10

CONNECTING CONCEPTS

Effects of Diversity of Interests and Interests’ Effects on Diversity

Ann Marie Ryan an Danielle D. King

MICHIGAN STATE UNIVERSITY

Diversity typically refers to differences and similarities among individuals in organizational contexts. While most often referencing demographic differences (race, ethnicity, gender, sexual orientation, religion, age, etc.), research on diversity in organizations has spanned a variety of individual attributes, including attitudes, knowledge, functions, skills and abilities. In this chapter, we consider the connection between interests and diversity.

We specifically focus on two ways the study of diversity and the study of interests intersect. First, we consider how “diversity of interests” in a work unit affects individual, group and organizational effectiveness. Workgroups that contain individuals with a variety of perspectives can produce more innovative solutions to problems (Bell, Villado, Lukasik, Belau & Briggs, 2011), although diversity can also decrease cohesion and increase conflict, negatively affecting team performance (Pelled, 1996; Thatcher & Patel, 2011). While researchers have addressed what conditions lead to more positive or negative effects of diversity, attention has not been specifically focused on diversity of vocational interests. We explore the questions: When there is greater heterogeneity or homogeneity in interests in a work unit, how, if at all, are relevant outcomes (e.g., attitudes, performance, withdrawal behaviors) affected? What moderates those effects? What can be done to foster positive outcomes when there is diversity in interests? While our primary focus on diversity of interests is at the work unit or interindividual level, we also briefly discuss how intraindividual diversity in interests (i.e., people who have more varied interest profiles) can affect these same outcomes.

Second, we consider how vocational interests themselves may influence the level of diversity in other characteristics in an organization. As a prime example, the lack of ethnic and gender diversity in certain occupational fields such as technology, physics, and elementary education has been widely noted (for a review of influences see Ceci, Williams, & Barnett, 2009; also, Iskander Gore, Furse, & Bergerson, 2013). Those seeking to diversify workforces in these fields often note the “pipeline problem” and the need to get underrepresented group members interested in these domains (Chen & Moons, 2015; Lubinski & Benbow, 1992). That is, vocational interests affect who is attracted to certain occupations (Le, Robbins, & Westrick, 2014) and given that there are demographic differences in some interests (Armstrong, Fouad, Rounds, & Hubert, 2010; Ryan, Tracey, & Rounds, 1996; Su, Rounds, & Armstrong, 2009), interests affect organizational demographic composition or diversity. While specific demographic differences in interest inventory responses are discussed in detail elsewhere in this volume, we consider how demographic correlates of interests may affect self-selection processes and thus influence the composition or diversity of an occupation, organization, or workgroup.

The first part of the chapter is devoted to a discussion of what little we know about the effects of the diversity of interests in workgroups, what research is needed, and practical implications. The second part focuses on how interests affect the demographic diversity of those in occupations and organizations, where that may be problematic, and the efficacy of efforts to change demographic composition.

Diversity of Interests

Diversity has most often been conceptualized and operationalized via a compositional approach, that is, the proportions of certain groups within a unit (Roberson, Ryan, & Ragins, 2017). However, Harrison and Klein (2007) proposed an influential typology of within-unit diversity that distinguishes between three forms of dispersion: separation, variety, and disparity. Separation refers to differences in values, beliefs, and attitudes, is associated with disagreement, and is most often operationalized as the average Euclidean distance of each member’s attribute from all other members. Variety can be thought of as differences in the knowledge, networks, and experiences, reflects the amounts and types of information available to a group, and is often operationalized by a categorical variable such as Blau’s index (1977). Disparity reflects differences in status or resources, is linked to power and influence, and is typically operationalized by coefficients of variation. How does this typology connect to interests? Typical thinking in discussions of diversity and interests resides around variety, and how differences in interests might lead to group members bringing something different to a task (van Knippenberg & Haslam, 2003). However, we should not neglect the fact that differences in interests may lead to differences in attitudes and beliefs or can be associated with status and resource differences. We draw on this related literature to speculate on how interest diversity in terms of variety, separation, and disparity might affect individual and organization outcomes in the sections that follow (see Figure 10.1 for an overview). Surprisingly, studies of interest diversity in organizational settings simply do not exist. There are a number of studies on potentially related variables—specifically on functional background (e.g., finance, sales) variety and educational background (i.e., major) variety, but not using measured interests. We draw on this related literature to infer likely effects of interest diversity.

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FIGURE 10.1 Relationship of Interest Diversity to Unit Level Outcomes.

Diversity in Interests as Variety

Work groups may be relatively homogeneous in interests (e.g., a team of accountants or microbiologists) or varied (e.g., a cross-functional task force). One might expect that variety in interests might be associated with differences in occupations, educational major, and/or specific knowledge, so research on diversity in these aspects is relevant to understanding potential effects of vocational interest variety. In a meta-analytic summary, Bell et al. (2011) found functional background variety to relate to group performance (ρ = .18) and in particular to creativity (ρ = .18); however, educational background variety related to creativity (ρ = .23) but not to team performance (ρ = .01). Thus, while knowledge variety can enhance decision-making (Huang, Hsieh, & He, 2014; Rietzschel, Nijstad, & Stroebe, 2007), this is not always the case. van Knippenberg and Schippers (2007), in their review of diversity research, concluded that the study of “main effects” of diversity on outcomes is not particularly useful, and that models should consider what moderators explain when positive effects occur. By extension then, we should not expect variety in interests to automatically lead to positive effects on creativity or performance.

In order to further research on how variety in interests affects functioning, one needs to consider whether that variety in interests leads to differences in experience and information, whether those differences are task relevant, and whether information sharing actually takes place. The Categorization-Elaboration Model (CEM; van Knippenberg, De Dreu, & Homan, 2004) holds that information elaboration is critical for experiencing the positive effects of diversity on group performance. Information elaboration refers to how information is exchanged and then expanded upon in a group where knowledge is initially distributed. The CEM suggests diversity can actually lead individuals to be less likely to share or to attend to information from others. Thus, while meta-analytic evidence hints that diversity in interests (as associated with functional and knowledge differences) should relate to greater effectiveness in problem-solving tasks, we need to understand under what conditions those differences lead to sharing of unique information versus discounting of others’ views (i.e., what moderates the diversity-information elaboration link). Possible moderators include the role of the leader in encouraging and fostering sharing as well as task interdependence levels that require sharing. The next two sections indicate that the extent to which interest variety is coupled with separation or disparity might also be a moderator.

Diversity in Interests as Separation

Differences in interests can be associated with different beliefs about a work-related issue. For example, individuals may possess a desire to gather data to investigate a problem (Investigative interests) versus a belief that creative brainstorming is the best way to a solution (Artistic interests); a willingness to embark on a new approach (Enterprising interests) versus a desire to stick with the tried and true (Conventional interests). Thus, interests can be linked to separation between members of a group. When examining how interest separation affects work group functioning, one could assess the Euclidean distance of one individual’s score on, say Investigative interests or data-people, from other group members.

How might separation in interests in a group affect outcomes? Research suggests that separation can be a source of conflict (Tsui, Ashford, St. Clair, & Xin, 1995); while task related conflict is often helpful in reaching a better solution, relationship conflict can have detrimental effects on group performance (O’Neill, McLarnon, Hoffart, Woodley, & Allen, 2015). As groups composed of members with homogeneous characteristics are likely to experience social cohesion and reduced interpersonal conflict (Pelled, 1996; Thatcher & Patel, 2011), interest similarity may produce such effects as well. Interest diversity that creates separation may have positive or negative effects depending on factors like task interdependence, conflict resolution processes, and how separation is managed by team leaders.

Diversity in Interests as Disparity

At first consideration, it may be hard to think of interests as associated with differences in status or resources. However, functions in organizations tend to contain people with different interests (HR, sales, manufacturing) and they can vary in status and power. One example would be the relative power and position of the sciences versus the humanities in most American universities (Hassan, 2010; Post, 2009). There may be many reasons for these power differences, but their link to interest diversity may have consequences for the effectiveness of a team/unit/organization. Groups with power differentials between members often do not have the best processes or perform the best (Berger, Fisek, Norman, & Zelditch, 1977; Berger, Rosenholtz, & Zelditch, 1980; Ragins, 1997). Also, Homan, van Knippenberg, van Kleef, and De Dreu (2007) note that “informationally diverse groups are often also diverse on other, more salient dimensions of diversity, such as gender, ethnicity, and age” (p. 79) and these are often linked to status and power. In terms of interests, any connections of interests to gender and ethnicity (reviewed in a subsequent section of this chapter) may prevent the positive effect of variety of information due to interest variety from emerging. For example, in a group with diverse interest profiles there can be unique information that individuals share, but there can also be categorization and stereotyping (“You are an artsy type so you will not attend to financial details”) that is linked to power in the group.

Research Needs

Figure 10.1 outlines the proposed effects of interest diversity on group-level outcomes as discussed above. The lack of studies on interest diversity effects in organizational contexts indicates a clear need for more research. It is important, though, that researchers proceed mindful of key issues in diversity conceptualization and operationalization if the work is to produce meaningful contributions. First, researchers must specify whether the questions of focus relate to diversity in interests as a source of variety, separation, or disparity and ensure that the appropriate operationalization of diversity be used (Harrison & Klein, 2007). Measurement concerns also apply to how interests are considered: researchers have noted that the links between interests and performance at the individual level require attending to congruence, profiles, and patterns, not just to mean score levels (Nye, Su, Rounds, & Drasgow, 2012). Attention to potential differences in conceptualization and operationalization of “interests” is just as important as conceptualization and operationalization of “diversity in interests” in pursuing research on interest diversity.

Second, researchers need to heed van Knippenberg and Schippers’s (2007) advice and focus on moderators rather than main effects of interest diversity and investigate when interest diversity has effects (i.e., what affects information elaboration, what affects social categorization based on interests). Third, researchers should measure proposed mediating mechanisms (e.g., information elaboration, voice) when possible in order to explicate why interest diversity may affect valued outcomes. One question to research is whether diversity in interests adds to prediction of outcomes above and beyond diversity in personality. Research on team personality composition shows the mean level of traits (e.g., conscientiousness, agreeableness) is positively associated with effectiveness (see Bell, 2007; LePine, Buckman, Crawford, & Methot, 2011 for reviews); however, that line of research does not suggest personality heterogeneity to be of benefit. It may be that homogeneity on high levels of some traits such as conscientiousness is critical, but heterogeneity on others (e.g., extraversion) can facilitate team performance in certain contexts (e.g., Kristof-Brown, Barrick, & Stevens, 2005). Whether the effects of interest diversity on performance are similar to those of personality diversity remains to be investigated.

Fourth, time may be an important consideration in understanding the effects of interest diversity. Specifically, Harrison, Price, and Bell (1998) found that the effects of deep-level diversity (differences in attitudes, beliefs, and values) become stronger the more frequently a group has interacted. This suggests that as groups interact more, any positive and any negative effects of interest diversity should magnify rather than decrease, as interests would be considered a deep rather than surface form of diversity.

Finally, levels of analysis should be given consideration in building theory on interest diversity. Work is needed that considers individual-level effects (e.g., how an individual’s interest profile affects their performance), team-level effects (e.g., how and when the variety in interests in a team affect team performance), dyadic effects (e.g., how similarity in interests with one’s supervisor might affect performance), broader context effects (e.g., how the type of organization might affect these outcomes), and the many potential cross-level effects (e.g., how being on a team with high interest variety might affect individual performance).

As a specific example of thinking at different levels noted earlier, “diversity of interests” can refer to the fact that some individuals have a more varied interest profile than others (also referred to as differentiation, Holland, Fritzsche, & Powell, 1994). How might this type of intraindividual diversity relate to work-group functioning? While empirical research to address this question is lacking, we would expect that such individuals may be able to contribute more information and more social resources to a team. That is, their diversity of interests may allow them to take on multiple roles and functions in a work group. However, this would depend upon not just their interests but their abilities, as well as the relevance of those interests to the tasks at hand.

Practical Implications

There is ample advice out there on how to “manage diversity,” which focuses on how to obtain the benefits of diverse perspectives while mitigating any negative effects (Stevens, Plaut, & Sanchez-Burks, 2008; van Knippenberg, Dawson, West, & Horman, 2011; Yang & Konrad, 2011). Beyond that advice, is there anything specific related to managing a diversity of interests?

First, we would advocate the importance of setting up processes within units to ensure that appropriate information exchange and elaboration is occurring. That is, individuals may tune out information from others that they find “uninteresting” and therefore miss out on the relevance of the information for task accomplishment. For example, an individual with strong conventional interests may be thinking through procedures and responsibilities while an individual with strong social interests may be focused on finding out more about who will be involved, and in doing so neither attends sufficiently to important information. Further, leadership can play an important role in facilitating information exchange and integration. Rico, Sanchez-Manzanares, Antino, and Lau (2012) demonstrated that the negative effects of educational specialization differences on group decision-making performance can be alleviated by cross-cutting roles and superordinate goals. Leaders can facilitate processes by which group members build on each other’s ideas through discussion as well (Ellis, Mai, & Christian, 2013).

Second, when a diversity of interests is associated with separation on a particular issue (e.g., valuing feelings over rules), it is important to understand the separation and to ensure it does not devolve into a faultline in the group. Lau and Murnighan (1998) advanced a theory of faultlines, where attributes divide a group into smaller subgroups that individuals identify with more strongly. Faultlines can negatively impact group functioning (Thatcher & Patel, 2011) if their strength is not reduced. In the case of interests, individuals may form alliances with like-profiled others in the group. Chiu and Staples (2013) suggest one can reduce faultlines by having members that cut across subgroups (e.g., the scientist who also loves art). Faultline reduction can be facilitated by creating mechanisms for greater information elaboration and for individual disclosure of individuating information. Researchers have noted the value of perspective-taking (Hoever, van Knippenberg, van Ginkeyl, & Barkema, 2012) to ensure that members can appreciate others’ views and why a particular focus might be appealing to someone with interests different from one’s own.

Interests as an Influence on Unit Diversity

The second part of this chapter focuses on how interests affect demographic diversity in a unit. Despite advancements, the world of work remains somewhat demographically segregated (Blau, Brummund, & Liu, 2013). Given that individuals seek interest congruence by pursuing and remaining in environments that match their vocational interests (Dawis & Lofquist, 1978; Holland, 1959; Lent, Brown, & Hackett, 1994), investigating the relations between demographic characteristics and vocational interests provides insight into the processes that can limit unit diversity on demographic and other characteristics.

One of the most well-known findings in measurement of vocational interests is the gender difference in interests in people versus things (Su et al., 2009), as most males exhibit a greater preference for working with things, gadgets, and inorganic material; while females often prefer working with people and organic content. The subsequent differential representation in vocational options that match those interests also has been well-documented. For example, in the United States, more women work in service-type careers such as health care and teaching, whereas more men work in managerial or physically oriented jobs (Hegewisch & Matite, 2013). There are also significant gender gaps between male and female entries into the STEM fields, despite recent research suggesting that both genders are academically comparable in ability and achievement (Lindberg, Hyde, Peterson, & Linn, 2010). Indeed, in a meta-analysis Su and Rounds (2015) found that gender differences in interests of those in STEM fields ranged from d = .083 to 1.21 in engineering (favoring males) to d = -.40 in medical services (favoring females) and concluded that intervening to change interest levels may be key to attracting and retaining women in some STEM occupations. Research on gender development reveals that sex differences in interests are some of the earliest to emerge (Ruble, Martin, & Berenbaum, 2006) and Gottfredson (1981) asserts that, by 6 to 8 years of age, children begin to narrow their aspirations based on attitudes about gender-appropriate occupations. Weisgram, Bigler, and Liben (2010) showed that, when asked about interest in novel jobs, children, adolescents, and adults all were affected by the depicted sex of job holders, suggesting the effects of demographic composition on interests.

The link between ethnicity and interests has received support as well. Gottfredson (1978) demonstrated that a narrower range of occupations are considered among ethnic-racial minorities as compared to majority members. In addition, Tracey and Hopkins’s (2001) research has shown that the specific occupations considered differ across ethnic groups. African Americans tend to have greater interest and subsequent representation in people-oriented social occupations as compared to others, Native Americans manifest the highest interest on the ideas pole of Holland’s (1997) data-ideas dimension, Mexican Americans demonstrate more interests in careers characterized by the data pole, and Asian Americans tend to have higher interests and representation in investigative areas such as science and technology. Further, Tracey and Hopkins (2001) showed that ethnicity moderated the relationship between interests and occupational choice, as some groups place greater weight on interest fit in making career choices than others. Finally, research indicates that occupational segregation (in both actual jobs and as depicted in novel jobs) affects children’s evaluations of job status and interest (Bigler, Averhart, & Liben, 2003).

These demographic differences in interests (which we will discuss in more detail later) can then lead to greater homogeneity and less demographic diversity in work units, although it is important to note that they are not the sole or even necessarily the primary contributor to occupational segregation and organizational demographic homogeneity. That is, sociocultural processes do fuel occupational segregation (Lee, Lawson, & McHale, 2015) and discrimination and perceptions of barriers affect the decision-making processes related to occupational choice (Chartrand & Rose, 1996; Hackett & Byars, 1996). Constrained opportunities—real or perceived—can limit individuals’ feelings of accomplishment and drive for atypical career options, thus reducing the number of skilled job applicants for an occupation and contributing to the demographic gaps in representation (Hegewisch, Liepmann, Hayes, & Hartmann, 2010). Segregation has also been linked to differential status and power in the larger society, as masculine-typed occupations typically have higher salaries than feminine-typed occupations and are imbued with greater prestige (McCall, 2001; Lee et al., 2015). Thus, while we recognize that discrimination and other sociological and economic factors contribute to lessened occupational demographic diversity, we focus here specifically on how interests may contribute to the lack of demographic diversity through 1) attraction-selection-attrition (ASA) processes and 2) potential adverse impact of interest inventories as selection tools.

ASA and Diversity

Interests have been a major variable representing the “person” side in research applying the person-environment (PE) fit model (cf. Tinsley, 2000). This work is grounded in theories such as ASA theory (Schneider, 1987; Schneider, Smith, & Goldstein, 2000), which focuses on the interaction of personal attributes with environmental attributes in the prediction of perception of fit and subsequent attitudes and behaviors. How might each stage of the ASA process in terms of interests affect the diversity of an organization’s membership?

First, as discussed earlier, demographic differences in interests may lead to proportionally more or less individuals self-selecting into and out of applying to certain occupations. Holland (1973, 1997) suggested that employees search for environments in which there is good fit between their own characteristics and the characteristics of their environment and where similar others (e.g. those with similar interests) can be found. The work of Schneider and colleagues (Schneider, 1987; Schneider et al., 2000) asserts that incumbents are those who were attracted to jobs and organizations that they believe will support their interests. There is empirical support for these ideas. Lent and colleagues (1994) conducted a meta-analysis examining interest’s relationship with career choices and found that interests were significantly related to career choice (ρ = .60). Tracey and Hopkins (2001) also examined this relationship and determined that 27% of the variance in occupational choice was due to interests, and that interests were greater predictors of occupational choice than self-assessed ability. Thus, interests affect attraction and to the extent that interests display demographic differences, applicant pools will differ demographically for different occupations, affecting organizational diversity.

Second, selection processes may directly (through use of interest inventories) or indirectly (through use of educational credentials, biodata related to experiences and interests, fit assessments) screen out those lacking certain interests. For example, Ryan and Johnson (1942) presented one of the earliest examples of using interest inventory scores in the selection of sales and service employees. Van Iddekinge, Putka, and Campbell’s (2011) validation efforts indicated that interests predicted a wide set of criteria including job knowledge and performance; Nye et al.’s (2012) meta-analysis also showed links from interest to outcomes. Thus, employers may find using interest inventories in selection a useful means of hiring employees that perform most effectively. However, as we will discuss in the next section, to the extent interests are linked to demographics, organizations may reduce diversity through selection on interests.

Third, attrition based on interests can affect organizational demographic diversity, as links between interests and continuance have been established (Van Iddekinge et al., 2011). One theoretical framework that presents a relationship between interests and employee retention is the social cognitive career theory (SCCT; Lent et al., 1994; Lent, Brown, & Hackett, 2000). This theory, drawn from the counseling psychology literature, focuses on the development of interests and their influence on intentions to pursue related activities over time. Empirically, Bolanovich (1948) found a correlation of .43 between interest scores and turnover in a sample of factory workers. Additional studies of U.S. forest service employee and police trainees and officers have also demonstrated significant correlations between interest inventory scores and turnover (Johnson & Hogan, 1981; Mayeske, 1964). Overall, individuals whose interest profiles are not congruent with characteristics of the environment will likely leave the environment (Schneider, 1987). Accordingly, interest profiles of those who stay in an environment come to represent the interest profile of the environment, thus fostering the expected outcome of the ASA process, homogeneity in interests. To the extent that interests relate to demographics, this also leads to demographic homogeneity.

In a straightforward relationship, those with interests that align less well with an occupation will tend to leave the occupation and those with aligned interests would stay. However, there is also a suggestion in the literature that the relationship of interests and attrition in segregated occupations is more complex. Interests that are seen as atypical for a group may relate to less perseverance and commitment to a career, such as when women drop out of sciences because they face or fear negative reactions for pursuing gender-atypical careers (Ceci et al., 2009; Heilman, Wallen, Fuchs, & Tamkins, 2004). That is, the interest-attrition relationship may be of a different form for those in a minority in an occupational setting.

Adverse Impact of Interest Inventories

One concern in selection processes in many countries is whether the use of certain procedures results in proportionally lower hiring rates for certain groups; that is, does the selection procedure have adverse impact? Interest inventories are seldom used in selection contexts, although recent evidence of their potential value in predicting performance may change that (Nye et al., 2012; Van Iddenkinge et al., 2011). Thus, it is important to consider whether interest inventories are likely to lead to adverse impact in hiring and, in particular, how the ways in which they are used might affect that.

As noted earlier, gender differences have been found to exist in interest inventory scores, with men showing greater scores on Realistic interests, and women scoring higher on artistic, conventional, and social scales (Fouad, 2002; Su et al., 2009). However, as Nye et al. (2012) note, using scale scores as direct predictors may not be the most effective way of selecting employees, and organizations may want to consider profiles as more meaningful. Armstrong et al. (2010) showed gender differences in the shape of profiles using Q correlations and Euclidean distance indices, so alternative methods of scoring interest inventories may still lead to adverse impact. Research is most definitely needed on this issue.

Further, since some interest inventories have separate norms for males and females, their use in selection settings can come under legal scrutiny in the United States. That is, the Civil Rights Act of 1991 prohibits the use of within-group norming in hiring contexts (Sackett & Wilk, 1994), which would disallow separate norming for males and females. While cautions and advice exist for using this information appropriately in career counseling contexts (e.g., Foud & Spreda, 1995), the ban on such use in selection contexts requires that organizations evaluate the interests of men and women on the same norms.

In general, there is inconsistent evidence of differences in interests across major ethnic and racial groups in the United States with some suggesting minimal differences (Fouad & Mohler, 2004), and others concluding that African Americans score higher on social, enterprising, and conventional interests than Whites (Tracey & Robbins, 2005). More recent meta-analytic work (Jones, Newman, Su, & Rounds, under review) suggests group differences in that Whites have greater realistic, investigative, and artistic interests, and African Americans have greater social interests. However, it is important to note that adverse impact is only in part determined by effect sizes of differences on an assessment tool, and is strongly affected by overall selection ratios (numbers hired out of numbers applying) as well as by applicant pool characteristics (Murphy, Osteen, & Myors, 1995). Thus, the effects of gender and ethnic group differences in interests on actual hiring rates and levels of adverse impact will likely vary across settings.

Further, one can look at how interests may indirectly relate to adverse impact through their correlations with cognitive ability, which exhibits large group differences (Cottrell, Newman, & Roisman, 2015). That is, in a meta-analysis, Jones et al. (under review) found cognitive ability correlates with investigative, artistic, and social interests, as well as to a small extent with enterprising interests. As Jones et al. demonstrated, considering mean group differences in interests as well as the correlation of cognitive ability with interests, one might have different expectations as to the level of expected adverse impact in different jobs. For example, in their study, they showed smaller Black-White differences on cognitive ability tests in investigative jobs because group differences in interests lead to greater portions of Whites applying as well as higher ability individuals applying (the A in ASA); however, Black-White subgroup differences were higher for social jobs because of greater attraction in terms of interests of African Americans as well as a greater range on cognitive ability in the applicant pool. The striking point made by Jones et al. is that indirect range restriction on interests affects observed adverse impact on cognitive ability predictors. Hence, interests affect demographic diversity in attraction directly, but also affect demographic differences in selection indirectly through their relation to cognitive ability test scores as well as to self-selection into hiring pools.

Research Needs

The research available on PE-fit and vocational interests is voluminous, so it may seem that we know all we need to know about interests, ASA, and diversity. However, there are some important unexplored questions. First, almost all of the work on ASA processes in organizations focuses on personality homogeneity, not interest homogeneity. Work on interest homogeneity has typically focused on the occupational level of analysis. Considering how interest homogeneity processes operate in occupations, but also in conjunction with potential effects in organizations and industries is important (i.e., a consideration of effects of multilevel ASA processes). For example, we might easily assume that there will be less diversity in interests among computer programmers (i.e., high in investigative and conventional interests) than across all jobs, and we can speculate a further extension to homogeneity in interest profiles when comparing computer programmers in a tech company to those in a retail or finance organization. Research on whether, how, and when interests affect homogeneity at levels other than the occupation may help us to understand potentially compounding effects on demographic diversity.

Another research area relates to faultlines in groups. In cases where interests and demographics are related, subgroups may emerge in groups where a “surface-level” characteristic (gender, ethnicity) may be strongly linked to a “deep-level” characteristic (interests). As we noted earlier, Harrison et al. (1998) found the effects of deep-level characteristics to become stronger over time and those of surface-level characteristics to lessen; in the case where surface and deep characteristics are linked, a stronger faultline may emerge that is harder to eradicate.

We see the research agenda on adverse impact and interest inventories as building on the work of Jones et al. (under review) regarding how interests can lead to indirect range restriction on other predictors, hence affecting pool demographic composition, as well as the work by Nye et al. (2012) suggesting greater direct use of interest inventories in selection. With regard to the latter, investigations are needed as to how to evaluate adverse impact when profiles and configural scoring are used as opposed to simply considering mean differences on interest scales. Further, how combinations of interest inventories with other selection assessments (DeCorte, Lievens, & Sackett, 2008; DeCorte, Sackett, & Lievens, 2010), as well as the order of assessments, might affect levels of adverse impact observed (DeCorte, Lievens, & Sackett, 2006; Finch, Edwards, & Wallace, 2009) will be important to investigate.

Practical Implications

As vocational interest fit has been shown to predict satisfaction with work (Dawis, 1991; Rounds & Tracey, 1990) and career stability (Holland, 1996), organizations composed of talented individuals pursuing environments that best match their interests will result in a satisfied and committed workforce (Robertson & Cooper, 2010). However, if greater homogeneity in interests does have negative effects on demographic diversity, organizations will need to consider how to counteract that influence while gaining the benefits of fit. Note that these effects on demographic diversity are not the result of a direct process of attracting, selection, or retaining only those of certain demographic groups, and are likely occurring despite strong efforts by organizations to recruit, select, and retain a diverse workforce. Organizational efforts to address ASA cycles based on legitimate job-fit criteria that happen to be demographically correlated can be resource-consuming and challenging to implement, but may be necessary. That is, for those interests where demographic differences do exist, there may be a need for targeted recruitment of women and minority group members to increase quality applicants in the initial pool (see Newman & Lyon, 2009, for analysis of how targeted recruiting can reduce adverse impact). Examples of this are currently happening in tech fields, where large employers of computer scientists make extra efforts to reach out to underrepresented individuals who have degrees in those fields through targeted recruitment and to retain such individuals through inclusion practices such as employee networks (e.g., Evans, 2012; Rice & Alfred, 2014).

Another practical implication would be the already popular notion of changing diversity of those in the field by changing interests (e.g., get girls interested in coding and engineering at an early age). While many of these interventions are relatively new efforts, their evaluation is important, particularly since—as we have already acknowledged—the reasons for lack of diversity in certain occupations may be multiple (e.g., discrimination and other barriers) and are not just based on interests. Interventions to develop interests may also need to be coupled with interventions to address other obstacles; for example, Woodcock, Hernandez, and Schultz (2015) demonstrated that a program for retaining underrepresented minorities in science was effective because of affecting students’ responses to stereotype threats, not just enhancing their academic knowledge and interest in science.

While there may appear to be other practical implications easily drawn from this chapter, we would urge caution in plunging ahead to implement those related to employee selection. For example, one might conclude that there is a need to eliminate group differences on interest inventories by designing tools organizations can use in selection that do not show gender differences. While doing so might be quite feasible, it can occur at the cost of the construct validity of the measures and coverage of the content range of interests. As has been widely acknowledged by organizational psychologists, one does not wish to make tradeoffs between validity and diversity in selection contexts but may end up doing so (Ployhart & Holtz, 2008); considering ways to use interest inventories effectively in hiring processes while minimizing any potential adverse impact is important.

Summary and Conclusions

In this chapter, we have connected vocational interests and diversity in organizations in two distinct ways: through examining how diversity in interests affects team and organizational outcomes and through examining how interests affect the demographic diversity of workforces. In both cases, there is surprisingly limited research on which to draw conclusions, suggesting that making these connections is a worthwhile direction for enhancing our understanding of the importance of vocational interests in the workplace.

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