THIRD PARTY EMPLOYMENT BRANDING: EMPLOYEE TURNOVER RATES
FOLLOWING ‘BEST PLACES TO WORK’ CERTIFICATIONS
BRIAN R. DINEEN
Purdue University
Krannert School of Management
West Lafayette, IN 47906
Tel: (765) 496-2022
E-mail: dineenb@purdue.edu
DAVID G. ALLEN
University of Memphis
Fogelman College of Business and Economics
Memphis, TN 38152
Tel : (901) 678-4729
E-mail : dallen@memphis.edu
This research has been funded by a grant from the SHRM Foundation. We thank Jason
Shaw for his work on the early stages of this project, Abbie Shipp for her assistance with
the data analysis process, and the faculties of the Krannert School of Management OBHR
area at Purdue University and the London Business School OB area for their helpful
comments and suggestions.
Keywords: Best Places to Work, turnover, employment brand image, employment branding
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ABSTRACT
“Best Places to Work” (BPTW) and similar competitions have proliferated and represent a form
of third party employment branding. Yet, little is known about how third party branding efforts
of this type might relate to turnover outcomes. Using archival information and survey data from
624 companies participating in fifteen state- and industry-based BPTW competitions across a
four-year period, we develop and examine competing theoretical predictions about the
relationship between BPTW rankings and turnover rates. We then develop and examine (1)
moderation predictions regarding organization size and workforce age (susceptibility effects) as
well as workforce satisfaction (sham effect), and further examine (2) celebrity and crystallization
effects that model the trajectory of this relationship with repeated rankings over time. This
investigation advances theory related to turnover and employment branding, and is relevant to
company decisions about entering or remaining in BPTW competitions from year to year.
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THIRD PARTY EMPLOYMENT BRANDING: EMPLOYEE TURNOVER RATES
FOLLOWING ‘BEST PLACES TO WORK’ CERTIFICATIONS
The evolution of employer-employee relations from a transactional to relational model
has received widespread attention, as has the need for companies to approach Human Resources
(HR) strategically (e.g., Becker & Huselid, 2006; Hammonds, 2005; Rousseau, 1995; SHRM,
2010). This evolution has led employers to strive to make workplaces more engaging,
developmental, and employee-centered. As part of this trend, the idea of branding the
organization as a great place to work is yielding increased practical and scholarly attention as a
key consideration for both attracting and retaining talent (e.g., Collins & Kanar, in press;
Gardner, Erhardt, & Martin-Rios, 2011). Research and theory demonstrate that individuals
develop and hold brand images in memory that influence preferences for products and services
beyond the tangible attributes of those products or services (Aaker, 1996; Keller, 1993). More
recently, scholars have turned this lens to the employment brand, and the possibility that
employment brand image could influence decisions to apply for, accept, and remain with an
organization’s job opportunities (see Collins & Kanar, in press, for a review). Others have even
suggested that certain branding events, coupled with emotional reactions of employees, can lead
to rapid “celebrity” status for firms, yielding above-normal outcomes for those firms (Rindova,
Pollock, & Hayward, 2006). Still others suggest that employment branding and reputationbuilding require consistency and thus take time to come to fruition in the form of discernible
outcomes (e.g., Rindova, Williamson, Petkova, & Sever, 2005). Either way, the duration and
generalizability of branding effects for important organizational outcomes such as turnover is
uncertain.
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Whereas employer image consists of individuals’ perceptions of what is distinctive,
central, and enduring about the organization as a place to work (Cable & Turban, 2001; Collins
& Stevens, 2002; Highhouse, Brooks, & Gregarus, 2009), and an employment brand is defined
as “names, terms, signs, symbols, or designs or a combination of them intended to identify the
employment offering of one employer and to differentiate it from the offerings of competing
employers” (Gardner et al., 2011), employment branding comprises efforts organizations make to
create or alter these image perceptions to convey a favorable value proposition to potential or
current employees (e.g., Edwards, 2010; Lievens, 2007; Van Hoye, Bas, Cromheecke, &
Lievens, 2012). The bulk of the empirical research to date has focused on the role of
organizational brand image in attracting talent to the firm (e.g., Chapman, Uggerslev, Carroll,
Piasentin, & Jones, 2005 summarized the effects of 27 studies linking organization image to
applicant attraction). We shift this focus to the impact of the organization’s employer image and
branding efforts on employee turnover, given the criticality of turnover to a host of
organizational performance metrics (Shaw, 2010).
Specifically, we address three primary questions of theoretical and practical importance.
First we investigate whether employment branding might influence the retention of current
employees, and more specifically, whether third party employment branding, defined as changes
in employer image resulting from communications, claims, or status-based classifications
generated by extra-organizational entities, impacts turnover rates. For example, a cornerstone of
the recent work on celebrity firms is that celebrity stature is largely conferred on firms by outside
entities such as the media (Rindova et al., 2006). Second, we examine the types of firms for
which these effects might be more prevalent. Third, we investigate instigation points at which
these effects might commence, and the sustainability of effects once set in motion (Rindova et
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al., 2006). For example, we ask whether third party employment branding results in immediate
positive (or negative) outcomes, or whether the employment brand must be better-established
before it can actually translate to tangible effects such as reduced turnover.
In addition to extending research on employment branding to consider it effects on
reactions of current employees, our approach addresses an important gap in turnover theory.
Holtom, Mitchell, Lee, and Eberly’s (2008) review identifies organization prestige as a new
construct warranting attention, but does not elaborate on how or why prestige matters.
Hausknecht and Trevor’s recent (2011) model of collective turnover identifies a variety of HR
practices, collective employee attitudes, and collective business and environmental
characteristics that may influence turnover rates, but does not address employer image,
reputation, or celebrity. Gardner et al. (2011) note that employment brands help workers make
better, less effortful decisions about continuing employment relationships, and argue that
employment brands are more critical to employee decision making than even product brands are
to consumers. It is therefore apparent that a melding of the turnover literature with the rising
interest in firm reputation, employment branding, and “celebrity” firms is warranted.
Should we expect employment branding in general, and third party employment branding
in particular, to influence current employees? Collins and Kanar (in press) suggest that current
employees likely form surface (overall evaluations) and complex (focused on specific attributes)
brand associations about their organization as an employer, and that these associations may
influence employment related decisions beyond objective job attributes. Cable and Graham
(2000) drew from a social identity perspective to suggest that job applicants will prefer
organizations with positive reputations because applicants will associate such prestigious
organizations with social status and self-esteem. Similar logic suggests firm reputation may also
5
influence the preferences of current employees. Moreover, Rindova and colleagues (2006)
differentiate between reputation and celebrity status, arguing that firms achieve the latter not
only based on public attention (i.e., through third party rankings of one sort or another), but also
on emotional responses to that attention, which might be even stronger when this attention is
focused on aspects of employee well-being than when it is linked to other aspects of firms such
as outlandish new products or unusual firm financial performance.
The possibility that current employee perceptions of an organization’s reputation or
celebrity status as an employer could influence employment-related decisions such as turning
over also raises questions about how employees form these perceptions and the extent to which
organizations can shape them. Certainly, pre-hire perceptions and on-going work experiences
can influence employee perceptions of what it is like to work at a particular organization, and
many organizations and managers routinely attempt to communicate to employees that the
organization is a desirable place to work. However, signaling theory (Spence, 1973) provides a
rationale for why organizations may also seek third party employment branding, whereby they
attempt to earn recognition for their positive employment brand from an external source.
Specifically, whereas organizations of course can tell applicants and current employees that the
company is a great place to work (and many do), individuals in organizations may question the
veracity of such self-serving claims, especially if these exhortations are inconsistent with
employees’ personal experiences.
Bangerter, Roulin, and Konig (2012) recently described how signaling theory addresses
the exchange of information among parties with somewhat divergent interests in a personnel
selection context: communication senders attempt to send signals that are honest, reliable, costly,
or hard to fake, because such signals are perceived as more credible. We extend this perspective
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to organizational communication with current employees in a context in which the sender may be
perceived as having incentives to be less than completely honest. Internal organizational
branding efforts may be perceived this way; thus, organizations may seek third party
employment branding endorsements as a way to communicate credible hard-to-fake signals to
employees that the organization is indeed a great place to work. Such signals tend to incur costs
(i.e., time and resource investment on the part of the organization) and are difficult to fake
(because they are bestowed by a third party and thus are largely outside organizational control).
A particularly interesting example of third party employment branding is the proliferation
over the last decade of “Best Companies to Work For,” “Best Places to Work,” or similar
evaluative certifications bestowed by third parties on companies with superlative employee
relations practices. BPTW and similar programs have grown from fewer than ten nationwide in
the late 1990s to more than one hundred today (Burke, 2010). Despite the obvious appeal and
marketing benefits for companies recognized as BPTW, and despite third party organizers’
frequent claims regarding benefits such as decreased turnover, researchers have conducted few
rigorous empirical investigations to demonstrate the direction and strength of these effects or the
validity of claims often proffered by organizers (Roehling, Boswell, Caligiuri, Feldman, Graham,
Guthrie, Morishima, & Tansky, 2005). Thus, companies entering these competitions – or,
perhaps more importantly, continuing to enter year after year – do so without a clear
understanding of potential gains to being named to these lists one or multiple times, or even
whether being recognized in this way could have potential downsides. Given difficult economic
conditions over the last several years, more limited employee mobility, and reduced job
opportunities, companies may legitimately question whether they should devote resources to
these competitions. As the economy improves, however, employees will likely have increased
7
mobility and choice (e.g., Allen, Bryant, & Vardaman, 2010), which implies that companies may
need to enhance their employment brand images and strive to retain employees through
ambitious people-management practices.
Even if BPTW certifications are viewed by employees as a credible signal that their
organization is a great place to work, there are legitimate competing theoretical perspectives as
to the likely effects of such recognition on employee turnover. These perspectives are illustrated
in Figure 1. As shown, an identity perspective suggests that being named a BPTW may reduce
turnover rates as employees prefer to be associated with an organization visibly and credibly
certified by a third party as having a positive employer image. However, a mobility perspective
suggests that working for such an organization could increase alternative opportunities, and thus
turnover rates. David D’Alessandro (2001, p. 152), former CEO of John Hancock, stated: “…the
best brands are the best places to be from. These names work magic on a resume…”
Therefore, we develop and test previously unexamined hypotheses designed to address
several key research questions about the nature of third party employment branding effects on
turnover rates and turnover trends across multiple branding cycles, as well as several moderators
that may help elucidate contingencies surrounding this relationship. In particular, Bangerter et al.
(2012) note that signaling systems consist not only of signals and senders, but also of receivers
who must interpret signals. However, we know little about how receivers may interpret signals,
so we focus our moderator analyses on characteristics of the organizational context and the
nature of the workforce that are likely to influence receiver interpretation and subsequent
reactions to being ranked in BPTW competitions.
Our research uses archival information and survey data from U.S. and Canadian BPTWparticipating companies throughout four BPTW competition cycles. By using data from multiple
8
program cycles, our research addresses calls by strategic HR scholars for longitudinal studies
(e.g., Wright, Gardner, Moynihan, & Allen, 2005). Our project also represents a break with past
empirical work examining publicized employee-relations competitions such as BPTW. To our
knowledge, this work has mostly examined BPTW outcomes using only publicly available data
or limited employee data gathered in the competitions (e.g., Filbeck & Preece, 2003; Fulmer,
Gerhart, & Scott, 2003; Lau & May, 1998). For example, Fulmer et al. compared Fortune “100
Best” companies with a matched group of companies that failed to make the list. They found that
employee attitudes in the 100 Best were stable over time and that those companies performed
better financially than the comparative sample. The authors acknowledged, however, that their
small sample did not allow them to partial out prior performance. They also lacked actual
company-provided competition data, which precluded examination of an intervening effect that
they acknowledged and we are able to examine: changes in voluntary turnover. Trevor and
Nyberg (2008) had access to employer data from the 1998 and 1999 100 Best competitions, but
investigated only relationships between downsizing and turnover rather than turnover effects of
making the 100 Best list. Thus, we know of no academic study that has used actual employer
data from BPTW competitions to examine turnover as a function of BPTW rankings over
multiple competition cycles.
Turnover Following Third Party Employment Branding
Theories about how individuals decide whether to remain with or leave their organization
have historically emphasized that the way individuals feel about and evaluate the organization is
an important driver of withdrawal-related cognitions and behaviors. In a comprehensive review,
Holtom et al. (2008) suggested that future research would benefit from expanding beyond
traditional individual-level attitudes such as job satisfaction and organizational commitment, to
9
address how organizational prestige influences withdrawal processes. These scholars also called
for studies examining alternative explanations for turnover. Thus, we first develop competing
hypotheses pertaining to the direction of third party employment branding effects on subsequent
turnover.
Potential decreases in turnover rates. Third party branding accolades, such as being
identified as a great place to work, should on the one hand be associated with lower turnover. As
shown in Figure 1, an identity perspective follows conventional wisdom and is plausible for
organizations soliciting third party employment branding (e.g., by investing in BPTW
competitions): BPTW rankings provide a credible signal to employees about the organization as
an employer that are likely to reduce subsequent turnover for several reasons. First, BPTW
success, especially over time, likely enhances corporate reputation and employment brand image.
Employment brand image and corporate reputation research suggests that positive public
recognition gained via internal company efforts or institutional intermediary-bestowed
certifications can improve a company’s reputation and increase public perceptions that a
company is a good employer. For example, Collins and Stevens (2002) found that publicity
interacted with several recruitment-related practices (advertising, endorsements, sponsorship) to
increase job seeker attitudes toward a company and the strength of perceived company attributes.
Even more relevant to our context, Rindova et al. (2005) found that media rankings were the
strongest predictor of organizational prominence (see also, Graffin & Ward, 2010). In turn,
prominence likely increases the attractiveness of working for such a company and maintaining
one’s association with such a company.
Second, research suggests that employees prefer to identify themselves with a “winning”
company burnished by reputational acclaim. Social identity theory (Tajfel & Turner, 1979)
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proposes that individuals take pride in being associated with “winners” and seek to maintain their
association with these entities (see also, Cable &Turban, 2003). Other work suggests that
individuals prefer to be associated with organizations that have a positive image because doing
so enhances perceived social status and self-esteem (Collins & Kanar, in press; Dutton,
Dukerich, & Harquail, 1994; Gardner et al., 2011). For example, Cable & Graham (2000)
suggested that individuals are attracted to organizations with more positive brands at least in part
because joining such organizations is a public expression of the individual’s values. Remaining a
member of a prestigious organization may serve a similar function. Thus, being part of an
organization recognized by an external entity as a great place to work could influence turnover
by reinforcing positive associations with being identified as a member of such an organization.
Third, being recognized as a BPTW may further embed employees in the organization
(e.g., Mitchell, Holtom, Sablynski, & Erez, 2001). Key considerations in why people remain
with organizations include their perceived fit with the organization and the sacrifices they would
incur by leaving. According to Collins and Kanar (in press), an important reason why brand
image is important for influencing organization attraction is because of substantial research
demonstrating that brand associations influence perceptions that a product, service, or
organization will fit one’s needs. Thus, being associated with an organization that has a positive
employer image is likely to increase perceptions of organizational fit. In turn, the perceived
sacrifice of leaving might rise as the perceived likelihood of finding a similar or better situation
elsewhere diminishes. Collins and Kanar (in press) further suggest that another reason brand
image influences decision making is by providing potential justification for decisions to external
constituents. Leaving a BPTW organization might entail a dual sacrifice: giving up a position at
a prestigious organization and having to justify the decision to friends, family, or associates.
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These constituents, if at all familiar with the company’s BPTW status, might ask “Why would
you leave a company that treats its workers so well?”
Hypothesis 1: Third party employment branding, in the form of BPTW rankings,
will be negatively associated with employee turnover rates.
Potential increases in turnover rates. Although the identity perspective is logical, it is
important to keep in mind that, in addition to sending a credible signal to current employees,
BPTW rankings may also send a credible signal to other potential employers. Recall the earlier
quote that being from an organization with a strong brand image works ‘magic’ on a resume.
Turnover theory emphasizes that the desire to leave an organization must be considered in
conjunction with the ease of leaving (e.g., Holtom et al., 2008; March & Simon, 1958). If being
associated with a BPTW increases external opportunities for current employees, this suggests an
alternate mobility perspective: strong employment brand image could actually signal employee
quality to the external market, thereby increasing employee mobility and turnover (see Figure 1).
Specifically, reports suggest a resume building effect of brand image (e.g., DelVecchio,
Jarvis, Klink, & Dineen, 2007; McNally & Spark, 2003; Peters, 1997). This further implies that
representatives of outside firms may perceive BPTW-recognized companies as able to be more
selective in hiring and more likely to develop employees’ skills. Such perceptions make
employees of BPTW-recognized firms appear more desirable. DelVecchio et al. (2007) found
that individuals view working for a strong brand as a way to build a powerful resume. Skill
development has similarly been linked to individuals’ marketability (e.g., Bretz & Boudreau,
1994; March & Simon, 1958). This logic is akin to the previously referenced relationship
between media rankings and the perceived quality (as well as prominence) dimension of firm
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reputation (Rindova et al., 2005). Hence, BPTW employees may enjoy enhanced marketability,
leading to greater risk that companies will lose them to turnover.
Similarly, turnover theory also recognizes that job dissatisfaction is not the only path to
turnover; sometimes even very satisfied employees leave. The unfolding model of turnover (Lee,
Mitchell, Holtom, McDaniel, & Hill, 1999) identifies certain system “shocks” that may prompt
turnover. A shock in this context is defined as any event that leads an individual to consider
leaving their job. Interestingly, while many shocks may be negative in nature, the unfolding
model emphasizes that some shocks can be positive. Indeed, Holtom, Mitchell, Lee, and Eberly
(2005) found that 64% of these system shocks were positive. A BPTW ranking may be such a
positive “shock.” By communicating a credible hard-to-fake signal about the company’s
employment brand image to potential alternative employers, a BPTW ranking could increase the
likelihood of turnover by making employees suddenly aware of their ease of movement via
perceptions of marketability and mobility; by increasing actual job alternatives; and in some
cases eliciting active attempts by external suitors to poach employees with unsolicited job offers.
Specifically, where such a ranking enhances the company’s employment brand image, it also
enhances the employees’ image, making them more appealing to these external suitors.
Hypothesis 2: Third party employment branding, in the form of BPTW rankings,
will be positively associated with employee turnover rates.
Moderating Effects
As noted earlier, signaling systems consist of signals and senders, as well as receivers
who must interpret signals. Even if a signal is verifiable (e.g. being named a BPTW), the signal
may be received and interpreted differently based on the context in which it is received or the
characteristics of receivers. Thus, in the present context, enhanced employment brand image may
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be more impactful for certain organizational or workforce types. That is, there may be conditions
under which the effects on turnover rates of being named a BPTW could be stronger than others.
We explore one organizational characteristic and two workforce characteristics as potential
moderators that may help explain how third party employment branding influences turnover
rates: organization size, workforce age, and baseline levels of workforce satisfaction.
Organization size. First, we anticipate that organization size will moderate the effects of
BPTW rankings on employee turnover. Rindova et al. (2005) recognized the small/large
company distinction as important to future research on company reputation effects, and Rindova
et al. (2006) suggest that celebrity effects are more likely to occur among previously lesser
known organizations. Therefore, we propose a susceptibility effect whereby smaller companies
(and the employees within those companies) are more susceptible to the effects of an
employment brand image boost accompanying a BPTW ranking, in terms of employee turnover.
By sheer size, larger companies are prone to greater baseline levels of reputation (i.e., their
employer “track record” over time is likely better known) or employment brand image (Cable &
Graham, 2000), reducing marginal gains for larger companies of signaling to their employees
through a BPTW ranking. Smaller organizations are more likely to realize greater rents through
public awards such as BPTW because the marginal effect of the signal that the organization is a
great place to work is stronger, enhancing the marginal effect on turnover.
Similarly, smaller companies may benefit to a greater extent from increased
organizational identification and their employees may feel more personally responsible for its
success in attaining positive third party employment branding. Because of their resource and
reputational advantages, employees of larger organizations likely already benefit from
perceptions of social status and esteem from being associated with these organizations. Thus, we
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suggest that the marginal identification boost will be greater in smaller companies. Although it is
possible that employees in smaller BPTW companies also benefit more from the external image
boost, potentially increasing mobility, we propose that the employer brand image and
identification effects will outweigh any boost in mobility. For larger companies, however, we
propose the opposite. Because they likely already enjoy reputational and resource advantages
associated with size, the identity enhancing effects of being named to a BPTW list will be
relatively lower; thus, potential boosts to mobility based on external signaling of employee
quality will negate potential reductions in turnover emanating from employee identification.
Hypothesis 3: Company size will moderate the relationship between BPTW
rankings and employee turnover rates; the relationship will be stronger for smaller
companies than for larger companies.
Workforce age. We anticipate a second susceptibility effect, such that workforce age
will help explain the extent to which BPTW rankings influence turnover rates. Researchers have
paid significant attention to the importance of understanding the work values, employment
decisions, and mobility patterns of younger workers (e.g., Coster, 2007; Dutra, 2010; Pfeffer,
2005; Twenge, Campbell, Hoffman, & Lance, 2010). Some sources suggest that younger
workers are more likely to quit and require greater levels of company engagement initiatives to
retain them (e.g., Brin, 2011), although meta-analytic evidence has been relatively weak (e.g.,
Costanza, Badger, Fraser, Severt, & Gade, 2012; Ng & Feldman, 2009). As the workforce ages,
companies also find it increasingly critical to understand how to retain older workers (e.g.,
Cadrain, 2007).
We propose that in terms of turnover, older workers are less likely to be influenced by
BPTW status than younger workers. First, older workers are likely to be more experienced and to
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have longer and more varied track records of professional accomplishments. They are therefore
less reliant on organizational status to boost their potential mobility or identification with their
work. Older workers are also likely more embedded in their communities (Mitchell et al., 2001)
and are thus buffered to a greater extent from system shocks such as BPTW rankings (Holtom et
al., 2008). Moreover, they tend to have greater tenure with their organizations and are more
attuned to generational norms regarding lifetime employment than younger workers (e.g.,
Cappelli, 2008). Thus, they are more likely to have developed significant side-bets (Becker,
1960) and tenure-related benefits, may be more embedded in the organization (Mitchell et al.,
2001), and less in need of third party branding signals about their employer to enhance their
external standing should they choose to search for alternative employment. Thus, it is less likely
that the organizational identification and the possible mobility of older workers are amenable to
the influence of BPTW signals.
The organizational identification and thus retention of younger workers, on the other
hand, may be more malleable. For example, although few academic studies have addressed
differences in the importance of work values and work-life balance across age groups, the
practitioner literature is replete with claims that younger workers more highly value working for
organizations that emphasize employee well-being and work-life balance (e.g., Casserly, 2013;
Schramm, 2004). Twenge et al. (2010) did find, in one of the few peer-reviewed academic
studies, that leisure values were stronger among younger generational workers; work centrality
was lower; and status-type values were higher among younger generations than among older
generations. Thus, because of the status imbued by BPTW rankings, as well as the signals
rankings send about ongoing people management practices, the impact of BPTW rankings on
turnover rates should be greater in organizations with younger workforces.
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Hypothesis 4: Workforce age will moderate the relationship between BPTW
ranking history and employee turnover rates; the relationship will be stronger
among younger workforces than older workforces.
Workforce satisfaction. We have suggested that, in general, BPTW recognition should
be viewed by employees as a credible signal that an organization is indeed a great place to work
because participation is costly and the result is largely out of the organization’s control.
However, this situation also raises interesting practical and theoretical concerns. From a practical
perspective, organizations may have to make decisions about how much to invest in their
workplace culture and people management strategies before applying for BPTW status.
Theoretically, it is important to assess how employees react to ostensibly credible signals that
nevertheless may be inconsistent with their own experiences. That is, there are likely to be
employees in BPTW-recognized organizations for whom personal experiences do not match the
purported signal being communicated. For example, a disenfranchised teller working for a bank
that is named a BPTW by a third party may view the ranking as a “sham,” such that the effects of
such branding fail to materialize or even have a reverse effect.
Research on perceived amelioration suggests that future outcome expectations as well as
the current situation can affect current attitudes (e.g., Aquino, Griffeth, Allen, & Hom, 1997).
That is, when assessing current attitudes or making decisions about whether to stay or turn over,
employees look not only at how they are currently faring, but how they believe their situation
might be improved going forward. In the case of the teller working for a bank just recognized as
a BPTW, he might perceive that (1) his current situation is untenable and (2) the bank is unlikely
to make major improvements to its people-management practices going forward, given that it has
17
already been recognized as superior in that realm. Consistent with this, Aquino et al. (1997)
found that amelioration likelihood was directly and negatively linked to withdrawal cognitions.
We therefore hypothesize a sham effect in which employees embedded in organizational
settings in which there tends to be less positive overall assessments of the work environment
might be influenced in a somewhat counter-intuitive manner by positive external employment
branding signals, compared to employees embedded in organizational settings in which there
tends to be more positive overall assessments of the work environment. On the one hand, it is
conceivable that dissatisfied employees in contexts in which they are outliers in terms of their
evaluation of the workplace may be forced to re-evaluate their circumstances when presented
with outside recognition of the employer as a great place to work. However, we suspect that in
settings with many less satisfied employees, more of these employees will view a BPTW
designation as a false signal because it is inconsistent with their own experiences as well as with
general perceptions in the workplace. This, coupled with potential enhanced mobility in the wake
of BPTW recognition for their company, suggests that employees in contexts where
dissatisfaction tends to be the norm may actually be more prone to turnover following a BPTW
designation. Based on the above, we propose:
Hypothesis: 5: Workforce satisfaction will moderate the relationship between
BPTW ranking history and employee turnover rates; the relationship will be
negative among more satisfied workforces and positive among less satisfied
workforces.
Celebrity and crystallization effects. Whereas in previous sections we have developed
predictions about the main and moderated effects of BPTW rankings on turnover rates, it is
important to further investigate possible lag times and durations of these effects. Indeed, most
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prior research has suggested a monotonic trend, reflecting simple linear relationships between
positive publicity or endorsements, and employment brand image (e.g., Collins & Stevens,
2002). However, BPTW recognition is typically a periodically repeating event (most often
annually), meaning that organizations can, and often do, compete for rankings year after year.
This raises the question of whether repeat rankings continue to influence turnover rates the same
way as initial rankings, or whether several consecutive rankings are required before discernible
turnover effects materialize.
This question is practically important because organizations must make repeated
decisions whether to continue to compete for BPTW recognition. If the effects remain constant
then such decisions may be different than if the effects are greatest after an initial ranking and
then decline, or if they are initially weak, but gain strength after repeated rankings. The question
is also theoretically important because signaling systems tend to adapt over time. For example, if
every organization was designated a BPTW then the signal would lose efficacy for conveying
useful information. Thus, at the organization level, it is fruitful to inquire whether repeated
signaling of being named a BPTW in successive years continues to convey the same information,
or whether subsequent repeated rankings begin to convey less useful information. Addressing
these issues may also have implications for the unfolding model of turnover. This model focuses
on shocks, but implicitly assumes a single shock that jars employees; in reality, many
organization shocks may repeat over time (or have the potential to repeat), and exploring these
shock patterns may advance understanding of how employees respond to potentially repeating
patterns of shocks, or whether “shock values” dissipate over repeated episodes.
Consistent with research finding that reputation-based (i.e., built more through
consistency) and celebrity-based (i.e., built more through defining events) social status led to
19
different outcomes (e.g., Pfarrer, Pollock, & Rindova, 2010), we develop two additional
competing perspectives. The first emanates from work describing certain organizations as
“celebrities,” defined by Rindova et al. (2006: 51) as “firms that attract a high level of public
attention and generate positive emotional responses from stakeholder audiences.” Both of these
criteria as likely met through BPTW rankings: the rankings bring publicity to the organization in
terms of the initial pronouncement as well as ongoing marketing highlighting the earned
accolade. Such acclaim is also likely to have an emotional impact on current employees, who are
key stakeholders. Specifically, as shown in Figure 2, based on the idea of celebrity firms, a
celebrity trend suggests rapid initial results (i.e., decreased turnover) but diminishing marginal
returns over time. Here a sharp initial decrease in turnover is likely following a publicized shift
in employment brand image, such as making a BPTW list for the first time. Subsequently, this
decrease likely continues with consecutive rankings, but with diminishing returns as a company
continues to be ranked. Returning to the signaling perspective, third party employment branding
likely communicates more useful information when it is novel, with information usefulness
diminishing with repeated rankings.
Hypothesis 6: Whereas turnover rates will be unchanged across ranking periods for
non-ranked organizations, turnover rates among organizations ranked for the first
time and then consecutive times after that will exhibit a negative linear trend and a
positive quadratic trend (i.e., decreasing at a decreasing rate).
Whereas we believe the celebrity perspective is a viable explanation for turnover trends
following third party employment branding episodes, an alternative perspective is also possible.
Specifically, enhancement of an organization’s employment image through third party
employment branding may take longer to translate to outcomes such as turnover, suggesting
20
those outcomes (i.e., decreased turnover) may be slighter at the outset, but may gain momentum
over time in the form of turnover that decreases at an increasing rate as consecutive rankings are
earned. As shown in Figure 3, a crystallization trend draws on the attributions and reputation
literatures (Nishii, Lepak, & Schneider, 2008; Rindova et al., 2005; Weiner, 1986) and suggests
that employees likely make stability attributions when evaluating these third party proclamations,
and look for consistent signals of quality. In the case of employee relations issues, they may look
for consistency in employee-friendly policies and handling of employee-related issues (Rindova
et al., 2005, 2006). Specifically, as consumers “wait to see how legitimate a new brand is going
to be” (e.g., GoogleGlass), employees might react (i.e., in terms of turning over or staying) only
to BPTW companies that demonstrate through consistent rankings that they have stable
employee-friendly policies. That is, employees may develop stability attributions about
employee-friendly policies and become extraordinarily identified with their company only after
the company earns BPTW rankings in successive years. Absent consistent rankings (i.e.., failure
to repeat), employee identity, and thus turnover, will not discernibly change because employees
will perceive that changes to the employment brand are whimsical or unstable.
Hypothesis 7: Whereas turnover rates will be unchanged across ranking periods for
non-ranked organizations, turnover rates among organizations ranked for the first
time and then consecutive times after that will exhibit a negative linear trend and a
negative quadratic trend (i.e., decreasing at an increasing rate).
METHOD
We obtained data from an independent company that organizes and conducts over forty
state-based, industry-based, and international BPTW competitions. Organizations pay an entry
fee to enter the competitions, and the competitions occur annually. Upon entering a competition,
21
organizations complete an employer survey which includes items regarding organization-wide
employment practices (e.g., work-life initiatives, salaries) and outcomes (e.g., turnover). At the
same time, a subset of employees in each organization (at least 40%, and 80% in companies with
fewer than twenty employees) completes an employee survey which includes demographic
information and items tapping perceptions of the workplace as well as employee satisfaction and
demographics. In the months following submission of this survey data, the company running the
competition uses these data to determine whether entrants are ranked or not for that year.
Specific rankings for companies “making the list” are publicized soon thereafter, usually at an
awards banquet and through media channels. Regardless of ranking outcome, all participating
companies receive a detailed feedback report generated by the company organizing the
competition.
Data made available for the present research comprised fifteen of these competitions
across the United States and one in Canada, for a period of four years (2009-2012). In total,
4,343 companies participated in these competitions in at least one of the four years under study.
Of these, 624 participated and reported turnover in both 2009 and 2012, and thus were eligible
for inclusion in the analyses. The final analysis sample size after listwise deletion of included
variables was 515.
Measures
Several of the measures used in this study are objective (e.g., whether a company was
ranked in a BPTW competition or not, in which size category it competed) or ask company
representatives to report company statistics (e.g., voluntary turnover). These and other measures,
assessed each year a company participated in a BPTW competition, are described below.
22
Voluntary employee turnover rates. The voluntary turnover measure is similar to
McElroy, Morrow, and Rude (2001). Company representatives completing the employer survey
were asked, “What was your organization’s percentage of voluntary turnover in the last fiscal
year?”
Company size. Organizations joining BPTW competitions compete in company size
categories ranging from small to large, with some designated as “small/medium” or “medium.”
Although precise cutoffs can vary across BPTW competitions, companies are typically
considered small if they comprise fewer than 50 employees, small/medium if they comprise
between 50-249 employees, and medium or large as size increases from there. For our purposes
we therefore created two size categories: the first comprised companies designated as small and
small/medium (coded 0), and the second comprised companies designated medium and large
(coded 1).
Workforce age. Employees completing the employer survey were asked to indicate their
age with the following item: “What is your age.” (1 = less than 21; 2 = 21-25; 3 = 26-35; 4 = 3645; 5 = 46-55; 6 = 56-65; 7 = above 65). Responses were aggregated such that workforce age
was the mean of these responses across employees surveyed in each respective company in 2009.
Workforce satisfaction. As part of the employee survey process, employees were also
asked, “Overall, how satisfied are you with this organization as an employer?” (1 = very
dissatisfied to 5 = very satisfied). Responses were aggregated such that workforce satisfaction
was the mean of these responses across surveyed employees in each respective company in 2009.
BPTW rankings. In addition to supplying employer and employee survey data for the
competitions under study, the company running the BPTW competitions supplied for purposes of
this research complete rosters of participating companies and rankings data for each year of the
23
competition. Using these data, we constructed the primary independent variable, operationalizing
it as the number of rankings (0, 1, 2, or 3) organizations achieved during the 2009-2011
competitions.
Control variables. We used archival data supplied by the organizing company to
retroactively create variables representing prior participation and ranking records, both of which
were used as control variables in tests of Hypotheses 1-5. For example, the Hawaii competition
has existed since 2005, whereas the Pennsylvania competition (the oldest for the organizing
company) has existed since 2000. Thus, participation prior to 2009 was operationalized as the
total number of times an organization participated in a BPTW competition between 2000 and
2008, whereas rankings prior to 2009 was operationalized as the total number of times that an
organization was ranked between the years 2000 and 2008. We also controlled for any changes
in reported compensation across the study period, to account for a plausible alternative
explanation for voluntary turnover. For example, it is possible that mobility or identity processes
would materialize if compensation was relatively lower or higher, respectively. Participating
organizations were asked on the employer survey to report average salary levels for their exempt
and non-exempt workforces in each year of the competition under study (2009-2012). Specific
items on the employer survey were, “Average annual salary for exempt employees (including
partners if salaried)” and “Average annual salary for non-exempt employees.” We computed a
percentage change in exempt and non-exempt salaries from 2009 to 2012. Finally, we controlled
for lagged (2009) voluntary turnover rates when examining 2012 turnover rates (Wright et al.,
2005).
Analysis Approach
24
We tested Hypotheses 1-5 using hierarchical regression analysis and Hypotheses 6-7
using random coefficient modeling (RCM). For the RCM analyses, we only examined
organizations that had never been ranked before (i.e., were either ranked or not for the first time
in 2009), to allow for conclusions about the effects of first-time and subsequent rankings. We
followed Bliese and Ployhart’s (2002) four-step process for conducting RCM (see also, Dunford,
Shipp, Boss, Angermeier, & Boss, 2012). In the Level 1 analyses, we first estimated the
intraclass correlation coefficient, ICC(1), to establish that there was sufficient betweenorganization variance in turnover to justify continued analyses between organizations across
time. Second, we used orthogonal polynomial terms representing linear and quadratic trends to
model proposed changes in turnover and increases or decreases in those changes over time.
Third, we investigated whether there was between-organization variance in the intercepts and
slopes (i.e., a random effect as well as fixed effect). This demonstrates potential differences in
baseline turnover, as well as trajectories of turnover, across companies. Fourth, we tested
autoregressive, unstructured, and autoregressive-heterogeneous error structures given the
likelihood that error terms could be correlated across time with the use of repeated measures.
Following these initial tests, we added the Level 2 ranking term (i.e., whether a given
organization was consistently ranked (coded 1) or unranked (coded 0) from 2009-2011). This
term was then tested as a predictor of the intercept, slope and curvature of turnover over time.
All RCM analyses were conducted using the SPSS linear mixed model function and restricted
maximum likelihood estimation. This estimation method allows for missing data in one or more
measurement periods, whereas traditional methods employ listwise deletion which can
considerably reduce sample size. For our purposes, we required that organizations completed at
least two of the four surveys from 2009-2012 to be included.
25
RESULTS
Means, standard deviations, and correlations for the organizational level data appear in
Table 1. Visual inspection of the data revealed the possibility of outlying cases in which turnover
was erroneously reported by company representatives.1 Thus, in testing Hypotheses 1-5, we
identified and removed cases from the final analyses that met both of the following criteria. First,
we screened for outliers using Bollen and Jackman’s (1990) low screening criteria for the
standardized dFits diagnostic statistic. According to these authors, this statistic offers a balance
between identifying studentized residuals and influential cases. Second, for those cases identified
as potential outliers, we also examined the raw data to ensure that reported turnover between
2009 and 2012 was at least four times different. This process resulted in 22 cases being removed
from these analyses, yielding a final sample size of 493. For the RCM analyses, because we were
interested in the pattern of turnover across adjacent years rather than just an overall change from
2009 to 2012, we also removed cases in which turnover between adjacent time periods was at
least four times different. This yielded a final sample of 448 organizations for these analyses.
Unit Level Analyses
Hypotheses 1 and 2 were competing hypotheses proposing either a negative (i.e., identity
perspective) or positive (i.e., mobility perspective) relationship between BPTW rankings and
turnover rates. After entering control variables in the first step, we regressed 2012 turnover on
the number of rankings achieved between 2009-2011. Results revealed a negative relationship
between rankings and turnover (β = -.09; R2 = .01; p < .05), providing support for the identity
perspective (Hypothesis 1) but not the mobility perspective (Hypothesis 2).
For example, one survey response indicated “0.3” for turnover, which could mean 0.3%, or
30%. In another case, an organization reported 86% turnover in 2009, but then 4%, 2%, and 2%
turnover in 2010-2012, respectively. Here, it could be the case that a respondent was indicating
“86 employees turned over” in 2009, rather than 86% turnover.
1
26
Hypothesis 3 proposed that the main effect of rankings on turnover rates would be
moderated by organization size, such that effects would be stronger among smaller companies.
This hypothesis was supported. As shown in Table 2 and illustrated in Figure 3, the relationship
between rankings and turnover was negative among smaller organizations and essentially flat
among larger organizations (β = .27; R2 = .01; p < .05).
Hypothesis 4 proposed that the rankings-turnover rate relationship would be moderated by
workforce age, such that effects would be stronger among organizations with younger
workforces. This hypothesis was supported. As shown Table 3 and illustrated in Figure 4, the
relationship between rankings and turnover was negative among organizations with younger
workforces and essentially flat among organizations with older workforces (β = .19; R2 = .01; p
< .05).
Hypothesis 5 proposed that the rankings-turnover rate relationship would be moderated by
baseline workforce satisfaction, such that effects would be negative among organizations with
initially more satisfied workforces and positive among organizations with initially less satisfied
workforces. The interaction term was significant (β = -.16, R2 = .01; p < .05), but the hypothesis
was only partially supported. Figure 5 shows that the relationship between rankings achieved
from 2009-2011 and turnover reported in 2012 was negative among organizations with
workforces that were more satisfied as of 2009. However, among organizations with less satisfied
workforces, this relationship also exhibited a negative, but non-significant, slope. Thus, among
more dissatisfied workforces, BPTW rankings do not appear to impact turnover rates.
Turnover Trend Analysis: Random Coefficient Modeling
Hypotheses 6 and 7 examined turnover trends across the four-year (2009-2012) time
period, comparing turnover rates in organizations that were (1) ranked for the first time in 2009,
27
and subsequently ranked in the next two years, to organizations that (2) failed to achieve a
ranking during this time. Following Bliese and Ployhart’s (2002) four-step procedure, the ICC(1)
value indicated that 77% of the variance in turnover was due to between-organization factors.
Second, tests of fixed effects revealed neither a linear (γ = -1.25; n.s.) nor quadratic (γ = .42; n.s.)
trend for the sample as a whole. However, in keeping with our theory, we retained both terms in
subsequent steps to test for differences between ranked and unranked organizations (e.g., Snijders
& Bosker, 1999). Third, we found that model fit improved significantly with a random intercept
(χ2diff (1) = 587.1, p < .01). Further improvement was discovered with the addition of a random
linear term (χ2diff (1) = 24.1, p < .01), as well as a random quadratic term (χ2diff (1) = 6.9, p < .01).
Combined, these results imply that organizations differ in their baseline level of turnover, as well
as the rate of change and acceleration/deceleration over time. Finally, after testing various error
structures, we found that the autoregressive, heterogeneous structure provided the best fit (χ2diff
(4) = 24.2, p < .01), and was thus retained in all further analyses. The final baseline model appears
in Table 5 (Model 1).
To test Hypotheses 6-7, we added the ranking dummy variable as a Level 2 predictor
(Table 5, Model 2), as well as the linear x ranking and quadratic x ranking terms (Table 5, Models
3 and 4). As shown, consistently ranked organizations exhibited lower initial turnover than nonranked organizations (γ = -3.02; p < .01), but did not exhibit a stronger decrease in turnover over
time than non-ranked companies (γ = -.05; n.s.). However, Model 4 results show that quadratic
trends differ across these groups (γ = .68; p < .05). Figure 7 provides a graphic depiction of these
results, and illustrates a pattern more consistent with Hypothesis 6 (i.e., the celebrity effect).
Specifically, graphic and statistical results indicate that, compared to unranked companies, the
sharpest decrease in turnover occurs following a first-time ranking, with turnover essentially
28
leveling off but remaining lower following a second consecutive ranking. This pattern is
consistent with the celebrity hypothesis, suggesting that the greatest benefits of third party
employment branding occur at its outset, yet diminish over time.
However, whereas the results for the period 2009-2011 are most consistent with the
celebrity hypothesis, the pattern following a third consecutive ranking is unexpected, showing an
increase in turnover, essentially back to original levels (albeit still lower than among non-ranked
organizations). This partially explains the lack of a significant difference in overall linear trends
across groups. Thus, overall we find partial support for Hypothesis 6 (celebrity effect) and no
support for Hypothesis 7 (crystallization effect).
DISCUSSION
This study combines and advances the turnover and employment branding literatures by
developing and testing predictions regarding the effects of third party employment branding on
turnover rates across a four-year period. Specifically, we draw on signaling theory to explain
why organizations might invest in efforts to engage third parties in employment branding efforts,
via providing credible hard-to-fake signals to current employees. These signals ostensibly
communicate to employees that they are employed at great places to work and are best served by
remaining with their organization. Thus, we extend previous research on employment branding
in two critical ways. First, we move beyond work that has mostly considered employment
branding for purposes of attracting talent, by considering the equally if not more important issue
of retaining talent. Second, we specifically consider branding that is initiated by third party
sources, rather than generated by the organization itself. We also provide a unique study of third
party employment branding that makes use of actual data gathered during a recognized
certification process (i.e., BPTW competitions); answer calls from employee turnover scholars to
29
study the effects of organizational reputation (e.g., Holtom et al., 2008); and provide evidence
about the likely efficacy of investing in BPTW competitions for organizations considering these
investments.
Consistent with calls for more investigations that examine alternative explanations for
turnover (e.g., Holtom et al., 2008), we proposed competing identity and mobility perspectives to
explain potential relationships between third party employment branding and subsequent
turnover rates. In general, we find more support for identity effects: BPTW rankings are
significantly negatively related to subsequent turnover rates even while controlling for baseline
turnover, previous participation and rankings in BPTW competitions, and changes in
compensation across a four-year period with three ranking cycles. This finding is consistent with
our argument that third party employment branding as a great place to work can help embed
current employees in the organization and increase the tendency for those employees to identify
with the organization. This finding also suggests that the internal signaling effect of third party
branding outweighs any possible effects that could yield increased mobility via signaling
employee quality to the external market.
We also found support for proposed susceptibility and sham effects: relationships with
turnover rates depend on characteristics of the organization and the workforce. In particular, our
results suggest that third party employment branding efforts are more effective in reducing
turnover in smaller organizations; among organizations with younger workforces; and in
workplaces where baseline employee satisfaction is relatively higher. These results extend the
unfolding model of turnover by specifying examples of groups likely to share elements of preexisting schema that influence responses to system-wide shocks, which in our context can be
considered positive shocks. Smaller organizations may have fewer resources to invest in third
30
party branding efforts, so it is useful to provide evidence that they may benefit to a greater extent
from these third party certifications. Organizations also sometimes struggle to retain younger
workers. In our sample, whereas younger-workforce turnover was unsurprisingly higher overall,
BPTW rankings narrowed the turnover gap between younger and older workforces considerably.
The observed sham effect also extends signaling theory by considering the effects of
potentially conflicting signals. The third party branding signal in this case had less of an impact
on turnover rates in organizations with relatively less satisfied workforces to begin with. This
suggests such signals may be less effective when they are at odds with pre-existing perceptions.
This is quite similar to the suggestion in the unfolding model of turnover that one of the key
mechanisms explaining reactions to shocks is the evaluation of fit or misfit with pre-existing
schema (Lee et al., 1999). Signaling theory suggests the possibility of sending fake or dishonest
signals; our results suggest it would not be effective for organizations to attempt to communicate
signals that are at odds with the experience of many employees in their workforces, prior to
actually developing their organization into a great place to work. On the other hand, the effects
of rankings appear to be stronger when the bulk of the workforce experiences the work
environment in a manner consistent with the third party branding signal.
We also develop celebrity and crystallization perspectives to examine temporal effects
associated with repeated third party employment branding certifications over time. Our results
are more consistent with a celebrity effect, in that there appears to be initially stronger decreases
in turnover following first-time third party employment branding, but diminishing returns in
terms of turnover reduction with repeated endorsements. In fact, our data suggest that repeated
rankings could eventually lose their efficacy altogether: for organizations repeatedly ranked,
turnover rates decline subsequent to the first ranking, but return to initial levels following a third
31
successive ranking. This is another important extension to signaling theory and the unfolding
model of turnover. Repeated signals or shock events may not only get weaker; they may also
lose their efficacy altogether.
There are several possible explanations for this observed pattern of results. One is that the
identity enhancing effects of third party employment branding diminish or even extinguish after
the initial signal. That is, learning for the first time that one’s organization is a BPTW enhances
organizational identification, in line with work examining celebrity firms (Pfarrer et al., 2010;
Rindova et al., 2006). However, learning that one’s organization is still a BPTW, and thus enjoys
an enhanced reputation gained through longer-term signal consistency (Rindova et al. 2005),
may not further enhance identification. Similarly, whereas an employment-related shock may jar
considerations of withdrawal, repetition of the same shock (at least a positive shock) may not.
Another possibility is that proposed mobility effects take longer to manifest than identity effects.
It may be the case that the internal signaling effects of third party branding are quick and largely
under the control of the organization (i.e. the organization can broadcast the signal directly to
employees); however, external signaling effects to competing employers may take longer to
manifest. Other organizations may not learn about BPTW certifications or the information may
not be as salient in the short run; however, over time and with repeated rankings, competing
organizations may begin to perceive that the BPTW organization is a good source of talent.
Although we recognize that we have not specifically explored these intervening mechanisms in
this study, we believe they offer several fruitful areas in which further turnover and employment
branding studies can expand.
Limitations
32
Although we believe our results contribute to research and theory in several areas, they
should be viewed in concert with some limitations, many of which derive from the archival
nature of these data. First, organization mortality from the sample places limitations on the
generalizability of our results. Specifically, while we were able to track turnover and assess
changes in turnover among companies that continued to compete in BPTW programs,
organizations that initially competed but then ceased competing did not provide ongoing data
once they withdrew. Thus, for example, we were not able to track changes in turnover from 2009
to 2012 among companies that entered BPTW competitions in 2009 but not in 2012.
Second, given the nature of these data, we are unable to directly assess some of the
proposed individual-level processes and mediating mechanisms that underlie the observed
relationships. For example, we suggest that the proposed identity effect is partially a function of
increased individual identification with and embeddedness in the organization, and we conclude
that the effects on individual identification are stronger than the effects on individual mobility.
However, we were not able to isolate and study these individual-level processes. For example, it
is possible that mobility effects are still occurring: it could be the case that the identity effects are
quite strong among employees with limited mobility, but the exit of mobile employees who
experience increased external opportunities attenuates this observed relationship. Future
research that is able to address these individual-level processes would provide valuable
additional insight.
Third, it is possible that baseline turnover among BPTW entrants (i.e., study participants)
was lower than turnover in the population of organizations, which could attenuate observed
effects. That is, it is likely that organizations that seek to enter BPTW competitions are already
among the elite of the population of organizations when it comes to people management
33
practices, or at least perceive themselves that way. This suggests potentially lower turnover on
average among these entrants than among more typical organizations that choose not to compete.
Finally, we recognize potential problems of utilizing company representatives to furnish
organizational level data such as turnover and compensation (Gerhart, Wright, McMahan, &
Snell, 2000). Although these data should ideally be straightforward to access and more reliable
than perceptual measures, organizations may differ in the rigor with which they track these
statistics, and we recognize the potential for misreported data, especially when company
representatives know it is being used in algorithms to determine eventual BPTW rankings.
Practical Implications
Despite these limitations, we believe the results of this study may be valuable to
organization in several ways. First, companies cumulatively spend millions of dollars in annual
BPTW entry fees (Burke, 2010). Our results suggest it is theoretically and practically sound for
organizations to consider investing in third party employment branding, as it appears to decrease
turnover rates. However, beyond justifying expenses of entering competitions for a first time, it
may be even more important to justify costs of entering multiple times. Thus, for example, HR
managers and CEOs need to know whether it is advisable to re-enter after being ranked. They
must also decide how many times they should fail to be ranked before prudence calls for them to
stop trying. Our results suggest initial positive results, but potentially diminishing returns to
multiple rankings such that two consecutive rankings appears to be the optimal number, and
rankings beyond that may actually yield turnover levels more in line with original levels. Of
course, there are likely several other benefits to BPTW success that should be considered, such
as the quantity and quality of applicants a BPTW company receives for its position openings, or
even spillovers to consumer reactions and purchasing patterns. Thus, we do not propose that
34
organizations cease competing in BPTW competitions after only a few years; but rather that they
carefully consider possible turnover effects in concert with other potential advantages and
disadvantages of competing.
Second, our research helps identify the type of companies that likely benefit from
participating. For example, we have shown that beneficial differences in turnover might accrue
to smaller versus larger companies, companies with younger versus older workforces, and
companies with more versus less satisfied workforces. In this latter case, it is interesting to note
that it appears companies cannot “compete” their way to reduced turnover via BPTW success.
That is, if their workforce is relatively dissatisfied to start, it is unlikely that they would be
ranked at all. However, should they somehow become ranked, our evidence suggests that this
form of third party employment branding may not sufficiently convince dissatisfied workers to
remain with the organization. Rather, companies need an initially satisfied workforce for
decreased turnover to materialize.
Third, following the previous point, it seems intuitive that BPTW companies would enjoy
greater employee retention. However, mobility arguments suggest that certain workers (e.g.,
younger) may use their companies’ new rankings as leverage to obtain other jobs, and our results
suggest the possibility that this occurs after several consecutive rankings. Thus, companies may
better target retention efforts at certain groups of employees or monitor turnover patterns more
carefully over time.
Future Research Directions
Several future research directions are possible, and we encourage scholars to continue
investigations in this area. For example, while turnover is an important outcome of BPTW
success, future work should examine other potential outcomes, such as longer-term financial
35
metrics, applicant pool characteristics, or even product marketing benefits that emanate from
one-time or a continued pattern of third party employment branding certifications. Our initial
attempt to develop theoretical perspectives could be overlaid on these additional studies. For
example, it might be that although the celebrity effect seems more explanatory than the
crystallization effect in regard to turnover, the opposite could be the case in regard to applicant
pool outcomes, with job seekers requiring a more consistent pattern of rankings (and thus
enhanced reputation) before they act on them. Current employees, already being more familiar
with their employees than job seekers, may react more quickly to third party signals such as
BPTW rankings. Likewise, current consumers might quickly increase their loyalty to companies
that are certified as treating their employees well, whereas consumers currently using competing
products might require more stability in ranking patterns before they will switch product
allegiances because of a positive employee relations record. These suggestions also raise the
interesting possibility of spillover effects from third party employment branding to increases in
product brand image. For example, sources suggest that certain consumer groups – particularly
younger consumers – account for aspects of organizations such as corporate social responsibility
when making purchasing decisions (e.g., Jayson, 2006). It is possible that certifiable perceptions
of employment practices could also have this effect.
In terms of how long it takes for third party employment branding effects to materialize
and how they persist, we have identified and tested two possible trends by which turnover might
increase with continued success in BPTW competitions. However, other trends are possible, such
as a one-time BPTW ranking followed by a non-ranking. Outcome sustainability has been
explored in areas such as personnel selection and strategic HR. In this latter area, for example,
Wright et al. (2005) addressed causality of HR practices on firm performance. They used a time
36
lag of fifteen months, but called for studies to employ even longer time spans. For example, an
adoption-diffusion trend derives from classic adoption-diffusion s-curve models of new product
acceptance (e.g., Rogers, 1962) and combines celebrity and crystallization trends. Specifically,
this model suggests that early acceptance is slow and limited to “innovators” and early adopters,
but is followed by an exponential increase as momentum builds among early and late majorities.
Finally, acceptance slows at later stages. These and other possible reaction trends should be
further tested as third party employment branding research continues to expand.
Finally it would be fruitful to examine how the organization itself reacts to third party
employment branding episodes. For example, a control theory perspective (Carver & Scheier,
2000) would suggest that BPTW-successful companies might “rest on their laurels” and not take
further steps to enhance their people-management offerings. Yet other firms might build on their
success and seek to further differentiate themselves from competitors on employee-related
issues. Or, firms that are not initially successful might redouble efforts to achieve ranking
success. In turn, how an organization reacts to BPTW success or lack of success may play a role
in determining ultimate levels of turnover or decreases in turnover in the years following one or
more rankings. We view our current research as but a starting point for these types of continued
investigations.
37
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43
Table 1: Means, Standard Deviations, and Correlations among Study Variables a
Variable
Mean
SD
1
2
3
4
1. BPTW participation pre2009
.94
1.19
2. BPTW rankings pre-2009
.91
1.43
3. Percent change in nonexempt salaries, 2009-2012
6.82 22.96
.01
.01
4. Percent change in exempt
salaries, 2009-2012
10.05 43.15
.02
.02
.51**
5. Turnover 2009
11.13 10.30
.08
.07
-.02
.05
5
6
7
8
9
.90**
6. Organization Size b
.67
.47
.02
.02
.01
.05
.16**
7. Workforce Age
4.03
.45
.08
.07
.06
.03
-.14**
.04
8. Workforce Satisfaction
4.37
.25
.05
.11*
-.01
-.03
-.23**
-.12*
-.04
9. Rankings, 2009-2011
2.07
1.10
.20**
.21**
-.02
-.05
-.10*
-.10*
-.02
.54**
10. Turnover 2012
10.32 9.27
.06
.02
-.01
.02
.48**
.13**
-.24**
-.10*
-.13**
N = between 392 and 493.
a
b
Turnover and salary descriptive statistics are percentages (i.e., “6.82” means 6.82%).
Coded as 0 = small; 1 = large
* p < .05; ** p < .01
44
Table 2: Regression Results with Organization Size Moderator a
Variables
Model 1
Model 2
Model 3
Model 4
Control Variables
BPTW participation pre-2009
BPTW rankings pre-2009
Change in non-exempt
salaries 2009-2012
Change in exempt
salaries 2009-2012
Turnover 2009
.18
-.18
.18
-.16
.18
-.16
.19
-.17
.01
.01
.01
.01
-.01
.45**
-.02
.43**
-.02
.42**
-.02
.42**
-.14**
-.14**
-.28**
.05
-.17
Independent Variable
BPTW rankings 2009-2011
Moderating Variable
Organization size
Interaction Term
BPTW rankings x size
R2
a
.27*
.21**
.02*
.00
.01*
Standardized regression coefficients shown. Dependent variable is 2012 turnover.
* p < .05
** p < .01
45
Table 3: Regression Results with Workforce Age Moderator a
Variables
Model 1
Model 2
Model 3
Model 4
Control Variables
BPTW participation pre-2009
BPTW rankings pre-2009
Change in non-exempt
salaries 2009-2012
Change in exempt
salaries 2009-2012
Turnover 2009
.15
-.15
.16
-.14
.17
-.13
.17
-.14
.01
.01
.02
.01
-.01
.48**
-.02
.47**
-.02
.44**
-.01
.44**
-.09*
-.10*
-.10*
-.19**
-.35**
Independent Variable
BPTW rankings 2009-2011
Moderating Variable
Workforce age
Interaction Term
BPTW rankings x age
R2
a
.19*
.24**
.01*
.03**
.01*
Standardized regression coefficients shown. Dependent variable is 2012 turnover.
* p < .05
** p < .01
46
Table 4: Regression Results with Workforce Satisfaction Moderator a
Variables
Model 1
Model 2
Model 3
Model 4
.15
-.15
.16
-.14
.18
-.16
.20*
-.18
.01
.01
.01
.01
-.01
.48**
-.02
.47**
-.02
.48**
-.02
.48**
-.09*
-.13**
-.17**
.09
.24**
Control Variables
BPTW participation pre-2009
BPTW rankings pre-2009
Change in non-exempt
salaries 2009-2012
Change in exempt
salaries 2009-2012
Turnover 2009
Independent Variable
BPTW rankings 2009-2011
Moderating Variable
Workforce satisfaction
Interaction Term
BPTW rankings x satisfaction
R2
a
-.16*
.24**
.01*
.01
.01*
Standardized regression coefficients shown. Dependent variable is 2012 turnover.
* p < .05
** p < .01
47
Table 5: Random Coefficient Models Predicting Turnover over Time
Model 1
γ
SE
Model 2
t
γ
SE
Model 3
t
γ
SE
Model 4
t
γ
SE
t
Variables
Intercept
11.31
.57 19.89
12.31 .64
19.17** 12.28 .69 17.80** 12.06 .69
BPTW participation
pre-2009
2.00
1.02 1.96
1.77 .97
1.82
1.81 .95 1.91
1.93 .95
2.04*
Linear
-1.25 .52
-1.35 .57 -2.37*
-.59 .68
-.87
Quadratic
Ranking
Linear x Ranking
Quadratic x Ranking
.42
.17
-2.39
-1.39 .51
-2.76**
2.46
.45 .16
2.76**
.45 .17
2.64**
-3.02 1.01 -2.99** -3.00 1.09 -2.74**
-.05 .46
-.12
.18
.21
-2.86 1.09
17.58**
.84
-2.62**
-1.88 1.02 -1.84
.68
.33
2.03*
N = 448 organizations.
* p < .05
** p < .01
48
Figure 1: Hypothesized Effects of BPTW Ranking on Turnover
49
Figure 2: Hypothesized Celebrity Turnover Trend
50
Figure 3: Hypothesized Crystallization Turnover Trend
51
Figure 4: Moderating Effect of Company Size on the BPTW Rankings-Turnover Relationship, 2009-2012
52
Figure 5: Moderating Effect of Workforce Age on the BPTW Rankings-Turnover Relationship, 2009-2012
53
Figure 6: Moderating Effect of 2009 Workforce Satisfaction on the BPTW Rankings-Turnover Relationship, 2009-2012
54
Figure 7: Trajectories of Turnover for Consistently Ranked and Unranked Companies between 2009-2012.
55