How Important Is Word of Mouth to College Students When Considering Jobs? A Policy-Capturing Study of Organizational Attraction

Abstract

This research examines the effect of reputational word of mouth (WoM) from trusted sources on naive job applicants’ organizational attraction toward a possible employer. We used a policy-capturing experiment to identify the weight placed on WoM relative to other types of hypothetical information that college students with limited work experience might have about a job. Our within-person results show that WoM affects attraction over and above other types of company-dependent information about pay, benefits, and learning opportunities, which underscores the importance of WoM to inexperienced job seekers. Further, our between-person results demonstrate that the weight placed on WoM depends on individual differences in career decision self-efficacy (CDSE). Specifically, people with higher CDSE placed a greater weight on WoM than people with lower CDSE. These findings are important to career counselors who work with college students to understand how they appraise and make decisions about jobs to pursue. Further, these findings have value to organizations by underscoring the importance of reputational information to entry-level job seekers.

Keywords

organizational recruiting advice seeking career decision-making career decision self-efficacy career counseling recruitment source

People can learn about jobs and organizations through many different sources of information. Some are company-dependent sources that organizations control, such as professional advertising campaigns, which typically convey a polished—and usually entirely positive—message to applicants about the organization’s qualities (Van Hoye & Lievens, 2009). However, informal, company-independent sources also exert a strong effect on applicants’ beliefs, values, and perceptions about an organization (Banks, Kepes, Johsi, & Seers, 2016; Cable & Turban, 2001). One of the most important types of company-independent information is word of mouth (WoM), which is the informal provision of information about a job or organization that occurs between two or more people. WoM can be influential beyond company-dependent sources because it can provide a positive or negative message to an applicant that oftentimes feels more trustworthy (Van Hoye, 2014).

Much research has documented that WoM has a strong impact on applicants’ organizational attraction, but this research generally considers the effect of WoM in a vacuum. In reality, applicants may learn a great deal of concurrent information about a job through multiple sources, and it is unclear to what extent WoM matters in this broader informational context. In the present research, we adopt an experimental design called policy capturing (Aiman-Smith, Scullen, & Barr, 2002) to examine the relative weight that college students place on WoM information from trusted sources. Policy capturing is a within-person approach that systemically manipulates the variables of interest in a full factorial design, which allowed us to determine how attraction to an employer changes as a function of manipulating information about a prospective job. Specifically, we provide a strong test of the importance of WoM by examining how it is weighted relative to information about pay, benefits, and learning opportunities in the organization, which are among the most important company-dependent job attributes that shape applicant attraction (e.g., Casper & Buffardi, 2004; Chapman & Webster, 2006). Policy capturing is useful for identifying these weights and examining whether or not they vary across individuals, making it an ideal method to study how people make important decisions including vocational choices (Dahling & Thompson, 2010).

Further, the effects of WoM likely depend heavily on individual difference moderators that are understudied. We begin to address this problem in our research by drawing on social cognitive theory (Bandura, 1986) to study the moderating effect of career decision self-efficacy (CDSE; Taylor & Betz, 1983). We expect that CDSE should moderate the effect of WoM on organizational attraction, with WoM information having a stronger influence among job seekers who have lower self-efficacy for making career decisions. We developed this expectation because individuals with low CDSE lack confidence in their own ability to make career decisions, and consequently, they may place a heavier weight on WoM from a trusted source who can provide more authoritative guidance.

Our research consequently makes several important contributions to the literatures on career decision-making and organizational recruitment. First, we shed light on the career decision-making processes of college students, who are likely to need and want WoM information to help them make decisions in the absence of much personal experience. This is an understudied population in the WoM literature. Second, we use a rigorous experimental design to evaluate how much positive and negative WoM matter relative to other information known about a job, which is an important advancement to the literature on WoM (Van Hoye, 2014). By examining WoM in conjunction with other pieces of job information, we address an important weakness in the WoM literature, which typically examines the effects of WoM provided in what is otherwise an information vacuum. Third, we evaluate whether or not individual differences in CDSE shape the importance that people place on WoM when rating organizational attractiveness, which further demonstrates the utility of social cognitive theory (SCT) for understanding how people make career decisions. Overall, our findings have important implications for theory and career counseling practice with college student populations.

WoM in Organizational Recruitment

WoM plays a critical role in the recruitment literature because this kind of information is abundant and easily accessed by job seekers (Van Hoye, 2014). Virtually anyone can be a source of job-related WoM, including friends, family, acquaintances, or strangers. Further, people can share WoM through a variety of different media, such as face-to-face communication or through online discussions. While WoM is oftentimes solicited by recipients who want to learn about a job or organization, sources of WoM can also freely volunteer unsolicited information that also influences job seekers’ decisions. Thus, WoM is ubiquitous in the job seeking environment, and much research has examined how people acquire and use this information.

The WoM literature invokes several key theories to explain the importance of this information to job seekers (Van Hoye, 2014; Van Hoye & Lievens, 2009). First, from the organizational standpoint, the effects of WoM can be understood in terms of signaling theory (Connelly, Certo, Ireland, & Reutzel, 2011; Spence, 2002). Signaling theory hinges on the existence of information asymmetry between two parties, such as a job seeker and an organizational representative. The job seeker knows far less information about the organization than the representative knows about the organization (Connelly et al., 2011), and the job seeker could certainly make better decisions with access to more of this relevant information. However, organizational representatives are usually motivated to selectively disclose company-dependent, formal information by providing signals of positive attributes and suppressing signals of negative attributes. Job seekers may consequently lack access to important information that might otherwise dissuade them from pursuing a low-quality job or employer.

The core contention of the WoM literature is that the organization and its formal representatives are not the only entities that can provide useful signals about the organization to its job seekers (Van Hoye, 2014). Other people may be able to provide company-independent signals, such as WoM, to job seekers because they have experience with the organization or access to information about the organization that would otherwise be withheld (Cable & Turban, 2001). These other sources of company-independent information can include current or former employees who share candid reactions and members of the public who are knowledgeable about the company (e.g., through media coverage or familiarity with its products or services). Thus, signaling theory highlights that many sources in the job seeker’s environment can provide signals about prospective employers through WoM that reduce information asymmetry and help the job seeker make an informed decision.

WoM researchers invoke different theories when they focus on how job seekers evaluate and use received WoM signals. For example, the accessibility-diagnosticity model (Feldman & Lynch, 1988) explains that WoM exerts a strong influence on decisions relative to other signals because it is a type of information that is both highly accessible and diagnostic. That is, WoM is theorized to be highly accessible in memory because it is distinctive, vivid, and personal in nature. Further, WoM information is highly diagnostic, particularly when it has a negative valence (Herr, Kardes, & Kim, 1991), because it helps job seekers evaluate and decide among job options. In conjunction, the accessible and diagnostic qualities of WoM encourage job seekers to easily retrieve and heavily rely upon WoM information when judging potential jobs.

A third theoretical perspective, the source credibility framework (Sternthal, Phillips, & Dholakia, 1978), helps explain when job seekers might discard WoM signals. Because WoM can come from anyone, its impact on job seekers’ decision-making processes depends heavily on how credible the source of the WoM is perceived to be. People make judgments about a source’s credibility based on three factors: truthfulness, trustworthiness, and believability (Allen, Van Scotter, & Ottondo, 2004). On average, job seekers are distrustful of information sources that do not strike them as credible. For example, in a recent policy-capturing study of different types of WoM, Van Hoye, Weijters, Lievens, and Stockman (2016) manipulated incentives for WoM, source expertise, source gender, relationship strength, and message content. In support of the source credibility framework, the results indicated that participants were less attracted to organizations when they knew that WoM had been provided by someone who had a financial incentive to solicit company referrals. Conversely, participants were more attracted when WoM was provided by someone with greater expertise and someone who was a closer friend (see also Van Hoye & Lievens, 2007, 2009). Other research has documented that people typically judge direct, personal information as more credible than indirect, impersonal information (e.g., online WoM; Allen et al., 2004). In aggregate, these findings underscore that only credible WoM is likely to influence job seekers’ career decisions.

Taken together, these theoretical frameworks suggest that WoM should have a particularly important influence on naive job seekers with extensive information asymmetries, like traditional college students, when compared to experienced job seekers. For example, research indicates that naive job seekers are highly emotional when searching for employment; they perceive a lack of control over the situation, which leads to stress, anxiety, panic, and frustration (Bonaccio, Gauvin, & Reeve, 2014). Further, because naive job seekers simply lack the knowledge required to make sound career decisions, they are strongly motivated to look for assistance from others (Bonaccio et al., 2014). A similar pattern of findings is evident in an older study by Dayton (1981), who found that previously employed job seekers over the age of 30 relied heavily on their resume to help them obtain a job, while naive job seekers sought out support from others, especially parents or teachers. Together, these results suggest that naive job seekers may be especially desirous of WoM signals, and they should find WoM to be particularly accessible and diagnostic information. Further, they may lack the experience to be good judges of source credibility, and consequently, they may be overly generous when appraising WoM as useful information. However, naive job seekers are understudied in WoM research, which typically focuses on populations with greater knowledge of the world of work, like people with full-time working experience (e.g., Van Hoye, 2013) or competitive graduate students (e.g., Jaidi, Van Hooft, & Arends, 2011).

Moreover, the effects of WoM on job seekers’ attitudes, organizational attraction, and job search decisions are typically modeled in isolation. The literature lacks strong designs that explicitly compare the effects of WoM to those of company-dependent information signals. As a consequence, while we know that WoM is important to job seekers, we do not know its relative importance compared to other attractive attributes of jobs that organizations typically share with job seekers.

CDSE as a Moderator

The weight that individuals place on WoM information is likely dependent on individual differences, particularly CDSE. The importance of CDSE to job seeking is explained by SCT (Bandura, 1986, 1989), which emphasizes that self-efficacy beliefs are essential to exercising human agency. An important tenet of SCT is that self-efficacy and the attainments that spring from it are domain-specific (Bandura, 1989). That is, self-efficacy is not a global trait but rather an evaluation of one’s capabilities in a specific performance domain; when people feel high self-efficacy in a given performance domain, they tend to expect positive outcomes to occur and set concordant goals to persist and achieve in that domain (Bandura, 1989).

Given our focus on making judgments of employers in a career decision context, CDSE is the specific self-efficacy most necessary to exercising agency. CDSE concerns beliefs about one’s capability to perform tasks related to the career decision-making process (Betz, Klein, & Taylor, 1996; Bullock-Yowell, Andrews, & Buzzetta, 2011; Taylor & Betz, 1983). People with high CDSE have high confidence in their ability to perform tasks and make decisions about careers. Conversely, individuals with low CDSE have low confidence and report a greater dependency on external help to offer insight into career choices (Bullock-Yowell et al., 2011; Luzzo, 1993). Consistent with this pattern of findings, we submit that the effect of WoM on organizational attraction should be weaker for people with high CDSE because they have the agency to make their own decisions without the input of others. Conversely, the effect of WoM on organizational attraction should be stronger for people with low CDSE, who lack confidence and are likely to seize on the assistance of others.

The Present Research

Policy-capturing designs present each participant with all levels and combinations of the independent variables. Consequently, the data are multilevel in nature, with a within-person component and a between-person component (Raudenbush & Bryk, 2002). In this study, the independent variables (i.e., WoM, pay, benefits, and learning opportunities) and dependent variable (i.e., organizational attraction) are all within-person measures, whereas CDSE and demographic variables are between-person measures. We refer to the within-person level of the analysis as Level 1, and the between-person level of analysis as Level 2, in the results that follow. Figure 1 summarizes our hypothesized effects at both levels of analysis.

Figure 1.
Hypothesized multilevel model of organizational attraction.

Our first hypothesis concerns effects at Level 1. Consistent with the accessibility-diagnosticity framework, we hypothesize that favorable WoM will have a positive effect on organizational attraction over and above company-dependent information about salary, benefits, and learning opportunities. We selected these specific pieces of company-dependent information for comparison because these attributes are strong drivers of attraction identified in past research (Casper & Buffardi, 2004; Chapman & Webster, 2006; Skule, 2004; Williams & Dreher, 1992). We operationalized pay, benefits, and learning opportunities as company-dependent pieces of information because these job attributes are usually signaled through formal organizational mechanisms (e.g., job descriptions, advertisements, or recruiter conversations). We operationalized WoM as a company-independent, positive or negative judgment about the organization from a trusted source, consistent with the source credibility framework. Further, we operationalized WoM in a traditional, conversational manner rather than information shared through mechanisms like social media, given evidence that traditional WoM is still extremely common and more influential to job seekers’ attitudes than social media WoM (Ahamad, 2019).
Hypothesis 1: WoM is positively related to applicant attraction, over and above the anticipated effects of company-dependent information concerning pay, benefits, and learning opportunities (Level 1).

However, the effect of WoM on organizational attraction should depend on individual differences in CDSE. As SCT explains, people who lack confidence in a domain are unlikely to strongly commit to choices in that domain. Consequently, reputational information shared via WoM should be seen as especially important for individuals with low CDSE; we expect that these students will place a heavier weight on WoM information because it reassures them that expressing favorable intentions toward the organization is a good choice.
Hypothesis 2: CDSE (Level 2) will exhibit a cross-level moderating effect on the relationship between WoM and attraction (Level 1). Specifically, the positive effect of WoM will be stronger for people with low CDSE than for people with high CDSE.

Method

Participants

Our participants were 163 undergraduate students (74.3% female, 68.2% European American) enrolled in psychology courses at a college in the mid-Atlantic region of the United States. The mean age of the sample was 19.5 (SD = 1.25). Freshman (23.5%), sophomores (38%), juniors (27.9%), and seniors (9.5%) were represented in the sample. We recruited these participants from an undergraduate participant pool in exchange for course credit and only excluded participants who were under 18 years of age or who had full-time working experience. These were a priori exclusion criteria given our interest in naive job seekers. We received Institutional Review Board (IRB) approval prior to initiating this study.

Procedure and Materials

In advance of conducting this research, we preregistered our experimental design on the website (https://AsPredicted.org) to improve the trustworthiness and replicability of our findings (Moore, 2016). The preregistration for this study, which mirrors the information reported in this article, can be accessed at http://aspredicted.org/blind.php/?x=49jd52

All participants in this research completed the study in small groups under supervised conditions. The survey was delivered via Qualtrics. Upon arrival to the laboratory, we transparently explained to participants that our research concerned career decision-making but did not indicate that we were specifically interested in WoM. Participants first provided informed consent, then reported on their demographic qualities, and completed a measure of CDSE. Next, they read introductory instructions about the experimental portion of the study, and they provided the name of a trusted person who they would approach if they needed to solicit information about potential jobs and organizations (e.g., “Mom,” “Professor Shah,” “Coach Rodgers”). This person’s name was subsequently piped into each vignette as the source of the hypothetical WoM as a means to increase the fidelity of the scenario (Aguinis & Bradley, 2014).

The study used a 2 (WoM: positive vs. negative) × 2 (salary: high vs. low) × 2 (benefits: good package vs. substandard package) × 2 (learning opportunities: a large number of vs. little to no opportunities) design, yielding 16 focal vignettes presented in a fully randomized order. The Appendix reports the stem scenario and the levels of each manipulation. The stem concerns a job at a fictional organization to avoid introducing any bias from participants’ existing knowledge or opinions about actual organizations. Note that we deliberately used nonspecific language to describe the levels of the independent variables (e.g., paying “more” or “less” than expected rather than specifying concrete salary levels). Pilot testing of the vignettes indicated that students with different majors and career outlooks had very different notions of what specific values might constitute “good” versus “bad” pay and benefits, so we adopted nonspecific language that would be appropriate for participants on a wide variety of career tracks. Additionally, we selected one vignette to repeat in a randomized position to allow us to check test–retest reliability (Rotundo & Sackett, 2002), yielding a total of 17 vignettes that were presented to each participant. Researchers commonly use experimental vignettes very similar to ours in scholarship on WoM (e.g., Ahamad, 2019; Van Hoye & Lievens, 2007; Van Hoye, Weijters, Lievens, & Stockman, 2016), although past research is largely limited to between-subjects, rather than within-subjects, designs.

We instructed participants to read each scenario carefully and to not assume that each was the same, despite their facial similarity. After reading each vignette, the participants completed the same measure of applicant attraction, the dependent variable. After completing the experimental portion of the study, participants were debriefed and awarded credit for their time.

Measures

CDSE (Level 2)

The Career Decision-Making Self-Efficacy–Short Form (CDSE-SF) Scale is a 25-item measure of beliefs about career choice abilities (Betz et al., 1996; Creed, Patton, & Watson, 2002). The scale is made up of five subscales: occupational information, self-appraisal, goal selection, planning, and problem-solving. Example items include “Choose a career that will fit your interests” and “Identify employers, firms, institutions relevant to your career possibilities.” The responses were measured on a 5-point Likert-type scale (1 = strongly disagree; 5 = strongly agree).

In previous research, all five subscales of the CDSE-SF, and the total scale, have been found to have high internal reliability coefficients (e.g., Betz et al., 1996; Conklin, Dahling, & Garcia, 2013; Creed et al., 2002). Betz, Klein, and Taylor (1996) and Osipow (1991) reported expected correlations between the CDSE Scale, the Certainty and Indecision subscales of the Career Decision Scale, and the Vocational Identity Scale. In this study, α = .87 for the 25-item total scale.

Perceived knowledgeability of WoM source (Level 2)

As noted above, we asked participants to nominate a real person as the source of the hypothetical WoM to improve the fidelity of the manipulation. After participants nominated their source, we asked them to rate the perceived knowledgeability of this person for the purpose of some exploratory analyses that follow. (Because these sources were generated by the participants, we could not make a priori hypotheses about the nature or importance of the source to our model, and we consequently did not have formal hypotheses about this measurement to preregister.) Participants made these ratings on a 3-item measure that we developed for this study: [Name] “really knows what he or she is talking about,” “really knows a lot about different jobs and organizations,” and “is an extremely credible source of information about jobs I might pursue” (α = .81).

Applicant attraction (Level 1)

We measured applicant attraction to the organization using a 4-item scale developed by Fisher, Ilgen, and Hoyer (1979). Sample items include “I am very interested in pursuing my application with this company” and “I would really like to work for this company.” Responses are made on a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree). Fisher and colleagues (1979) reported that α = .83 for this scale. This measure has been widely used in vocational scholarship concerning organizational attraction (e.g., Honeycutt & Rosen, 1997; Turban, Forret, & Hendrickson, 1998). In this study, the average reliability across participants and vignettes was α = .88.

Results

Analysis Strategy and Data Treatment

We analyzed our data using the software HLM 6 (Raudenbush & Bryk, 2002). Our analysis unfolded over several steps. First, we tested an unconditional, or intercept-only model, which estimates the proportion of variability in organizational attraction that occurred between-person versus within-person. Second, we tested a random coefficients model, which evaluates the fixed effects of the four Level-1 variables (WoM, pay, benefits, and learning opportunities) on attraction, while allowing the slopes of these effects to vary randomly across individuals. Third, we tested a slopes-and-intercepts-as-outcomes model, which adds the Level-2 variable, CDSE, to the model as a predictor of the intercept of applicant attraction and the slope of the Level-1 variables. Lastly, we report the results of several exploratory analyses concerning demographic variables and the sources of WoM information that our participants nominated.

The levels of each of the four independent variables were coded as 0 (low/negative) or 1 (high/positive). We did not center these manipulations in the analyses that follow because centering would complicate their interpretation without influencing the obtained values (Aguinis, 2004). CDSE and all continuous Level-2 predictors included in the exploratory analyses were grand-mean centered (Enders & Tofighi, 2007). Because we included reminders about skipped questions in the survey, we had no missing data at either level of analysis.

To test for the possibility of fatigue or noncompliance in the study, we correlated responses to attraction measure in the repeated scenario, as recommended by Rotundo and Sackett (2002). We found that responses were strongly correlated (r = .66, p < .001) to a degree similar to past vocational, policy-capturing research (Dahling & Thompson, 2010), which suggests that our participants did attend carefully to the scenarios.

Unconditional and Random Coefficients Models

Prior to testing our hypotheses, we ran an unconditional model. Results indicated that the variance component for the intercept was small but statistically significant (τ = 0.02, p < .05). Consequently, only a small, but significant, proportion of the variability in organizational attraction resided between-person at Level 2 (intraclass correlation coefficient [ICC] = .02). Put differently, the vast majority of variability in attraction scores was a function of the Level-1 manipulations of WoM, salary, benefits, and learning opportunities. Given statistically significant levels of variability at both levels of analysis, we turned to testing our hypotheses.¹

Hypothesis 1 stated that WoM would have a positive effect on organizational attraction over and above the effects of information about pay, benefits, and learning opportunities. Table 1 shows the fixed effects with robust standard errors in the random coefficients model. As shown in the table, all four independent variables had significant effects on applicant attraction (all p < .001), with benefits exhibiting the weakest effect. Thus, Hypothesis 1 was supported; the positive coefficient for WoM in Table 1 indicates that shifting from the negative to positive WoM condition was associated with an increase in organizational attraction ratings. Further, each of the variance components for these four predictors was significantly different from zero (all p < .001). These results indicate that the slopes of the Level-1 predictors vary across individuals and that consequently the variability in these slopes can be predicted by between-person differences.

Table 1.
Fixed Effects of Level-1 Variables on Organizational Attraction in Random Coefficients Model (Hypothesis 1).

Predictor Variable Coefficient (γ) SE t

Intercept (γ₀₀) 1.54 .05 29.91

Word of mouth (γ₁₀) 0.93 .04 23.39

Salary (γ₂₀) 0.78 .03 25.01*

Benefits (γ₃₀) 0.47 .04 13.13*

Learning opportunities (γ₄₀) 0.87 .04 23.43***

Note. Results shown are fixed effects with robust standard errors. Coefficients are unstandardized.

p < .001.

Intercepts-and-Slopes-as-Outcomes Model

Hypothesis 2 stated that CDSE would moderate the effect of WoM on organizational attraction such that this positive relationship is stronger for people with low rather than high CDSE. Table 2 reports the results of the intercepts-and-slopes-as-outcomes model, where CDSE is added as a Level-2 predictor of the intercept of organizational attraction and the slope of all four predictors. As shown in the table, CDSE does not significantly influence the intercept, or the slopes of the pay, benefit, or learning opportunity manipulations. However, CDSE does exhibit a significant moderating effect on the slope of WoM. Thus, CDSE shapes the weight attached to WoM, but not to the company-dependent information about pay, benefits, or learning opportunities provided about the organization.

Table 2.
Results of Slopes-and-Intercepts-as-Outcomes Model (Hypothesis 2).

Predictor Variable Coefficient (γ) SE t Ratio

Intercept (γ₀₀) 1.54 .05 30.01

CDSE (γ₀₁) −0.13 .15 −0.88

Word of mouth (γ₁₀) 0.93 .04 24.43*

CDSE (γ₁₁) 0.38 .11 3.56

Salary (γ₂₀) 0.78 .03 25.02*

CDSE (γ₂₁) 0.03 .09 0.30

Benefits (γ₃₀) 0.47 .04 13.23*

CDSE (γ₃₁) −0.14 .19 −0.77

Learning opportunities (γ₄₀) 0.87 .04 23.62***

CDSE (γ₄₁) 0.15 .10 1.56

Note. Results shown are fixed effects with robust standard errors. Coefficients are unstandardized. CDSE = career decision self-efficacy.

p < .01. p < .001.

To further explore this moderating effect, we followed procedures recommended by Preacher, Curran, and Bauer (2006) to plot the interaction, which is presented in Figure 2. Figure 2 shows that the effect of WoM is positive for both students with low CDSE (−1 SD below the mean; b = 0.78, SE = .05, t = 16.51, p < .001) and students with high CDSE (+1 SD above the mean; b = 1.07, SE = .06, t = 16.92, p < .001). However, the slope was stronger for students with high CDSE than students with low CDSE, which is the reverse of our expectation expressed in Hypothesis 2. Thus, although the interaction term is significant and interpretable, the nature of the interaction does not support Hypothesis 2.

Figure 2.
Cross-level moderation of career decision self-efficacy on the relationship between word of mouth and applicant attraction.

Exploratory Analyses

Given the significant variance components found in the random coefficients model, we began our exploratory analyses by examining if any participant demographic variables moderated the effects of WoM on organizational attraction. We found no support for further moderation; neither participant age (γ = −.06, p = .12), gender (γ = −.06, p = .48), nor academic class (γ = .08, p = .16) qualified this relationship.

Next, we conducted exploratory analyses concerning the WoM source that participants nominated. Parents were by far the most common source of WoM information that our participants nominated (64%), which is consistent with Dayton’s (1981) much earlier findings concerning college-aged job seekers. About 16% of the sample listed a professor as a source, with the remaining 20% of responses scattered among extended family members, athletic coaches, and other working adults. Interestingly, students perceived their parents to be less knowledgeable sources of WoM about jobs/organizations (M = 3.97, SD = 0.82) than professors (M = 4.36, SD = 0.52; t[58.82] = −3.03, p < .01), despite overwhelmingly turning to parents instead of professors for this information.

We subsequently examined if either these source knowledgeability ratings or the source type (coded as 0 = parents, 1 = other) qualified the effect of WoM in the model as cross-level moderators. We found no support for source knowledgeability ratings (γ = −.01, p = .80) or the dichotomous source-type variable (γ = .07, p = .35) as a moderator. Thus, neither the nature of the source nor the perceived insight of the source had any bearing on the weight assigned to WoM from the source in this research.

Discussion

The purpose of the current study was to examine how company-independent WoM affected the organizational attraction of naive job seekers relative to company-dependent information. Consistent with Hypothesis 1, we demonstrated that WoM had a strong, positive effect on applicant attraction toward an organization, consistent with previous research (Van Hoye, 2014). Moreover, we found that this effect was quite strong when compared to the effects of company-dependent information about pay, benefits, and learning opportunities. This finding makes an important contribution to the literature on WoM by examining its consequences when presented in the context of a broader set of information about a prospective job.

Our findings concerning CDSE were interesting but inconsistent with our expectations. We predicted that CDSE would moderate the effect of WoM on applicant attraction, such that positive WoM would have a weaker effect for those who have high CDSE. We found the reverse, however: WoM had a stronger* effect on attraction for those with high CDSE. Why might this be the case? Based on SCT, we originally reasoned that people with low CDSE might utilize WoM information to a greater degree because it helps compensate for their low confidence when making career decisions. However, perhaps only those with high CDSE have the perceived capability to act on the WoM that they received to differentiate potential employers. Alternatively, a second reason for this unexpected finding might be that naive job seekers with high CDSE are overly confident in their chances on the job market, making them more selective and critical when making employment decisions. Thus, these individuals may react more strongly to WoM than individuals who lack the same level of confidence. Globally, although our results concerning CDSE were unexpected and are in need of further exploration, our research does advance the literature by offering one of the first considerations of how individual differences shape the weight placed on WoM information by recipients.

Our exploratory analyses also provide some insight into where students are likely to turn for WoM information. The majority of the sample chose their parents as their trusted source of WoM information. As Van Hoye and colleagues (2016) observed, WoM is generally more powerful when it originates from a close source. Consequently, it is not surprising that students preferred to turn to their parents for career advice more often than other sources. However, it is interesting that students evaluated their parents as less knowledgeable sources of job information than their professors; naive job seekers prioritized trust and closeness above perceived expertise when picking an influential source of WoM. This finding is broadly consistent with the results of Van Hoye et al.’s (2016, Study 1) policy-capturing study, in which “tie strength” (whether the source was an acquaintance or friend) exerted a stronger effect than “source expertise” (whether the source was an employee of the actual organization or not).

Implications for Practice

Our findings have practical importance for organizational recruiters and career counselors who work with inexperienced job seekers. For organizations, our findings clearly demonstrate that company-independent WoM information exerts a strong influence on job seekers’ intentions, and organizationally controlled recruiters and advertisements may not be able to compensate for negative WoM. Further, the effects that we observed for the company-dependent information manipulations vary in ways that are worth noting. Our findings illustrate that naive job seekers do not place a heavy weight on benefits, likely to their detriment. Organizations that recruit inexperienced job seekers may need to carefully explain the value and importance of benefits. Conversely, participants placed a heavy weight on learning opportunities that was on par with salary. This finding is broadly consistent with research documenting that younger adults tend to be more concerned with learning and growth opportunities than older adults (Adkins & Rigoni, 2016), and our results underscore that organizations can emphasize learning and development opportunities in their signaling to attract recent graduates.

Career counselors who work with college-aged job seekers should understand the outsized role that WoM may play in their decisions, particularly from trusted sources like parents. This tendency to rely on parents may be detrimental; parents may have positive intentions and high-perceived credibility in the eyes of their children, yet they sometimes lack the domain-specific expertise needed to provide truly useful and accurate career information. Career counselors should also consider the role that CDSE plays in the utilization of WoM information. Our results indicate that those with high CDSE responded more strongly to WoM information than those with low CDSE. Consequently, naive job seekers who have low CDSE may benefit less from WoM information intended to help with career decisions. Taking steps to bolster CDSE may be a useful first step before encouraging job seekers to pursue WoM, such as through formal career development courses or programming intended to bolster confidence (e.g., Reese & Miller, 2006).

Future Research Directions

Future research could expand on the results of this study in several respects. First, there are important, untapped connections between the organizational literature on WoM and the vocational literature that more broadly concerns social learning about the “world of work” that should be explored (Hartung, Porfeli, & Vondracek, 2005). Conversations with parents/caregivers concerning work are important learning experiences that shape career development processes throughout adolescence and early adulthood (e.g., Thompson, Nitzarim, Her, Sampe, & Diestelmann, 2017), and WoM about particular organizations from trusted adults fits within this broader developmental theme. For example, the heavy reliance on parents and caregivers for WoM that we observed in this study is consistent with previous research documenting that parents remain among the strongest influences on career development through late adolescence (Peterson, Strivers, & Peters, 1986). Future research might build on this literature to examine when, and under what circumstances, young adults begin turning to other sources of career information rather than their parents. On a related point, future research could focus on WoM information seeking within the family, such as when mothers versus fathers are seen as preferable sources of WoM about jobs or organizations (Herr et al., 1991; Whiston & Keller, 2004).

A second important direction for future research concerns the processes used to resolve competing WoM information. For example, how do naive job seekers weigh conflicting WoM from different sources, such as when a professor speaks positively about a prospective employer but an internship supervisor disparages it? Most WoM literature do not take into account the possibility of conflicting information, particularly when that information comes from sources that are both considered knowledgeable and trustworthy. In such circumstances, one source or the other could be downplayed or disregarded, or the overall weight given to WoM might be reduced in light of the conflict. More research is needed to understand the complex judgments that unfold when presented with conflicting WoM information.

Third, we note that our results are subject to cultural norms and practices. We expect that the magnitude of the weights observed in this study for salary and benefits will naturally vary across countries with differing laws and practices that influence the nature of job offers. For example, corporate benefit packages are likely to be less important in countries with more progressive social policies, such as universal health care, relative to the United States (Thompson & Dahling, 2019). More research is needed to compare WoM to other company-dependent variables in different cultural contexts.

Fourth, the role of CDSE in seeking and using WoM information should be examined further. For example, high CDSE may help people identify and approach knowledgeable sources to request WoM information about prospective, real-life jobs and organizations. We could not test this idea given our experimental design, but future studies of source choice should examine how CDSE shapes this decision. After receiving WoM, CDSE may also be important when people are confronted with contradictory or conflicting bodies of information, as noted previously. We suspect that CDSE plays a complex role in the WoM process that deserves further research attention.

Fifth, other person-level constructs should be studied in future research that examines how people weigh and use WoM information to make career decisions. Work values and needs may be especially important to consider. For example, a person with high self-enhancement values may react especially strongly to WoM about the reputational prestige of an organization (Ros, Schwartz, & Surkiss, 1999). This kind of alignment between received WoM and job seekers’ values and needs may help create a sense of person–organization (or person–job) fit that mediates the effects of WoM on attraction. However, further research is needed to explore these ideas.

Limitations

Despite our promising results, this study has important limitations. First, realism is a concern for any experimental vignette methodology including policy capturing. Although we followed best practices in the design of this experiment (Aguinis & Bradley, 2014), and experimental vignette methods are common in the WoM literature (e.g., Ahamad, 2019; Van Hoye et al., 2016), written vignettes lack the psychological fidelity of real-world events. Consequently, replication of our findings with other methods is important.

Second, some limitations of our sample should be noted. Our sample consisted mostly of female and European American participants. Although we believe the results of this study are broadly generalizable to other naive job seekers in the United States, our findings should be replicated with more diverse samples. Research in marketing contexts suggests that people oftentimes prefer WoM that comes from sources that they perceive to be similar to them (e.g., Herr et al., 1991). In the recruiting domain, students from underrepresented groups may consequently have a greater difficulty in acquiring and trusting career-related WoM. Although we excluded participants with any prior full-time working experience, we also presumed that they were naive job seekers for the purposes of this study. Our results would be strengthened by measuring and controlling for any past career exploratory behaviors to account for the role of any prior experience.

Third, the information conveyed via WoM in this research concerned a global reputation judgment, but other types of information may be conveyed by WoM. For example, sources might comment on qualities such as industry trends or the company’s expected trajectory (e.g., “it’s a good company, but they may be pulling back over the next few years”). Our results may not generalize to more specific types of information shared via WoM, and future research should replicate our design taking into account a wider variety of company-independent information.

Conclusion

In conclusion, our results indicate that WoM has a strong effect on organizational attraction that persists in the presence of important company-dependent information. We also extended the literature on WoM by demonstrating that its effects are contingent on individual differences in CDSE. In aggregate, these findings can inform both organizational recruiting practices and the career counseling of college-aged job seekers.

Predictor Variable	Coefficient (γ)	SE	t
Intercept (γ₀₀)	1.54	.05	29.91***
Word of mouth (γ₁₀)	0.93	.04	23.39***
Salary (γ₂₀)	0.78	.03	25.01***
Benefits (γ₃₀)	0.47	.04	13.13***
Learning opportunities (γ₄₀)	0.87	.04	23.43***

Predictor Variable	Coefficient (γ)	SE	t Ratio
Intercept (γ₀₀)	1.54	.05	30.01***
CDSE (γ₀₁)	−0.13	.15	−0.88
Word of mouth (γ₁₀)	0.93	.04	24.43***
CDSE (γ₁₁)	0.38	.11	3.56**
Salary (γ₂₀)	0.78	.03	25.02***
CDSE (γ₂₁)	0.03	.09	0.30
Benefits (γ₃₀)	0.47	.04	13.23***
CDSE (γ₃₁)	−0.14	.19	−0.77
Learning opportunities (γ₄₀)	0.87	.04	23.62***
CDSE (γ₄₁)	0.15	.10	1.56

Footnotes

Appendix

Acknowledgment

We thank Greet Van Hoye for her helpful feedback on an earlier draft of this article.

Authors’ Contribution

Both authors made equal contributions to this work.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Jason J. Dahling

Note

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