• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Tm kim lehtomorrison2006
 

Tm kim lehtomorrison2006

on

  • 526 views

 

Statistics

Views

Total Views
526
Views on SlideShare
526
Embed Views
0

Actions

Likes
0
Downloads
3
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Tm kim lehtomorrison2006 Tm kim lehtomorrison2006 Document Transcript

    • ARTICLE IN PRESS Tourism Management ] (]]]]) ]]]–]]] www.elsevier.com/locate/tourman Research article Gender differences in online travel information search: Implications for marketing communications on the internet Dae-Young Kima, Xinran Y. Lehtob, Alastair M. Morrisonc,Ã a Hotel & Restaurant Management Program, University of Missouri-Columbia, Columbia, MO, USA b Department of Hospitality and Tourism Management, Purdue University, Indiana, USA c College of Consumer and Family Sciences Purdue University, IN 47907-2059, USA Received 30 March 2006; accepted 2 April 2006 Abstract Gender has been and continues to be one of the most common forms of segmentation used by marketers in general and advertisers in particular. In general, males and females are likely to differ in information processes and decision making. The growing predominance of Internet use has further highlighted the need for understanding online users’ attitudes and behaviors from a gender perspective. Reflecting this research need, the purpose of this study was to examine gender differences within the context of online travel Website functionality and content preferences as well as search behavior. The data used for this study were obtained from the Internet Tourism & Travel 2001 Study conducted for the Canadian Tourism Commission (CTC). There was a usable sample of 1334 qualified respondents in this study. The results indicated that there were substantial gender differences both in terms of attitudes to information channels and travel Website functionality preferences. The implications of such differences for online tourism Website message design were discussed. r 2006 Elsevier Ltd. All rights reserved. Keywords: Gender difference; Information search process; Destination website 1. Introduction experiences is perceived as essential for the success of tourism organizations. The revolutionary development of information technol- Acknowledging gender differences arising from factors ogy has dramatically changed society and people’s every- such as ‘‘biological factors’’ (Buss, 1995; Everhart, day lives, including the way travelers search for Shucard, Quatrin, & Shucard, 2001; Hall, 1984; Saucier information and plan trips. Recent studies by NFO Plog & Elias, 2001) ‘‘gender identity’’ (Bem, 1974; Fischer & Research show that the Internet has become one of the Arnold, 1994; Spence & Helmreich, 1978), and ‘‘gender most important information sources for travel information role attitudes’’(Buss & Schaninger, 1987; Douglas, 1976; acquisition (Lake, 2001). Tourism by nature is an Eagly, 1987; Fisher & Arnold, 1990, 1994; Schaninger & information-oriented phenomenon due to structural rea- Buss, 1985), gender has been frequently used as a basis for sons (Schertler, Schmid, Tjoa, & Werthner, 1995). For segmentation for a significant proportion of products and consumers, decision-making and consumption are sepa- services (Putrevu, 2001). The fact that men and women are rated in time and space. These distances can only be different is commonly acknowledged in most societies. The overcome by the information about the product, which is prevalent research question, however, has focused on available in advance and which can be gathered by the whether biological make-up or social factors drive these consumer (Werthner & Klein, 1999). As a result, informa- gender differences. That is, the study of gender differences tion quality has emerged as a major research topic and encompasses several unexplored dimensions that lately providing relevant and meaningful information search have attracted research attention. Within the context of information search processes, relatively little research has ÃCorresponding author. Tel.: +1 765 494 7905; fax: +1 765 496 1168. been done on gender differences. An intriguing question E-mail address: alastair@purdue.edu (A.M. Morrison). facing consumer researchers is whether gender differences 0261-5177/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.tourman.2006.04.001
    • ARTICLE IN PRESS 2 D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] can be translated into consistent differential patterns in Worrall, 1990). In many aspects, tourist information- information-processing and judgment. In order to deliver processing is different from that of other consumers. The products and services that cater to the unique needs and differences are mainly due to structural reasons (Schertler aspirations of each gender, marketers need to understand et al., 1995). Tourists have to leave their daily environment, the origins and psychological differences between the two having to move to geographically distant places to genders. Accordingly, the purpose of this research was to consume the tourism product. According to Werthner provide a review of the literature on the information- and Klein (1999), the tourism product normally cannot be processing differences between females and males, empiri- tested and controlled in advance. Thus, decision-making cally examine the gender differences in online information and consumption are separated in time and space. These attitudes, preferences and behaviors within the domain of distances can only be overcome by the information about travel-related information, and discuss the major implica- the product, which is available in advance and which can tions of such differences for more effective marketing and be gathered by the consumer (Werthner & Klein, 1999). advertising strategies. Another reason is due to the characteristics of the tourism product. In consumer behavior research, Nelson 2. Literature review (1970) suggests that goods can be classified as possessing either search or experience qualities. Search qualities are 2.1. Characteristics of tourism information those that ‘‘the consumer can determine by inspection prior to purchase,’’ and experience qualities are those that ‘‘are Various typologies of information sources have been not determined prior to purchase’’ (Nelson, 1974, p. 730). proposed. There is general consensus, however, that With respect to classification, tourism is a confidence good; information search can be divided into internal search, an a priori comprehensive assessment of its qualities is which is a scan in long-term memory for relevant product impossible. This requires information from the consumer knowledge, and external search, which happens when an and supplier sides, entailing high information search costs internal search cannot provide sufficient and adequate and causing informational market imperfections (William- information and consumers need to collect information son, 1985). Tourism organizations rely on an exchange of from the external world (Bettman, 1979; Engel, Blackwell information with travelers through various channels to & Miniard, 1990; Fodness & Murray, 1997, 1998; Mullen market products and build customer relationships. Trave- & Johnson, 1990; Wicks & Schuett, 1991). Based on these lers depend on travel-related information for functional two concepts, Fodness and Murray (1997) conceptualized needs such as travel planning and also other social, visual, tourist information search as ‘‘a dynamic process wherein entertainment, and creativity needs (Vogt & Fesenmaier, individuals use various amounts and types of information 1998). Recent studies show that travelers use different sources in response to internal and external contingencies combinations of information sources to plan trips such as to facilitate travel planning.’’ For external sources, personal experience, friends and family, travel agencies, travelers rely on both marketing-dominated and non- travel brochures and guidebooks, highway welcome marketing-dominated information sources to search for centers, magazines and newspapers. These sources are travel-related information and plan their trips. The former influenced by different search contingencies and individual information sources include advertising and commercials characteristics (Fodness & Murray, 1998). in the mass media, travel brochures, guidebooks from clubs In addition, the tourism product is a complex product; it and welcome centers; the latter includes friends, relatives is a set of basic products, delivered by a large number of and personal experiences. Further, tourist information suppliers (Werthner & Klein, 1999). The basic products are search may vary depending on the purpose of the trip aggregated by some intermediary entities. The product (Fodness & Murray 1998), planning horizon (Gitelson & aggregation and consolidation process is also information Crompton 1983; Schul & Crompton 1983), motivation intensive. Products have to have well defined interfaces so (Gitelson & Crompton 1983; Vogt & Fesenmaier, 1998), that they match consumer needs, processes, and distribu- and level of involvement (Crotts, 1999; Kerstetter, & Cho, tion channels. For example, a hotel may be packaged with 2004; Lehto, O’Leary, & Morrison, 2004). different transportation arrangements or combined with Many studies have indicated that the major purpose of demand-generators such as sports or cultural events. These information search is to support decision-making (i.e., packages can be sold to different consumer groups, if the reduce risk and uncertainty) and product choice in which product attributes and the consumers’ interests can be the information search behavior strengthens the decision- mapped onto each other. Another important feature of making and choice behavior (Bettman, 1979; Bloch, tourism products is their perishability (Kotler, Bowen & Sherrell, & Ridgway, 1986; Moorthy, Ratchford, & Makens, 1999). They have to be consumed when they are Talukdar, 1997). For tourists, information acquisition is available and cannot be stored. This is true for nearly all necessary for choosing a destination and for onsite components of the tourism product; a hotel bed not sold decisions such as selecting accommodations, transporta- for one night represents lost income, and the same is true tion, activities, and tours (Fodness & Murray, 1998; for a seat on an airplane or for a sports event. Thus, Gursoy and Chen, 2000; Snepenger, Meged, Snelling & suppliers bear high risks and are vulnerable if consumers
    • ARTICLE IN PRESS D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] 3 are unaware of product offerings. This risk can be some- shows that female students are better at reading and male what reduced if suppliers or intermediaries have complete students are better at math in every country surveyed access to information about inventory and availability. In (Sokoloff, 2001). It would be assumed that the cognitive short, the unique characteristics of the tourism product gender differences influence information searchers’ prefer- further underscore the importance of successful informa- ences and abilities to successfully search and navigate tion dissemination strategy. information on the Web, since there is evidence suggesting that women lag behind men in the degree to which they are 2.2. Gender difference in information processing experienced with and motivated by technology (Light, Littleton, Bale, Joiner, & Messer, 2000; Schumacher & Gender is socially constructed; it is based in a person’s Morahan-Martin, 2001). view of him- or herself as possessing those qualities that The research literature seems consistent in ascribing society deems to be masculine, feminine, or both. However, specific personality traits to men and women and in sex is a biological classification; the term refers to whether suggesting that the unique interests and knowledge an individual is biologically and genetically male or female associated with the genders’ social roles guide their (Wilson, 2002). The study of gender and gender-related judgments. In general, men are reported to be more behavior has been and continues to be one of the most independent, confident, competitive, willing to take risks, important forms of segmentation used by marketing and less prone to perceive product risk than females communicators (Darley & Smith, 1995; Holbrook, 1986; (Darley & Smith, 1995). Based on previous cognitive Meyers-Levy, 1988; Meyers-Levy & Sternthal, 1991; researches, Meyers-Levy (1988) examined gender differ- Putrevu, 2001). Holbrook (1986) saw gender as a key ences of information search behavior in visual-spatial and variable in moderating consumers’ evaluative judgments. verbal abilities, and argued that males had a tendency not Meyers-Levy & Sternthal (1991) and Darley & Smith to process all available information as a basis for judgment. (1995) suggested that the use of gender in market Instead, they relied more on their own opinions. As a segmentation met several of the requirements for successful result, males made decisions more quickly than females, implementation: the segments were easy to identify, easy to relying on only highly available information. Additionally, access, and large enough to be profitable. males focused on concrete, objective cues such as form and The human brain is divided into two hemispheres, and physical attributes. In contrast, females relied on multiple lateralization refers to the specialization in the functioning sources of information before making a decision. Females of each hemisphere: The left hemisphere specializes in processed information in a more exhaustive and inter- verbal abilities and the right hemisphere specializes in pretive way, relying on a broad variety of information. spatial perception (Hansen, 1981). Recent clinical and Females processed information resorting more to sources experimental research shows that the two hemispheres are in the external world rather than to their own judgments. more symmetrically organized in females and more In terms of information processes, Krugman (1966) specialized in males (Everhart et al., 2001; Saucier & Elias, reported that women engaged in greater elaboration of 2001). Likewise, women have speech- and language-specific advertisements than did men, regardless of whether the areas on both sides of our brain (Whitesel, 2005). For advertisements focused on contents considered of more males, speech and language are not specific brain skills, and interest to men or to women. Rosenthal and DePaulo they primarily operate on the left side of the brain. Because (1979) found greater stimulus elaboration among women of this ‘‘non-compartmentalizing’’ of women’s brains, than among men when subjects were given adequate time talking is necessary for processing information. In regard to process information. Similarly, Meyer-Levy and to emotion, men’s emotion is located in two areas of the Sternthal (1991) noted that men were more likely to be right side of their brain (Gorman, Nash, & Ehrenreich, driven by overall message themes or schemas and women 1992). Located in only one side, men’s emotions can were more likely to engage in detailed elaboration of the operate separately from the other brain functions. On the message content. Specifically, men are considered to be other hand women’s emotions are located in both hemi- ‘‘selective processors’’ who often do not engage in spheres of the brain, making her more able to ‘‘switch her comprehensive processing of all available information emotions on’’ while her brain performs other functions. before rendering judgment. Instead, they seem to rely on The brain lateralization differences attributed to the various heuristics in place of detailed message elaboration. sexes are also likely to influence product evaluation and These heuristics involve a cue or cues that are highly judgment. Like the clinical findings about the brain available and salient and imply a particular inference. Such lateralization, in cognitive studies, it is also widely accepted processing implies that men often base their judgments on that women excel in verbal skills (Hyde & Linn, 1988), a select subset of all available information. In contrast, whereas men show superiority in mathematical ability women are considered to be ‘‘comprehensive processors’’ (Geary, 1996; Hyde, Fennema, & Lamon, 1990) and spatial who attempt to assimilate all available information before abilities (Linn & Peterson, 1986). Consistent with these rendering judgment. Women usually attempt effortful findings, a recently released 32-nation OECD (Organiza- elaboration of all available information unless they are tion for Economic Cooperation and Development) study restricted by memory constraints. Therefore, women give
    • ARTICLE IN PRESS 4 D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] equal weight to self- and other-generated information, en- (2001) argued that the digital media are affecting the code more message claims, and more extensively elaborate information environment and consumer behaviors in an on specific claims. unprecedented way as a result of the unique characteristics Despite several arguments that gender differences are of the Internet such as the speed of access, scope of access, not significant (O’Keefe, 2002) in cognitive theories, the provision of interactive assistance, and flexibility in research literature contains evidence of dependable gender representing information. differences in persuasibility, with women being more easily Previous research has shown that people vary widely in persuaded than men (Becker, 1986; Eagly & Carli, 1981). their ability to find and retrieve information in loosely For instance, women conform more, are more susceptible structured information environments (Chang & McDaniel, to influence, and are more adept in encoding and decoding 1995). Some factors that predict search success in such nonverbal communications (Hall, 1984; Everhart et al., environments include level of domain knowledge and 2001). Additionally, women are considered to be more search expertise (MacGregor, 1999), ability (Chang & visually oriented, more intrinsically motivated, and more McDaniel, 1995), gender (ChanLin, 1999; Mantovani, romantic compared to men (Holbrook, 1986). Wood 1994), learner control (Dillon & Gabbard, 1998; Mac- (1966) also observed that women responded to nonverbal Greggor, 1999), learner style (Shute, 1993), and interest stimuli by evoking more associative, imagery-laced inter- (Tobias, 1994). In general, more experienced, knowledge- pretations, and more elaborate descriptions than did their able, interested, male users who are active learners and male counterparts. In a similar sense, compared to men, oriented towards an internal locus of control are associated women show more sensitivity to a variety of situation- with being successful in such environments. Gender specific cues in determining their self-evaluations (Lenney, difference in technology adaptation rates may exist because Gold, & Browning, 1983), and use more elaborate men and women differ in socioeconomic status, which descriptive terms (Nowaczyk, 1982), which means that influences computer and Internet access and use (Bimber, men pay less attention to the colors and details of 2000). Men tend to be more interested in computers than information than women do. Men have been depicted as women, on average, contributing to gender differences in more analytical and logical in processing orientation, Internet use (Shashaani, 1997). Others speculate that whereas women are more subjective and intuitive since technology per se is a product of social relations, so they indulge in more associative, imagery-laced interpreta- diffusion of new innovations favors particular social tions (Hass, 1979) (Table 1). groups, such as men (Edward, 1995; Wajcman, 1995). In this sense, men show a greater interest in information and 2.3. User information search process in online environment communications technology products (e.g., video, mobile telephones and computers), and show a greater fondness Concomitant with the rapid growth of the Internet, for the latest technical products (Mitchell & Walsh, 2004). online information search behavior has become a major It has been also reported that women are slightly less likely research topic. The Internet has gained considerable to live in a household with a computer (Losh, 2003), and importance as a communicative and adaptive means of men dominate household decisions about computer pur- sharing and disseminating information. It is generally chases (Papadakis, 2001). Some studies conclude that women assumed that the digital media of computer networks are are less likely to use the Internet at all (e.g., UCLA, 2001; fundamentally different from the current mass media of Bimber 2000) and use the Internet less frequently, given television, radio, newspapers, and magazines because of Internet use at all (Ono & Zavodny, 2003). their designs and the technology upon which they function. A recent tracking research study on online user activities From a business perspective, the Internet makes available performed by the Pew Internet Project (Pew Internet & new tools for marketers to reduce costs, transform American Life Project, 2004a) reported some 78 percent of relationships, open new channels, streamline processes, men thought the Internet was a good place to go for and contribute to shareholder value (Oliva, 1998). From a transactions, compared to 71 percent of women. Some 72 consumer behavior perspective, Dholakis and Bagozzi percent of men viewed the Internet as a good place to go Table 1 Gender difference in information-processing Female (Comprehensive Processors) Male (Selective Processors) References Engaged in greater elaboration of ads Engaged in less elaboration of ads Krugman, 1966; Rosenthal & Depaulo, 1979; Darley & Smith, 1995 Central or systematic route Peripheral or heuristic route Meyers-Levy, 1989 Influenced by detailed message contents Influenced by overall message themes Holbrook, 1986; Meyers-Levy and Sternthat, More visually, intrinsically motivated 1991; Nowaczyk, 1982; Wood, 1966 Rely on external sources Rely on internal sources (e.g., own judgment) Lenney et al., 1983 Use All available information Select subset of all available information Meyers-Levy, 1988
    • ARTICLE IN PRESS D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] 5 for personal entertainment, compared to 66 percent of record responses. The survey collected information on US women. There were a few notable differences in how and Canadian Internet users (iTravelers) in the following thoroughly men and women blended Internet use into daily categories: (1) trip planning information search sources; (2) routines. Men were more likely than women to engage in number and types of online information used; (3) time online activities on a regular and frequent basis. Men did spent online for planning purposes for most recent trips; (4) online activities more frequently: 66 percent checked sports information search timelines (before, during, and post- scores online at least several times a week, compared to 46 trip); (4) influence of online information in the decision- percent of women. Some 79 percent of men accessed news making process; (5) online travel booking patterns; and (6) online at least several times a week, compared to 63 percent socio-demographic backgrounds of the respondents. An of women. By contrast, women showed a deeper engage- available sample of 1334 qualified respondents for the ment with Internet use for communicating with friends and gender difference study resulted. family. Some 64 percent of women communicated with Data analysis was completed following a four-step friends and family online at least several times a week, procedure. First, the demographic profile of respondents compared to 59 percent of men, a finding consistent with in the survey was identified through frequency analysis. past Pew Internet research about the importance of the Second, one-way Analysis of Variance (ANOVA) tests Internet among women for interpersonal relationships. were conducted to examine whether there were statistically significant gender differences in terms of their travel 3. Research objectives information search behaviors and attitudes toward differ- ent types of on/off-line information sources. Third, 15 Despite these prior research efforts on user online items of number of visits on travel-related Website and 11 activities, relatively little research attention had been given items related to attitudinal measurements of travel-related to gender differences in information seekers’ attitudes Website functionality were factor-analyzed to identify towards information channels and search behaviors in the underlying dimensions of online travel information atti- online environment. It is reasonable to assume that tudes and behaviors. Fourth, one-way ANOVA tests were understanding how gender-related issues affect online undertaken to detect any significant differences between information search and processing behaviors is essential males and females based on the factors obtained. for tourism marketing organizations to make more effective Web-based advertising channel selection and 5. Results content development decisions. Therefore, this study contributes to the literature on gender differences both in 5.1. Profile and trip characteristics of respondents terms of attitudes toward Web travel information sources and information search behavior. The primary objectives The demographic profile of the respondents by gender is of this research study were to: summarized in Table 2. About 60 percent of the male respondents were in the age range of 40 to 59 years, (1) Investigate gender differences in terms of attitudes compared to 55 percent of the females. One notable towards on/off-line travel information sources. characteristic of the respondents was that a large majority (2) Identify the underlying patterns of online channel usage (male—90 percent/female—84 percent) of the respondents based on patronage frequency to various tourism were highly educated (some college education or higher), Websites and assess gender differences with regard to and approximately 65 percent of the males and about 45 these patterns. percent of the females had household incomes over (3) Delineate the underlying cognitive dimensions of Website $60,000. Regarding employment, over 75 percent of the information attitudes and preferences, and assess gender males and about 65 percent of the females were self- differences with regard to these dimensions. employed or in full-time employment. Chi-square tests showed there were significantly difference in demographics between men and women. It was observed that males 4. Methods tended to have higher education and household income levels. The data used for the study were obtained from the One-way ANOVAs tests (Table 3) revealed men were Internet Tourism & Travel 2001 Study conducted among likely to have more vacation trips and nights away from 2470 North Americans between November 8th and home than their female counterparts. A significant mean December 18th, 2001 for the Canadian Tourism Commis- difference (po0:1) was also found in ‘‘the number of sion (CTC). The survey was conducted in both the US and business trips made.’’ On average, men tended to have Canada primarily to evaluate online travel purchase more frequent and longer trips than women did. The result behavior. Respondents were randomly selected from showed, in particular, there was more difference between telephone directories and interviewed by telephone on a men and women in the number of business trips than for wide range of travel behavior questions. A Computer vacation trips. In terms of primary decisions for trips, Aided Telephone Interface (CATI) system was used to about 63 percent of women were the primary trip decision
    • ARTICLE IN PRESS 6 D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] makers; that was significantly higher than their male behavior’’ variables (i.e., online hours per week, experience counterparts. of Web use, and hours for trip planning) and 13 ‘‘attitudes toward different on/off-line information sources’’ variables 5.2. Gender differences in online trip planning behaviors and were the dependent variables, and gender was the indepen- attitudes dent variable. The results revealed significant mean differ- ences (po0:05) for ‘‘online hours per week,’’ ‘‘experience of The gender differences in online trip planning information Web use,’’ and four attitudinal variables toward information behaviors and attitudes were first examined by employing sources (see Table 4). No significant differences (po0:05) one-way ANOVA tests. In this analysis, the three ‘‘online were found for ‘‘hours spent online planning trips’’ and the nine other attitudinal variables. The results indicated that females spent more time on the Table 2 Profile of respondents Internet per week and had stronger positive attitudes toward both on/off-line information sources. However, the Characteristic Frequency (%) Chi-saure results seemed to suggest that females’ longer hours online did not transfer to longer online planning trip hours. It was Female Male noted that men had more experience with Web use. This Age 69.22ÃÃ could be explained by men generally starting to use the 18–29 96 (12.2) 49 (9.0) Internet earlier than women because of social factors such 30–39 199 (25.3) 107 (19.6) as different types of employment or higher levels of 40–49 232 (29.4) 149 (27.3) 50–59 189 (24.0) 146 (26.7) education. In terms of online travel channels, females Over 60 72 (9.1) 95 (17.4) attached more value to channels such as ‘‘general Websites’’ and ‘‘official destination Websites’’ than their Education 47.15ÃÃ High school 128 (16.3) 50 (9.2) male counterparts. Females also gave higher ratings to the Some college 266 (33.8) 129 (23.6) value of printed materials such as brochures and travel College graduate 245 (31.1) 195 (35.7) guidebooks. Other channels such as TV, newspapers, and Post graduate 148 (18.8) 172 (31.5) travel agents showed no significant differences by gender. Annual household income 69.22ÃÃ Less than 24,999 104 (13.6) 36 (6.8) 5.3. Factor analysis on attitudes towards travel Website 25,000–59,999 324 (42.4) 158 (29.8) functionalities and contents 60,000–99,999 217 (28.4) 161 (30.4) 100,000–149,999 71 (9.3) 101 (19.1) Over 150,000 48 (6.3) 74 (14.0) To examine the dimensions underlying the perceived importance of contents and functionalities of destination Employment 124.12ÃÃ Websites, a principal components factor analysis with Self-employed 78 (9.9) 67 (12.3) Employed full-time 416 (53.0) 355 (65.3) Varimax rotation was performed on the 11 categories of Employed part-time 66 (8.4) 9 (1.7) information. The 11 items yielded three factors with Homemaker 101 (12.9) 0 (0) Eigenvalues greater than 1.0 (Table 5). These factors Student 26 (3.3) 19 (3.5) explained 54 percent of the variance and were labeled: Retired 67 (8.5) 84 (15.4) ‘‘interactive features,’’ ‘‘search features,’’ and ‘‘information Unemployed 31 (3.9) 10 (1.8) scope.’’ Factor loadings and communalities for all 11 items ÃÃ po0:01. were greater than 0.59 to 0.41. The reliability alpha values Table 3 Trip behaviors and primary decision maker by gender Trip behaviors Gender F-value p-value Female Male Number of vacation trips in last yeara 3.04 3.20 4.16 0.04 Number of business trips in last yearb 1.35 2.26 55.37 0.00 Number of nights away on recent trip 7.50 8.10 3.99 0.05 Chi-square p-value Primary decision maker 7.22 0.00 I am the primary decision maker 437 (62.5%) 262 (37.5%) I share the responsibility 351 (55.3%) 284 (44.7%) a Once (1), four (4), more than 5 (5). b Once (1), four (4), 5–10 (5), 11–15 (6), 16–20 (7), more than 20 (8).
    • ARTICLE IN PRESS D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] 7 Table 4 ANOVA test for gender comparison of information search behaviors and attitudes Behaviors and attitudes Gender F-value p-value Female (n ¼ 788) Male (n ¼ 546) a Online hours per week 3.68 3.39 13.57 0.00 Experience of online useb 4.49 4.61 4.03 0.05 Hours spent online planning tripc 3.95 3.91 0.28 0.60 Value of ‘‘been there before’’ in choosing destinationd 3.56 3.49 1.67 0.19 Value of ‘‘info center’’ in choosing destination 3.29 3.17 1.20 0.27 Value of ‘‘relatives/friend living there’’ in choosing destination 3.51 3.40 1.84 0.18 Value of ‘‘recommended by friends’’ in choosing destination 3.33 3.14 5.48 0.02 Value of ‘‘general Website’’ in choosing destination 3.61 3.43 10.74 0.00 Value of ‘‘official Website’’ in choosing destination 3.64 3.50 3.17 0.07 Value of ‘‘travel magazine’’ in choosing destination 3.05 2.88 2.36 0.13 Value of ‘‘general magazine’’ in choosing destination 2.78 2.42 2.62 0.11 Value of ‘‘newspaper’’ in choosing destination 3.06 2.72 1.50 0.23 Value of ‘‘TV’’ in choosing destination 3.09 2.85 1.05 0.31 Value of ‘‘travel agent’’ in choosing destination 3.37 3.33 0.03 0.85 Value of ‘‘brochures’’ in choosing destination 3.40 3.09 10.64 0.00 Value of ‘‘travel guide books’’ in choosing destination 3.57 3.37 6.33 0.01 a 2 h or less (1), 3–4 (2), 5–10 (3), 11–20 (4), 21–30 (5), more than 30 (6). b less than 6 months (1), 6 months to 1 year (2), 1 to 2 years (3), 3–4 (4), 5–6 (5), more than 6 years (6). c less than 1/2 hour (1), 1/2 to 1 hour (2), 1–2 (3), 3–5 (4), 6–10 (5), more than 10 h (6). d Measured on a 4-point Likert-type scale: not at all useful (1), very useful (4). Table 5 Principal components factor analysis for attitudes toward destination Website functionality Constructs and items Factor Loadings Communality Item Means 1 2 3 Female Male F-value Interactive features Importance of wireless capability 0.79 0.64 1.16 1.16 0.00 Importance of multi-media effects 0.74 0.58 1.36 1.29 4.73* Importance of chat room 0.71 0.51 1.17 1.13 2.73 Importance of e-newsletter 0.65 0.47 1.46 1.48 0.22 Search features Importance of searching by keyword 0.78 0.62 2.35 2.15 19.72** Importance of searching by location 0.77 0.61 2.55 2.42 11.14** Importance of searching by activity 0.67 0.49 2.35 2.27 4.78* Importance of easy to surf 0.62 0.41 2.52 2.35 16.94** Information scope Importance of planning the entire trip 0.75 0.61 2.33 2.20 10.83** Importance of comparing price 0.71 0.53 2.80 2.71 9.08** Importance of saving personal profile 0.59 0.47 1.97 1.77 19.52** Eigenvalues 3.22 1.60 1.13 Variance explained 20.99 19.32 13.70 Reliability coefficients 0.73 0.70 0.51 Measured on a 3-point Likert-type scale: not too important (1), somewhat important (2), very important (3) *po0:05; **po0:01. for the three factors, designed to check the internal tance of multi-media effects;’’ ‘‘importance of chat room;’’ consistency of the items within each factor, provided and ‘‘importance of e-newsletter.’’ search features was adequate support for internal consistency (0.73, 0.70, and labeled as the second factor; Which included high loadings 0.51 for interactive features, search features, and informa- for ‘‘importance of searching by keywords;’’ ‘‘importance tion scope, respectively). of searching by location;’’ ‘‘importance of searching Interactive features were represented by a total of four by activity;’’ and ‘‘importance of easy to surf.’’ the variables; ‘‘importance of wireless capability;’’ ‘‘impor- third factor; Information scope had high loadings for
    • ARTICLE IN PRESS 8 D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] ‘‘importance of planning the entire trip;’’ ‘‘importance of 5.5. Factor analysis on visit frequencies to travel-related comparing price;’’ and ‘‘importance of saving personal Websites profile.’’ A principal components factor analysis with Varimax rotation was performed on visit frequency to 15 categories 5.4. Gender comparison of travel Website functionalities and of information in order to examine the dimensions under- contents lying the content of destination Websites. The 15 items identified three dimensions with Eigenvalues greater than In the next phase, a series of one-way ANOVA tests were 1.0 (Table 6). These factors explained 85 percent of the performed on each of the measurement items under on the variance and were labeled: ‘‘pleasure and logistics,’’ three constructs to identify mean gender differences in ‘‘transportation and weather,’’ and ‘‘testimonials.’’ Factor attitudes towards destination Website functionality and loadings and communalities for all 15 items ranged from contents. Under the ‘‘interactive features’’ construct, the 0.59 to 0.75. All factors had relatively high reliability results revealed a significant mean difference (po0:05) for coefficients, ranging from 0.61 to 0.94. only one measurement item: ‘‘importance of multi-media ‘‘Pleasure and logistics’’ consisted of nine items; ‘‘attrac- effects’’. Under the ‘‘search features’’ construct, all four tions,’’ ‘‘events,’’ ‘‘accommodation,’’ ‘‘package tour,’’ items (‘‘importance of searching by keyword,’’ ‘‘impor- ‘‘entertainment,’’ ‘‘activities,’’ ‘‘local information,’’ ‘‘flight’’ tance of searching by location,’’ ‘‘importance of searching and ‘‘restaurant.’’ The second domain of ‘‘transportation by activity,’’ and ‘‘importance of easy to surf’’) showed and weather’’ contained four variables including ‘‘weath- significant gender differences (po0:01). For the informa- er,’’ ‘‘map,’’ ‘‘transportation,’’ and ‘‘rental cars.’’ The third tion scope construct, all three items (‘‘importance of domain of ‘‘testimonials’’ includes two items: ‘‘testimo- planning the entire trip,’’ ‘‘importance of comparing nials’’ and ‘‘general information.’’ price,’’ and ‘‘importance of saving personal profile.’’) differed by gender (po0.01). Noticeably, all significant 5.6. Gender comparison of patronage frequencies to travel- mean differences indicated that females consistently had related Websites more favorable perceptions. This is consistent with previous studies which found that men are classified as Gender differences with regard to visit frequencies to heuristic processors and women are portrayed as compre- various travel-related Websites were identified by using hensive information processors (Meyers-Levy, 1989). one-way ANOVA tests (Table 6). Under the ‘‘pleasure and Table 6 Principal component factor analysis for the number of visits on travel-related Websites Constructs and items Factor loadings Communality Item means Item means per unit cost 1 2 3 Female Male F-value Female Male F-value Pleasure and logistics Attraction 0.91 0.94 1.77 1.74 0.16 0.66 0.57 8.63** Events 0.88 0.89 1.54 1.51 0.43 0.57 0.47 16.42** Accommodation 0.86 0.84 1.97 2.13 6.56** 0.75 0.69 2.83 Package tour 0.83 0.81 1.20 1.21 0.01 0.44 0.37 15.95** Entertainment 0.81 0.89 1.43 1.33 4.71* 0.52 0.41 28.83** Activities 0.80 0.90 1.45 1.49 0.99 0.54 0.46 10.54** Local information 0.71 0.87 1.40 1.31 4.04* 0.50 0.40 26.07** Flight 0.67 0.75 0.90 0.93 4.75* 0.64 0.58 2.76 Restaurants 0.62 0.85 1.57 1.45 6.74** 0.58 0.45 25.35** Transportation and weather Weather 0.89 0.83 1.54 1.66 4.44* 0.54 0.47 5.70* Map 0.75 0.82 1.79 1.66 7.78** 0.68 0.52 29.69** Transportation 0.72 0.90 1.37 1.41 0.84 0.49 0.43 9.50** Rental cars 0.70 0.89 1.36 1.48 6.30** 0.50 0.47 1.31 Testimonial Testimonials 0.89 0.85 1.13 1.13 0.01 0.41 0.34 23.30** General information 0.59 0.77 1.59 1.67 2.18 0.58 0.53 4.57* Eigenvalues 10.11 1.48 1.20 Variance explained 45.11 26.32 13.84 Reliability coefficients 0.94 0.78 0.61 Measured on a 3-point Likert-type scale: once (1), 2 or 3 times (2), more than 3 (3). *po0:05, **po0:01.
    • ARTICLE IN PRESS D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] 9 logistics’’ construct, the results exposed a significant mean past research assertions about women being more exhaus- difference for two measurement items at po0.01 (‘‘accom- tive in information search than men. modation’’ and ‘‘restaurant’’), and three items at po0:05 (‘‘entertainment,’’ ‘‘local information,’’ and ‘‘flight’’). 6. Conclusions and implications Under the ‘‘transportation and weather’’ construct, two items (‘‘map,’’ and ‘‘rental car’’) at po0:01, and one item This research demonstrates that there are significant (‘‘weather’’) at po0:05 showed significant gender differ- differences between females and males in terms of attitudes ences. For the ‘‘testimonials’’ construct, it was observed toward travel Website functionality and scope as well as that no items were significantly different. Out of the eight actual online information search behavior. The results are gender significant items, women tended to patronize more consistent with the gender difference arguments from of sites that contained ‘‘entertainment,’’ ‘‘local informa- previous research regarding how females and males process tion,’’ ‘‘restaurant,’’ and ‘‘map’’ information while men information in different ways. For instance, it was were more likely to seek information related to ‘‘flight’’, observed that females attached higher values to a wider ‘‘accommodation’’, ‘‘rental car’’ and ‘‘weather’’. Given the variety of both online and offline information sources while fact that women held consistently more favorable percep- choosing travel destinations. More specifically, this result tions towards Web-based information, the results of the supports the gender difference argument that females are ANOVA tests appear to imply that females’ high positive more exhaustive and elaborative in external information attitudes did not reflect proportionally on their actual search (Meyers-Levy, 1988). Compared to their male information search behavior. This could potentially be counterparts, females are more likely to have favorable explained by the economics of information theory (Stigler, attitudes towards different types of Website functionalities 1961). The economics of information theory suggests and scope of contents. Moreover, based on ‘‘item means that information searchers would acquire information per unit cost,’’ it was observed that females are also more till the point where the marginal cost of acquiring involved in online information search, visiting more travel additional information equals or exceeds the marginal websites and visiting them more frequently. This is also benefit (Stigler, 1961; Goldman & Johansson, 1978; consistent with previous computer mediated communica- Urbany, 1986). That is, the differential levels in the tion (CMC) studies. A number of studies have empirically perceived costs of information search and the expected assessed gender differences in CMC as a main research benefits of that search activity would guide individual focus (independent variable) (Allen, 1995; Hiltz & Johnson, consumers’ search behavior for information. Within the 1990). Hiltz and Johnson (1990) found that females viewed context of travel information search, different number of CMC more favorably than males and that they had trips and trip costs would influence the amount of traveler stronger online information needs for women than for information search. As noted before, males, on average, men. Coupled with the fact that females do not have as had more trips than females had, and it naturally caused much experience in online searching as males, it seems that more information search needs. In this sense, even though the need for user-friendly functionalities and a wider scope males’ general perceived importance of information was of information contents are more important issues of lower than that of females on some items, males’ concern for women. information search behaviors were a little higher or, at According to the Pew Internet & American Life Project least at the same level as females due to the higher number (2004b), women have reached parity with men in the of trips and trip costs. Internet population. In the year 2000, about 60 percent of Dividing trip expenditures by the number of Websites Internet population was men and about 40 percent was visited, a group of variables indicating ‘‘mean number of women. In February 2004, the gender ratio among Internet visits per unit cost’’ was constructed. The purpose was to users has shifted to 50 percent men and 50 percent women. evaluate gender differences in the actual amount of In this sense, the findings of this research have practical information sought per se without the confounding effect implications for women’s participation in Web-based of trip cost. Significant gender mean differences at po:01 marketing communications, and their use of the Internet were observed for 10 items (‘‘attraction,’’ ‘‘events,’’ in general. The findings of this research also seem to ‘‘package tour,’’ ‘‘entertainment,’’ ‘‘activities,’’ ‘‘local suggest that while most Websites may be gender-neutrally information,’’ ‘‘restaurant,’’ ‘‘map,’’ ‘‘transportation,’’ designed both in terms of functionality and content, and ‘‘testimonial’’). Two items showed significant mean women may actually be likely to use them more than difference at po:05 (‘‘weather,’’ and ‘‘general informa- men do, since men in general do not resort to external tion’’). Noticeably, all significant mean differences showed information as much. Consequently, females’ more positive that females consistently had higher item visit means per attitudes to Website functions require marketers to have unit cost. This implies that females have not only higher more appropriate Web marketing strategies. In today’s perceived importance attached to the functionalities as well competitive e-environment, the placement of appropriate as contents of Websites, but also had higher number of messages on a Website in an appropriate manner is visits to various travel Websites, when information amount paramount to success. The appropriateness of the content is measured at per unit cost level. This is consistent with as well as the presentation of the message, however, hinges
    • ARTICLE IN PRESS 10 D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] upon having a good understanding of the characteristics of Douglas, S. (1976). Cross-national comparisons and consumer stereo- the audiences. Thus, marketers may benefit by creating types: A case study of working and nonworking wives in the U.S. and gender-sensitive Website content and presentation. Based France. Journal of Consumer Research, 3(1), 12–20. Eagly, A. H., & Carli, L. (1981). Sex of researchers and sex-typed on the findings of this research, tourism marketers should communications as determinants of sex differences on influenceability: develop gender-sensitive online communication strategies. A meta-analysis of social influence studies. Psychological Bulletin, For example, Website contents targeting men should 90(1), 1–20. highlight the distinctive nature of selected attributes, and Eagly, A. H. (1987). Sex differences in social behavior: A social-role the contents targeting women should focus on more interpretation. Hillsdale, NJ: Erlbaum. Edward, P. N. (1995). From ‘impact’ to social process. In S. Jasanoff, G. affective themes underlying the various attributes identified E. Markle, J. C. Peterson, & T. Pinch (Eds.), Handbook of Science and in messages. That is, Websites targeting men should not Technology Studies, (pp. 257–285). London: Sage Publications. emphasize features common to the product category, but Engel, J. F., Blackwell, R. D., & Miniard, P. W. (1990). Consumer instead focus on one or two features that are unique to the behavior. Orlando, FL: The Dryden Press. advertised product or brand. In contrast, women, as Everhart, D. E., Shucard, J. L., Quatrin, T., & Shucard, D. W. (2001). Sex-related differences in event-related potentials, face recognition, relational processors, would value category-based messages and facial affect processing in prepubertal children. Neuropsychology, that focus on the common themes of the claim rather than 15(3), 329–341. the unique features. In sum, the different gender attitudes Fisher, E., & Arnold, S. J. (1990). More than a labor of love: Gender roles towards destination Website design and contents empiri- and Christmas gift shopping. Journal of Consumer Research, 17, cally supported in this study represent valuable inputs in 333–345. Fisher, E., & Arnold, S. J. (1994). Sex, gender identity, gender role designing tourism Websites, communicating with potential attitudes, and consumer behavior. Psychology & Marketing, 11(2), visitors, and defining the most appropriate messages to 163–182. deliver in the online environment. Fodness, D., & Murray, B. (1998). A typology of tourist information search strategies. Journal of Travel Research, 37, 108–119. Fodness, D., & Murray, B. (1997). Tourist information search. Annals of Tourism Research, 24(3), 503–523. References Geary, D. C. (1996). Sexual selection and sex differences in mathematical abilities. Behavioral and Brain Sciences, 19, 229–247. Allen, B. J. (1995). Gender and computer-mediated communication. Sex- Gitelson, R., & Crompton, J. (1983). The planning horizons and a sources Roles, 32(7), 557–563. of information used by pleasure vacationers. Journal of Travel Becker, B. J. (1986). Influence again: An examination of reviews and Research, 21, 2–7. studies of gender differences in social influence. In J. S. Hyde, & M. C. Goldman, A., & Johansson, J. K. (1978). Determinants of search for lower Linn (Eds.), The psychology of gender: Advances through meta-analysis prices: An empirical assessment of the economics of information (pp. 178–209). Baltimore: Johns Hopkins University Press. theory. Journal of Consumer Research, 5, 176–186. Bem, S. (1974). The measurement of psychological androgyny. Journal of Gursoy, D., & Chen, J. (2000). Competitive analysis of cross Consulting Clinical Psychology, 42, 155–162. cultural information search behavior. Tourism Management, 21, Bettman, J. R. (1979). Information processing theory of consumer choice. 583–590. Boston: Addison-Wesley. Hall, J. A. (1984). Nonverbal sex differences: Communication accuracy and Bimber, B. (2000). Measuring the gender gap on the Internet. Social expressive style. Baltimore: Johns Hopkins University Press. Science Quarterly, 81, 868–876. Hass, A. (1979). Male and female spoken language differences; Stereo- Bloch, P. H., Sherrell, D. L., & Ridgway, N. M. (1986). Consumer search: types and evidence. Psychological Bulletin, 86, 616–626. An extended framework. Journal of Consumer Research, 13, 119–126. Hiltz, R. S., & Johnson, K. (1990). User satisfaction with computer- Buss, D. M. (1995). Psychological sex differences: Origins through sexual mediated communication systems. Management Science, 36, 739–751. selection. American Psychologist, 50(3), 164–168. Holbrook, M. B. (1986). Aims, concepts, and methods for the presentation Buss, W. C., & Schaninger, C. (1987). An overview of dyadic family of individual differences to design features. Journal of Consumer behavior and sex roles research: A summary of findings and an agenda Research, 13, 337–347. for future research. In M. Houston (Ed.), Review of marketing (pp. Hyde, J. S., Fennema, E., & Lamon, S. J. (1990). Gender differences in 293–324). Chicago: American Marketing Association. mathematics performance: A meta-analysis. Psychological Bulletin, Chang, C. K., & McDaniel, E. D. (1995). Information search strategies in 107, 139–153. loosely structured settings. Journal of Educational Computing Research, Hyde, J. S., & Linn, M. C. (1988). Gender differences in verbal ability: 12(1), 95–107. A meta-analysis. Psychological Bulletin, 104, 53–69. ChanLin, L. J. (1999). Gender differences and the need for visual control. Kerstetter, D., & Cho, M.-H. (2004). Prior knowledge, credibility and International Journal of Instructional Media, 26(3), 329–335. information search. Annals of Tourism Research, 31(4), 961–985. Crotts, J. (1999). Consumer decision making and prepurchase information Kotler, P., Bowen, J., & Makens, J. (1999). Marketing for hospitality and search. In A. Pizam, & Y. Mansfeld (Eds.), Consumer behavior in travel tourism. Upper Saddle River, NJ: Prentice-Hall, Inc. and tourism (pp. 149–168). New York: The Haworth Hospitality Press. Krugman, H. E. (1966). The measurement of advertising involvement. Darley, W. K., & Smith, R. E. (1995). Gender differences in information Public Opinion Quarterly, 30, 583–596. processing strategies: An empirical test of the selectivity model in Lake, D. (2001). American go online for travel information (online). advertising response. Journal of Advertising, 24(1), 41–59. CNN, June 14, 2001. Available http://www.cnn.com/2001/TECH/ Dillon, A., & Gabbard, R. (1998). Hypermedia as an educational internet/06/14/travelers.use.net.idg/index.htm technology: A review of the quantitative literature on learner Lehto, X. Y., O’Leary, J. T., & Morrison, A. M. (2004). The effect of prior comprehension, control, and style. Review of Educational Research, experience on vacation behavior. Annals of Tourism research, 31(4), 68(3), 322–349. 801–818. Dholakis, U., & Baggozzi, R. (2001). Consumer behavior in digital Lenney, E., Gold, J., & Browning, C. (1983). Sex differences in self- environments. In J. Wind, & V. Mahajan (Eds.), Digital marketing (pp. confidence: The influence of comparison to others’ ability level. Sex 163–200). New York: Wiley. Roles, 9, 925–942.
    • ARTICLE IN PRESS D.-Y. Kim et al. / Tourism Management ] (]]]]) ]]]–]]] 11 Light, P., Littleton, K., Bale, S., Joiner, R., & Messer, D. (2000). Gender Rosenthal, R., & DePaulo, B. M. (1979). Sex differences in accommoda- and social comparison effects in computer-based problem solving. tion in nonverbal communication. In R. Rosenthal (Ed.), Skill in Learning and Instruction, 10, 483–496. nonverbal communication (pp. 68–103). Cambridge, MA: Oelgeschla- Linn, M. C., & Peterson, A. C. (1986). A meta-analysis of gender ger, Gunn and Hain. differences in spatial ability: Implications for mathematics and science Saucier, D. M., & Elias, L. J. (2001). Laternal and sex differences in achievement. In J. S. Hyde, & M. C. Linn (Eds.), The psychology of manual gesture during conversation. Laterality, 6(3), 239–245. gender: Advances through meta-analysis (pp. 67–101). Baltimore: Johns Schaninger, C., & Buss, C. (1985). The relationship of sex-role norms to Hopkins University Press. household task allocation. Psychology and Marketing, 2(2), 93–104. Losh, S. C. (2003). Gender and educational digital chasms in computer Schertler, W., Schmid, B., Tjoa, A. M., & Werthner, H. (1995). and Internet access and use over time: 1983–2000. IT & Society, 1, Information and communication technologies in tourism. New York: 73–86. Springer, Wien. MacGregor, S. K. (1999). Hypermedia navigation profiles: Cognitive Schul, P., & Crompton, J. (1983). Search behavior of international characteristics and information processing strategies. Journal of vacationers: Travel-specific lifestyle and sociodemographic variables. Educational Computing Research, 20(2), 189–206. Journal of Travel Research, 22(3), 25–31. Mantovani, G. (1994). Is computer-mediated communication intrinsically Schumacher, P., & Morahan-Martin, J. (2001). Gender, Internet and apt to enhance democracy in organizations? Human Relations, 47, computer attitudes and experiences. Computers in Human Behavior, 45–62. 17(1), 95–110. Meyers-Levy, J., & Sternthal, B. (1991). Gender differences in the use of Shashaani, L. (1997). Gender differences in computer attitudes and use message cues and judgments. Journal of Marketing Research, 26(4), among college students. Journal of Educational Computing Research, 84–96. 16, 37–51. Meyers-Levy, J. (1989). Gender differences in information processing: A Shute, V. (1993). A comparison of learning environments: All that glitters. selective interpretation. In P. Cafferata, & A. Tybout (Eds.), Cognitive In S. LaJoie, & S. Derry (Eds.), Computers as cognitive tools and affective responses to advertising (pp. 219–260). Lexington, MA: (pp. 47–73). Hillsdale, NJ: LEA. Lexington Books. Snepenger, D., Meged, K., Snelling, M., & Worrall, K. (1990). Meyers-Levy, J. (1988). Influence of sex roles on judgment. Journal of Information search strategies by destination-naı¨ ve tourist. Journal of Consumer Research, 14, 522–530. Travel Research, 29(1), 13–16. Mitchell, V.-W., & Walsh, G. (2004). Gender differences in German Sokoloff, H. (2001). Test shows boys trail in reading ability—Parents, consumer decision-making styles. Journal of Consumer Behaviour, 3(4), educators urged to take action (online). National post, June, 12. 33–346. Available http://www.pisa.oecd.org/dataoecd/36/0/33714794.pdf Moorthy, S., Ratchford, B. T., & Talukdar, D. (1997). Consumer Spence, J., & Helmreich, R. (1978). Masculinity and femininity: Their information search revisited: theory and empirical analysis. Journal psychological dimensions, correlates and antecedents. Austin: University of Consumer Research, 23(4), 263–277. of Texas Press. Mullen, B., & Johnson, C. (1990). The psychology of consumer behavior. Stigler, G. J. (1961). Economics of information. Journal of Political Hillsdale: Lawrence Erlbaum. Economy, 69, 213–215. Nelson, P. (1974). Advertising as information. Journal of Political Tobias, S. (1994). Interest, prior knowledge, and learning. Review of Economy, 83(4), 729–754. Educational Research, 64, 37–54. Nelson, P. (1970). Information and consumer behavior. Journal of UCLA Center for Communication Policy (2001). The UCLA Internet Political Economy, 78(2), 311–329. report 2001: Surveying the digital future — Year two. Los Angeles: Nowaczyk, R. H. (1982). Sex-related differences in the color lexicon. UCLA Center for Communication Policy. Language and Speech, 25(3), 257–265. Urbany, J. E. (1986). An experimentation of the economics of informa- O’Keefe, D. J. (2002). Persuasion: Theory and research (2nd ed.). tion. Journal of Consumer Research, 13, 257–271. Thousand Oaks, CA: Sage. Vogt, C. A., & Fesenmaier, D. R. (1998). Expanding the functional Oliva, R. A. (1998). Playing the ‘Web Wild Cards’. Marketing Manage- information search model. Annals of Tourism Research, 25(3), 551–578. ment, 7(1), 51–54. Wajcman, J. (1995). Feminist theories of technology. In S. Jasanoff, G. E. Ono, H., & Zavodny, M. (2003). Gender and the Internet. Social Science Markle, J. C. Peterson, & T. Pinch (Eds.), Handbook of Science and Quarterly, 84, 111–121. Technology Studies (pp. 189–204). London: Sage Publications. Papadakis, M. C. (2001). The application and implications of information Werthner, H., & Klein, S. (1999). Information technology and tourism – technologies in the home: Where are the data and what do they say. A challenging relationship. New York: Springer, Wien. Arlington, VA: National Science Foundation. Wicks, B., & Schuett, M. (1991). Examining the Role of Tourism Pew Internet & American Life Project (2004a). The Internet and daily life promotion through the use of brochures. Tourism Management, 11, (online). August 11, 2004. Available http://www.pewinternet.org. 301–312. Pew Internet & American Life Project (2004b). Older Americans and the Williamson, O. E. (1985). A history of computing technology. Englewood Internet (online). March 25, 2004. Available: http://www.pewinternet.org. Cliffs, NJ: Prentice Hall. Putrevu, S. (2001). Exploring the origins and information processing Wilson, S. R. (2002). Seeking and resisting compliance. Thousand Oaks, differences between men and women: Implications for advertisers CA: Sage Publications. (online). Academy of Marketing Science Review, Available http:// Wood, M. M. (1966). The influence of sex and knowledge of commu- www.amsreview.org/articles/putrevu10-2001.pdf. nication effectiveness of spontaneous speech. Word, 22, 112–137.