Journal of Applied Psychology 2012, Vol. 97, No. 1, 214 –224
© 2011 American Psychological Association 0021-9010/11/$12.00 DOI: 10.1037/a0025847
Diversity Cues on Recruitment Websites: Investigating the Effects on Job Seekers’ Information Processing H. Jack Walker
Hubert S. Feild
Texas Tech University
Jeremy B. Bernerth
J. Bret Becton
Louisiana State University
University of Southern Mississippi
Although job seekers’ motivation to process the information encountered during recruitment partially influences recruitment success, little is known about what motivates more thorough information processing. To address this issue, we integrated recruitment and social information processing theories to examine the possibility that diversity cues on recruitment websites influence website viewers’ processing of presented information. Utilizing a controlled experiment and a hypothetical organization, Study 1 revealed that both Blacks and Whites spent more time viewing recruitment websites and better recalled website information when the sites included racial diversity cues. These relationships were stronger for Blacks, and organizational attractiveness perceptions mediated these effects for Blacks but not for Whites. Study 2 found similar relationships for Black and White participants viewing real organizational recruitment websites after taking into account perceived organizational attributes and website design effects. Implications of these findings for recruiting organizations are discussed. Keywords: diversity cues, information processing, recruitment
Although job seekers’ attraction to recruiting organizations is an important outcome of the recruitment process, it is only one indicator of recruitment success. Recruitment researchers have theorized that recruiting success is also determined by job seekers’ comprehension of recruitment information, accuracy of expectations (Breaugh & Starke, 2000), and motivation to explore recruitment websites (Cober, Brown, Keeping, & Levy, 2004). In addition, Dineen and Soltis (2010) argued that the way job seekers process recruitment information influences how effective recruitment activities are in persuading job seekers to apply for job openings. They further contended that understanding job seekers’ motivation to process recruitment information is important because it likely affects applicant pool quality. Given these alternative conceptualizations of recruitment success, the dearth of empirical research examining job seekers’ cognitive processing of recruitment information is surprising (see Dineen, Ling, Ash, & DelVecchio, 2007, for an exception). Further, we are not aware of any research that considered the effects of diversity cues in recruitment materials on job seekers’ processing of recruitment information. We designed the present research to address this gap in the recruitment literature. In investigating these unexplored issues, we advance our theoretical understanding of recruitment by examining how the design of recruitment materials influences important cognitive processing outcomes that have been largely ignored (i.e., recruitment website viewing time and information recall). As noted by Dineen et al. (2007), these outcomes are extremely important to recruitment success, considering “the proliferation of
Recognizing that a racially diverse workforce has the potential to provide a competitive advantage (Thomas, 2004) and improve organizational performance (Jackson, Joshi, & Erhardt, 2003), many organizations have dramatically increased efforts to recruit more minority job seekers (Fullerton & Toosi, 2001; ThalerCarter, 2001). Scholars have suggested that organizations can accomplish this goal by proactively managing organizational diversity perceptions through the design of recruitment activities (e.g., Avery, 2003; Highhouse & Hoffman, 2001; Highhouse, Stierwalt, Bachiochi, Elder, & Fisher, 1999). Several empirical studies have supported these predictions and found that recruiting organizations are more attractive to minorities when they advertise diversity in recruitment materials (e.g., Avery, 2003; Avery, Hernandez, & Hebl, 2004; Walker, Feild, Giles, Armenakis, & Bernerth, 2009).
This article was published Online First October 17, 2011. H. Jack Walker, Area of Management, Rawls College of Business, Texas Tech University; Hubert S. Feild, Department of Management, College of Business, Auburn University; Jeremy B. Bernerth, Department of Management, Louisiana State University; J. Bret Becton, Department of Management and International Business, University of Southern Mississippi. We sincerely thank Derek Avery and Michael Cole for their comments regarding previous versions of this paper. Correspondence concerning this article should be addressed to H. Jack Walker, Area of Management, Rawls College of Business, Texas Tech University, Lubbock, TX 79409. E-mail: [email protected]
DIVERSITY CUES AND INFORMATION PROCESSING
vacancy information available on the Web and concomitant increased stakes for companies trying to gain a competitive advantage in sourcing human capital by first capturing and retaining job seeker attention” (p. 368). At the same time, we contribute to the diversity management literature by examining more objective versus affective (e.g., organizational attractiveness perceptions) measures of diversity cue salience among Black and White job seekers. Our predictions are based on an integrative elaboration likelihood model (Petty & Cacioppo, 1986) and social identity theory (Tajfel & Turner, 1986) conceptual framework and are tested with both unfamiliar, hypothetical (Study 1) and familiar, real (Study 2) organizations.
Conceptual Background The elaboration likelihood model originated in the persuasive communications literature (see Eagly & Chaiken, 1998; Petty & Wegener, 1998) and has recently been used to investigate how recruitment materials influence job seekers’ processing of recruitment information (Jones, Shultz, & Chapman, 2006; Roberson, Collins, & Oreg, 2005; Walker, Feild, Giles, & Bernerth, 2008). According to this theoretical framework, individuals process information via either a central or a peripheral route (Petty & Cacioppo, 1986). Central processing involves message recipients closely evaluating the merits of the message itself and, therefore, requires message recipients to possess the ability and motivation to evaluate the message (i.e., high elaboration of message content). Peripheral processing, on the other hand, is less dependent on evaluation of the persuasive message and is instead characterized by attitude formation resulting from positive or negative cues peripherally associated with the message (i.e., low elaboration of message content). Attitudes resulting from central processing tend to be specific, enduring, and predictive of behavior, whereas peripheral processing leads to attitudes that are more general, fleeting, and subject to change (Cialdini, Petty, & Cacioppo, 1981; Petty & Cacioppo, 1981, 1986). In a recruiting context, most job seekers have the ability to process recruitment information (i.e., they can navigate the website and read the presented information; Cable & Turban, 2001). Variability in job seekers’ motivation to process recruitment information, however, is likely due to the content and characteristics of recruitment materials (Cober et al., 2004). For example, Dineen et al. (2007) found that job seekers spent more time viewing and better recalled website information (indicating central processing) when a recruitment website was visually appealing and provided customized information. They theorized that higher quality website aesthetics (i.e., use of color, pictures, and unique fonts) influenced job seekers’ motivation to process website information because these website characteristics produced positive initial affective reactions and led job seekers to further evaluate website content. Additionally, customized information (i.e., information permitting job seekers to assess organizational fit) increased job seekers’ motivation because it enhanced the personal relevance of the message, a central factor in the motivation process (Petty & Cacioppo, 1986).
Diversity Cues on Recruitment Websites and Information Processing According to social identity theory (Tajfel & Turner, 1986), individuals naturally categorize themselves and others in terms of
important visible characteristics (e.g., race, gender, age). To maintain high levels of self-esteem, individuals develop more favorable attitudes toward in-group members and seek environments that affirm their identity (Ashforth & Mael, 1989; Hogg & Terry, 2000). Additionally, research suggests that these tendencies are more pronounced when individuals have experienced situations that threaten their identity (e.g., racial discrimination; Ethier & Deaux, 1994; Saylor & Aries, 1999). Because racial minorities experience more racial discrimination in the workplace than Whites (Avery, McKay, & Wilson, 2008; Deitch et al., 2003), it is likely that minorities will be more concerned with potential employers’ diversity climates (i.e., the perceived extent to which minorities are socially integrated and accepted by organizations; McKay, Avery, & Morris, 2009). As such, diversity cues in recruitment materials may form the basis for evaluating an important decision standard (i.e., Does the organization value diversity?) used by minority job seekers to screen potential employers (Stevens & Beach, 1996). Minority job seekers will likely remove those organizations including few diversity cues in recruitment materials from consideration (i.e., spend less time and effort evaluating presented information) and will further evaluate the information presented on organizations’ websites including diversity cues. Stated another way, diversity cues should provide motivation for minority (vs. White) job seekers to carefully evaluate presented information as they attempt to find environments free of racial discrimination (McKay & Avery, 2006). Therefore, we predict a two-way interaction between job seeker race and diversity cues on recruitment websites such that inclusion of diversity cues will result in more thorough information processing (central processing; Petty & Cacioppo, 1981, 1986) among Black job seekers (vs. Whites) as indicated by increased website viewing time and more accurate recall of presented information (cf. Dineen et al., 2007). Hypothesis 1a: Job seeker race will moderate the relationship between diversity cues on recruitment websites and time spent viewing recruitment websites such that Blacks will spend more time than Whites viewing the website when diversity cues are included. Hypothesis 1b: Job seeker race will moderate the relationship between diversity cues on recruitment websites and accuracy of website information recall such that Blacks will be more likely than Whites to accurately recall website information when diversity cues are included.
Organizational Attractiveness as a Mediator One generative mechanism that might explain why minority job seekers are more likely than Whites to centrally process recruitment information when diversity cues are presented is because this information produces positive affective reactions. Previous research suggests affective reactions are important in the recruitment context because they motivate job seekers to further explore recruitment material (Cober et al., 2004; Dineen et al., 2007). Because individuals are likely to evaluate those perceived as similar more positively (Tajfel & Turner, 1986), diversity cues in recruitment materials should produce more positive affective reactions for minorities than Whites because
WALKER, FEILD, BERNERTH, AND BECTON
they signal that the workforce includes minorities (Avery & McKay, 2006). Empirical findings generally support these predictions, as increased minority representation in recruitment advertisements positively influences organizational attractiveness perceptions (Avery, 2003; Walker et al., 2009). Combining these findings with the predictions made in Hypotheses 1a and 1b suggests a mediated-moderation relationship (Edwards & Lambert, 2007) in which the Job Seeker Race ⫻ Website Diversity Cue interaction on (a) website viewing time and (b) accuracy of website information recall is mediated by organizational attractiveness perceptions. In particular, we expect that diversity cues on websites will indirectly affect information processing via organizational attractiveness perceptions and job seeker race will moderate the first stage of this indirect effect (i.e., website diversity cue 3 organizational attractiveness perceptions). Hypothesis 2: The interactive effects of recruitment website diversity cues and job seeker race on (a) website viewing time and (b) accuracy of website information recall will be mediated by job seekers’ organizational attractiveness perceptions.
Study 1 Method Participants We obtained the data used to test Study 1’s hypotheses as a part of a larger data collection effort (see Walker et al., 2009). We recruited research participants from upper level undergraduate management courses at a predominantly White university and three historically Black universities. For the purpose of Study 1, we considered only those participants from the larger data set who saw the appropriate manipulations and completed all three phases of the study. Of those recruited, 141 students met these criteria and were included in our analyses. Participants included 94 (67%) Whites, 47 (33%) Blacks, 77 (55%) men, and 64 (45%) women with a mean age of 21.57 years (SD ⫽ 1.16).
Procedure Time 1 data collection. Course instructors informed participants of an opportunity to participate in a research study in exchange for extra course credit and entry into a random drawing for restaurant gift certificates. Each participant received an e-mail containing a Web address for survey completion. Before completing the survey, participants provided a unique user name that was used to match responses across the three phases of Study 1. After logging in, participants answered survey questions assessing several demographic items and measures not included in this study. Time 2 data collection. Approximately three weeks after Time 1 data collection, course instructors informed the students that a Fortune 500 organization named HBA Corporation (a hypothetical organization) requested assistance in evaluating its recruitment website. We provided students with HBA’s website along with an instruction page. The instruction page told students to take the role of an active job seeker and evaluate HBA’s
recruitment website as if they were considering HBA as a potential employer. The participants then answered a series of questions intended to gauge their reactions to HBA and its recruitment website. Time 3 data collection. Approximately three weeks after Time 2 data collection, we sent students an e-mail containing a link to the final study survey. Survey instructions asked participants to answer a series of questions intended to assess their recall of information presented on HBA’s recruitment website. The participants could not revisit HBA’s website during Time 3 data collection.
Manipulations We developed experimental recruitment websites to test Study 1’s hypotheses. Each website included the following links from which participants could gather information: “Career Development,” “Pay and Benefits,” “Meet Our People,” “Company Information,” and “Our Plan for Growth.” All website versions contained identical link information with the exception of the “Meet Our People” link. Because the racial composition of employees included in recruitment advertisements can signal the extent to which diversity is valued (Avery & McKay, 2006; Cable & Graham, 2000), we varied the racial diversity of employees depicted on this link to manipulate diversity cues on recruitment websites (cf. Avery, 2003). We presented participants used to test Study 1’s hypotheses with one of two websites. We manipulated four employees on HBA’s recruitment website as either all White (depicting 4 White employees and 0 Black employees; no racial diversity cue) or balanced (depicting 2 Black employees and 2 White employees; racial diversity cue). We held the gender ratio constant (2 men and 2 women) to control for possible confounding effects. Additional design features. We presented employee testimonials on HBA’s recruitment website using either (a) video with audio or (b) picture with text (communication medium was entered as a covariate in our analyses). Actors from a university theater department delivered the scripted employee testimonials in response to four questions: Why did you choose HBA? What do you enjoy most about working at HBA? How would you describe HBA’s culture? How do you like to spend your free time? Testimonials ranged from 355 to 371 words.
Measures Organizational attractiveness. We measured participants’ organizational attractiveness perceptions with Highhouse, Lievens, and Sinar’s (2003) five-item general attractiveness scale (␣ ⫽ .93). A sample item is “For me, this company would be a great place to work.” Recruitment website viewing time. Online computer software recorded the time participants spent viewing HBA’s recruitment website (in seconds) during Time 2 data collection. Total website viewing time ranged from 269 to 1,100 s with a mean of 708.77 s (SD ⫽ 151.16). Recruitment website information recall. We assessed participants’ website information recall by developing five multiplechoice questions, with each question having four response op-
DIVERSITY CUES AND INFORMATION PROCESSING
Table 1 Means, Standard Deviations, Intercorrelations, and Coefficient Alphas Between Study 1 Variables Variable 1. 2. 3. 4. 5. 6. 7. 8.
Gender Age (years) Raceb Communication mediac Website diversity cue conditionsd Organizational attractiveness Website viewing time (in seconds) Accuracy of website information recall
0.45 21.57 0.33 0.56 0.47 3.66 708.77 2.97
0.50 1.17 0.47 0.50 0.50 0.76 151.16 0.79
— ⫺.14 ⫺.19ⴱ ⫺.14 ⫺.08 ⫺.03 ⫺.03 ⫺.26ⴱⴱ
— .23ⴱⴱ ⫺.08 .06 .15 ⫺.01 .27ⴱⴱ
— ⫺.13 .06 .07 .08 .16
— .01 .11 ⫺.10 .02
— .13 .37ⴱⴱ .36ⴱⴱ
(.93) .25ⴱⴱ .32ⴱⴱ
Note. N ⫽ 141. All tests are two-tailed. Coefficient alpha is in parentheses on the main diagonal. a 0 ⫽ male, 1 ⫽ female. b 0 ⫽ White, 1 ⫽ Black. c 0 ⫽ picture with text, 1 ⫽ video with audio. d 0 ⫽ no racial diversity cue condition (4 White employees, 0 Black employees), 1 ⫽ racial diversity cue condition (2 Black employees, 2 White employees). ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.
tions.1 Scores could range from 0 to 5, with higher scores indicating greater recruitment website recall. On average, participants answered 2.97 (SD ⫽ 0.79) recall questions correctly.
Study 1 Results Manipulation Check Before testing Study 1’s hypotheses, we performed a manipulation check to ensure that changes in the racial composition of employees reflected perceptions of workplace diversity. We collected data used for this manipulation check at the end of Time 2 data collection to avoid priming participants regarding the true nature of the study. Participants indicated the degree to which they perceived HBA as valuing diversity using a four-item scale from Avery et al. (2004; ␣ ⫽ .86). As anticipated, analysis of variance (ANOVA) results indicated a difference in perceptions that HBA valued diversity depending on the racial composition of employees, F(1, 139) ⫽ 61.22, p ⬍ .01, 2 ⫽ .31. The no racial diversity cue condition (4 White employees; M ⫽ 2.26, SD ⫽ 0.67) was rated lower in valuing diversity than the racial diversity cue condition (2 Black employees and 2 White employees; M ⫽ 3.17, SD ⫽ 0.72).
Hypotheses Tests Table 1 reports the means, standard deviations, intercorrelations, and coefficient alphas for all Study 1 variables. To test Hypotheses 1a and 1b, we first conducted a one-way multivariate analysis of variance (MANCOVA) with recruitment website viewing time and accuracy of website information recall as the dependent variables and participant race, website diversity cues, and their interaction as the independent variables. Additionally, we entered age, gender, and communication media as covariates to account for possible confounding effects. Results revealed differences for the website diversity cue, Wilks’s ⫽ .74, F(2, 133) ⫽ 23.06, p ⬍ .01, 2 ⫽ .26, and the Participant Race ⫻ Website Diversity Cue interaction, Wilks’s ⫽ .92, F(2, 133) ⫽ 6.02, p ⬍ .01, 2 ⫽ .08. Next, we conducted two, one-way analyses of covariance (ANCOVAs; see Table 2). Results indicated significant website diversity cue main effects for website viewing time, F(1, 134) ⫽ 29.56, p ⬍ .01, 2 ⫽ .18, and for website information recall, F(1, 134) ⫽ 23.98, p ⬍
.01, 2 ⫽ .15. The Participant Race ⫻ Website Diversity Cue interaction was also significant for website viewing time, F(1, 134) ⫽ 8.37, p ⬍ .01, 2 ⫽ .06, and for website information recall, F(1, 134) ⫽ 5.56, p ⬍ .05, 2 ⫽ .04. As expected, Blacks’ website viewing time and website information recall accuracy were higher (viewing time, t(46) ⫽ 5.75, p ⬍ .01, d ⫽ 1.68; information recall, t(46) ⫽ 3.95, p ⬍ .01, d ⫽ 1.15) when participants were presented with the racial diversity cue website (viewing time, M ⫽ 825.63, SD ⫽ 121.39; information recall, M ⫽ 3.63, SD ⫽ 0.82) than with the no racial diversity cue website (viewing time, M ⫽ 621.97, SD ⫽ 121.59; information recall, M ⫽ 2.65, SD ⫽ 0.88). Time spent viewing the website and accuracy of information recall were also higher for Whites (viewing time, t(93) ⫽ 2.11, p ⬍ .05, d ⫽ 0.43; information recall, t(93) ⫽ 2.52, p ⬍ .05, d ⫽ 0.52) when participants were presented with the racial diversity cue website (viewing time, M ⫽ 735.29, SD ⫽ 173.36; information recall, M ⫽ 3.07, SD ⫽ 0.64) than with the no racial diversity cue website (viewing time, M ⫽ 671.81, SD ⫽ 117.22; information recall, M ⫽ 2.73, SD ⫽ 0.66). We plotted the results to clarify the nature of the two significant interactions but included only the plot for website viewing time because the plot for website information recall was similar in nature (see Figure 1). These results provide full support for Hypotheses 1a and 1b. We tested the mediated-moderation model proposed in Hypothesis 2 using the general path analytic framework (Edwards & Lambert, 2007). Although we predicted only that race would moderate the first-stage effect (website diversity cue 3 organizational attractiveness perceptions), this procedure allowed us to examine the direct, indirect, and total effects of website diversity cues on information processing for both Blacks and Whites. We estimated 1,000 bootstrap samples to create bias-corrected confi1
We developed the questions used to assess website recall in Study 1 from website content; they included the following: “Which of the following was used to describe the culture at HBA?” “Where is HBA’s headquarters located?” “Which of the following was mentioned on HBA’s website as a way that they encourage employee development?” “Where is HBA planning to expand its operations within the next five years?” and “Which of the following was NOT mentioned on HBA’s website as a benefit option?”
WALKER, FEILD, BERNERTH, AND BECTON
Table 2 Summary of ANCOVA Results for Website Diversity Cues and Participant Information Processing (Study 1) Accuracy of website information recall
Website viewing time (in seconds) F
0.48 0.00 1.67
.01 .00 .01
7.55ⴱ 5.17 0.04
.05 .04 .00
Variable Covariates Age (years) Gendera Communication mediab Main effects Website diversity cuec Raced Interaction effects Website diversity cue ⫻ race Blacks
No racial diversity cue Racial diversity cue d
Note. N ⫽ 141. Overall MANCOVA results: Website diversity cue conditions, Wilks’s ⫽ .74, F(2, 133) ⫽ 23.06, p ⬍ .01, ⫽ .26; participant race, Wilks’s ⫽ .99, F(2, 133) ⫽ 0.52, p ⫽ ns, 2 ⫽ .01; Website Diversity Cue Conditions ⫻ Participant Race, Wilks’s ⫽ .92, F(2, 133) ⫽ 6.02, p ⬍ .01, 2 ⫽ .08. ANCOVA ⫽ analysis of covariance; MANCOVA ⫽ multivariate analysis of covariance. a 0 ⫽ male, 1 ⫽ female. b 0 ⫽ picture with text, 1 ⫽ video with audio. c 0 ⫽ no racial diversity cue condition (4 White employees, 0 Black employees), 1 ⫽ racial diversity cue condition (2 Black employees, 2 White employees). d 0 ⫽ White, 1 ⫽ Black. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. 2
dence intervals for the population value of the conditional (i.e., moderated) indirect effect (Edwards & Lambert, 2007; Stine, 1989). As indicated in Table 3, the indirect effect of website diversity cues on viewing time was significant for Blacks (P ⫽ 46.35, p ⬍ .05) but not for Whites (P ⫽ ⫺4.31, p ⬎ .10). In addition, the direct effects of website diversity cues on viewing time were significant for both Blacks (P ⫽ 157.32, p ⬍ .05) and Whites (P ⫽ 67.78, p ⬍ .05). These results indicate that organizational attractiveness perceptions partially mediated the relationship between website diversity cues and website viewing time for Blacks but not Whites. With regard to accuracy of website information recall, results revealed significant indirect effects for Blacks (P ⫽ 0.38, p ⬍ .05) but not Whites (P ⫽ ⫺0.04, p ⬎ .10) and significant
Website Viewing Time
900 850 800 750 700 650 600 550 500 No Racial Diversity Cues
Racial Diversity Cues
Recruitment Web Site
Figure 1. Plot of the interactive effects of Website Diversity Cues ⫻ Participant Race on time spent viewing the recruitment website (Study 1).
direct effects for Whites (P ⫽ 0.38, p ⬍ .05) but not Blacks (P ⫽ 0.58, p ⬎ .05). These results indicate that organizational attractiveness perceptions fully mediated the relationship between website diversity cues and accuracy of website information recall for Blacks but not Whites. Taken collectively, these results provide partial support for Hypothesis 2.
Study 1 Discussion Study 1 results provided initial evidence that diversity cues on recruitment websites influence the way job seekers process website information. Consistent with our predictions, Black participants, as compared to Whites, spent more time on recruitment websites and more accurately recalled website information when websites include racial diversity cues. Moreover, Black participants’ organizational attractiveness perceptions partially mediated the relationship between website diversity cues and viewing time and fully mediated the relationship between website diversity cues and information recall. Unexpectedly, Study 1 results indicated that Whites were also more likely to thoroughly process information when websites included diversity cues, although to a lesser extent than Blacks. Although Study 1 provided insight into the relationship between diversity cues on recruitment websites and job seekers’ processing of website information, it is important to note several potential limitations. First, Study 1’s results were from a hypothetical organization. Unfamiliarity with an employer limits our ability to generalize Study 1’s findings to organizations in which job seekers likely have preexisting attitudes based on information gathered from other sources (e.g., news media, word of mouth). Second, we did not consider the possible influence of perceived organizational
DIVERSITY CUES AND INFORMATION PROCESSING
Table 3 Simple Effects Analyses for Recruitment Website Viewing Time and Accuracy of Website Information Recall (Study 1) Stage Variable DV: Website viewing time Blacks Whites Differences DV: Accuracy of website information recall Blacks Whites Differences
Total PYX ⫹ PYMPMX
0.96ⴱ ⫺0.20 1.16ⴱ
48.45ⴱ 21.40 27.05
157.32ⴱ 67.78ⴱ 89.54
46.35ⴱ ⫺4.31 50.65ⴱ
203.67ⴱ 63.47ⴱ 140.19ⴱ
0.96ⴱ ⫺0.20 1.16ⴱ
0.40ⴱ 0.21ⴱ 0.20
0.58 0.38ⴱ 0.21
0.38ⴱ ⫺0.04 0.42ⴱ
0.96ⴱ 0.34ⴱ 0.63ⴱ
Note. N ⫽ 141. DV ⫽ dependent variable; PMX ⫽ website diversity cue 3 organizational attractiveness perceptions; PYM ⫽ organizational attractiveness perceptions 3 website viewing time/information recall; PYX ⫽ website diversity cue 3 website viewing time/information recall. ⴱ p ⬍ .05.
attributes other than workplace diversity (e.g., promotion opportunities, job location) or website design effects (e.g., website entertainment). With these potential limitations in mind, we developed a second study to replicate Study 1’s findings but used recruitment websites of more familiar, real organizations.
Study 2 Method Participants We recruited Study 2 participants from three upper level undergraduate business courses and one master’s-level business course; advertisements were also posted in a campus newsletter sent daily to all students at a large southwestern university. These recruitment methods resulted in 148 participants completing Phase 1. Of these, 116 (78%) completed Phase 2 and were included in our analyses. The final sample consisted of 73 (63%) Whites and 43 (37%) Blacks; 69 (60%) were men and 47 (40%) women, with a mean age of 22.78 years (SD ⫽ 1.86).
Procedure Time 1 data collection. During Time 1, we randomly assigned each participant a real organization. Next, we provided participants with a link to the recruitment website of their assigned organization and asked them to evaluate their organization as if they were considering it as a potential employer. After viewing the website, participants completed a survey assessing their reactions to the website and their assigned organization. Time 2 data collection. Approximately two weeks after Time 1 data collection, we directed participants to a second survey assessing their recall of website information.
Recruitment Websites of Real Organizations We first attempted to identify one actual organizational recruitment website that represented a “strong” website diversity cue condition (i.e., conveyed that the organization valued diversity) and one website that represented a “weak” website diversity cue condition (i.e., did not convey that the organization valued diversity). Two researchers visited the recruitment websites of 10 randomly selected organizations from Fortune magazine’s ratings of
the most diverse organizations (“Top Companies: Most Diverse,” 2009) and independently evaluated each website in terms of the diversity cues included. After these assessments, the raters discussed their evaluations and agreed on an organization that included strong diversity cues on its recruitment website. The chosen website included pictures of racially diverse organizational members and information related to diversity goals and initiatives. Next, we developed a list of “matching” companies using a method advocated by previous researchers (Fulmer, Gerhart, & Scott, 2003; Loughran & Ritter, 1997).2 After generating a list of matching companies, two researchers independently visited each organization’s recruitment website and evaluated it in terms of diversity cues. The researchers discussed their evaluations and agreed on a recruitment website that included few diversity cues (labeled the “weak” diversity cue condition because it did not include as many pictures of diverse organizational members or information related to diversity goals and initiatives). We monitored the two websites to ensure that there were no major changes in the websites’ diversity cues during data collection. Last, we conducted a pilot test to ensure the two chosen organizations were familiar to the targeted participants. Using a method similar to that of Slaughter, Zickar, Highhouse, and Mohr (2004), we gave undergraduate students in business (N ⫽ 41) a list of 20 Fortune 500 organizations (2 of which were the organizations chosen for Study 2’s manipulation) and asked them to indicate (a) whether they recognized the name of the organization and (b) the degree to which they were familiar with the organization (1 ⫽ very unfamiliar to 5 ⫽ very familiar). Both organizations met Slaughter et al.’s criteria for high familiarity; that is, more than 90% of participants indicated that they recognized the name of both organizations, and the mean familiarity rating was greater than 4.0 (strong diversity cue, M ⫽ 4.02, SD ⫽ 0.79; weak diversity cue, M ⫽ 4.20, SD ⫽ 0.69), t(80) ⫽ 1.10, ns.
We used Compustat to find organizations similar to the one chosen to represent the strong website diversity cue condition in terms of (a) industrial classification code, (b) total assets, and (c) the ratio of operating income before depreciation to ending assets (OIBD/assets ratio).
WALKER, FEILD, BERNERTH, AND BECTON
Table 4 Means, Standard Deviations, Intercorrelations, and Coefficient Alphas Between Study 2 Variables Variable
1. Gender 2. Age (years) 3. Raceb 4. Website diversity cue conditionsc 5. Perceived organizational attributes 6. Website entertainment 7. Website informativeness 8. Website organization 9. Organizational attractiveness 10. Accuracy of website information recall
0.41 22.78 0.37 0.48 3.39 3.05 3.08 3.16 3.61 2.79
0.49 1.86 0.49 0.50 0.64 0.75 0.78 0.81 0.73 0.96
— ⫺.15 .02 .01 .02 ⫺.02 .07 .06 .14 .07
— ⫺.02 ⫺.01 .01 .14 ⫺.06 ⫺.01 .03 .14
— .12 ⫺.12 ⫺.13 .01 .04 ⫺.03 .05
— .12 ⫺.09 ⫺.01 ⫺.01 .08 .33ⴱⴱ
(.76) .20ⴱ .28ⴱ .17 .36ⴱⴱ .32ⴱⴱ
(.91) .28ⴱⴱ .26ⴱⴱ .04 .28ⴱⴱ
(.94) .28ⴱⴱ ⫺.01 .29ⴱⴱ
(.87) .01 .20ⴱ
Note. N ⫽ 116. All tests are two-tailed. Coefficient alphas are in parentheses on the main diagonal. 0 ⫽ male, 1 ⫽ female. b 0 ⫽ White, 1 ⫽ Black. c 0 ⫽ weak website diversity cue condition (few pictures of diverse organizational members and little information about diversity goals and initiatives), 1 ⫽ strong website diversity cue condition (portrayed diverse organizational members and included information about diversity goals and initiatives). ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. a
Perceived organizational attributes. During Time 1 data collection, we assessed participants’ perceived organizational attributes with an eight-item measure (Collins & Stevens, 2002). Participants rated how likely it was that their assigned organization possessed the following attributes: good salary/wage, desirable location, advancement opportunities, opportunities to learn new skills, availability of excellent training programs, interesting work, good benefits, and job security (␣ ⫽ .76). Website design effects. We measured participants’ website design perceptions with Chen and Wells’ (1999) 16-item website attitude measure. This scale assessed three dimensions of website attitudes: entertainment (␣ ⫽ .91), informativeness (␣ ⫽ .94), and organization (␣ ⫽ .87). Organizational attractiveness. We measured participants’ organizational attractiveness perceptions with the same five-item measure used in Study 1 (␣ ⫽ .92; Highhouse et al., 2003). Recruitment website information recall. We assessed participants’ recall of website information by developing five multiple-choice questions for each of the websites.3 On average, participants answered 2.79 (SD ⫽ 0.96) recall questions correctly.
Table 4 provides the means, standard deviations, coefficient alphas, and intercorrelations for all Study 2 variables. In order to investigate the relationships between website diversity cues and information processing using more familiar, real organizational websites, we performed a one-way ANCOVA analysis and included participant age, gender, perceived organizational attributes, website entertainment, website informativeness, and website organization as covariates. As indicated in Table 5, the Website Diversity Cue ⫻ Participant Race interaction was significant for accuracy of website information recall, F(1, 115) ⫽ 4.13, p ⬍ .05, 2 ⫽ .04. Similar to Study 1’s findings, accuracy of information recall increased for Blacks, t(42) ⫽ 3.67, p ⬍ .01, d ⫽ 1.10, and for Whites, t(72) ⫽ 1.78, p ⬍ .10, d ⫽ 0.43, when participants were presented with the strong diversity cue website (Blacks, M ⫽ 3.33, SD ⫽ 0.82; Whites, M ⫽ 2.97, SD ⫽ 0.96) as compared to the weak diversity cue website (Blacks, M ⫽ 2.26, SD ⫽ 1.09; Whites, M ⫽ 2.59, SD ⫽ 0.81). Figure 2 contains a plot of these relationships.
Study 2 Results Manipulation Check Similar to Study 1, we performed a manipulation check to ensure participants recognized the intended website diversity cue manipulations. We adapted a three-item measure from Avery et al. (2004). A sample item was “_____ does a good job of advertising their efforts to increase workplace diversity on their website.” Coefficient alpha for the scale was .84. ANOVA results, F(1, 115) ⫽ 30.25, p ⬍ .01, 2 ⫽ .21, supported our manipulation, as participants assigned to the strong diversity cue website rated these websites higher (M ⫽ 3.81, SD ⫽ 0.84) in terms of valuing diversity than did participants assigned to the weak diversity cue website (M ⫽ 2.89, SD ⫽ 0.94).
3 To ensure the questions were consistent across the websites in terms of difficulty, we initially developed eight questions for each website and conducted a pilot test. First, we asked 15 students to visit each of the websites. Then, for each website, they rated the eight multiple-choice questions designed to assess website recall using a scale ranging from 1 (the answer to this question would be very easy to remember two weeks after visiting the website) to 5 (the answer to this question would be very difficult to remember two weeks after visiting the website). We used these rating results to choose five questions to measure information recall for each recruitment website used in Study 2. We chose one easy question (mean rating ⫽ 1.0 –1.5), one hard question (mean rating ⫽ 4.0 – 4.5), and three medium difficulty questions (mean rating ⫽ 2.5–3.5). Example questions include the following, “Which of the following was used to describe the culture at _____?” “Which of the following was mentioned on _____’s website as a way that they are trying to balance employees’ work/life commitments?” and “As indicated on their recruitment website, _____ received which of the following awards?”
DIVERSITY CUES AND INFORMATION PROCESSING
Table 5 Summary of ANCOVA Results for Website Diversity Cues and Participant Information Processing (Study 2) Accuracy of website information recall F
2.08 0.47 3.97ⴱ 6.24ⴱ 2.81 0.94
.02 .00 .04 .06 .03 .01
Variable Covariates Age (years) Gendera Perceived organizational attributes Website entertainment Website informativeness Website organization Main effects Website diversity cueb Racec Interaction effects Website diversity cue ⫻ race Blacks
Weak website diversity cue Strong website diversity cue d
Note. N ⫽ 116. ANCOVA ⫽ analysis of covariance. 0 ⫽ male, 1 ⫽ female. b 0 ⫽ weak website diversity cue condition (few pictures of diverse organizational members and little information about diversity goals and initiatives), 1 ⫽ strong website diversity cue condition (portrayed diverse organizational members and included information about diversity goals and initiatives). c 0 ⫽ White, 1 ⫽ Black. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01. a
As in Study 1, we also performed a mediated-moderation analysis to examine the role of organizational attractiveness perceptions on the relationship between website diversity cues and information recall (see Table 6). Similar to our Study 1 findings, the indirect effect of website diversity cues was significant for Blacks (P ⫽ 0.15, p ⬍ .05) but not Whites (P ⫽ ⫺0.02, p ⬎ .10). The direct effects of website diversity cues were significant for Blacks (P ⫽ 0.92, p ⬍ .05) and for Whites (P ⫽ 0.40, p ⬍ .05). These results indicated organizational attractiveness perceptions partially mediated the relationship between website diversity cues for Blacks but not Whites.
Website Informaon Recall
5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 Weak Diversity Cues
Strong Diversity Cues
Recruitment Web Site
Figure 2. Plot of the interactive effects of Website Diversity Cues ⫻ Participant Race on accuracy of website information recall (Study 2).
General Discussion Previous researchers have investigated diversity cue effects in job advertisements on important outcomes such as job seeker attraction and intentions to pursue employment (e.g., Avery, 2003; Avery et al., 2004; Perkins, Thomas, & Taylor, 2000). We extend this research and consider the effects of website diversity cues on objective measures of job seekers’ information processing (cf. Dineen et al., 2007). Results of our two studies suggest that both Blacks and Whites are more likely to thoroughly process the information presented by familiar and unfamiliar organizations when diversity cues are included in recruitment materials. These findings have several important theoretical and practical implications. First, our findings refine existing diversity management and recruitment theory by clarifying the effects that diversity cues embedded on recruitment websites have on both Black and White job seekers. Consistent with our predictions drawn from the elaboration likelihood model and social identity theory, diversity cues were found to evoke positive affective reactions (i.e., enhanced organizational attractiveness perceptions) among Blacks, and these positive reactions increase Blacks’ motivation to further evaluate website content. However, our findings regarding the positive direct effect of website diversity cues on Whites’ information processing are not as intuitive. Whereas some have concluded that diversity cues are less salient for Whites (Mehra, Kilduff, & Brass, 1998; Perkins et al., 2000), our findings suggest that Whites recognize diversity cues, and these cues influence important cog-
WALKER, FEILD, BERNERTH, AND BECTON
Table 6 Simple Effects Analyses for Accuracy of Website Information Recall (Study 2) Stage
Total PYX ⫹ PYMPMX
DV: Accuracy of website information recall Blacks Whites Differences
0.44ⴱ ⫺0.07 0.51ⴱ
0.34ⴱ 0.24ⴱ 0.10
0.92ⴱ 0.40ⴱ 0.52
0.15ⴱ ⫺0.02 0.17ⴱ
1.07ⴱ 0.38ⴱ 0.69ⴱ
Note. N ⫽ 116. DV ⫽ dependent variable; PMX ⫽ website diversity cue 3 organizational attractiveness perceptions; PYM ⫽ organizational attractiveness perceptions 3 website information recall; PYX ⫽ website diversity cue 3 website information recall. ⴱ p ⬍ .05.
nitive processes such as website viewing time and accuracy of website information recall. It appears that Whites are also interested in potential employers’ diversity climates, but the positive relationship between diversity cues and information processing is not driven by positive affective reactions. Future research should explicitly examine the mechanisms responsible for enhanced information processing among Whites when diversity cues are included in recruitment materials. A second implication is associated with our inclusion of both unfamiliar (Study 1) and familiar (Study 2) organizations in this research. Previous recruitment researchers have noted that reliance on fictitious recruitment websites alone limits generalizability and ignores the likely influence of job seekers’ existing organizational attitudes (Dineen, Ash, & Noe, 2002; Dineen et al., 2007). Additionally, marketing scholars have posited that advertisement (recruitment website) effects are limited for familiar brands (Anand & Sternthal, 1990; Campbell & Keller, 2003). However, our findings suggest otherwise. That is, even familiar organizations can facilitate applicants’ processing of website information by incorporating diversity cues in recruitment materials. Third, encouraging more thorough recruitment website information processing through actions such as including pictures of diverse organizational members and providing information related to diversity goals and initiatives has important practical implications. Our results indicate that such websites are more likely to maintain applicant interest so that website viewers evaluate and retain more website information (Breaugh & Starke, 2000; Cable & Turban, 2001). This is particularly important considering the ease with which job seekers can quickly visit multiple recruitment websites, which likely makes it more difficult for them to differentiate among potential employers (Cober et al., 2004; Sumser, 2004). Additionally, encouragement of more thorough processing among Blacks and Whites may lead some job seekers to self-select out of the recruitment process based on other information they evaluate on the recruitment website. For example, increased motivation to process website information resulting from diversity cues may lead job seekers to discover that the organization does not offer the career advancement opportunities or benefits they expected. Researchers have begun to stress the importance of self-selection during recruitment (Dineen et al., 2002; Dineen & Noe, 2009) for a variety of reasons including the decreased legal liability associated with rejecting fewer job applicants (Dineen & Soltis, 2010) and reduced resources invested in reviewing job application materials.
Study Limitations and Future Research We note several potential limitations in our research and areas for future research. One limitation is associated with our operationalization of website diversity cues in Study 1 and Study 2. Study 1’s diversity cues included pictures of diverse organizational members, and Study 2’s diversity cues included diverse organizational members and information related to diversity goals and initiatives. Because different diversity information has the potential to influence reactions (Thomas & Wise, 1999), we call for a more explicit investigation into the salience of different diversity cues and their effects on job applicants’ information processing. For example, researchers might consider how other diversity cues, such as placing advertisements in targeted media or presenting inclusive policy statements (Avery & McKay, 2006), influence job seekers’ processing of recruitment website information. Another concern involves the relatively low information recall rates observed in Study 1 (M ⫽ 2.97, SD ⫽ 0.79) and Study 2 (M ⫽ 2.79, SD ⫽ 0.96). Although these rates are actually higher than those obtained by previous research investigating recruitment information processing (e.g., Dineen et al., 2007), we were surprised by these findings. However, the human communications literature provides a possible explanation, as nonlinear information sources (e.g., websites in which individuals can view information in multiple orders) often lead to decreased information recall as compared to linear information sources (e.g., traditional print advertisements in which order is predetermined; Eveland, Cortese, Park, & Dunwoody, 2004; Eveland, Marton, & Seo, 2004). This is not to say that learning does not occur in a Web environment. Rather, knowledge structure density (i.e., one’s ability to determine how information fits within the big picture) is enhanced when individuals are presented with nonlinear versus linear information sources (Eveland et al., 2004). Future research should further investigate different learning outcomes, such as knowledge structure density, in a recruitment context.
Conclusion Our research contributes to the existing recruitment literature by investigating the effects of website diversity cues on job seekers’ processing of website information. Including pictures of diverse organizational members and information related to diversity goals and initiatives on recruitment websites appears to encourage more attentive processing among Blacks and Whites. These are impor-
DIVERSITY CUES AND INFORMATION PROCESSING
tant recruitment outcomes that have been largely overlooked by researchers but are increasingly important, given the increased use of the Internet for recruitment purposes.
References Anand, P., & Sternthal, B. (1990). Ease of message processing as a moderator of repetition effects in advertising. Journal of Marketing Research, 27, 345–353. doi:10.2307/3172591 Ashforth, B. E., & Mael, F. (1989). Social identity and the organization. Academy of Management Review, 14, 20 –39. Avery, D. R. (2003). Reactions to diversity in recruitment advertising— Are differences Black and White? Journal of Applied Psychology, 88, 672– 679. doi:10.1037/0021-9010.88.4.672 Avery, D. R., Hernandez, M., & Hebl, M. R. (2004). Who’s watching the race? Racial salience in recruitment advertising. Journal of Applied Social Psychology, 34, 146 –161. doi:10.1111/j.1559-1816.2004 .tb02541.x Avery, D. R., & McKay, P. F. (2006). Target practice: An organizational impression management approach to attracting minority and female job applicants. Personnel Psychology, 59, 157–187. doi:10.1111/j.17446570.2006.00807.x Avery, D. R., McKay, P. F., & Wilson, D. C. (2008). What are the odds? How demographic similarity affects the prevalence of perceived employment discrimination. Journal of Applied Psychology, 93, 235–249. doi:10.1037/0021-9010.93.2.235 Breaugh, J. A., & Starke, M. (2000). Research on employee recruitment: So many studies, so many remaining questions. Journal of Management, 26, 405– 434. doi:10.1177/014920630002600303 Cable, D. M., & Graham, M. E. (2000). The determinants of job seekers’ reputation perceptions. Journal of Organizational Behavior, 21, 929 – 947. doi:10.1002/1099-1379(200012)21:8⬍929::AID-JOB63⬎3 .0.CO;2-O Cable, D. M., & Turban, D. B. (2001). Establishing the dimensions, sources and value of job seekers’ employer knowledge during recruitment. Research in Personnel and Human Resources Management, 20, 115–163. doi:10.1016/S0742-7301(01)20002-4 Campbell, M. C., & Keller, K. L. (2003). Brand familiarity and advertising repetition effects. Journal of Consumer Research, 30, 292–304. doi: 10.1086/376800 Chen, Q., & Wells, W. D. (1999). Attitude toward the site. Journal of Advertising Research, 39, 27–37. Cialdini, R. B., Petty, R. E., & Cacioppo, J. T. (1981). Attitude and attitude change. Annual Review of Psychology, 32, 357– 404. doi:10.1146/ annurev.ps.32.020181.002041 Cober, R. T., Brown, D. J., Keeping, L. M., & Levy, P. E. (2004). Recruitment on the net: How do organizational web site characteristics influence applicant attraction? Journal of Management, 30, 623– 646. doi:10.1016/j.jm.2004.03.001 Collins, C. J., & Stevens, C. K. (2002). The relationship between early recruitment-related activities and the application decisions of new labormarket entrants: A brand equity approach to recruitment. Journal of Applied Psychology, 87, 1121–1133. doi:10.1037/0021-9010.87.6.1121 Deitch, E. A., Barsky, A., Butz, R. M., Chan, S., Brief, A. P., & Bradley, J. C. (2003). Subtle yet significant: The existence and impact of everyday racial discrimination in the workplace. Human Relations, 56, 1299 – 1324. doi:10.1177/00187267035611002 Dineen, B. R., Ash, S. R., & Noe, R. A. (2002). A web of applicant attraction: Person– organization fit in the context of web-based recruitment. Journal of Applied Psychology, 87, 723–734. doi:10.1037/00219010.87.4.723 Dineen, B. R., Ling, J., Ash, S. R., & DelVecchio, D. (2007). Aesthetic properties and message customization: Navigating the dark side of web recruitment. Journal of Applied Psychology, 92, 356 –372. doi:10.1037/ 0021-9010.92.2.356
Dineen, B. R., & Noe, R. A. (2009). Effects of customization on application decisions and applicant pool characteristics in a web-based recruitment context. Journal of Applied Psychology, 94, 224 –234. doi: 10.1037/a0012832 Dineen, B. R., & Soltis, S. M. (2010). Recruitment: A review of research and emerging directions. In S. Zedeck (Ed.), APA handbook of I/O psychology: Volume 2. Selecting and developing members for the organization (pp. 43– 66). Washington, DC: American Psychological Association. Eagly, A. H., & Chaiken, S. (1998). Attitude structure and function. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (4th ed., Vol. 1, pp. 269 –322). New York, NY: McGrawHill. Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Methods, 12, 1–22. doi:10.1037/1082989X.12.1.1 Ethier, K. A., & Deaux, K. (1994). Negotiating social identity when contexts change: Maintaining identification in responding to threat. Journal of Personality and Social Psychology, 67, 243–251. doi: 10.1037/0022-35220.127.116.11 Eveland, W. P., Cortese, J., Park, H., & Dunwoody, S. (2004). How web site organization influences free recall, factual knowledge, and knowledge structure density. Human Communication Research, 30, 208 –233. doi:10.1111/j.1468-2958.2004.tb00731.x Eveland, W. P., Marton, K., & Seo, M. (2004). Moving beyond “just the facts”: The influence of online news on the content and structure of public affairs knowledge. Communication Research, 31, 82–108. doi: 10.1177/0093650203260203 Fullerton, H. N., & Toosi, M. (2001). Labor force projections to 2010: Steady growth and changing composition. Monthly Law Review, 21–38. Fulmer, I. S., Gerhart, B., & Scott, K. S. (2003). Are the 100 best better? An empirical investigation of the relationship between being a “great place to work” and firm performance. Personnel Psychology, 56, 965– 993. doi:10.1111/j.1744-6570.2003.tb00246.x Highhouse, S., & Hoffman, J. R. (2001). Organizational attraction and job choice. In C. L. Cooper & I. T. Robertson (Eds.), International review of industrial and organizational psychology (Vol. 16, pp. 37– 64). New York, NY: Wiley. Highhouse, S., Lievens, F., & Sinar, E. F. (2003). Measuring attraction to organizations. Educational and Psychological Measurement, 63, 986 – 1001. doi:10.1177/0013164403258403 Highhouse, S., Stierwalt, S. L., Bachiochi, P., Elder, A. E., & Fisher, G. (1999). Effects of advertised human resource management practices on attraction of African American applicants. Personnel Psychology, 52, 425– 442. doi:10.1111/j.1744-6570.1999.tb00167.x Hogg, M. A., & Terry, D. J. (2000). Social identity and self-categorization processes in organizational contexts. Academy of Management Review, 25, 121–140. Jackson, S. E., Joshi, A., & Erhardt, N. L. (2003). Recent research on team and organizational diversity: SWOT analysis and implications. Journal of Management, 29, 801– 830. Jones, D. A., Schultz, J. W., & Chapman, D. S. (2006). Recruiting through job advertisements: The effects of cognitive elaboration on decision making. International Journal of Selection and Assessment, 14, 167– 179. doi:10.1111/j.1468-2389.2006.00342.x Loughran, T., & Ritter, J. (1997). The operating performance of firms conducting seasoned equity offerings. Journal of Finance, 52, 1823– 1850. doi:10.2307/2329466 McKay, P. F., & Avery, D. R. (2006). What has race got to do with it? Unraveling the role of racioethnicity in job seekers’ reactions to site visits. Personnel Psychology, 59, 395– 429. doi:10.1111/j.17446570.2006.00079.x McKay, P. F., Avery, D. R., & Morris, M. A. (2009). A tale of two
WALKER, FEILD, BERNERTH, AND BECTON
climates: Diversity climate from subordinates’ and managers’ perspectives and their role in store unit sales performance. Personnel Psychology, 62, 767–791. doi:10.1111/j.1744-6570.2009.01157.x Mehra, A., Kilduff, M., & Brass, D. J. (1998). At the margins: A distinctiveness approach to the social identity and social networks of underrepresented groups. Academy of Management Journal, 41, 441– 452. doi:10.2307/257083 Perkins, L. A., Thomas, K. M., & Taylor, G. A. (2000). Advertising and recruitment: Marketing to minorities. Psychology and Marketing, 17, 235–255. doi:10.1002/(SICI)1520-6793(200003)17:3⬍235::AIDMAR3⬎3.0.CO;2-# Petty, R. E., & Cacioppo, J. T. (1981). Attitudes and persuasion: Classic and contemporary approaches. Dubuque, IA: Brown. Petty, R., & Cacioppo, J. (1986). The elaboration likelihood model of persuasion. In L. Berkowitz (Ed.), Advances in experimental social psychology (pp. 123–205). Orlando, FL: Academic Press. Petty, R. E., & Wegener, D. T. (1998). Attitude change: Multiple roles for persuasion variables. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (4th ed., Vol. 1, pp. 323–390). New York, NY: McGraw-Hill. Roberson, Q. M., Collins, C. J., & Oreg, S. (2005). The effects of recruitment message specificity on applicant attraction to organizations. Journal of Business and Psychology, 19, 319 –339. doi:10.1007/s10869-0042231-1 Saylor, E. S., & Aries, E. (1999). Ethnic identity and change in social context. Journal of Social Psychology, 139, 549 –566. doi:10.1080/ 00224549909598416 Slaughter, J. E., Zickar, M. J., Highhouse, S., & Mohr, D. C. (2004). Personality trait inferences about organizations: Development of a measure and assessment of construct validity. Journal of Applied Psychology, 89, 85–103. doi:10.1037/0021-9010.89.1.85 Stevens, C. K., & Beach, L. R. (1996). Job search and job selection. In L. R. Beach (Ed.), Decision making in the workplace: A unified perspective (pp. 33– 47). Hillsdale, NJ: Erlbaum.
Stine, R. (1989). An introduction to bootstrap methods. Sociological Methods & Research, 18, 243–291. doi:10.1177/0049124189018002003 Sumser, J. (2004, May 18). Consider the audience. Electronic Recruiting News. Retrieved from http://www.interbiznet.com/ern/archives/ 040518.html Tajfel, H., & Turner, J. C. (1986). The social identity theory of intergroup behavior. In S. Worchel & W. G. Austin (Eds.), Psychology of intergroup relations (pp. 7–24). Chicago, IL: NelsonHall. Thaler-Carter, R. E. (2001). Diversify your recruitment advertising. HR Magazine, 46, 92–100. Thomas, D. A. (2004). Diversity as strategy. Harvard Business Review, 82, 98 –108. Thomas, K. M., & Wise, P. G. (1999). Organizational attractiveness and individual differences: Are diverse applicants attracted to different factors? Journal of Business and Psychology, 13, 375–390. doi:10.1023/A: 1022978400698 Top companies: Most diverse. (2009, February 2). Fortune. Retrieved from http://money.cnn.com/magazines/fortune/bestcompanies/2009/minorities/ Walker, H. J., Feild, H. S., Giles, W. F., Armenakis, A. A., & Bernerth, J. B. (2009). Displaying employee testimonials on recruitment web sites: Effects of communication media, employee race, and job seeker race on organizational attraction and information credibility. Journal of Applied Psychology, 94, 1354 –1364. doi:10.1037/a0014964 Walker, H. J., Feild, H. S., Giles, W. F., & Bernerth, J. B. (2008). The interactive effects of job advertisement characteristics and applicant experience on reactions to recruitment messages. Journal of Occupational and Organizational Psychology, 81, 619 – 638. doi:10.1348/ 096317907X252487
Received May 6, 2010 Revision received August 23, 2011 Accepted August 31, 2011 䡲