Korea, India, Thailand and Senegal). For the U.S., students conformed to the stereotypical pattern of males being more interested in new technical products (e.g., cameras, watches, computers), and females more willing to try symbolic innovations (e.g., new clothing fashions, hair styles).
METHODOLOGY
The purpose of this paper is to explore gender differences in relations to technology caused by differences in socialization, involvement, values, problem solving style, and personal efficacy. We will look at relevant sociological, psychological
and consumer behavior literature which may offer evidence of and reasons for differences in male and female approaches to technology. Literature and exploratory research results will be used to generate testable hypotheses regarding gender differences in consumer behavior for products which incorporate technological innovations or advancements, i.e., high-tech goods and services.
The focus will be on perceptions of need for high-tech products. Do differences in socialization and other factors lead to gender differences in judgment of technology and willingness to adopt high-tech products? Our premise is not that one gender is "technophobic,"and the other "technophilic." As implied by the title of this paper, we will explore the question of gender differences by employing the distinction between technology-based products as toys to be played with, or as tools to be used to get a job done.
The personal computer (PC) will be used as a case study, to illustrate and further explore the application of gender differences to attitudes and behavior regarding a high-tech product. While the PC cannot represent all high-tech products, it offers the advantage of being a fairly complex, yet familiar technology, with a wide variety of applications, which has also been the subject of many studies. Computer technology is in many cases the basis for other high-tech products and services (e.g., electronic banking), and in com'mon parlance, computerization is often synonymous with one type of technological change.
Gender and Technology
While the importance of technology is universally recognized, national studies have shown a disparity between the genders in attitudes toward and adoption of technology. For instance, Miller (1983) found in his 1979 and 1981 studies that men and women were equally interested in scientific discoveries. However, women were less likely than men to see themselves as knowledgeable about science and technology, and a significantly higher proportion of men (40%) than women (28%) expressed a high level of interest in the use of new inventions and technologies. Danko and MacLachlan (1983) found only five women among the 212 respondents identified as early adopters of personal computers in their 1980 survey. By 1984, 8.2% of all U.S. households reported owning a
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personal computer. Of these, 63.1% of male respondents and 42.8% of the females actually used it at honle (U.S. Bureau of the Census 1988).
It is our contention that differences in socialization, involvement, values, problem solving style and personal efficacy contribute to the differences in adoption of such a high-tech product. Moreover, these differences can be used to generate hypotheses related to consunler decision-making for high-tech products.
Socialization
There is much historical and social evidence of differences in males' and females' relationship to technology. Though recent works have revealed the great contributions of women inventors (Vare and Ptacek 1987), by and large men assume the role of inventors, designers and producers of technology, while women are the consumers, users and operators. Merchant (1983) points out that metaphors which link nature to females (e.g., "nurturingearth mother," "virgin earth") and science to males ("hard facts," "penetratingmind" and "thrustof his argument") pervade our language and culture.
Cowan (1979) suggests that the differences between the genders' relations to technology may be based on four factors: women's unique role as bearers and rearers of children (though related technologies, e.g. the baby bottle or teething ring, are ignored by historians); their work roles (e.g., sex typing of jobs, and lower pay for women); women's "place"in the home, which has been very resistant to industrialization (e.g., although men's work has become more centralized, housework remains a decentralized "cottage industry"); and socialization of women to be anti-technocrats ("If something is broken, daddy will fix it. If feelings are hurt, mommy will salve them."). As women come to resent their exclusion from science and technology, they may exhibit hostility toward it.
Cowan makes the point that "Women have experienced science and technology as consumers, not as producers" (1979:63). Indeed, elsewhere she hypothesizes that advertisers played an important role in fostering social change in the 20th century household by suggesting to wonlen that they could buy an appliance and fire the maid (1976). Ads playing on embarrassment and guilt
associated with household work sold appliances, but did not necessarily improve women's lives. As the title of her later book suggests, increased standards of cleanliness and additional household duties resulted in "more work for mother" (Cowan 1983).
Society's notions of gender-appropriate technology are reinforced through the toys that boys and girls are given to play with (Pursell 1979). The popularity of Nintendo's "Game Boy" attests to the subtle and obvious ways in which sex roles are perpetuated through the design and diffusion of technology.
It is possible that males and females share the same orientations toward computer technology, but have been socialized to have different attitudes. Thus, young boys and girls may share affinity for computer games, but if the content of the ganles is designed to appeal to boys (how many girls want to slay dragons and rescue scantily-clad princesses?), and teachers assign male students to a computerized lesson and females (including the author's nine-year old daughter) to a card game to learn about electricity, attitudes about what is appropriate for each sex will soon be formed.
The role of socialization in the computer field has been documented by Wilder, Mackie and Cooper (1985), whose survey of 1600 school children revealed that both boys and girls perceived computers to be more appropriate for boys. Ware and Stuck (1985) did a content analysis of three computer magazines, and found that men appeared twice as often as women. Men were more likely to appear in positions of authority, or portraying managers, experts and repair technicians, while women played a more passive role as clerical workers and sex objects. Only women were shown rejecting the computer.
McClain (1983) suggests that women's apparent resistance to purchasing computers may be due to the male oriented image of computer stores, and women's inability to afford the product (since they earn $.59 to the male dollar). While some might argue that reluctance to buy a PC is evidence of fenlales' superior intelligence or common sense, since home computers are in some cases wasteful purchases, one would hope that purchase of a product is determined by individual consumer needs and wants, and not by gender-based
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psychological and economic barriers.
Will the gender gap be smaller for future generations? While a Harvard study found that parents are currently more willing to spend n10ney to send boys to computer camps (Markoff 1989), as computers pervade education and parents and teachers begin to treat male and female children more equitably, it is expected that younger girls will grow up with less computer anxiety. Increased numbers of female role models in computer fields will also help to lessen gender differences in .attitudes toward the computer at school, work and home--all of which exert socializing influences.
Two hypotheses can be generated on the basis of socialization.
HI: Due to different socialization experiences vis a vis technology, males will be more interested in and accepting of high-tech products.
As support for this hypothesis, Gentry et al. (1989) found American males more willing than females to try "technical"innovations. In a survey of business students, Rudell (1990) found that twice as many males as females owned a personal computer (43% vs. 22%). In a national survey of computer owners, 68% of the primary owners were male, and 32% were female (Newspaper Advertising Bureau 1988).
H2: Attitudes toward high-tech products will also be influenced by age. As social norms move toward equality, the differences between male and female attitudes toward technology will decrease.
In support of both hypotheses, Nickel and Pinto (1986) tested a computer attitude scale on four samples of students and one sample of computer operators. Males had significantly more positive attitudes toward computers in two of three samples where sex was recorded (and the third was significant at .08). For computer operators (whose age was recorded), older subjects had significantly n10re negative attitudes toward computers. In exploratory research using a projective technique, Rudell (1989) found an age gap among female subjects. A Thematic Apperception Test featured a male cartoon character showing an ad for home computers to a female character. When compared to responses
of older female subjects, younger female subjects projected greater interest in product information about a home computer on the female cartoon character.
INVOLVEMENT
Venkatraman (1988) relates innovative behavior to the consumer's enduring involvement i.e., long-term perception of product importance based on the strength of the product's relationship to an individual's central needs and values. This is contrasted with instrumental involvement, the temporary perception of product importance. Males' greater "attentiveness"to news about developments in scienGe and technology (Miller 1983) may be taken as evidence of their more enduring involvement, since such ongoing information gathering was found by Venkatraman to be associated with it.
Venkatraman maintains that an enduringly involved consumer "has a strong hobby-like interest in or enthusiasm for the product, sometimes this interest can even take on an obsessional quality" (p. 299). This is very descriptive of the overwhelmingly male population of computer "hackers,"whose obsession with the machine can border on addiction (Lewis 1988). It is said that "Women and girls use computers; men and boys love them" (Markoff 1989). According to McClain (1983):
"One pattern that emerges after talking to men and women about why and how they use computers is that men on the whole have more fun with computers than women do. Men are more interested in computer games; they enjoy experimenting with computer graphics more; they go further afield in programming and design. Women tend to view the computer as a tool, a means to an end: the secretary wants to lessen her workload through word processing; the freelance writer wants to revise her work without typing out another draft; the bored clerk wants to jump to a more lucrative job; the computer science major wants to 'make her age' in the first year out of school." (p.76)
Whether due to early socialization (e.g., with mechanical toys) or cognitive and value differences, it would appear that men have more enduring involvement and regard computer technology as intrinsically interesting, while
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women judge it by its ability to accomplish needed tasks. This may be related to gender differences in time use or demands on time. Women's liberation notwithstanding, household tasks and childcare duties are still borne inequitably, leaving men more free time to tinker with cars, motorcycles and computers. This would not be evidence of female technophobia, but rather a more realistic approach to technology and its role in one's life.
The resulting hypothesis will be stated:
H3: Females will be less enduringly involved with high-tech products, regarding them as important only for specific tasks.
Personal Values
The role of values in shaping consumer attitudes toward innovation has been explored by others. In building his model, Ram (1987) lists value orientation among the personal characteristics which affect consumer resistance to innovation. Might gender differences in values result in differential resistance?
Gilligan (1982) argues that females base their moral reasoning on different criteria than males. Girls tended to view moral dilemmas in the context of social relationships, with emphasis on values, consequences, responsibilities and caring; boys saw scenarios as isolated, abstract events, and based their judgment on rules, laws, "rights" and the concept of justice. These differences in cognitive schemes derive from childhood needs to attach or separate from the primary caretaker, usually the mother. Extending these aspects of object relations theory to consumer behavior, Johnson, Zimmer and Golden (1987) tested the difference in cognitive schemes with respect to visual information processing of soft drink advertising messages. As expected, females were more likely to report seeing relationships, and to express them in terms of gender roles (e.g., wife, husband, son).
In his study of gender differences in materialism, Rudmin (1990) found that women are more sharing than men, and prefer benevolence over dominance. He speculates that this is related to Gilligan's contention that women have a greater concern for social context and relationships. Money and property are valued by men for the
power they bring, while women prefer to use such possessions for altruistic purposes.
Perhaps these gender differences in object relations can be used to explain observations of differences in use of computers. Turlde (1984) found that girls exhibited more "soft mastery" of computers, characterized by negotiation and compromise, while boys were "hard masters," exerting control over the machine. In her study of II-year old children, Motherwell (1988) found that boys were more likely to relate to computers as objects, while girls modeled their interactions with computers on their relationships with people. One of McClain's (1983) informants, an engineering instructor at Columbia University, felt that women are more likely to write programs with subsequent users in mind, which may reflect greater concern for human relationships, and consequences of actions.
McQuarrie and Langmayer (1985) applied Rokeach's values to computer ownership, and found strongest associations with pleasure, sense of accomplishment, and wisdom (terminal values), and imaginative, capable, and ambitious (instrunlental values). But these values might have different importance for males and females.
Using Rokeach's value inventory, a survey of 97 business students carried out by the author revealed gender differences in the same values. Respondents were asked to imagine that they were planning to buy a personal computer for their own use, for the first time. They were asked which one terminal and which one instrumental value would be gained by buying such a computer. Table I shows the results.
These exploratory findings show a stronger connection of computers with pleasure for males, while females see the computer as helping them to be more capable, and gain a sense of accomplishment and wisdom. This is consistent with the evidence cited above regarding the "toyvs. tool" distinctions between the genders.
Possible gender differences in values yield the following hypothesis. H4: Males and females will differ in the values which underlie their purchase of high-tech products. E.g., Males will value pleasure more highly, while females will pursue a sense of accomplishment.
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Resistance to Technology
As one of the first to deal with diffusion from the perspective of the "less developed concept" of resistance, Sheth (1979) claims that innovation resistance is determined by two factors--habit and perceived risk. Consumers with strong habits toward existing practices and technology, and consumers who perceive greater uncertainty or negative consequences, will be more resistant to innovations. Exploration of gender differences in problem solving style and personal efficacy may yield hypotheses relevant to habit and perceived risk.
Problem-Solving Style
Gender differences in cognitive functioning and learning styles have been noted, though not well explained. For instance, in their review of research on sex differences in cognitive functioning, Burstein, Bank and Jarvik (1980) concluded that women had better verbal skills than men, and were more field dependent (i.e., when shown a tilting rod within a tilting frame, they have difficulty judging whether the rod is in the vertical position). However, the authors were unable to draw conclusions about the determinants of those differences (which could be hormonal, genetic, cultural, or neuroanatomical).
In their test of Kirton's Adaption-Innovation theory, Foxall and Haskins (1986) noted that females tended to score as more adaptive than males. That is, in their problem-solving and decision making style, females were more likely to confine problem solving to the frame of reference in which the problem arose. (This may be related to "field dependency.") Males exhibited greater innovativeness, redefining and reconstituting problems and their context when needed.
A table of Kirton's behavior descriptions of Adaptors and Innovators (Foxall and Haskins 1986, 66) revealed that adaptors' behavior would also be, among other things: characterized by precision, reliability, efficiency, methodicalness, prudence, discipline and conformity; impervious to boredom, able to maintain high accuracy in long spells of detailed work; tend to high self-doubt; sensitive to people, maintains group cohesion and co-operation. On the other hand, innovators are described as: undisciplined, thinking tangentially, approaching tasks from unsuspected angles;
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capable of detailed routine for only short bursts, quick to delegate routine tasks; appears to have low self-doubt when generating ideas, not needing consensus to maintain certitude in the face of opposition; and insensitive to people, often threatens group cohesion and cooperation.
Mandinach and Corno (1985) found gender differences in cognitive engagement in 7th and 8th grade students using a computerized game. Females tended to adopt and maintain only one of four identifiable forms of engagement. High ability males switched to task-focused learning, but high ability females continued to request support from the experimenter even when it was not needed. Gutek and Bikson (1985) studied workers in computerized offices, and found' gender differences in usage patterns. Women used computers more, and more routinely, while men were more flexible and autonomous in their use.
It would appear that female problem-solving style is characterized by greater habit and routine, while males are more flexible and willing to change their perspective or practice.
Personal Efficacy
Adoption of innovative technologies also has been associated with personal efficacy, i.e., belief that a particular behavior can successfully be performed, or that a new technology can be mastered (Hill, Smith and Mann 1986). A consumer with low personal efficacy will perceive an innovation to be more complex, which will slow the rate of adoption. Experimental manipulation of self-efficacy resulted in greater resistance to change from manual to computerized methods of performing a task (Ellen 1990).
Given the cultural and historical relationships of the genders to technology discussed above, it may be predicted that males will have higher personal efficacy than females. Miura (1987) attributes gender differences in computer interest and course enrollment among college students in part to males' greater perceived self-efficacy. Hawkins (1985) traces differential interest and achievement in science and math (and computers, which are often associated with those disciplines), to greater sensitivity to failure feedback among females. Girls are more likely to attribute problem solving difficul ty to personal lack of ability, while boys
blame other situational factors. This may result in different willingness to take risks in a learning situation that involves computers.
McClain (1983) learned from her survey of expert opinion that while both sexes have computer anxiety, females tend to have more fear of taking computer courses, and more commonly take general computer courses than those presented in a mathematical context. While teaching computer courses, Brecher (1985) noted that adult males approached conlputers in a trial and error fashion; adult females needed to know more about how the computer operated before trying it out.
Two studies have found evidence of gender differences in college freshmen's attitudes toward computers. Wilder, Mackie and Cooper (1985) found that females fel t significantly less comfortable with and less well equipped to deal with computers than males with equal prior experience. Palmer and Harnisch's (1987) male students initially had more favorable attitudes and higher self-confidence, but overall effects of an experiment which placed computers in residence halls were greater for women, who scored lower in anxiety and higher in desire to use them and self-rated skills.
In light of gender differences in problem solving style and personal efficacy, and their relationships to habit and perceived risk, the last two hypotheses can be posed.
H5: Due to greater inertia with respect to habitual ways of accomplishing tasks, females will have greater initial resistance to adoption of high-tech products.
H6: Because of lower personal efficacy and higher perceived risk, females will have greater ini tial resistance to adoption of high-tech products.
Support for these two hypotheses is mixed. Temple and Lips (1989) concluded from their attitude survey of 305 Canadian students that women were just as intrigued by computers as the men were, but were inhibited from pursuing formal study of computers by uncertainty about their own abilities, reinforced by negative attitudes of their male peers. Contradictory evidence is presented by Vernon-Gerstenfeld (1989), who found that female patent examiners were more
likely to adopt the computer for patent searches and used it for significantly more time than their male co-workers. Other differences in background and experience might have contributed to this outcome, but it is still consistent with the thesis that females will respond more positively to technology as a tool designed to perform a specific task. To the extent that exposure to new technology at school and work will influence later consumer behavior of males and females, these findings will be relevant.
Can these hypotheses about habit and perceived risk be applied to other technologies? Electronic home shopping and banking services, which require replacing current habits with new computerized practices, and have significant negative consequences if mistakes are made, are not meeting industry expectations for consumer acceptance (Sloane 1989). This is in sharp contrast to the history of residential telephone technology. Fischer (1988) documents female "appropriation" of supposedly masculine technology from 1890-1940. By facilitating social interaction, this "instrumentof sociability" filled women's needs, reduced their isolation, and made their work easier, (with little risk of failure or negative consequences).
DISCUSSION
We have attempted to generate hypotheses regarding gender differences in decision nlaking for high technology products on the basis of differences in socialization, involvement, values, problem solving style, and personal efficacy. Table 2 summarizes the hypotheses and their sources.
The picture that emerges is one of children being socialized to regard technology as more appropriate for males. As a result, males are nlore involved with technology, feel more confident and comfortable with it, and derive greater pleasure from its toy-like qualities. Females are less involved or comfortable with technology, viewing high-tech products as tools to help them accomplish tasks efficiently. Adoption of a high-tech product by a female consumer may depend more on its ability to "get the job done" with least disruption to current habits and minimum risk of failure, while male consumers may be drawn to the power and pleasure afforded
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by it use.
To test these hypotheses, various types of research could be used. If differences are observed in the relatively homogeneous student convenience samples, clearly a survey of a more representative sample of male and female consumers regarding a variety of high-tech products would be useful. Existing data sets from past surveys regarding attitudes toward and purchase of technological innovations could also be re-analyzed for gender differences in needs, values, confidence, perceived risk, etc. Depth interviews of male and female consunlers regarding their purchases of high-tech products might reveal differences in decision making processes that elude structured questionnaires. Interviews of salespeople or direct observation of purchasing situations might also shed light on gender differences in approaches to high-tech products. If the toy/tool distinction is supported by such research, experimental manipulation of promotional appeals could be used to test their effectiveness on male and female consumers.
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Terminal Values Pleasure
Sense of accomplishment
Wisdom
Instrunlental Values Imaginative
Capable
Ambitious
TABLE 1 Gender Differences in Values
% of males % of females 15.9 2.0
20.5 48.0
9.1 16.0
9.1 7.7
31.8 48.1
18.8 17.3
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TABLE 2 Areas of Gender Difference and Related Hypotheses
Socialization Cultural metaphors Daddy will fix it Consumers vs. producers Childhood toys Media images Role models
Involvement Enduring vs. instrumental
involvement Toy vs. tool
Values Moral reasoning Object relations Rokeach values
Problem Solving Style Field dependency Adaption vs. innovation Cognitive engagement
Personal efficacy Attribution of failure
feedback Confidence
Hypotheses
HI. Due to different socialization experiences vis a vis technology, males will be more interested in and accepting of high-tech products.
H2. Attitudes toward high-tech products will also be influenced by age. As social norms move toward equality, the differences between male and female attitudes toward technology will decrease.
H3. Females will be less enduringly involved with high-tech products, regarding them as important only for specific tasks.
H4. Males and females will differ in the values which underlie their purchase of high-tech products. E.g., males will value pleasure more highly, while females will pursue a sense of accomplishment.
H5. Due to greater inertia with respect to habitual ways of accomplishing tasks, females will have greater initial resistance to adoption of high-tech products.
H6. Because of higher perceived risk, females will have greater initial resistance to adoption of high-tech products.
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