Content uploaded by Florian Kunze
Author content
All content in this area was uploaded by Florian Kunze on Feb 11, 2020
Content may be subject to copyright.
LINKING EMPLOYER BRANDING ORIENTATION AND FIRM
PERFORMANCE:
TESTING A DUAL MEDIATION ROUTE OF RECRUITMENT
EFFICIENCY AND POSITIVE AFFECTIVE CLIMATE
This Document is in Press at Human Resource Management. It is a post-review prepublication of this
manuscript. Please refer to Human Resource Management for the proof-read final version of the
manuscript:
https://onlinelibrary.wiley.com/doi/full/10.1002/hrm.21980
Please cite as:
Tumasjan, A., Kunze, F., Bruch, H., & Welpe, I. M. (2020). Linking employer branding orientation
and firm performance: Testing a dual mediation route of recruitment efficiency and positive affective
climate. Human Resource Management, 59(1), 83-99., DOI: doi.org/10.1002/hrm.21980
2
Abstract
Faced with competitive labor markets, firms increasingly use employer branding to build a
qualified workforce and engage their employees. However, our understanding of the impact of
employer branding orientation on firm performance and the theoretical firm-level mechanisms
underlying this potential impact is very limited. To address this gap, we integrate brand
marketing theory with human resource management (HRM) research to develop a model
explicating how employer branding orientation is linked to firm performance through a dual
route by enhancing both recruitment efficiency (i.e., external route: applicants) and positive
affective climate (i.e., internal route: incumbent employees). The results of a multi-source study
(i.e., top management, human resource managers, employees) with N=93 firms show that
employer branding orientation is positively related to firm performance through positive
affective climate but not recruitment efficiency. Using a brand equity approach to HRM, our
results advance the literature by demonstrating the generalizability of employer branding effects
independent of concrete brand attributes and explaining the firm-level mediating mechanisms
linking it to firm performance.
Keywords: employer branding, firm performance, recruitment, positive affective climate,
human resource management
3
Introduction
Building, sustaining, and engaging a qualified workforce is crucial for organizational
success and therefore of the most important goals of human resource management (HRM;
Collings & Mellahi, 2009; Taylor & Collins, 2000). To attract and engage employees in
increasingly competitive labor markets, many firms have started to strategically manage their
employer brand, both externally toward potential applicants and internally toward incumbent
employees (Martin, Gollan & Grigg, 2011). Building on concepts from brand marketing, this
integrated HRM approach has been termed employer branding, which aims at “internally and
externally promoting a clear view of what makes a firm different and desirable as an
employer” (Lievens 2007: 51).
While employer branding is a concept that resides at the firm-level of analysis, prior
research has mainly investigated employer branding antecedents and outcomes at the
individual-level of analysis (for review, see Theurer, Tumasjan, Welpe, & Lievens, 2018),
which constitutes a limitation of the field. This is a major limitation because “[f]indings at one
level of analysis do not generalize neatly and exactly to other levels of analysis […] and
therefore ”[t]o blindly generalize findings across levels of analysis is to commit a fallacy”
(Klein & Kozlowski, 2000: 213). Thus, the current state of research – showing that employer
branding has positive effects on individual level outcomes – does not allow generalizing on
potentially positive effects at the firm level. Therefore, it remains theoretically unclear
whether employer branding actually influences firm-level outcomes (Francis & Reddington,
2012) or whether there are only individual-level effects.
Relatedly, whereas extant conceptual propositions (e.g., Backhaus & Tikoo, 2004)
speculate that employer branding will have positive firm-level effects, the current empirical
literature is surprisingly silent on employer branding’s effects on firm-level mediating
mechanisms and outcomes (Theurer et al., 2018, notable exceptions include Turban & Cable,
2003; Collins & Han, 2004). Finally, the overwhelming majority of employer branding
4
research has focused on the role of employer branding in the very early applicant generation
phase (e.g., Collins & Stevens, 2002; Holtbrügge, Friedmann, & Puck, 2010). In this vein,
extant research has mainly concentrated on identifying concrete employer brand attributes
(e.g., prestige or location; Cable & Graham, 2000; Lievens & Highhouse, 2003; Van Hoye,
Bas, Cromhecke & Lievens, 2013) rather than testing a generalizable model of employer
branding and its effects at the firm level. Thus, from a firm’s perspective it is currently
unclear if and how employer branding translates into firm performance (Sung & Choi, 2014).
Recognizing these limitations, scholars have called for research addressing the effects of
employer branding on firm performance and investigating the underlying mechanisms of this
effect (e.g., Ambler & Barrow, 1996; Phillips & Gully, 2015) in order to “identify the
mediators that operate between the employer branding program and the firm’s profit margin
or profit growth” (Backhaus & Tikoo, 2004, p. 512).
To address this unresolved puzzle in the current literature, we reconceptualize the
extant approach to studying employer branding by introducing the construct of employer
branding orientation. As an overarching HR guiding principle at the firm level (Becker &
Gerhart, 1996), the construct reflects the notion of firms putting a high value on employer
brand building by seeking to actively promote the employer brand externally and internally.
Hence, we argue that, on the one hand, employer branding orientation facilitates building a
distinct and an attractive external employer image (Lievens, 2007), which may lead to
improved recruitment efficiency, such as the time to hire and cost per hire (Laumer, Maier, &
Eckhardt, 2015; Ulrich, 1997). On the other hand, employer branding orientation may also
positively impact incumbent employees’ positive affective climate, i.e., “the shared
experience of positive affect within an organization” (Menges, Walter, Vogel & Bruch, 2011,
p. 894). Ultimately, we assume that both improved employee recruitment efficiency and
positive affective climate will enhance firm performance (Jiang et al., 2012; Shaw, Gupta &
Delery, 2005).
5
We make four major contributions to the literature. First, integrating branding theory
from the field of marketing with HRM research, we reconceptualize employer branding as a
guiding “HR principle” (Becker & Gerhart, 1996), by introducing the concept of employer
branding orientation, capturing the extent to which firms uphold employer branding as a
principle that is strategically important to build employer brand equity (Collins & Stevens,
2002). Thereby, we build and test theory at the firm-level of analysis and advance employer
branding research, which currently bases almost all firm-level claims on individual-level
studies (e.g., Han & Ling, 2016; for review, see Theurer et al., 2018).
Second, by conceptualizing and measuring employer branding at the level of a guiding
HR principle (Becker & Gerhart, 1996), we advance extant research by making it possible to
empirically test the generalizability of employer branding effects beyond concrete attributes.
Prior research has conceptualized employer branding in terms of concrete brand attributes
(e.g., “sincerity” or “ruggedness”; Lievens & Highhouse, 2003; see also Aaker, 1997; Aaker
& Fournier, 1995) residing at the concrete “HR practice” level (Becker & Gerhart, 1996), and,
therefore, their effect is contingent on specific firm characteristics. Thus, it is not clear from
extant studies whether employer branding can be considered part of “best practice” HR
approaches from a so-called “universalistic” theoretical viewpoint as conceptualized by
Delery & Doty (1996). We hence contribute to the literature by showing how employer
branding’s effects may be conceptualized at the guiding-principle level (Becker & Gerhart,
1996).
Third, addressing several calls in the literature, we explicate firm-level mechanisms
underlying the effect of employer branding on firm performance (Backhaus & Tikoo, 2004).
Our study yields a novel explanation for how employer branding orientation influences firm
performance through its impact on different key HR performance indicators (i.e., recruitment
efficiency and positive affective climate) in different target groups (i.e., potential employees
and current employees). Our study thereby also speaks to extant research on the concept of
6
marketing as auto-communication (Christensen, 1997) reflecting that firms’ employer
branding activities re-confirm their culture toward different audiences.
Fourth, we advance the field by investigating whether and how employer branding
impacts employees’ collective emotions as repeatedly suggested the literature (e.g., Lievens &
Slaughter, 2016). Since employer branding aims at creating positive emotional responses in
its target groups, it is surprising that there is a dearth of research on emotional outcomes
(Rampl, 2014). To address this limitation, we theorize and test how employer branding
influences positive affective climate as a mediating mechanism for its impact on firm
performance.
Theory and hypothesis development
Employer branding and firm-level outcomes
In the past decades, a literature stream integrating research from the field of marketing
with HRM research has been emerging, mainly focusing on the notion of brands and branding
in HRM (Martin et al., 2005; Russell & Brannan, 2016; Timming, 2017). At the core of this
stream is the insight that brands, branding, and reputation play an important role in HRM and
may influence key HRM processes and outcomes (Edwards, 2017; Theurer et al., 2018). In
their seminal article, Ambler and Barrow (1996) conceived employer branding as an
application of brand marketing principles to improve key HR outcomes, such as applicant
attraction, recruitment efficiency, current employees’ engagement, to ultimately increase firm
performance. In short, employer branding usually involves a three-step process (Backhaus &
Tikoo, 2004; Lievens, 2007). First, firms create a unique and differentiating employer value
proposition, which serves as the central message positioning the value that the firms offer to
their employees (Backhaus & Tikoo, 2004), such as organizational culture, leadership styles,
employment benefits (Backhaus & Tikoo, 2004; Dineen & Allen, 2016). In the second and
third steps of the employer branding process, the employer value proposition is marketed to
7
potential applicants and promoted to incumbent employees (Backhaus & Tikoo, 2004; Francis
& Reddington, 2012; Lievens, Van Hoye & Anseel, 2007). Thus, the goal of employer
branding is to position the employment experience as attractive and distinctive from other
employers (Lievens, 2007) and to promote it to both an external (labor market) and an internal
(firm) audience to enhance key HR outcomes and, as a result, contribute to firm performance
(see also Christensen, 1997).
The existing employer branding literature has mainly investigated the attributes that
make up employer brands from the applicants’ perspective (e.g., Lievens & Highhouse,
2003), the influence of recruitment practices on applicants’ employer images (e.g., Collins &
Han, 2004), and the influence of employer brands on the early-stage applicant outcomes (e.g.,
Collins & Stevens, 2002).
In what has become the dominant employer branding framework, Lievens and
Highhouse (2003) have conceptualized employer brands as consisting of instrumental (e.g.,
pay, benefits or career advancement) and symbolic (e.g., prestige, innovativeness or
competence; Lievens, 2007) employer image attributes. Building on this framework, most
employer branding studies have investigated the concrete attributes of employer brands (e.g.,
Berthon, Ewing & Hah, 2005; Edwards & Edwards, 2013) and their influence on potential
applicants’ reactions, at the individual level, such as perceived organizational attractiveness
and job choice intentions (e.g., Baum & Kabst, 2013; Collins & Stevens, 2002).
However, while these studies provide valuable insights on the effects of different
brand attributes from the applicants’ perspective, a key issue from the firm-level perspective
(i.e., HRM and general management) is whether and how employer branding actually
translates into tangible desired HR outcomes, such as enhanced employee recruitment and
engagement, that in turn contribute to firm performance (Backhaus & Tikoo, 2004). Some
studies have started to investigate the effects of employer reputation and recruitment practices
on employer brand awareness and employer image on firm-level outcomes. However, these
8
studies focused solely on applicant outcomes, such as applicant pool quantity and quality
(e.g., Cable & Turban, 2003; Collins & Han, 2004; Dineen & Williamson, 2012) rather than
incumbent employees. Thus, while there are a few studies investigating the influence of
employer branding on incumbent employees at the individual level of analysis (e.g., Hanin et
al., 2013; Lievens et al., 2007), research on employer branding’s impact on incumbent
employees at the firm-level is scant. In this vein, Gardner, Erhardt & Martin-Rios (2011) have
called researchers to investigate the impact of employer branding on incumbent employees.
Similarly, a major limitation constitutes the dearth of research on employer branding’s effects
on firm performance and the underlying mediating mechanisms (Theurer et al., 2018) which
we will focus on in the next sections.
Employer branding orientation as a guiding HR principle at the firm level
To address the question if and how employer branding translates into these firm-level
outcomes, we introduce the concept of employer branding orientation to the literature. In
marketing research, brand orientation describes “an approach in which the processes of the
organization revolve around the creation, development, and protection of brand identity in an
ongoing interaction with target customers, with the aim of achieving lasting competitive
advantages in the form of brands” (Urde, 1999, p. 117). Applying this concept to employer
branding, we define employer branding orientation as an approach in which the HRM
processes revolve around the creation, development, and protection of employer brand equity
in an ongoing interaction with potential and incumbent employees to achieve sustainable
competitive advantages in the labor market.
We conceptualize employer branding orientation as an overarching HR guiding
principle (Becker & Gerhart, 1996) reflecting an approach that applies “brand thinking to
people management” (Mosley, 2014, p. 1). Such guiding principles describe firms’ general
HRM principles and reside at the most abstract level of an HR system (Posthuma, Campion,
9
Masimova, & Campion, 2013). Becker and Gerhart (1996) were among the first to distinguish
between levels of abstraction in HR systems and reasoned that “it is at this level within the
HR system that effects are ‘generalizable or universal’” (Monks et al., 2013, p. 380). Extant
research has demonstrated that it is important to adopt a multiple level perspective to HRM
and examine effects on their respective level as well as in a cross-level manner (Ostroff and
Bowen 2000, 2004, 2016; Jackson et al., 2014; Paauwe, 2009; Peccei & Van De Voorde,
2016; Renkema et al., 2016).
Building on Becker and Gerhart’s (1996) reasoning, we assume that specific employer
brand attributes or contents (e.g., prestige, freedom, innovativeness) reside at the practice
level of abstraction, and their effects on HR outcomes and firm performance may thus not be
generalizable across contexts (Becker & Gerhart, 1996). Thus, conceptualizing employer
branding orientation as a general guiding principle allows us to study the influence of
employer branding independent of concrete policies and practices (e.g., certain brand
attributes, such as “excitement” or “sincerity”) or reputation rankings (e.g., Fortune
magazine), the use and resulting effects of which may depend on specific firm characteristics.
For instance, “excitement” as an employer brand attribute may not work for every firm and
being listed in Fortune reputation rankings may not be possible for small and medium-sized
firms. Therefore, our novel conceptualization goes beyond employer brand attributes at the
practice level, that have been used in past research, toward conceptualizing employer
branding at the level of a higher-order principle to examine whether its effects on firm-level
outcomes are generalizable (Becker & Gerhart, 1996; Colbert, 2004). In this regard, we
follow the so called “universalistic” theoretical perspective (Delery & Doty, 1996) which
reflects the view that there are “best practices” that generally have positive effects on
organizational performance (Becker & Gerhart; 1996). Delery and Doty (1996) contrast the
“universalistic perspective” with the “contingency” perspective and the “configurational”
perspective, which posit that HR practices need to be consistent with a certain firm strategy
10
(contingency perspective) or need to be placed in a certain constellation with other HR
practices (configurational perspective) to successfully contribute to firm performance. In this
sense, our study employs a “universalistic” theoretical perspective because we assume that
more employer branding orientation will in principle always contribute to higher firm
performance (irrespective of a certain firm strategy or certain HR practice configuration) than
less or no employer branding orientation.
To explain why employer branding orientation leads to enhanced HR outcomes and
increased firm performance, we use employer brand equity theory (e.g., Cable & Turban,
2003; Theurer et al., 2018), which is based on the brand equity literature from marketing
research (Keller, 1993; Keller & Lehmann, 2006). Recently, Theurer et al. (2018) have
adapted Keller and Lehmann’s (2006) brand equity model to employer branding and HRM,
creating the employer branding value chain model as an overarching theoretical framework.
Based on this overarching theoretical framework, we argue that employer branding
orientation will lead to enhanced recruitment efficiency (applicant side) and higher levels of
positive affective climate (incumbent employee side), which, in turn, increase firm
performance. Figure 1 displays our conceptual model.
***Insert Figure 1 here***
Employer branding orientation: Effects on recruitment efficiency and positive affective
climate
In the HRM literature there is significant debate about opening “the black box”
between HRM activities and firm performance (see for reviews, Combs, Liu, Hall & Ketchen,
2006; Lepak, Liao, Chung & Harden, 2006). Based on employer brand equity theory (Collins
& Stevens, 2002; Theurer et al., 2018), we therefore theorize on which mechanisms translate
employer branding orientation into firm performance by considering a dual mechanism
11
consisting of HR outcomes related to applicants (i.e., recruitment efficiency; “external route”)
and incumbent employees (i.e., positive affective climate; “internal route”).
Recruitment efficiency. Building on previous work on applicant attraction, we
hypothesize that employer branding orientation will be positively related to firms’ recruitment
efficiency (Backhaus & Tikoo, 2004; Collins & Stevens, 2002; Delery & Roumpi, 2017). In
particular, we argue that higher levels of employer branding orientation will improve the
applicant pool, such that the share of employees that exhibit high levels of fit with the firm’s
needs will increase, which in turn will improve recruitment efficiency (Collins & Han, 2004)
for the following reasons.
Firms that actively market their employer brand and uphold it as an important value
will create higher levels of positive employer brand awareness in their target group (Cable &
Turban, 2001, 2003). At the same time, high levels of employer branding orientation make it
likely that firms successfully communicate a clear picture of what they stand for in terms of
the employment experience, such as corporate culture, values, and employment conditions
(Backhaus & Tikoo, 2004). In turn, this communication should allow job seekers to make
veridical comparisons between their own needs and values and the organization’s culture and
values (Braddy, Meade & Kroustalis, 2006). Thus, candidates perceiving fit with the
employer brand will self-select to apply, whereas candidates that do not see a fit to the brand
positioning will refrain from applying.
Therefore, higher levels of employer branding orientation will increase recruitment
efficiency because the applicant pool will contain relatively more applicants that exhibit fit
with the organization’s culture and values, which will lead to less time and cost required to
appropriately fill a position. In contrast, lower levels of employer branding orientation may
lead to an applicant pool with lower levels of applicant-organization fit. In turn, the firm may
require spending more time and resources per hire – for example because the firm will need to
post further job advertisements if the applicant pool was insufficient in the first round of
12
recruiting. In sum, higher applicant quantity and quality will result in more favorable levels of
recruitment efficiency. Thus:
H1: Employer branding orientation will be positively related to recruitment efficiency.
Positive affective climate. We also hypothesize that employer branding orientation
will be positively related to firms’ levels of positive affective climate. Positive affective
climate describes collective positive employee emotions and has been defined as “the shared
experience of positive affect within an organization” (Menges et al., 2011, p. 894). Positive
affective climate reflects collective emotions that emerge from individual employees’ positive
feelings and are transferred through sharing and contagion among employees (Menges et al.,
2011; Knight, Menges, & Bruch, 2018). While positive affective climate shares the aspect of
positivity with constructs such as job satisfaction and organizational commitment, it is a
distinct construct. First, positive affective climate is a group or organizational level construct
rather than residing at the individual level. Second, positive affective climate is a purely
emotional construct, whereas job satisfaction and commitment also reflect cognitive aspects
(Menges et al., 2011; Knight et al., 2018).
Building on prior employer branding research (Lievens & Slaughter, 2016) and
general branding research from marketing (Keller, 1993; Keller & Lehmann, 2006), we
propose that employer branding positively influences incumbent employees’ positive
collective emotional states, which will be reflected in positive affective climate on the
aggregate firm level (Ashkanasy, Troth, Lawrence, & Jordan, 2017; Menges et al., 2011),
based on the following arguments.
First, employer branding orientation and the resulting employer brand equity will
signal a favorable employer image to employees (Bangerter, Roulin, & König, 2012). As a
result, incumbent employees will likely perceive the employer image to be desirable, which
will lead to higher levels of positive affect (Cable & Turban, 2003; Hanin, Stinglhamber, &
13
Delobbe, 2013; Lievens et al., 2007). For instance, Hanin et al. (2013) showed positive effects
of employer branding on affective commitment at the individual level of analysis. Moreover,
the resulting employer brand equity (Keller, 1993) will foster employees’ identification with
their employer (Backhaus & Tikoo, 2004; Edwards, 2010; Maxwell & Knox, 2009), which
has been shown to be related to higher levels of positive affect (Herrbach, 2006).
Second, individuals derive increased levels of self-esteem and social status from
membership in an organization with an attractive and salient employer brand (Backhaus &
Tikoo, 2004 Cable & Turban, 2001, 2003; Edwards, 2010). Therefore, higher levels of
employer branding orientation may enhance incumbent employees’ perception of working for
an attractive employer and will increase their social status and self-esteem (Lievens et al.,
2007), which should also result in higher levels of positive affective climate. Moreover, prior
research on marketing as auto-communication (Christensen, 1997; Cheney, Christensen,
Conrad & Lair, 2004) suggests that firm branding messages may “instill pride among
employees, enhance an internal esprit de corps and perhaps even stimulate motivation and
productivity-developments” (Christensen, 1997, p. 206), which further supports a positive
effect of employer branding orientation on positive affective climate.
Third, employer branding has been associated with increased activity in brain regions
linked to positive emotions and the reward system (Rampl, Opitz, Welpe, & Kenning, 2016).
In particular, using functional magnetic resonance imaging (fMRI), Rampl et al. (2016)
showed that an employer brand attractive to an individual elicited higher level of activation in
areas linked to positive emotions and the reward system compared to other employer brands.
These results provide support for the link between employer branding and emotion elicitation
(Rampl, 2014), which has also been shown in (consumer) branding research (Chaudhuri &
Holbrook, 2001; Thompson, Rindfleisch, & Arsel, 2006).
14
We assume that these mechanisms at the individual level may become shared among
firm members by translating via contagion and affective sharing socialization processes into
firm-level affective climates (Knight et al., 2018) and thus propose:
H2: Employer branding orientation will be positively related to positive affective
climate.
HR outcomes and firm performance
We now turn to our argumentation on the link between recruitment efficiency and
positive affective climate on the one hand, and firm performance on the other hand.
Recruitment efficiency. Research directly linking recruitment or staffing efficiency
and outcomes at the firm level is relatively scarce (Gully, Philipps, & Kim, 2014; Martins &
Lima, 2006; Rao & Drazin, 2002). In most of the numerous strategic HRM studies, the
influence of recruitment practices on firm performance has been measured only as a part
within HR systems, for example within high-performance work systems (HPWS; e.g., Lepak
& Snell, 2002; Guest et al., 2003; Delery & Roumpi, 2017; Saridakis et al., 2017). For
instance, Huselid (1995) examined recruitment within HPWS using one item assessing the
number of qualified applicants per position. Terpstra and Rozelle (1993), conducted one of
the few studies linking effective staffing and firm performance, demonstrating that effective
staffing is indeed related to profit and profit growth (see also Gully et al., 2014). Further
evidence suggesting a positive effect of recruitment efficiency on firm performance comes
from recent studies in the context of small and medium sized companies. In this vein, Seehan
(2014) finds a positive association between the use of formal recruitment methods and
financial performance as well as innovation, respectively. Similarly, Greer et al. (2016) report
that small firms’ use of effective recruitment practices used in large firms positively
influences perceptual firm performance. In a related study, Kim and Ployhart (2014) show
15
that firms with more selective staffing have greater productivity and profit growth than firms
with less selective staffing.
Accordingly, in line with the extant literature, we argue that recruitment efficiency
may contribute to firm performance. Although efficiency within the HR function may not
necessarily directly translate into increased firm value, HR efficiency can create value through
its influence on efficient business operations. In this vein, Becker et al. (2001) argue that there
may be a “clear line of sight between efficient HR recruiting processes and the firm’s bottom
line through HR’s contribution to improved operating effectiveness” (Becker et al., 2001, p.
54). This notion is supported by firm case studies showing that recruitment efficiency (e.g.,
cost per hire, time to hire) contributes to the bottom line across different industries, such as
banking, health care, and semiconductor industries (Schnars & Kleiner, 2000). Thus:
H3: Recruitment efficiency will be positively related to firm performance.
Positive affective climate. We also propose that higher levels of positive affective
climate will be related to increased levels of firm performance (Ashkanasy & Dorris, 2017;
Parke & Seo, 2017). First, positive affective climate has been shown to relate to higher levels
of aggregate employee productivity, task performance, and organizational citizenship
behavior (Menges et al., 2011). This research has built on broaden-and-build theory
(Fredrickson, 2003) to argue that positive affect will broaden employees’ thought–action
repertoire, reflected in broader mindsets that results in an extended array of actions, such as
explorative behaviors, novel ideas, and creative actions. In turn, employees will be more
likely to build enduring personal resources, such as physical resources, intellectual, and social
resources (Fredrickson, 2004). Both broadened mindsets and actions as well as enduring
personal resources will enable employees to achieve higher levels of productivity (Menges et
al., 2011; Knight et al., 2018), contributing to increased firm performance. We follow this
logic and empirical findings and assume that positive affective climate may also positively
16
contribute to firm performance, which is strongly influenced by these employee-level
behaviors.
Second, previous research has documented that positive affect positively influences
employee performance (for review, see Menges & Kilduff, 2015). For instance, a study by
Tsai, Chen, and Liu (2007) shows that positive affect relates to task performance mediated by
various desirable employee behaviors (e.g., task persistence, helping co-workers). Relatedly,
positive affect has also been shown to increase creativity and innovative behaviors (Baas, De
Dreu & Nijstad, 2008; Baron & Tang, 2011), which also both may contribute to increased
level of firm performance (Rosenbusch, Brinckmann & Bausch, 2011). Supporting this link at
the firm level of analysis, Patterson et al. (2004) have shown that a range of different positive
organizational climates are related to firm productivity. A similar link at the group level was
found by Liu et al. (2014) demonstrating that positive workgroup emotional climate was
associated with increased group performance. Finally, in their comprehensive review, Menges
and Kilduff (2015) document a host of research showing that group-shared emotions have a
positive impact on the performance of both small and large groups. Therefore, we propose:
H4: Positive affective climate will be positively related to firm performance.
Mediated relationship between employer branding orientation and firm performance
through recruitment efficiency and positive affective climate
In line with employer brand equity research (e.g., Backhaus & Tikoo, 2004; Edwards,
2010; Theurer et al., 2018), our basic argument is that higher levels of employer branding
orientation will not enhance firm performance directly but rather will do so through
enhancing key HR outcomes that, in turn, influence firm performance. Building on prior
marketing research (e.g., Wong & Merrilees, 2008), we base our rationale underlying this
mediation hypothesis on the insight that the adoption of an employer branding orientation
(i.e., an intra-organizational inclination) does not necessarily directly result in increased firm
17
performance (Wong & Merrilees, 2008). Rather, employer branding orientation may only
affect firm performance if it first results in enhanced HR outcomes as intermediating
mechanisms. This reasoning is in line with a theoretical account of employer brand equity
building (Cable & Turban, 2001) in which HR principles do not directly lead to firm
performance outcomes but indirectly lead to such outcomes through building brand equity,
which manifests in enhanced applicant-related and employee-related outcomes.
There are further reasons why an employer branding orientation may not directly
affect recruitment and retention processes. First, employer branding orientation may take
some time to develop in the firm and, thus, may fail to directly generate higher levels of firm
performance. Additionally, a firm may adopt an employer branding orientation but may
unsuccessfully implement the necessary operative employer branding activities; this will also
fail to lead to the desired effects. We therefore argue that adopting an employer branding
orientation lays the groundwork for brand success (Cable & Turban, 2001) and that having
such an orientation is necessary but not sufficient for achieving positive firm performance
outcomes.
Thus, considering the extant literature, and based on the employer brand value chain
model (Keller & Lehmann, 2006; Theurer et al., 2018), we assume that employer branding
orientation will be associated with recruitment efficiency and positive affective climate. In
turn, both components will contribute to firm performance (Gerhart, 2007). As a consequence,
we argue that these two HR outcomes are the core theoretical mechanisms that translate
employer branding orientation into firm performance. Building on this argumentation we
propose an indirect, fully mediated effect between employer branding orientation and firm
performance, leading to the following two mediation hypotheses:
H5a: The effect of employer branding orientation on firm performance will be
mediated by recruitment efficiency.
18
H5b: The effect of employer branding orientation on firm performance will be
mediated by positive affective climate.
Method
Sample
We collected data for this study in 93 German small and medium sized firms.
1
The
companies participated in a benchmarking study on various HR-practices and were recruited
and surveyed by an external service provider. To be eligible for participating, companies had
to be located in Germany and should not exceed 5,000 employees, as a cut-off for medium-
sized companies. The companies received a detailed benchmarking report on their HR
practices in exchange for their participation, and could also use their benchmarking position
for third party employer branding activities (e.g., adding a specific label to their job
advertisements) If requested, the firms could also use their benchmarking position for third-
party employer branding. Some of the participating companies (n=21) had missing values of
some of the study’s measures. To avoid potential non-response bias and increase the statistical
power for our analyses we use an expected maximization (EM) technique to impute the
missing values and to calculate all models with 93 firms.
The companies belonged to four different sectors: manufacturing (29%); service
(47%), finance (7%), and trade (16%). A total of 16,254 employees participated in the overall
survey (mean company size: 327 employees), representing an average within-organization
response rate of 73% (range 3-100 percent, SD=25). The participating employees (58% male)
were, on average, 39 years old (SD=11.43) and had an average organizational tenure of 8
years (SD=8.33).
1
One further paper has used the same dataset. There is only one variable overlap (i.e., firm performance)
between the two papers and no bivariate relationships are investigated in both papers. Nonetheless, we carefully
addressed this issue through robustness tests in which we replicated our findings in a model including all
variables from the other paper as controls (for more details, see the result section).
19
We applied a multi-source data sampling approach to limit the likelihood that a
common source bias (Podsakoff, MacKenzie & Podsakoff, 2012) might affect our results.
Therefore, we used three data sources. First, we asked the top human resource manager in
each firm to assess employer branding orientation and several of the control variables (i.e.,
industry sector). Second, we asked 25 percent (n=4,080) of all employees in each company
(randomly selected) to assess the positive affective climate of the company.
2
Third, we
collected information on recruitment efficiency and firm performance from all members of
the top management team (TMT) in each company. The average TMT size was three, and the
TMT members were mainly male (87%), had an average tenure of 13 years (SD=8.92) and
were on average 48 years old (SD=8.84). In 58 companies, more than one TMT member
answered the questionnaire.
Measures
Unless stated otherwise, we used 7-point scales (1=strongly disagree, 7=strongly
agree) for our measures. To justify aggregation procedures for the measures that were
answered by multiple respondents, we inspected common statistical benchmarks such as the
intra-class coefficient (ICC1 and ICC2; Bliese, 2000) and rwg (James, Demaree & Wolf, 1984).
Employer branding orientation (=.84). To measure this construct, we
reconceptualized a general branding orientation scale by Wong and Merrilees (2008). In
particular, we developed the following four items: (1) Employer branding is essential to our
HR strategy, (2) Employer branding is essential in running this company, (3) Long-term
employer brand planning is critical to our future success, (4) Employer branding flows
2
This procedure was applied to limit the amount of question that each employee had to answer for the overall
benchmarking study. There were four other employee surveys with randomly selected 25 percent of the
employees that were not used for this study.
20
through all of our HR activities. A separate confirmatory factor analysis (CFA) indicated
good model fit properties (χ2=16.58, df=2; CFI=.91, IFI=.91, SRMR=.06)
Recruitment efficiency (=.85, ICC1=.30, ICC2=.64; median rwg=.85). Recruitment
efficiency was assessed with two items, time to hire and cost per hire (Ulrich, 1997), which
were answered by the TMT members of each company and were adopted from Münstermann,
Eckhardt & Weitzel (2009; see also Laumer et al., 2015): (1) We are satisfied with the
average time between the identification of a vacancy and the fill of a vacancy and (2) We are
satisfied with our average costs for filling a vacancy. If two or more TMT members provided
responses, their answers were averaged and aggregated to the firm level.
Positive affective climate (=.94 ICC1=.16, ICC2=.89; median rwg=.76). We
measured positive affective organizational climates in line with existing affective climate
measures in the literature (Knight et al., 2018, Kunze & Menges, 2017, Menges et al. 2011).
In more detail we used four items from the Job-Related Affective Well-Being Scale (Van
Katwyk, Fox, Spector, & Kelloway, 2000) to measure how often employees in their
organization experience the respective positive affective states in their jobs on a 5-point scale
from 1 (never) to 5 (extremely often/always). (Sample item: Employees in our company feel
enthusiastic in their job). These items were then aggregated to the firm level of analysis. A
separate confirmatory factor analysis (CFA) indicated good model fit properties (χ2=6.41,
df=2; CFI=.99, IFI=.99, SRMR=.02).
Firm performance (=.82, ICC1=.31, ICC2=.64; median rwg=.86). In line with
existing research (Kunze, Boehm, & Bruch, 2011, 2013), firm performance was assessed by
asking TMT members of each company to rate their firms regarding the following aspects of
operational performance (effectiveness of business procedures, employee productivity,
employee retention) and organizational performance (company growth, financial
performance, return on assets). Consistent with other studies that used perceptual measures of
21
firm performance in multi-industry samples (e.g., Kunze et al., 2013; Delaney & Huselid,
1996; Wall et al., 2004), we asked respondents to assess their organization’s effectiveness
over the last six months compared to that of their main competitors within the same region
and industry (1=far below average; 7=far above average). If two or more TMT members had
answered the question, their responses were averaged per question and aggregated to the
organizational level of analysis.
Controls. We included twelve control variables, which might also affect our outcome
measures. First, we used the 18-item reflective measure of high-performance work practices
(HPWP) (=.85) developed by Datta, Guthrie and Wright (2005), which was answered by the
top HR manager to control for these general HR practices. The scale captured numerous
dimensions of HPWP, such as feedback and reward systems (sample item: How many of your
employees receive formal performance appraisals and feedback on a routine basis? [in %]);
internal training measures (sample item: How many of your employees receive regular
training for firm-specific capabilities? [in %]); career systems (sample item: How many of
your employees have been promoted to a higher hierarchal level since their employment? [in
%]); and recruiting measures (sample item: How many of your employees have been recruited
based on proactive recruitment measures? [in %]). Second, we controlled for the contextual
ambidexterity consisting of adaptive and alignment oriented management systems by using
the eight item scale of Gibson and Birkinshaw (2004) (sample item: The management systems
in this organization evolve rapidly in response to shifts in our business priorities) that was
answered by the top HR manager in each company (=.85), to inspect if the adaption of the
general management systems to complex goals affect firm performance beyond employer
branding orientation. Third, in line with recent research that has investigated effects of
organizational climates on performance (Barrick, Thurgood, Smith & Courtright, 2015), we
controlled for a measure of CEO transformational leadership (TFL) behavior. To assess the
construct employees directly reporting to the CEO in the top management answered seven
22
items (sample item: The CEO leads by example) based on the scale by Rubin, Munz, and
Bommer (2005). These items (=.83) were averaged to form one overall CEO TFL score.
Fourth, firm size, reported by the top HR-representative, was included as a control
variable. Since this measure was skewed, we log transformed it. Fifth, we controlled for age
diversity (operationalized through the standard deviation) and the mean age of the workforce,
since prior studies (i.e., Kunze et al., 2011), have shown that workforce age configurations are
important for organizational processes and outcomes. Sixth, we also accounted for the
dynamism of the organizations’ environment with a one item measure from Jansen, Van Den
Bosch & Volberda’s (2006) scale (The conditions in our key markets change very often;
1=totally disagree; 7=totally agree) rated by the top HR representative. Seventh, we also
incorporated information captured from the top HR-representatives on the recruitment
difficulties experienced by the firm with two items (How difficult is it for your company to
recruit qualified personnel?; How difficult is it for your company to retain qualified
personnel? 1=very easy; 7=very difficult) (=.66), and the current economic situation in the
local region of the company (How bad is the current economic situation in your region,
compared to other regions in Germany?; 1=very bad; 7=very good), as both variables are
likely to affect recruitment efficiency processes and company performance
3
.
Finally, we also controlled for the two main industry sectors in our sample –
production and service – as dummy variables.
3
We included recruitment difficulties as a control variable for two reasons. First, this global measure of hiring
success taps the state of the recruitment processes that might be affected by both external factors (e.g.,
difficulties to attract candidates due to rural company location) and internal factors (e.g., inefficient recruiting
procedures). We thus assume that this measure should be a driver of recruitment efficiency (measured as the
internal efficiency of recruitment processes) and firm performance. Second, as this measure was assessed by the
top HR representative in each company, it also offers us the opportunity to cross-validate the recruitment
efficiency measure that was assessed by members of the top management team in each firm. In line with
theoretical expectations, the recruitment difficulty is negatively and significantly related to recruitment
efficiency (-.35**; see Table 1), indicating that the TMT members indeed assess recruitment related processes.
Further, the moderate correlation size also indicates that both measures are tapping different concepts.
23
Analytical techniques
We used two analytical approaches to establish the measurement structure of our model
test our hypotheses. First, to establish the distinctiveness of our constructs and the overall
measurement structure, we applied structural equation modeling using the AMOS software
package. Second, we used the PROCESS macro developed by Hayes (2012) to test the
hypothesized relationships based on estimates with heteroscedasticity robust standard errors
and bootstrapping procedures to test for the indirect effects and performed multiple test for
alternative model solutions.
4
Results
Table 1 displays the intercorrelations and descriptive statistics of the study variables.
All focal relationships were in the expected directions.
***Insert Table 1 here***
Measurement model
Our hypothesized measurement model consisted of four latent constructs – employer
branding orientation, recruitment efficiency, positive affective climate, and firm performance.
To inspect the overall model fit, we report on absolute fit index – the standardized root mean
square error of approximation (SRMR) – and two incremental fit indices – the comparative fit
index (CFI) and the incremental fit index (IFI) – as proposed for sample sizes smaller than
200 (Hu & Bentler, 1999). To assess the overall model fit, we use commonly applied cut-off
points of <.08 for the SRMR and >.90 for the comparative fit indices. Furthermore, we also
4
We did not test our full model with SEM procedures, due to our relatively small sample size, which might lead
to unreliable results (Westland, 2010). In a robustness check, however, we show that all our results also
remained constant, when simultaneously tested with SEM procedures.
24
report the Akaike Information Criterion (AIC; Akaike, 1987) to compare different model
solutions, with lower values signifying a better model fit.
Based on the selected fit indices, our proposed measurement model showed good fit
properties (χ2=153, df=98, CFI=.94, IFI=.94, SRMR=.08, AIC=229). Moreover, all
standardized factor loadings were above .50 and significant at the 1% level. As shown in
Table 2, we compared our measurement model to three alternative model solutions to
establish discriminant validity for the study constructs. First, a model allowing the recruitment
efficiency and the firm performance items to load on one factor (since both were obtained
from the TMT members (alternative model 1) had a worse fit (Δχ2=74, Δdf=3, p<.001,
AIC=297). Second, a model in which the two mediators (recruitment efficiency and positive
affective climate) were allowed to load on one common factor (alternative model 2) had a
significantly worse fit (Δχ2=67, Δdf=3, p<.001, AIC=290), indicating that the two factors
were indeed different. Finally, a model with all items loading on one common factor
(alternative model 3) was also fitting worse (Δχ2=383, Δdf=6, p<.001, AIC=600). The
average latent correlations between the study constructs are reported in Table 3.
***Insert Table 2 here***
***Insert Table 3 here***
Hypotheses testing
Main analyses. Table 4 displays the regression analyses for testing Hypotheses 1-4.
Supporting Hypothesis 1, model 1 shows that employer branding orientation is positively
related to recruitment efficiency (B=.31, t=2.44, p<.05). Furthermore, employer brand
orientation is also positively related to positive affective climate (B=.12, t=3.20, p<01) as
shown in model 2 and supporting Hypothesis 2. Recruitment efficiency, in contrast, is related
to firm performance only at a marginally significant level (B=.16, t=1.84, p=.07), hence not
25
supporting Hypothesis 3. Additionally, model 3 shows that in line with Hypothesis 4, positive
affective climate (B=.66, t=2.11, p<.05) is positively related to firm performance.
Given these results, we further inspected whether recruitment efficiency and positive
affective climate mediated the relationship between employer branding orientation and firm
performance as postulated in Hypotheses 5a and 5b. For this purpose, 10,000 bootstrap
samples were drawn within the PROCESS model. Not supporting Hypothesis 5a there was no
indirect effect of employer brand orientation on firm performance via recruitment efficiency
within a 95 percent confidence interval (B=.06; 95% BCCI [-.002, .149]), but only within a 90
percent confidence interval, thus not supporting Hypothesis 5a (B=.06; 90% BCCI [.005,
.128]). Supporting Hypothesis 5b, the results indicated that there was no direct, but a
significant indirect effect of employer branding orientation on firm performance via positive
affective climate within a 95 percent confidence interval (B=.11; 95% BCCI [.015, .235]). In
sum, these results indicate support for a mediation chain between employer branding
orientation, positive affective climate and firm performance, while our data do not support a
mediation chain between employer branding orientation, recruitment efficiency, and firm
performance.
***Insert Table 4 here***
Alternative model testing. To ensure the validity of our findings, we performed
multiple alternative model tests. First a model only including the significant control variables
(i.e., that showed a positive relationship to either one mediator or firm performance in the
correlation analysis) resulted in similar and significant (at a 5 percent level, two-sided) effects
for all proposed relationships that were significant in the main analysis.
Second, a model with no control variables also resulted in similar and significant (at a
5 percent level, two-sided) effects for all significant relationships from the main analysis. This
signifies that our results did not depend on the inclusion or exclusion of specific control
variables.
26
Third, we inspected a model in which we included all further variables from the
above-mentioned further paper using the same dataset as control variables in our model. In
total, we added eight further control variables to our model (health related human resource
management, employees’ stress mindset, collective organizational engagement,
transformational leadership climate, industry trade dummy, collective emotional exhaustion,
mean company tenure, and coworker support). In this alternative model there was a positive
relationship between employer branding orientation and positive affective climate (B=.06,
t=3.45, p<.01), and between positive affective climate and firm performance (B=.79, t=1.98,
p<.05). The indirect effect of employer branding on firm performance via positive affective
climate was not significant within a 95% confidence interval (B=.06; 95% BCCI [-.009,
.145]) but within a 90% confidence interval (B=.06; 90% BCCI [.001, .127]). These results
indicate that our main findings from the initial analyses remain constant, despite including the
variables from the above-mentioned further paper as control variables.
Finally, we also replicated our findings with a more objective performance measure.
For that purpose, we collected data on the annual net profit of the participating companies
from the balance sheet that many German companies need to publish in an official publicly
available online portal (www.bundesanzeiger.de). We calculated the delta of the net profit of
the year of the survey and the following year to account for the increase or decrease of the
profit in the period after our survey. Given legal reporting standards in Germany, not all of the
companies had to report their net profits (or net losses), which resulted in a reduced sample
size of 41 companies. To obtain reliable estimates also for this smaller sample size, we did not
include all twelve control variables from the main analyses, but only those six that showed a
significant relationship to any of the three mediators or outcome variables. As common for
such objective performance measures with companies of different sizes, the data distribution
was heavily skewed. Since we had positive and negative values (in case of net losses) we
could not apply a log transformation to the data but had to apply a so-called Johnson
27
transformation that can deal with positive and negative values (Chou, Polansky & Mason,
1998) to obtain a normal distribution of the outcome measure. The results of this robustness
test indicate that there was a positive relationship between employer branding orientation and
positive affective climate (B=.14, t=2.45, p<.05), and between positive affective climate and
net profits (B=.96, t=3.00, p<.01). The indirect effect of employer branding orientation on
performance via positive affective climate was not significant within a 95% confidence
interval (B=.12; 95% BCCI [-.012, .444]), but within a 90% confidence interval (B=.12; 95%
BCCI [.003, .378])
In sum, these robustness tests indicate that the observed mediation effect of employer
branding orientation via positive affective climate and firm performance that we found in the
main analyses is robust among a multiple number of alternative model solutions and
measures, further increasing the confidence in our results.
Discussion
Our study integrates brand marketing research with HRM theory to build a mediated
model of the effect of employer branding on HRM outcomes and firm performance. The
present findings by and large lend support to the assumed (e.g., Backhaus & Tikoo, 2004;
Edwards, 2010; Mosley, 2014) – but, as yet, not theorized and tested –positive effect of
employer branding on HRM outcomes and, partly, firm performance at the firm level of
analysis. Using the employer branding value chain model (Theurer et al., 2018) as a guiding
theoretical framework, we conceptualize and test a mediation model explicating the effects of
employer branding orientation on firm performance through recruitment efficiency and
positive affective climate. We find support for most of the proposed relationships using a
multi-source firm-level design while controlling for a comprehensive set of HPWP and other
central control variables (Datta et al., 2005). We find that employer branding orientation
directly affects both recruitment efficiency and positive affective climate. Importantly, we
28
find differentiating indirect effects of employer branding orientation on firm performance:
employer branding orientation indirectly influences firm performance via the internal route
(i.e., incumbent employees’ positive affective climate), but not via the external route (i.e.,
recruitment efficiency). Thus, complementing existing employer branding research, we show
that although employer branding does influence recruitment efficiency, the positive effects on
firm performance emerge via the internal route, i.e., positive affective climate rather than via
the external route, i.e., recruitment efficiency. Moreover, we do not find a positive
relationship between recruitment efficiency and firm performance. The few extant studies that
have investigated the link between recruitment variables and firm performance (e.g., Seehan,
2014; Greer et al., 2016), generally do show positive effects, and, thus, our finding is not in
line with these results. We speculate that our non-significant findings in this regard might be
due to our global perceptual measure of recruitment efficiency based on Likert type scales
rather than the use of objective data from the HR information system (we discuss this issue in
more detail in the limitations section below).
Our study makes a contribution to management research in a broader sense by
demonstrating how insights from marketing, in particular, branding orientation, brand equity,
and the branding value chain model (Keller & Lehmann, 2006; Urde, 1999; Baumgarth,
Merrilees & Urde, 2013) can be fruitfully combined with HRM theory to yield firm-level
explanations of HRM outcomes and firm performance.
Our study contributes to the HRM literature by conceptualizing employer branding as
a guiding HR principle (Becker & Gerhart, 1996; Jackson, Schuler & Jiang, 2014; Jiang et al.,
2012) and thereby enable us to examine whether the effect of employer branding on firm-
level outcomes is generalizable, i.e., independent of concrete brand attributes or practices. In
line with Becker and Gerhart (1996; see also Colbert, 2004), we show that employer branding
as a “best practice” enhances key HR outcomes and firm performance. Whereas previous
research focusing on brand attributes answers the question of to what extent applicants
29
perceive the specific brand attributes examined in a particular context (e.g., “sincerity” or
“ruggedness” in the banking or fast food industries) as attractive, our study generalizes
beyond concrete attributes to answer the question of whether engaging in employer branding
has a generalizable effect on HR outcomes and firm performance (Becker & Gerhart, 1996).
Our study thus takes into account the idea that successful branding may be achieved in
different ways depending on the specific firm context (Grohs et al., 2016). Our research thus
provides insight on the question of whether an employer branding orientation as a general
approach to HRM, i.e., “applying brand thinking to people management” (Mosley, 2014, p. 1)
is connected to firm performance.
Moreover, our approach of conceptualizing employer branding as a guiding HR
principle (Becker & Gerhart, 1996) also advances research by making it possible to test the
underlying mediational mechanisms that potentially connect employer branding with firm
performance. Building on the employer branding value chain model (Theurer et al., 2018), we
hypothesize that employer branding may not only affect application-related outcomes, as has
been the focus in the majority of extant employer branding research but also on incumbent
employees’ engagement. In fact, our empirical results show that the effect via the internal
route is even stronger than the external route. We thus contribute to current theory by
developing a holistic approach – empirically testing both routes at the same time in one model
– to explain employer branding’s effect on firm performance. In so doing, we answer
outstanding calls in the literature (Ambler & Barrow, 1996; Backhaus & Tikoo, 2004; Phillips
& Gully, 2015) to investigate these effects and the mediational mechanisms through which
they are achieved. We directly respond to these calls and show an effect of employer branding
even when controlling for multiple HPWP and additional control variables, which strengthens
the role of employer branding research in the broader field of HRM.
Furthermore, by shifting our theorizing and analysis of employer branding to the firm
level of analysis, our approach enables us to provide evidence on the firm-level mediating
30
mechanisms connecting employer branding and firm performance. While previous research
has (with notable exceptions; e.g., Collins & Han, 2004; Turban & Cable, 2003) mainly
focused on the individual-level outcomes of employer brand characteristics (e.g., Cable &
Turban, 2003; Lievens, 2007; Van Hoye et al., 2013), we advance the field by examining the
mechanisms underlying its firm performance effects.
Our study also contributes to the field by advancing the scant but emerging research
on emotions in employer branding (Rampl, 2014; Rampl et al., 2016) by investigating
collective emotions, i.e., in our case: positive affective climate, as a mediator. Whereas
emotions have often been implicitly conceptualized in prior employer branding studies, there
is a lack of explicit theorizing, modelling, and empirically testing its effects (Lievens &
Slaughter, 2016). Our study addresses this void and contributes beyond existing studies –
which have all been conducted at the individual level of analysis – by demonstrating that
employer branding impacts collective employee emotions at the firm level, and that this
positive affective climate will translate into firm performance.
Overall, our research brings forward the emerging brand equity perspective in HRM
(Cable & Turban, 2001; Collins & Kanar, 2014) by gearing the research focus toward
examining employer branding effects beyond the target group of applicants toward incumbent
employees, and, ultimately, firm performance. We thus open new theoretical and empirical
avenues for employer branding research by concentrating on tangible firm outcomes and their
effects when building an effective employer brand (Backhaus & Tikoo, 2004). Because the
extant research perspective has had a strong focus on single employer brand characteristics
(e.g., Van Hoye et al., 2013), this internal mechanism perspective is important for extending
our knowledge on the consequences of employer brand building at a strategic level. Our
research thus contributes to viewing employer branding as a strategic firm-level approach
(Jiang et al., 2012) by focusing its the firm-level outcomes.
31
Practical implications
In terms of practical implications, our findings imply that employer branding has
benefits in terms of both recruitment efficiency and higher positive affective climate of
incumbent employees. Thus, given the vast interest in employer branding in corporate and
SME firms, our study may serve as an argument for HR professionals supporting investment
in employer branding to enhance these two key HR outcomes. However, we do not find a link
between recruitment efficiency and firm performance, and also no indirect effect of employer
branding orientation on firm performance through recruitment (but through positive affective
climate). Thus, based on our findings, HRM professionals need to be aware that the positive
effect of employer branding orientation on firm performance may be due to its effect on
incumbent employees (i.e., positive affective climate; “internal route”) rather than recruitment
efficiency (“external route”). In this vein, HRM professionals may refer to our results when
explaining to their leadership why employer branding may be important and what effects it
may have on incumbent employee outcomes, and firm performance. Specifically, our results
support an investment in “internal employer branding” (Lievens et al., 2007; Theurer et al.,
2018), i.e., promoting the employer brand to incumbent employees through firm-internal
communication channels. Doing so, HR professionals may be able to engage employees
around the employer brand as a “platform” to spark positive affective climate. As an example
of this practice, the LEGO group uses its employer brand (with its main employer value
proposition pillars: “Purpose driven”, “Systematic creativity”, “Clutch Power”, and “Action
ability”) to engage its employees (Mosley, 2014). Their employer brand is one of four brands
developed specifically for different stakeholders (the others being customers, business
partners, and the global environment and society), and provides a “common platform” for
shaping HRM activities (Mosley, 2014; People in Business, 2016). Thus, in contrast to widely
held beliefs in practice that employer branding is purely a recruitment-related activity that is
in place to attract applicants (i.e., focusing on recruitment), we demonstrate that the positive
32
effects on firm performance unfold through incumbent employee-related outcomes rather than
applicant-related outcomes. Because our findings identify the concrete mechanism through
which employer branding orientation has a beneficial impact on extant employees’ positive
engagement, our study enhances HR professionals’ understanding of the underlying points of
leverage.
Limitations and suggestions for future research
While our study has several strengths, such as the integrative theoretical model, firm-
level analysis, multi-source design with three data sources, and control for common method
bias, we also acknowledge several limitations. First, while we base our model on theoretically
solid assumptions regarding the proposed causal order of our variables and run and robustness
test with a time lagged performance measure, we cannot ultimately derive causal inferences
based on our cross-sectional design. To further lower the likelihood of a reversed causal
order, we also controlled for an endogeneity bias, as selection effects and uncontrolled
confounding variables are a main threat to causality (Antonakis, Bendahan, Jacquart,, Lalive,
2010). For this purpose, we performed a Hausmann test for the significant hypotheses from
our main analyses applying a 2SLS estimation, technique. For both H2 [Employer
orientation-> positive affective climate] χ2:.32, p=.85; and H4 [positive affective climate->
firm performance] χ2: .65, p=.72) this test showed that the 2SLS results were not significantly
different from our main results, indicating that endogeneity was not a main threat to our
reported findings. In sum, these further tests make us confident that a reversed causality is
unlikely for our proposed model. Still we would encourage future studies to further establish
causality within these posited relationships, for example, by using panel data on the effects of
employer branding orientation on firm performance or even by conducting an experimental or
quasi-experimental manipulation of employer branding orientation.
33
Second, our sample consisted mostly of small and medium-sized enterprises (SMEs)
in Germany, which might limit the generalizability of our research. However, since SMEs
make up most of the economic activity in most developed countries, and because the
participating companies represent multiple industries, we may nevertheless assume a decent
level of generalizability of our results. Additionally, we argue that the study of employer
branding is especially appropriate in SMEs. While large corporations are often publicly well-
known due to their size and widespread product brands, SMEs are less familiar to the public
and, therefore, need to engage in employer branding to raise awareness of their brands on the
labor market (Ewerlin & Süß, 2016). Thus, employer branding may be even more important
for SMEs than for large corporations. Moreover, while we theoretically employ a
“universalistic” perspective (Delery & Doty, 1996) – assuming that more employer branding
orientation will always contribute to higher firm performance (irrespective of a certain firm
strategy or certain HR practice configuration) than less or no employer branding orientation –
we are not able to test whether our findings apply to any firm (e.g., large firms or startups).
Therefore, we encourage future studies to investigate employer branding orientation at a
strategic level in other organizational contexts to examine whether our relationships can be
replicated in settings outside the SME context (e.g., larger firms above 5,000 employees).
Third, our perceptual measures might raise concerns regarding the accuracy and
validity of our study. For the firm performance measure, we addressed this issue by
replicating our findings with an objective net-profit measure in a smaller sub-sample. Still, for
both the employer branding orientation measure and the recruitment efficiency measure, our
data collection strategy with surveying one or several key informants per company (i.e., top
HR representatives or members of the top management team) might raise concerns about the
reliability and validity of theses scales. Regarding the employer branding orientation
measurement, it would be ideal to also assess actual employer brand performance resulting
from employer branding orientation using external sources (e.g., external applicants or current
34
employees) to validate the assessment of the top HR representatives. We therefore encourage
such multi-source assessment in future research. To assess recruitment efficiency, it would be
desirable to obtain process generated information from the firms’ HR and accounting systems
(e.g., actual time to fill a position, actual calculated cost to fill a position) to get a more
objective assessment of the recruitment processes. We would also speculate that our global
assessment of recruitment efficiency might have affected the predictive validity of this
measure and might thus be one of the explanations for the observed non-significant
relationship between recruitment efficiency and firm performance. Consequently, we highly
encourage future research using more objective recruitment measures, although such data
might be difficult to collect in a multi-company sample.
Conclusion
In conclusion, our research offers a model of the effects of strategic engagement in
employer branding at the firm level. In addition to demonstrating the positive effects of
employer branding orientation on recruitment efficiency and positive affective climate, our
findings yield differentiating mediating effects by showing that positive affective climate
rather than recruitment efficiency functions as the mediating mechanism linking employer
branding orientation with firm performance. Given the widespread use of employer branding
in today’s HRM practice, our research aids in conceptually clarifying the relationships
underlying the effects of employer branding. We hope that our study will stimulate further
theory and empirical research on the firm-level effects of employer branding.
35
References
Aaker, J. L. (1997). Dimensions of brand personality. Journal of Marketing Research, 34(3),
347-356.
Aaker, J., & Fournier, S. (1995). A brand as a character, a partner and a person: Three
perspectives on the question of brand personality. In F. R. Kardes, & M. Sujan (Eds.),
Advances in Consumer Research (Vol. 22, pp. 391–395). Provo, UT: Association for
Consumer Research.
Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52, 317-332.
Ambler, T. & Barrow, S. (1996). The employer brand. Journal of Brand Management, 4, 185-
206.
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). On making causal claims: A
review and recommendations. Leadership Quarterly, 21, 1086-1120.
Ashkanasy, N. M., & Dorris, A. D. (2017). Emotions in the workplace. Annual Review of
Organizational Psychology and Organizational Behavior, 4, 67-90.
Ashkanasy, N. M., Troth, A. C., Lawrence, S. A., & Jordan, P. J. (2017). Emotions and
Emotional Regulation in HRM: A Multi-Level Perspective. In Research in Personnel and
Human Resources Management (pp. 1-52). Emerald Publishing Limited.
Baas, M., De Dreu, C. K., & Nijstad, B. A. (2008). A meta-analysis of 25 years of mood-
creativity research: Hedonic tone, activation, or regulatory focus?. Psychological Bulletin,
134, 779-886.
Backhaus, K. B. & Tikoo, S. (2004). Conceptualizing and researching employer branding.
Career Development International, 9, 501-517.
Bangerter, A., Roulin, N., & König, C. J. (2012). Personnel selection as a signaling game.
Journal of Applied Psychology, 97, 719-738.
36
Baron, R. A., & Tang, J. (2011). The role of entrepreneurs in firm-level innovation: Joint
effects of positive affect, creativity, and environmental dynamism. Journal of Business
Venturing, 26, 49-60.
Barrick, M. R., Thurgood, G. R., Smith, T. A., & Courtright, S. H. (2015). Collective
organizational engagement: Linking motivational antecedents, strategic implementation,
and firm performance. Academy of Management Journal, 58, 111-135.
Baum, M., & Kabst, R. (2013). How to attract applicants in the Atlantic versus the Asia-
Pacific region? A cross-national analysis on China, India, Germany, and Hungary. Journal
of World Business, 48, 175-185.
Baumgarth, C., Merrilees, B., & Urde, M. (2013). Brand orientation: Past, present, and future.
Journal of Marketing Management, 29, 973-980.
Becker, B., & Gerhart, B. (1996). The impact of human resource management on
organizational performance: Progress and prospects. Academy of Management Journal, 39,
779-801.
Becker, B. E., Huselid, M. A., & Ulrich, D. (2001). The HR scorecard: Linking people,
strategy, and performance. Boston: Harvard Business School Press.
Bliese, P. D. (2000). Within group agreement, non-independence, and reliability. In Klein, K.
J. & Kozlowski, S. W. (Eds), Multilevel Theory, Research, and Methods in Organizations.
San Francisco: Jossey-Bass, 349-381.
Berthon, P., Ewing, M., & Hah, L. L. (2005). Captivating company: dimensions of
attractiveness in employer branding. International Journal of Advertising, 24, 151-172.
Bowen, D. E., & Ostroff, C. (2004). Understanding HRM–firm performance linkages: The
role of the “strength” of the HRM system. Academy of Management Review, 29(2), 203-
221.
37
Braddy, P. W., Meade, A. W., & Kroustalis, C. M. (2006). Organizational recruitment website
effects on viewers’ perceptions of organizational culture. Journal of Business and
Psychology, 20, 525-543.
Cable, D. M., & Graham, M. E. (2000). The determinants of job seekers' reputation
perceptions. Journal of Organizational Behavior, 21(8), 929-947.
Cable, D. M., & Turban, D. B. (2001). Establishing the dimensions, sources, and value of job
seekers'employer knowledge during recruitment. Research in Personnel and Human
Resources Management, 20, 115-164.
Cable, D. M., & Turban, D. B. (2003). The value of organizational reputation in the
recruitment context: A brand-equity perspective. Journal of Applied Social Psychology, 33,
2244-2266.
Chaudhuri, A., & Holbrook, M. B. (2001). The chain of effects from brand trust and brand
affect to brand performance: the role of brand loyalty. Journal of Marketing, 65, 81-93.
Cheney, G., Christensen, L. T., Conrad, C. and Lair, D. J. (2004). Corporate rhetoric as
organizational discourse. In Grant, D., Hardy, C., Oswick, C., Phillips, N. and Putnam, L.
L. (Eds), Handbook of Organizational Discourse. London: Sage, 79-103.
Chou, Youn-Min, Alan M. Polansky, and Robert L. Mason. (1998). Transforming non-normal
data to normality in statistical process control. Journal of Quality Technology, 30, 133-141.
Christensen, L. T. (1997). Marketing as auto-communication. Consumption, Markets and
Culture, 1, 197-227.
Colbert, B. A. (2004). The complex resource-based view: Implications for theory and practice
in strategic human resource management. Academy of Management Review, 29, 341-358.
Collings, D. G., & Mellahi, K. (2009). Strategic talent management: A review and research
agenda. Human Resource Management Review, 19, 304-313.
38
Collins, C. J., & Han, J. (2004). Exploring applicant pool quantity and quality: The effects of
early recruitment practice strategies, corporate advertising, and firm reputation. Personnel
Psychology, 57, 685-717.
Collins, C.J. & Kanar, A. (2014). Employer brand equity and recruitment research. In Yu,
K.Y.T. & Cable, D.M. (Eds.) Oxford Handbook of Recruitment. New York: Oxford
University Press, 284-297.
Collins, C. J., & Stevens, C. K. (2002). The relationship between early recruitment-related
activities and the application decisions of new labor-market entrants: A brand equity
approach to recruitment. Journal of Applied Psychology, 87, 1121-1133.
Combs, J., Liu, Y., Hall, A., & Ketchen, D. (2006). How much do high performance work
practices matter? A meta analysis of their effects on organizational performance. Personnel
Psychology, 59, 501-528.
Datta, D. K., Guthrie, J. P., & Wright, P. M. (2005). Human resource management and labor
productivity: Does industry matter? Academy of Management Journal, 48, 135-145.
Delaney, J. T., & Huselid, M. A. (1996). The impact of human resource management practices
on perceptions of organizational performance. Academy of Management Journal, 39, 949-
969.
Delery, J. E., & Doty, D. H. (1996). Modes of theorizing in strategic human resource
management: Tests of universalistic, contingency, and configurational performance
predictions. Academy of Management Journal, 39, 802-835.
Delery, J. E., & Roumpi, D. (2017). Strategic human resource management, human capital
and competitive advantage: Is the field going in circles? Human Resource Management
Journal, 27(1), 1-21.
Dineen, B. R., & Allen, D. G. (2016). Third party employment branding: Human capital
inflows and outflows following “Best Places to Work” certifications. Academy of
Management Journal, 59, 90-112.
39
Dineen, B. R., & Williamson, I. O. (2012). Screening‐oriented recruitment messages:
Antecedents and relationships with applicant pool quality. Human Resource Management,
51, 343-360.
Edwards, M. R. (2010). An integrative review of employer branding and OB theory.
Personnel Review, 39, 5-23.
Edwards, M. R. (2017). Employer branding and talent manegement. In D. G. Collings, W. F.
Cascio, & K. Mellahi (Eds.), Oxford Handbook of Talent Management (pp. 233-248). Oxford:
Oxford University Press.
Edwards, M. R., & Edwards, T. (2013). Employee responses to changing aspects of the
employer brand following a multinational acquisition: A longitudinal study. Human
Resource Management, 52, 27-54.
Ewerlin, D., & Süß, S. (2016). Dissemination of talent management in Germany: Myth,
facade or economic necessity? Personnel Review, 45, 142-160.
Francis, H., & Reddington, M. (2012). Employer branding and organisational effectiveness. In
Francis, H. Holbeche, L. & Reddington, M. (Eds.), People and organisational
development: A new agenda for organisational effectiveness. London: CIPD, 260-285.
Fredrickson, B. L. (2003). The value of positive emotions: The emerging science of positive
psychology is coming to understand why it's good to feel good. American Scientist, 91,
330-335.
Fredrickson, B. L. (2004). The broaden-and-build theory of positive emotions. Philosophical
Transactions of the Royal Society B: Biological Sciences, 359, 1367-1377.
Gardner, T. M., Erhardt, N. L., & Martin-Rios, C. (2011). Rebranding employment branding:
Establishing a new research agenda to explore the attributes, antecedents, and
consequences of workers’ employment brand knowledge. Research in Personnel and
Human Resources Management, 30, 253-304.
40
Gerhart, B. (2007). Horizontal and vertical fit in human resource systems. In Ostroff, C. &
Judge, T. A. (Eds.), Perspectives on organizational fit. New York: Psychology Press, 317-
348.
Gibson, C. B., & Birkinshaw, J. (2004). The antecedents, consequences, and mediating role of
organizational ambidexterity. Academy of Management Journal, 47, 209-226.
Greer, C. R., Carr, J. C., & Hipp, L. (2016). Strategic staffing and small‐firm performance.
Human Resource Management, 55(4), 741-764.
Grohs, R., Raies, K., Koll, O., & Mühlbacher, H. (2016). One pie, many recipes: Alternative
paths to high brand strength. Journal of Business Research, 69, 2244-2251.
Guest, D. E., Michie, J., Conway, N., & Sheehan, M. (2003). Human resource management
and corporate performance in the UK. British Journal of Industrial Relations, 41(2), 291-
314.
Gully, S. M., Phillips, J. M., & Kim, M. S. (2014). Strategic recruitment: A multilevel
perspective. In Yu, K. Y. T. and Cable, D. (Eds.), Oxford Handbook of Recruitment. New
York, NY: Oxford University Press, 161-183.
Han, J., & Ling, J. (2016). Emotional appeal in recruitment advertising and applicant
attraction: Unpacking national cultural differences. Journal of Organizational Behavior,
37(8), 1202-1223.
Hanin, D., Stinglhamber, F., & Delobbe, N. (2013). The impact of employer branding on
employees: The role of employment offering in the prediction of their affective
commitment. Psychologica Belgica, 53, 57-83.
Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable
mediation, moderation, and conditional process modeling [White paper]. Available at:
http://www.afhayes.com/public/process2012.pdf (accessed 1.2.2018)
Herrbach, O. (2006). A matter of feeling? The affective tone of organizational commitment
and identification. Journal of Organizational Behavior, 27, 629-643.
41
Holtbrügge, D., Friedmann, C. B., & Puck, J. F. (2010). Recruitment and retention in foreign
firms in India: A resource-based view. Human Resource Management, 49, 439-455.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis:
Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55.
Huselid, M. A. (1995). The impact of human resource management practices on turnover,
productivity, and corporate financial performance. Academy of Management Journal, 38,
635-672.
Jackson, S. E., Schuler, R. S., & Jiang, K. (2014). An aspirational framework for strategic
human resource management. Academy of Management Annals, 8, 1-56.
James, L. R., Demaree, R. G., & Wolf, G. (1984). Estimating within-group interrater
reliability with and without response bias. Journal of Applied Psychology, 67, 219-229.
Jansen, J. J., Van Den Bosch, F. A., & Volberda, H. W. (2006). Exploratory innovation,
exploitative innovation, and performance: Effects of organizational antecedents and
environmental moderators. Management Science, 52, 1661-1674.
Jiang, K., Lepak, D. P., Han, K., Hong, Y., Kim, A., & Winkler, A. L. (2012). Clarifying the
construct of human resource systems: Relating human resource management to employee
performance. Human Resource Management Review, 22, 73-85.
Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand
equity. Journal of Marketing, 57, 1-22.
Keller, K. L., & Lehmann, D. R. (2006). Brands and branding: Research findings and future
priorities. Marketing Science, 25, 740-759.
Kim, Y., & Ployhart, R. E. (2014). The effects of staffing and training on firm productivity
and profit growth before, during, and after the Great Recession. Journal of Applied
Psychology, 99(3), 361-389.
Kozlowski, S. W. J., & Klein, K. J. (2000). A multilevel approach to theory and research in
organizations: Contextual, temporal, and emergent processes. In K. J. Klein & S. W. J.
42
Kozlowski (Eds.), Multilevel theory, research, and methods in organizations: Foundations,
extensions, and new directions (pp. 3-90). San Francisco, CA, US: Jossey-Bass.
Knight, A. P., Menges, J. I., & Bruch, H. (2018). Organizational affective tone: A meso
perspective on the origins and effects of consistent affect in organizations. Academy of
Management Journal, 61(1), 191-219.
Kunerth, B., & Mosley, R. (2011). Applying employer brand management to employee
engagement. Strategic HR Review, 10, 19-26.
Kunze, F., Boehm, S. A., & Bruch, H. .(2011). Age diversity, age discrimination climate and
performance consequences – a cross organizational study. Journal of Organizational
Behavior, 32, 264-290.
Kunze, F., Boehm, S., & Bruch, H. (2013). Organizational performance consequences of age
diversity: Inspecting the role of diversity-friendly HR policies and top managers’ negative
age stereotypes. Journal of Management Studies, 50, 413-442.
Kunze, F., & Menges, J. I. (2017). Younger supervisors, older subordinates: An
organizational‐level study of age differences, emotions, and performance. Journal of
Organizational Behavior, 38, 461-486.
Laumer, S., Maier, C., & Eckhardt, A. (2015). The impact of business process management
and applicant tracking systems on recruiting process performance: An empirical study.
Journal of Business Economics, 85, 421-453.
Lepak, D., Liao, H., Chung, Y., & Harden, E. (2006). A conceptual review of human resource
management systems in strategic human resource management research. In Martocchio, J.
J. (Ed.), Research in personnel and human resources management, 25. Oxford, UK:
Elsevier, 217–271.
Lepak, D. P., & Snell, S. A. (2002). Examining the human resource architecture: The
relationships among human capital, employment, and human resource configurations.
Journal of Management, 28, 517-543.
43
Lievens, F., Van Hoye, G., & Anseel, F. (2007). Organizational identity and employer image:
towards a unifying framework. British Journal of Management, 18, 45-59.
Lievens, F. (2007). Employer branding in the Belgian Army: The importance of instrumental
and symbolic beliefs for potential applicants, actual applicants, and military employees.
Human Resource Management, 46, 51-69.
Lievens, F. & Highhouse, S. (2003). The relation of instrumental and symbolic attributes to a
company's attractiveness as an employer. Personnel Psychology, 56, 75-102.
Lievens, F., & Slaughter, J. (2016). Employer image and employer branding: What we know
and what we need to know. Annual Review of Organizational Psychology and
Organizational Behavior, 3, 407-440.
Martin, G., Beaumont, P., Doig, R., & Pate, J. (2005). Branding: A new performance
discourse for HR? European Management Journal, 23(1), 76-88.
Martin, G., Gollan, P. J., & Grigg, K. (2011). Is there a bigger and better future for employer
branding? Facing up to innovation, corporate reputations and wicked problems in SHRM.
International Journal of Human Resource Management, 22, 3618-3637.
Martins, P., & Lima, F. (2006). External recruitments and firm performance. Applied
Economics Letters, 13, 911-915.
Maxwell, R., & Knox, S. (2009). Motivating employees to “live the brand”: A comparative
case study of employer brand attractiveness within the firm. Journal of Marketing
Management, 25, 893-907.
Menges, J. I., Walter, F., Vogel, B., & Bruch, H. (2011). Transformational leadership climate:
Performance linkages, mechanisms, and boundary conditions at the organizational level.
Leadership Quarterly, 22, 893-909.
Menges, J. I., & Kilduff, M. (2015). Group emotions: Cutting the Gordian knots concerning
terms, levels of analysis, and processes. Academy of Management Annals, 9, 845-928.
44
Monks, K., Kelly, G., Conway, E., Flood, P., Truss, K., & Hannon, E. (2013). Understanding
how HR systems work: The role of HR philosophy and HR processes. Human Resource
Management Journal, 23, 379-395.
Mosley, R. (2014). Employer branding: Practical lessons from the world's leading employers.
Hoboken, NJ: John Wiley & Sons.
Münstermann, B., Eckhardt, A., & Weitzel, T. (2009). Join the standard forces: Examining
the combined impact of process and data standards on business process performance. IEEE
Proceedings of the 42nd Hawaii International Conference, 1-10.
Ostroff, C., & Bowen, D. E. (2000). Moving HR to a higher level: HR practices and
organizational effectiveness. In K. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory,
research, and methods in organizations: Foundations, extensions, and new directions (pp.
221−266). San Francisco: Jossey-Bass.
Ostroff, C., & Bowen, D. E. (2016). Reflections on the 2014 decade award: Is there strength
in the construct of HR system strength? Academy of Management Review, 41(2), 196-214.
Paauwe, J. (2009). HRM and performance: Achievements, methodological issues and
prospects. Journal of Management Studies, 46(1), 129-142.
Parke, M. R., & Seo, M. G. (2017). The role of affect climate in organizational effectiveness.
Academy of Management Review, 42(2), 334-360.
Peccei, R., & Van De Voorde, K. (2019). The application of the multilevel paradigm in
human resource management–outcomes research: Taking stock and going forward. Journal
of Management, 45(2), 786-818.
People in Business (2016). LEGO case study. Retrieved from http://www.people-in-
business.com/our-clients/#/case-studies/
Phillips, J. M., & Gully, S. M. (2015). Multilevel and strategic recruiting Where have we
been, where can we go from here? Journal of Management, 41, 1416-1445.
45
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in
social science research and recommendations on how to control it. Annual Review of
Psychology, 63, 539-569.
Posthuma, R. A., Campion, M. C., Masimova, M., & Campion, M. A. (2013). A high
performance work practices taxonomy integrating the literature and directing future
research. Journal of Management, 39, 1184-1220.
Rampl, L. V. (2014). How to become an employer of choice: transforming employer brand
associations into employer first-choice brands. Journal of Marketing Management, 30,
1486-1504.
Rampl, L. V., Opitz, C., Welpe, I. M., & Kenning, P. (2016). The role of emotions in
decision-making on employer brands: insights from functional magnetic resonance
imaging (fMRI). Marketing Letters, 27, 361-374.
Renkema, M., Meijerink, J., & Bondarouk, T. (2017). Advancing multilevel thinking in
human resource management research: Applications and guidelines. Human Resource
Management Review, 27(3), 397-415.
Rao, H., & Drazin, R. (2002). Overcoming resource constraints on product innovation by
recruiting talent from rivals: A study of the mutual fund industry, 1986–1994. Academy of
Management Journal, 45, 491-507.
Rosenbusch, N., Brinckmann, J., & Bausch, A. (2011). Is innovation always beneficial? A
meta-analysis of the relationship between innovation and performance in SMEs. Journal of
Business Venturing, 26, 441-457.
Rubin, R. S., Munz, D. C., & Bommer, W. H. (2005). Leading from within: The effects of
emotion recognition and personality on transformational leadership behavior. Academy of
Management Journal, 48, 845-858.
46
Russell, S., & Brannan, M. J. (2016). „Getting the Right People on the Bus”: Recruitment,
selection and integration for the branded organization. European Management Journal,
34(2), 114-124.
Saridakis, G., Lai, Y., & Cooper, C. L. (2017). Exploring the relationship between HRM and
firm performance: A meta-analysis of longitudinal studies. Human Resource Management
Review, 27(1), 87-96.
Schnars, C. Z., & Kleiner, B. H. (2000). Best in class staffing practices. Management
Research News, 23, 35-38.
Schreurs, B., Derous, E., Van Hooft, E. A., Proost, K., & De Witte, K. (2009). Predicting
applicants’ job pursuit behavior from their selection expectations: The mediating role of
the theory of planned behavior. Journal of Organizational Behavior, 30(6), 761-783.
Sheehan, M. (2014). Human resource management and performance: Evidence from small
and medium-sized firms. International Small Business Journal, 32(5), 545-570.
Shaw, J. D., Gupta, N., & Delery, J. E. (2005). Alternative conceptualizations of the
relationship between voluntary turnover and organizational performance. Academy of
Management Journal, 48, 50-68.
Sung, S. Y., & Choi, J. N. (2014). Multiple dimensions of human resource development and
organizational performance. Journal of Organizational Behavior, 35(6), 851-870.
Taylor, M. S., & Collins, C. J. (2000). Organizational recruitment: enhancing the intersection
of research and practice. In Cooper, C. L. & Locke, E. A. (Eds.), Industrial and
organizational psychology: Linking theory and practice. Oxford, UK: Blackwell, 304–334.
Terpstra, D. E., & Rozell, E. J. (1993). The relationship of staffing practices to organizational
level measures of performance. Personnel Psychology, 46, 27-48.
Theurer, C., Tumasjan, A., Welpe, I. M., & Lievens, F. (2018). Employer branding: A brand
equity-based literature review and research agenda. International Journal of Management
Reviews, 20, 155-179.
47
Thompson, C. J., Rindfleisch, A., & Arsel, Z. (2006). Emotional branding and the strategic
value of the doppelgänger brand image. Journal of Marketing, 70, 50-64.
Timming, A. R. (2017). Body art as branded labour: At the intersection of employee selection
and relationship marketing. Human Relations, 70(9), 1041-1063.
Tsai, W. C., Chen, C. C., & Liu, H. L. (2007). Test of a model linking employee positive
moods and task performance. Journal of Applied Psychology, 92, 1570-1583.
Turban, D. B., & Cable, D. M. (2003). Firm reputation and applicant pool characteristics.
Journal of Organizational Behavior, 24, 733-751.
Ulrich, D. (1997). Measuring human resources: an overview of practice and a prescription for
results. Human Resource Management, 36, 303-320.
Urde, M. (1999). Brand orientation: A mindset for building brands into strategic resources.
Journal of Marketing Management, 15, 117-133.
Van Hoye, G., Bas, T., Cromheecke, S., & Lievens, F. (2013). The instrumental and symbolic
dimensions of organizations' image as an employer: A large-scale field study on employer
branding in Turkey. Applied Psychology, 62, 543-557.
Van Katwyk, P. T., Fox, S., Spector, P. E., & Kelloway, E. K. (2000). Using the Job-Related
Affective Well-Being Scale (JAWS) to investigate affective responses to work stressors.
Journal of Occupational Health Psychology, 5(2), 219-230.
Wall, T. D., Michie, J., Patterson, M., Wood, S. J., Sheehan, M., Clegg, C. W., & West, M.
(2004). On the validity of subjective measures of firm performance. Personnel Psychology,
57, 95-118.
Westland, J. C. (2010). Lower bounds on sample size in structural equation
modeling. Electronic Commerce Research and Applications, 9(6), 476-487.
Wong, H., & Merrilees, B. (2008). The performance benefits of being brand-orientated.
Journal of Product and Brand Management, 17, 372-383.
48
Figure 1
Conceptual model
49
Table 1
Descriptives and intercorrelations
MSD 1 2 3 4 5 6 7 8 9 10 11 12 13 14
1
Employer branding orientation 5.85 .79
2
Recruitment efficiency 5.11 1.07 .23 *
3
Positive affective climate 3.33 .32 .34 ** .35 **
4
Firm performance 4.77 .75 .19 .30 ** .34 **
5
High performance work practices (HPWPs) 5.12 1.17 .18 -.02 .38 ** .08
6
Ambidextrous management practices 68.19 13.05 .20 -.01 .28 ** .35 ** .41 **
7
Transformational leadership CEO 3.46 .37 .13 .25 * .48 * .16 .32 ** .30 *
8
Company size (log) 4.96 .67 .23 * -.06 -.25 * -.01 -.01 -.01 -.11
9
Workforce mean age 39.11 3.98 -.05 -.05 -.20 -.07 .09 -.25 * -.17 * .09
10
Workforce age diversity 10.75 1.89 -.04 -.01 -.03 .01 .07 -.10 -.01 .07 -.03
11
Environmental dynamism 5.24 1.55 .20 .00 .01 -.15 -.01 .19 .17 -.02 -.10 .04
12
Local economic situation 2.70 1.23 .03 -.11 -.16 -.05 .21 * -.02 -.04 .22 * .15 -.02 -.08
13
Recruiting difficulties 3.65 1.13 -.18 -.35 ** -.22 * -.10 -.17 .01 -.10 -.17 -.12 -.23 * .06 .14
14
Industry: manufacturing .29 .46 -.11 -.09 -.07 -.08 -.15 -.31 ** -.13 -.15 -.01 .31 ** -.07 -.10 .09
15
Industry: service .47 .50 .09 -.02 .14 -.15 -.11 .21 * -.04 -.11 -.02 -.34 ** -.04 .04 -.07 -.61 **
* p < .05
** p < .01
*** p < .001 (two-sided)
Variable
Note. N = 93
50
Table 2
Comparison of measurement models
Model
c
2df
c
2/df D
c
2Ddf CFI IFI SRMR AIC
Hypothesized model 153 98 1.56 .94 .94 .08 229
Alternative model 1: Recruitment efficiency and
perceptual firm performance one factor
227 101 2.25 74
***
3 .86 .86 11 297
Alternative model 2: Recruitment efficiency and
positive affective climate one factor
220 101 2.18 67
***
3 .87 .87 .11 290
Alternative model 3: All one factor 536 104 5.15 383
***
652 52 11 600
* p<.05
** p<.01
Note : CFI = Comparative Fit Index; IFI = Incremental Fit Index; SRMR = Standardized Root Mean Square Residual. The three alternative
measurement models are compared to the hypothesized measurement model . The lowest Akaike Information Criterion (AIC) value shows the
best fitting model.
*** p<.001 chi-difference statistic compared to the hypothesized model.
51
Table 3
Latent correlations between study constructs
1 2 3
1
Employer branding orientation
2
Recruitment efficiency .29 *
3
Positive affective climate .33 ** .40 **
4
Perceptual firm performance .22 .31 * .37 **
** p < .01
*** p < .001 (two-sided)
Variable
Note. * p < .05
52
Table 4
Regression results
Model 3
BSE BSE BSE
3.32 *** .76 2.63 *** .21 .13 *** .77
1
High performance work practices (HPWPs) -.11 .11 .06 .03 -.13 .08
Ambidextrous management practices -.20 .12 -.01 .03 .33 *** .06
Transformational leadership CEO .22 .10 .12 *** .03 -.08 .08
Company size (log) -.22 .11 -.09 ** .03 -.01 .07
Workforce mean age -.11 .09 -.03 .03 .00 .06
Workforce age diversity -.09 .10 .00 .02 .04 .06
Environmental dynamism -.01 .10 -.04 .02 -.22 * .05
Local economic situation -.01 .10 .03 .03 .09 .07
Recruiting difficulties -.42 *** .10 -.06 * .03 .13 .08
Industry: manufacturing -.19 .14 .03 .04 -.25 * .09
Industry: service -.20 .13 .02 .04 -.32 * .09
2 Main effects Employer brand orientation .31 *.13 .12 ** .04 .06 .08
Positive affective climate -- -- -- -- .66 *.31
Recruitment efficiency -- -- -- -- .16 .08
R2.28 ** .49 *** .42 *
***p<.001
**p<.01
*p<.05
Model 1
Positive affective climate
Variables
Model 2
Perceptual firm performance
Constant
Note. N=93
Recruitment efficiency