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RELATIONAL ENERGY AT WORK 1
Relational Energy at Work:
Implications for Job Engagement and Job Performance
Bradley Owens, Brigham Young University
Wayne Baker, University of Michigan
Dana McDaniel Sumpter, California State University, Long Beach
Kim Cameron, University of Michigan
Forthcoming in Journal of Applied Psychology
RELATIONAL ENERGY AT WORK 2
Relational Energy at Work:
Implications for Job Engagement and Job Performance
Abstract
Energy is emerging as a topic of importance to organizations, yet we have little understanding of
how energy can be useful at an interpersonal level toward achieving workplace goals. We
present the results of 4 studies aimed at developing, validating, and testing the relational energy
construct. In Study 1, we report qualitative insights from 64 individuals about the experience and
functioning of relational energy in the workplace. Study 2 draws from 3 employee samples to
conduct exploratory and confirmatory factor analyses on a measure of relational energy,
differentiating relational energy from related constructs. To test the predictive validity of the new
relational energy scale, Study 3 comprises data from employees rating the level of relational
energy they experienced during interactions with their leaders in a health services context.
Results showed that relational energy employees experienced with their leaders at Time 1
predicted job engagement at Time 2 (one month later), while controlling for the competing
construct of perceived social support. Study 4 shows further differentiation of relational energy
from leader-member exchange (LMX), replicates the positive relationship between relational
energy (Time 1) and job engagement (Time 2), and shows that relational energy is positively
associated with employee job performance (Time 3) through the mechanism of job engagement.
We discuss the theoretical implications of our findings and highlight areas for future research.
Keywords: energy, job engagement, social contagion, social support, social networks, leader-
member exchange, job performance.
RELATIONAL ENERGY AT WORK 3
Energy is an organizational resource that increases employees’ capacity for action and
motivation, enabling them to do their work and attain their goals (Quinn, Spreitzer, & Lam,
2012, p. 6). Unfortunately, this critical organizational resource may not always be efficiently
managed and may even be in decline (Loehr & Schwartz, 2003; Pfeffer, 2010). Availability of
energy is highly relevant to workers and employers, as the absence of energy can result in
burnout (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001), stress (Sonnentag, Kuttler, & Fritz,
2010), or disengagement (Schaufeli, Bakker, & Van Rhenen, 2009). Increasing job demands of
longer work hours, continual change, technology blurring the boundaries of work and personal
life, workload increases, and the risk of job loss all contribute to deteriorating energy in the
workplace. As employees and organizations continually strive to do more with less, human
energy in the workplace is an increasingly critical and relevant issue in organizational research.
Though firms experiment with ways to better manage and enhance worker energy (such
as wellness programs, day care, flexible work schedules, or ergonomic workspaces), we know
little about how workers can endogenously resource their own human energy. As organizations
are, fundamentally, systems of interdependent individuals (Griffin, Neal, & Parker, 2007; Katz &
Kahn, 1966), we shift focus to one relatively unexplored source of energy: other people at work.
Existing literature identifies a variety of sources of energy, such as nourishment and sleep
as well as social interaction in groups (Cole, Bruch, & Vogel, 2012). It is clear that individuals
can be energized by other people. Existing research suggests that people who are energized by
others have higher levels of work performance (Baker, Cross, & Wooten, 2003; Cross & Parker,
2004) and knowledge transfer in organizations (Casciaro & Lobo, 2008), but the literature is
hampered by conceptual ambiguity, a lack of theoretical development, and the lack of a reliable
and validated measure of how this energy transfer occurs in “the space between” individuals
(Bradbury & Lichtenstein, 2000, p. 551), or at an interpersonal level. Therefore, the purpose of
this paper is to provide greater theoretical elaboration, conceptual clarification, and rigorous
RELATIONAL ENERGY AT WORK 4
operationalization of energy derived from a relational experience, or what we refer to as
relational energy. In this paper, we both elaborate upon and test a theory, leading to more
informed theory and conceptual clarity about the construct of relational energy.
To do so, we first review existing theory and research on human energy at work,
clarifying the nomological network of relational energy and describing its unique conceptual
space. We then bridge to the relational level, reporting findings from a qualitative Study 1 that
provides contextual insight into the phenomenon of energy transfer within work dyads. In Study
2, we sought to develop a measure of relational energy and report on its psychometric properties
by conceptually and empirically differentiating it from the related concepts of social support,
relational identification, productive energy, emotional energy, and leader-member exchange
(LMX). With data from two different points in time, Study 3 aims to show that relational energy
predicts employee job engagement. In Study 4, we sought to replicate the positive relationship
between relational energy and job engagement, and through bootstrapped mediation analyses
show that relational energy is positively associated with employee job performance through the
mechanism of job engagement. We conclude with a discussion of the contributions of these
findings and suggestions for future research.
Theoretical Background
The concept of human energy is inherent in a variety of theories of human activity.
Studies of engagement (Kahn, 1990; Rothbard, 2001), thriving (Spreitzer, Sutcliffe, Dutton,
Sonenshein, & Grant, 2005), and vigor (Shraga & Shirom, 2009), for example, all rely to some
extent on the concept of human energy. In the workplace, energy is often considered a resource
that can be applied toward the doing of work. Notably, the construct of motivation encompasses
several facets of energy, capturing how individuals choose the direction in which they choose to
expend their efforts, the intensity or how much energy to expend in doing so, and how long they
will persist in doing so (Pinder, 2008). The degree to which one experiences aroused feelings of
RELATIONAL ENERGY AT WORK 5
vitality, vigor, and enthusiasm serves as a helpful resource, compelling feelings of motivation
and ability to complete work tasks and achieve work goals.
In an overview of the energy literature and its relation to organizations, Spreitzer, Lam,
and Quinn (2012) characterize the energy literature as interdisciplinary and diverse, with six
disparate research streams. Five of the six streams examine energy at the individual level, where
energy is considered to be physical or psychological. Some scholars refer to energy as the
availability of glucose in the bloodstream that enables individuals to self-regulate behavior (e.g.,
Baumeister, 2002). Indeed, the predominance of empirical work and conceptual development in
the management literature has focused on energy at the individual level (Cole et al., 2012; Quinn,
Spreitzer, & Lam, 2012).
The sixth stream, which draws primarily from interaction ritual theory (e.g., Collins,
1993, 2004), shifts focus toward human energy in social interactions. There has been some
preliminary empirical work exploring this social, interpersonal, and relational form of energy.
Social network studies have measured organizational implications of network ties that are
considered “energizing” or “de-energizing” (Baker, Cross, & Wooten 2003; Cross & Parker,
2004). Parker, Gerbasi, and Porath (2013) explore the destructive outcomes associated with de-
energizing ties, including decreased motivation, reduced thriving, and turnover. Other research
examines the interactive experience of two actors focusing on those who give (or express) rather
than receive (or interpret) energy. McDaniel (2011), for example, studied relational energy from
the perspective of the giver of energy. Proposing a theoretical model for the cognitive and
affective factors involved in an individual’s energy expression choices, McDaniel developed a
self-report measure that captures an individual’s perception about the appropriateness and
contagion of his or her own energy expression in interdependent work relationships.
While this work focused on the givers of energy in relationships (i.e., the energizers),
extant research has neglected the experience and impact of relational energy from the perspective
RELATIONAL ENERGY AT WORK 6
of the receiver (i.e., the energized), giving us only partial understanding of how this process
works. This study is designed to evaluate how relational energy plays a role in interactions from
the perspective of the recipient. To fully develop how this relational perspective can apply to the
conceptualization of energy, we draw from three well-established and relevant theories:
interaction ritual theory, social contagion theory, and conservation of resources theory.
Interaction ritual theory. Collins’ (1993, 2004, p. 47) interaction ritual theory refers to
face-to-face interactions wherein “participants develop a mutual focus of attention and become
entrained in each other’s bodily micro-rhythms and emotions.” A common example is feeling
increasingly excited while participating in a cheering crowd at a sports game. The entrainment
that occurs is due to “emotional energy” (Collins’ term for energetic activation) that is generated
and shared contagiously amongst interaction partners. It is this shared experience that influences
both the intensity of an individual’s emotions and also how that individual continues to interact
with interaction partners. This is because as people “become . . . more aware of what each other
is doing and feeling, and more aware of each other’s awareness, they experience their shared
emotion more intensely” (Collins, 2004, p. 48). A core assumption of interaction ritual theory is
that individuals are motivated to pursue experiences and social interactions that elevate their
energy and to avoid interactions that reduce it. Casciaro and Lobo (2008) found that participants
were more likely to go to a colleague for task-related information with whom the information-
seeker felt positive interpersonal affect and less likely to go to someone with whom the seeker
felt negative interpersonal affect. Participants sought interactions where they expected to
experience positive activation, even if it meant going to a less knowledgeable person. Interaction
ritual theory provides two fundamental assumptions for an emerging theory of relational energy:
(1) energy is a mechanism in social and interpersonal settings that influences individual
behavior, and (2) activation is shared and spread contagiously between people.
Social contagion theories. Social contagion focuses on the spread of stimuli to other
RELATIONAL ENERGY AT WORK 7
people, such as the spread of emotions through emotional contagion (Hatfield, Cacioppo, &
Rapson, 1994). The spread of positive emotions can have a host of desired effects on work
behaviors, such as enhanced cooperativeness, minimized conflict, and increased task
performance (Barsade, 2002). More generally speaking, social contagion extends beyond
affective experience, describing the social transference of thoughts and ideas (Hirshleifer &
Teoh, 2009), attitudes (Paxton, Schultz, Wertheim, & Muir, 1999), motivation (Radel, Sarrazin,
Legrain, & Wild, 2010), and behaviors (Crandall, 1988). Importantly, these transfers share these
resources between interacting individuals. Social contagion theory thus complements the
contagious effect insinuated by interaction ritual theory, providing a potential mechanism by
which human energy can be transmitted through social interaction.
Conservation of resources theory. Conservation of resources theory (COR) argues that
people retain, protect, and build resources, including energy, by striving to create social
circumstances that help secure these resources (Hobfoll, 1989). COR scholars consider energy
to be a scarce resource, such that it must be replenished when depleted (Hobfoll & Shirom,
2001). Thus, COR suggests that individuals may seek to maintain or replenish resources such as
energy through other individuals. Scholars have employed COR theory to explain the
functioning of several interpersonal constructs, including perceived social support (Demerouti,
Bakker, de Jonge, Janssen, & Schaufeli, 2001), social capital (Carmeli, Ben-Hador, Waldman, &
Rupp, 2009), and positive work relationships (Fritz, Lam, & Spreitzer, 2011). Overall, COR
theory supports the idea that individuals can and will seek to foster the resource of energy
through social interactions.
Together, these theories provide a theoretical foundation for relational energy, explaining
why individuals are motivated to associate with others who increase their feelings of energy and
how this energetic activation transfers between interaction partners. We next empirically explore
and test this construct. As relational energy is an emergent construct, we follow Edmonson and
RELATIONAL ENERGY AT WORK 8
McManus (2007) in employing a mixed-method approach to develop new theory based on scant
existing theory. To do so, we first engaged in a qualitative study which garnered employee
insights on the nature and functioning of relational energy at work.
Study 1: Emergent Understandings of Relational Energy
To understand how relational energy may function in a real work context, we
administered an open-ended survey question to 64 individuals employed in a wide variety of
industries (retail, financial, food, educational, health care, and hospitality), which enabled
effective and efficient sampling of a broad range of perspectives about the experience of
relational energy at work (Gephart, 1993). The survey asked these participants (41% female,
64% Caucasian, 4 years average work experience, ages from 18 to 38): “Have you ever had a co-
worker, boss/supervisor, or team member that you felt energized to be around?” They were then
prompted to type 100–200 words describing specifically how and why they were energized by
this person and how this person influenced their work. The majority of respondents (59%)
identified a leader as a relational energizer. In line with word-text coding analysis
recommendations (Mossholder, Settoon, Harris, & Armenakis, 1995), we uploaded the responses
into Excel and initially reviewed responses to generate a list of themes. All responses were then
independently coded by the first author and another trained researcher. Analysis of these
independent codings suggested that codings were identical 84% of the time, yielding a cross-
tabbed Cohen’s Kappa of ҡ = .67 (p < .001), which represents “substantial strength of
agreement” (Landis & Koch, 1977, p. 165). Differences in codings were discussed until
consensus was reached on all coding categorizations.
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Insert Table 1 about here
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Several themes emerged which match existing energy literature (Cole et al., 2012;
RELATIONAL ENERGY AT WORK 9
McDaniel, 2011) including positive affect, cognitive stimulation, and behavioral modeling.
Descriptions of energizing partners were consistently associated with enhanced psychological
resources—including the motivation, stamina, and activation language captured by our
participants—that help employees meet work demands. Regarding this function of relational
energy, respondents mentioned that their relational energizer made them feel as if they could
work harder, enjoy their work, or be motivated to stick to their tasks: “She . . . keeps me
motivated to keep up the hard work,” “I was very motivated to do better at work,” “[This person]
made me want to achieve more in work,” “People wanted to be around her and wanted to do well
for her,” and “I always feel . . . ready to go to these group meetings because of her.” Other times,
relational energy was described in terms of a renewed sense of vigorous capability (“He made
me feel . . . driven,” “He believes in me and what I am capable of doing, which pushes me to
work harder and better”). For one participant, an energizing leader “bolstered [his] drive to
complete the job with unfailing quality.” We focus our analysis on motivational arousal, or the
generation of feelings of motivation and elevated arousal towards one’s capacity to do work, as
more than nine of ten (92%) responses indicated this connection. Splitting the sample up by
relationship type, we found that though the dimension of motivational arousal emerged most
often in descriptions of leader energizers (97%), this aspect of relational energy was also
prominent in coworker descriptions (81%).
Upon reviewing the data, it became clear that participants resonated with different types
of energizer stimuli. While not all individuals were energized by the same means, motivational
arousal emerged as the common crux of the experience of relational energy. Rather than
suggesting a multi-faceted relational energy construct incorporating affective, cognitive, and
behavioral components (which were each inconsistently described by participants), our data
revealed motivational arousal as the most prominent and consistent feature of relational energy.
Table 1 contains sample illustrative quotes from several participants which show how different
RELATIONAL ENERGY AT WORK 10
types of energizer stimuli yielded similar forms of psychological resources. Drawing from this
finding, we conceptualize relational energy as energy which comes from another person, which
captures the energizing toward the accomplishment of work tasks. Thus, we define relational
energy as a heightened level of psychological resourcefulness generated from interpersonal
interactions that enhances one’s capacity to do work. Following Quinn, Spreitzer, and Lam
(2012), we use the broader term psychological resourcefulness to capture the motivation, vitality,
stamina, and vigor that is generated as a result of a series of interpersonal exchanges. To be
clear, we are not implying that relational energy is a different “type” of energy, but rather use the
adjective “relational” to identify the level at which energy (or energetic activation) exists or is
enacted.
Nomological Network and Hypothesis Development
Our next task was to determine the extent to which this concept of relational energy is
distinct from related constructs, and how it relates to desired work outcomes. This section
addresses relational energy’s distinctiveness from rival constructs and develops hypotheses for
the influence of relational energy on job engagement and job performance.
Relational Energy and Related Constructs
Perceived social support. Perceived social support can refer to support from dyadic
partners or collectives and captures the extent to which individuals perceive that they experience
supportive social relationships at work with others (Wiesenfeld, Raghuram, & Garud, 2001).
Social support also captures the perceived level of help or backing available for work-related
difficulty, and its source can be from co-workers or supervisors. Dyadic social support is
associated with, but distinct from, relational energy. Though both capture aspects of dyadic
relationships, social support relates to a sense of connection and belonging and is proposed to
yield positive feelings about the self (Halbesleben, 2006), while relational energy entails how
another individual can influence the transfer of psychological resources towards doing work.
RELATIONAL ENERGY AT WORK 11
Thus, we propose the following:
Hypothesis 1: Relational energy is positively related to but distinct from perceived social
support.
Leader-member exchange. Given that leader-follower dyads were the most common
relational type identified when describing relational energy, it is important to differentiate
relational energy from the most commonly studied leader-follower relational construct: leader-
member exchange. Leader-member exchange (LMX) is a construct that captures the level of
reciprocal satisfaction, trust, and understanding in a leader-follower dyad (Graen & Uhl-Bien,
1995). Conversely, relational energy is not reciprocal. It reflects the energizing psychological
resources that one individual receives from another. Relational energy is not limited to leader-
follower dyads, but can occur between any two individuals. Also, relational energy connotes the
outcome of dyadic interactions (i.e., enhanced motivation to do one’s work) rather than the
cognitive evaluation of relational quality typical of LMX. Therefore, we propose:
Hypothesis 2: Relational energy is positively related to but distinct from LMX.
Relational Energy, Job Engagement, and Performance
In addition to its conceptual distinctiveness, we endeavored to investigate the extent to
which relational energy predicts work outcomes. Two common and useful outcomes in the
literature are job engagement and job performance (Hinkin, 1995; Rich, Lepine, & Crawford,
2010). Study 1 provided qualitative evidence that the transference of energy from one person to
another is an important mechanism through which individuals are motivated to do work. This
occurs through the receipt of psychological resources to cope with job demands and meet
performance expectations. We formulated hypotheses that address how this process may be
associated with engagement and performance outcomes.
Job engagement. Job engagement captures the level of absorption and dedication an
employee has toward his or her job (Schaufeli & Bakker, 2004), reflecting the degree to which
RELATIONAL ENERGY AT WORK 12
employees apply their entire selves to their work roles (Rich, Lepine, & Crawford, 2010). The
enhanced psychological resources entailed in relational energy will likely be associated with
increased job engagement. Based on interaction ritual and social contagion theories, we theorize that
the types of interactions employees have with others would likely impact employee job
engagement. Kahn (1990) suggested that interpersonal interactions marked by dignity, respect, and
appreciation from others in a work environment can foster job engagement, but he did not delineate
the specific mechanisms that explain this relationship. We pose that relational energy serves as such
a mechanism, as the transference of resources provides employees with the motivation and ability to
act, which translates into engaged behaviors. In addition, conservation of resources (COR) theory
suggests that the presence of work resources fosters job engagement, while their absence results in
burnout (Saks, 2006), supporting the idea that the receipt of psychological resources, such as those
produced by relational energy, will be associated with greater job engagement.
Some evidence emerged in the qualitative data that a connection exists between relational
energy and job engagement. For example, “When working with him I'm more eager to engage.”!
Interview statements also reflected other antecedents of job engagement (Kahn, 1990; Rich, Lepine,
& Crawford, 2010) including meaningfulness, value congruence (“She turned tasks and ‘work’!into
purpose and meaning”), and feelings of psychology safety in the environment (“She reinforced a lot
of positive feedback which encouraged you to do well”) (Edmondson, 1999). Energizers were
described as being able to engage others by making menial or tedious tasks exciting and enjoyable
(“He made the ‘grind’!of that work [public accounting] tolerable and . . . exciting, believe it or not”!
and “I worked harder with him because he made work fun and easy”). These statements suggest that
relational energy is associated with some of the core antecedents of job engagement. Therefore, we
predict relational energy will be positively related to job engagement.
Hypothesis 3: Relational energy is positively related to employee job engagement.
Job performance. We also expect that experiencing relational energy at work will be
RELATIONAL ENERGY AT WORK 13
positively associated with an employee’s job performance. Cole et al. (2012) positively
associated productive energy at the collective level with unit performance. Carmeli et al. (2009)
associated employee vigor with increased performance. Baker, Cross, and Wooten (2003) found
that individuals who acted as energizers to others had higher job performance. Employees who
receive energy from coworkers or leaders in their organization will reciprocate with loyalty and
extra effort, and would thus be associated with higher overall performance (Homans, 1961).
Increased persistence and motivation has been found to lead to higher task performance (Brief &
Weiss, 2002). We therefore hypothesize that relational energy is associated with increased
individual performance.
Hypothesis 4: Relational energy is positively related to employee job performance.
We hypothesize that relational energy with another person at work will enhance an
employee’s job performance through job engagement. Job engagement, entailing enhanced
persistence, dedication, and vigor at work, has been empirically associated with enhanced task
performance. For example, across a variety of industries and occupations, job engagement was
found to be positively associated with self-rated (r = .28), coworker-related (r = .27), and
supervisor-rated (r = .32) performance (Halbesleben & Wheeler, 2008). In addition, job
engagement mediated the relationship between organizational support and job performance
(Rich, LePine, & Crawford, 2010). Since relational energy, like organizational support, is a type
of job resource, we also predict that job engagement will mediate the relationship between
relational energy and employee job performance.
Statements from the qualitative data also suggest that the personal resources received
from relational energy enhanced the job engagement of employees, leading to higher job
performance. In line with the literature which has shown a strong engagement–job performance
relationship (Rich et al., 2010), we expect that the transfer of psychological resourcefulness
comprised in relational energy will enhance employee job performance through the mechanism
RELATIONAL ENERGY AT WORK 14
of job engagement.
Hypothesis 5: The relationship between relational energy and employee job performance is
mediated by employee job engagement.
To empirically test our hypotheses related to relational energy, we conducted three
quantitative studies, drawing data from both field and lab samples. In Study 2, we develop and
validate a measure of relational energy and differentiate it from related constructs. In Study 3, we
examine relational energy’s prediction of unique variance beyond that of another predictor. In Study
4, we test our full model. Quantitatively examining relational energy forced us to make decisions
about study design and scope. To isolate the effects of relational energy it was important to keep
relationship type constant in our quantitative studies. Though we anticipate our hypotheses would
also apply to coworker to coworker relational energy, Studies 2 through 4 focus on leader-member
dyads, the most prevalent relationship type that emerged from our qualitative data.
Study 2: Relational Energy Scale Validation and Discriminant Analysis
Participants and Procedures
Three samples were used to develop and validate the relational energy scale. Samples A
(184 full-time employees) and B (200 full-time employees) were drawn from a commercial
subject pool (that is, a pool with registered participants who were paid to complete surveys).
Sample C was drawn from a United States health services organization. Details and
demographics of each sample are summarized in Table 2. All surveys were administered online.
Development of Relational Energy Measure
Item generation. Following the guidelines suggested by Hinkin (1995), our goal was to
develop a robust and valid measure of relational energy from the perspective of the receiver.
Informed by relevant literature and our inductively derived definition, the authors independently
generated an initial list of 22 items and then met to discuss the face validity of each item. After
discussion about the face validity and item clarity, we settled on 10 relational energy items to be
RELATIONAL ENERGY AT WORK 15
used for subsequent empirical testing, the number of items we felt allowed for subsequent
refinement and deletion. Items were scaled using a Likert scale from 1 (strongly disagree) to 7
(strongly agree).
Exploratory factor analysis. Participants from Sample A were asked to rate someone
they work with based on the initial 10 relational energy items. From this data we ran a series of
principal components analyses using Varimax rotation. The factors were free to vary based on
the traditional Eigenvalue cutoff of 1.0. Following Hinkin (1995), we eliminated relational
energy items with low loadings (i.e., below .40) on the first factor or with unacceptably high
cross-loadings (i.e., above .40) on the second factor. The factor analysis was then rerun using the
remaining items. Three rounds of this process resulted in five items being dropped, yielding a
five-item, one-factor solution (α = .94). Scale items statistics are presented in Table 3.
Exploratory discriminant validity analysis. The survey administered to Sample B
asked participants to rate their immediate supervisor on relational energy and the rival constructs
of social support (Rhoades, Eisenberger, & Armeli, 2001; four items, e.g., “My supervisor really
cares about my goals and values”) and LMX (Scandura & Graen, 1984; seven items, e.g., “I have
enough confidence in my immediate supervisor that I would defend and justify his or her
decisions if he or she were not present to do so”). The Sample B survey also included three other
related measures of energy or relational connection at work: collective energy (productive energy
measure; Cole et al., 2012; 14 items, e.g., “People in my work group feel excited in their job”),
individual energy (emotional energy scale; Shirom, 2004; four items, e.g., “I feel I am capable of
investing emotionally in coworkers and customers”), and relational identification (Zhang, Chen,
Chen, Liu, & Johnson, in-press; seven items, e.g., “I feel strongly identified with this workgroup
because I share mutual respect with other members”). These three added constructs do not
capture dyadic phenomena (like perceived social support and LMX) and therefore are not direct
rivals to the relational energy construct. However, the energy and relational identification
RELATIONAL ENERGY AT WORK 16
measures were included in our discriminant validity analysis since they also represent aspects of
the experience of energy at work and the strength or quality of relational connections at work.
All measures were scaled to a 5-point agreement scale from 1 (strongly disagree) to 5 (strongly
agree), with exception of the Scandura & Graen (1984) LMX scale which comprises multiple
anchors that reflect low (1) or high (5) frequency, magnitude, probability, and effectiveness. The
alpha reliabilities for these scales ranged from .86 to .96 (Table 4).
A principal components analysis (Varimax rotation, factors free to vary) revealed that all
relational energy items loaded strongly onto one factor (loadings ranging from .82 to .86) with
no cross-loadings onto other factors (full analysis results are available from the first author upon
request). In addition, based on the .40 factor loading cutoff, no items from any of the other scales
loaded on to the relational energy factor (cross-loadings ranged from .02 to .27). Overall, these
results offer initial empirical evidence that relational energy is distinct from perceived social
support, leader-member exchange, productive energy, emotional energy, and relational
identification. Table 4 contains descriptive statistics, reliabilities, and correlations for all Sample
B variables. As shown in Table 4, relational energy was positively related to its rival constructs
of perceived social support (r = .49, p < .001) and leader-member exchange (r = .45, p < .001).
Using data from Sample C, we conducted a confirmatory factor analysis using Amos 19
(Arbuckle, 2010) to confirm the factor structure of the relational energy measure and further
distinguish relational energy from perceived social support and leader-member exchange. The
Sample C survey contained the same measures of relational energy, perceived social support, and
leader-member exchange used in Sample B. As shown in Table 5, the three-factor solution (χ2
[98] = 169.83, CFI = .98, TLI = .98, SRMR = .03, RMSEA = .05) fit the data better than either
two-factor or one-factor solutions, supporting the uniqueness of relational energy from rival
constructs. Overall, results from Samples B and C suggest that relational energy is related to but
distinct from the rival constructs of perceived social support and leader-member exchange,
RELATIONAL ENERGY AT WORK 17
supporting Hypotheses 1 and 2.
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Insert Tables 2 through 5 about here
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Study 3: Relational Energy, Perceived Social Support, and Employee Job Engagement
In this study, we test the usefulness of the relational energy scale in predicting criteria
beyond the rival construct of perceived social support. Data from 221 employees from a large
United States health services organization (75% female, 64% Caucasian, average age 38, average
tenure under supervisor 10.62 months) were used to test Hypothesis 3, specifically, that
relational energy will predict employee job engagement. The two-part survey was administered
as part of a voluntary and anonymous organizational assessment. Time 1 contained demographic
questions, relational energy, and perceived social support measures. Time 2 (approximately one
month later) contained an assessment of employee job engagement. Both surveys were
administered online and sent to employee e-mails provided by the organization. The organization
also provided us the supervisor number associated with each employee e-mail address, enabling
us to link employees with their supervisor.
Measures
Relational energy. Participants were asked to rate their immediate supervisors on the
five-item relational energy scale developed and tested in Study 2, using a 7-point Likert scale (7
= strongly agree). The alpha reliability for this scale was .96.
Perceived supervisor social support. Participants completed the same four-item
supervisor social support scale administered in Study 2 using a 5-point Likert scale (5 = strongly
agree). The alpha reliability for this scale was .87.
Employee job engagement. Participants were asked to complete a nine-item job
engagement scale scaled to a 7-point Likert scale (7 = strongly agree) as in Schaufeli, Bakker, &
RELATIONAL ENERGY AT WORK 18
Salanova (2006). Sample items include: “I am immersed in my work” and “I am proud of the
work that I do.” The alpha reliability for this scale was .94.
Controls. Spector and Brannick (2011) recommend providing clear theoretical
justification for the inclusion of controls and framing the impact of control variables as
alternative hypotheses. We controlled for leader and employee gender since female employees
and bosses are generally more relationally oriented (Eagly, 2009) and may be more likely to seek
meaningful relational connections that are motivating. We controlled for leader and employee
race to capture potential differences in cultural power distance or collectivism that could account
for bosses and employees with lower power distance and higher collectivism, who will be more
likely to develop closer working ties that are motivating (Gaines et al., 1997). We controlled for
employee age to account for the possibility that those who report more relational energy could be
simply younger, as vitality and productivity in the workplace has been reported to diminish with
age (Skirbekk, 2008). We controlled for employee tenure in case relational energy is explained
by newness in the organization where the employees may be in a honeymoon phase and are
simply excited about working in their new job, or alternatively, to account for the possibility that
those who have not self-selected out of the organization may be more likely to enjoy the work or
have developed the personal stamina and motivation to persevere in the work. As mentioned
above, we included perceived social support as a control to test the alternative hypothesis that the
effect of relational energy on job engagement is not a matter of relational energy but rather a
matter of perceived supportiveness from one’s leader that fosters feelings of connection and
belonging that generally enhance one’s desire to be at work.
Analyses and Results
Since this sample had an average of 2.59 employees under each supervisor, we computed
ICC scores and a design effect score (Kish, 1965: Deff = 1 + [[average group size – 1]* ICC1])
to justify analyzing this data on the dyadic level. The ICC 1 and 2 scores for relational energy
RELATIONAL ENERGY AT WORK 19
were .20 and .39, respectively. The ICC2 score is well below Glick’s (1985) recommended cut
off of .60. In addition, the design effect score was also low (Deff = 1.31), which suggests that we
are justified in not accounting for group effects in our estimations (Muthen & Satorra, 1995).
Together, these results support our use of the data on the dyadic level, which is the theorized
level of the relational energy phenomenon. Two sets of confirmatory factor analyses were
conducted using Amos 19 (Arbuckle, 2010) to test Hypothesis 1 and ensure the distinctiveness of
all study variables.
Hypothesis 1 states our prediction that relational energy will be related to but distinct
from perceived social support. We first conducted confirmatory factor analyses using structural
equation modeling to test the discriminant validity of relational energy and perceived social
support. Fit-indices were compared across two rival models. The two-factor model with
relational energy and social support modeled separately fit the data well (χ2 [22] = 37.37; CFI =
.99; TLI = .99; SRMR = .04; RMSEA = .05); significantly better than the one factor model (χ2
[23] = 279.86; CFI = .79; TLI = .80; SRMR = .11; RMSEA = .21). We then tested the three-
factor solution including the nine employee job engagement items in the analysis and found it
was superior to any two- or one-factor solution, based on the χ2 different test and standard
cutoffs for fit indices (χ2 [128] = 257.85; CFI = .98; TLI = .98; SRMR = .03; RMSEA = .05).
Full analyses are available from the first author upon request.
Bivariate correlations shown in Table 6 demonstrate that the five-item relational energy
scale was significantly associated with perceived social support (r = .58, p < .001), in support of
Hypothesis 1. Hypothesis 3 states our prediction that relational energy will be positively
associated with employee job engagement. Table 6 also shows that relational energy was also
related to employee job engagement (r = .40, p < .001), showing initial support for Hypothesis 3.
As shown in Model 2 in Table 7, perceived social support was positively associated with
employee job engagement beyond demographic controls (B = .42; 95% C.I. [.29, .55]; p < .001;
RELATIONAL ENERGY AT WORK 20
∆R2 = .14). In Model 3, relational energy predicted additional variance in job engagement
beyond social support (B = .27; 95% C.I. [.14, .40]; p < .001; ∆R2 = .07), further supporting
Hypothesis 3. We note here that relational energy explains unique variance beyond leader social
support whether or not demographic control variables were included in our analyses.
----------------------------------------
Insert Tables 6 and 7 about here
--------------------------------------
To address potential concerns of common method variance, we conducted several post-
hoc tests. Utilizing Harman’s one-factor test with all self-report data, we found that one factor
did not explain the majority of the variance in this study. As a more robust test and in line with
past research (Conger, Kanungo, & Menon, 2000), we also created unmeasured latent method
factors in structural equation modeling, connecting all self-report study items to this latent factor
and constraining all the paths from this latent factor to be equal. By squaring the resulting
regression coefficients from this latent factor, we observed that only 2% of the variance across
these items was due to an unmeasured common factor. Furthermore, the association between the
study variables was still highly significant (p < .001) when the unmeasured latent method factor
was included in the model. Thus, it appears unlikely that our findings are explained by common
method variance.
In Study 3, relational energy was shown to be related to yet distinct from perceived social
support and to account for unique variance in employee job performance beyond perceived
social support, supporting Hypotheses 1 and 3.
Study 4: Construct and Predictive Validity
To further establish the relational energy scale, in Study 4 we replicated the factor
structure of the scale with another field sample, showed further differentiation from LMX
(Hypothesis 2), and tested Hypotheses 3 through 5. While controlling for leader-member
RELATIONAL ENERGY AT WORK 21
exchange, we replicated the positive relationship between relational energy and job engagement
(Hypothesis 3), and showed that relational energy is positively associated with employee job
performance (Hypothesis 4) through the mechanism of job engagement (Hypothesis 5).
Participants and Procedures
The sample for this study consisted of 123 employees from a large health services
organization. Of the employees, 76 percent were female, 53 percent were Caucasian, and the
average age was 37. The average tenure of each employee was 62 months. As part of a two-stage
annual organization assessment, we sent employees an e-mail through the company listserv with
a link to an online survey asking employees, like Study 3, for information about their
relationship with their direct supervisor, job attitudes, and demographics. Though the annual
assessment was encouraged, it was also voluntary and anonymous (i.e., leaders would not know
who did or did not participate), as all reporting of results to their supervisor was done in
aggregate form. Time 1 and Time 2 assessments were administered approximately four weeks
apart. The Time 1 survey contained items assessing relational energy and general demographic
information. The Time 2 survey contained items for the employee to assess employee job
engagement and leader-member exchange. We obtained objective employee performance data at
Time 3, spanning the month after the Time 2 survey administration from the organization. Due to
differences in employee functions, only 81 of the 123 total employees had objective performance
data. Two of the employees with performance data did not fully complete the survey, and
casewise diagnostics revealed an extreme outlier in this group with a standard residual value of
3.64. These three cases were not included in analyses making a total of 78 employees with
performance data. ANOVA tests revealed that there was no difference between these employee
groups. The organization provided us the supervisor number associated with each employee e-
mail address, enabling us to link employees with their supervisor.
Measures
RELATIONAL ENERGY AT WORK 22
Relational energy. The relational energy scale developed in Study 2 (see Table 3) was used
in Study 4. To make each item specific to their supervisor, “this person”!was replaced with “my
immediate supervisor”!for each item. The alpha reliability for this scale was .96.
Job engagement. The same scale used in Study 2 (Schaufeli et al., 2006) was used to
measure employee job engagement in Study 4. The alpha reliability for this scale was .93.
Job performance. As a proxy for employee performance, we requested and received
objective productivity data that represents a key performance metric for this organization. This
metric, which ranges from 1.50 (most productive) to-1.0 (least productive), captures the
employees’ discretionary decisions regarding how much time they spend performing core work
tasks, as opposed to non-work activities (specifically, how much of the employee’s shift was
spent working to assist clients as recorded in the firm’s computerized client support system).
This performance criterion was selected based on insights from the qualitative study, capturing
employee stamina and enduring motivation in doing repetitive work tasks.
Leader-member exchange. We controlled for employee ratings of leader-member
exchange using a 7-item Likert scale (Scandura & Graen, 1984). Sample items from this scale
include “Regardless of the amount of formal authority your immediate supervisor has, to what
extent can you count on him or her to ‘bail you out’ at his or her expense when you really need
it?” and “I have enough confidence in my immediate supervisor that I would defend and justify
his or her decisions if he or she were not present to do so.” The alpha reliability for this scale was
.94.
Controls. We controlled for the same leader and employee demographic variables
included in Study 3: leader gender and race, employee gender, race, age, and organizational
tenure. We also had frequency of interactions with one’s leader, but the results were equivalent
whether or not we included this control, so we report the same controls as Study 3. We note here
that relational energy explained unique variance beyond leader-member exchange whether or not
RELATIONAL ENERGY AT WORK 23
demographic control variables were included in our analyses.
To show scale independence, we conducted a CFA for relational energy, leader-member
exchange, and job engagement. The three-factor model fit the data significantly better (χ2 [178] =
463.05; RMSEA = .05; SRMR = .03; CFI = .98; TLI = .97) than any other model, including the
two-factor model with relational energy and leader-member exchange combined (χ2 [180] =
1543.59; RMSEA = .11; SRMR = .10; CFI = .89; TLI = .87; ∆χ2[3] = 1080.54, p < .001), or the
one factor model (χ2 [181] = 3793.02; RMSEA = .18; SRMR = .18; CFI = .71; TFI = .66; ∆χ2[3]
= 3329.97, p < .001).
Analyses and Results
Since we had an average of 4.71 employees under each leader, and relational energy is a
dyadic phenomenon, we conducted two tests to determine if we were justified in using this
clustered data on the dyadic level, drawing from Glick (1985) and Muthen and Satorra (1995;
similar to Study 3). The ICC 1 and 2 scores for relational energy were-.02 and-.09, respectively,
the mean square between value (MSB = .95) was lower than the mean square within value
(MSW = 1.04), and the design effect score was also low (Deff = .93). These low scores suggest
that we are justified in not accounting for group effects in our estimations, supporting our use of
the data at the dyadic level. As mentioned, casewise diagnostics revealed one outlier with a
standard residual value of 3.64. Although results were equivalent when including this case, to
conform with regression normality assumptions, this case was eliminated from analyses.
Table 8 contains the descriptive statistics and bivariate correlations of all study variables.
We found initial support for Hypotheses 3 and 4: relational energy positively relates to job
engagement (r = .43; p < .001) and job performance (r = .27, p < .01). To test Hypotheses 3 and
4 we conducted regression analyses, and to test Hypothesis 5 we conducted a bootstrapped
indirect effect analysis (Preacher & Hayes, 2008). For our regression analysis (Table 9), we
computed a total of five models. All variance inflation factor (VIF) values were below standard
RELATIONAL ENERGY AT WORK 24
cutoffs (i.e., VIF < 2.1), suggesting that multicolinearity was not an issue. Hypothesis 3 states
that relational energy will be positively associated with employee job engagement. In Table 9
Model 3 we report that relational energy predicted job engagement beyond the rival construct of
leader-member exchange, and demographic controls (B = .24; 95% CI [.06, .41]; p < .05; ∆R2 =
.04). Thus, Hypothesis 3 is supported.
---------------------------------------
Insert Tables 8 and 9 about here
---------------------------------------
Hypothesis 4 states that relational energy will be positively associated with employee job
performance. In Model 6, relational energy positively predicted employee job performance
beyond demographic controls and leader-member exchange (B = .13; 95% CI [.02, .29]; p < .05;
∆R2 = .05), supporting Hypothesis 4. Hypothesis 5 states that relational energy will influence
employee performance indirectly through employee job engagement. In Model 7, employee job
engagement was positively associated with job performance (B = .21; 95% CI [.09, .32]; p < .01;
∆R2 = .12) and the effect of relational energy on job performance went to zero, providing initial
support for Hypothesis 5. However, as a more robust test of indirect effects, we used the
bootstrap approach advocated by Preacher and Hayes (2008). This approach entails randomly
sampling 5,000 bootstrapped sets of cases from the original data to derive a bias corrected and
accelerated confidence interval that reflects the mediation effect. This approach helps to offset
the weaknesses of a causal steps approach (Hayes, 2009). Our bootstrapped procedure resulted in
an indirect effect of .04 with a 95% confidence interval that did not include zero [.001, .124],
providing support for the mediating role of job engagement in support of Hypothesis 5.
To again address common method variance concerns, we conducted several post-hoc
tests. Harman’s one-factor test with all self-report data found that one factor did not explain the
majority of the variance. We also created an unmeasured latent method factor in structural
RELATIONAL ENERGY AT WORK 25
equation modeling, connecting self-report items to this latent factor and constraining all the paths
from this latent factor to be equal. By squaring the resulting regression coefficients from this
latent factor, we observed that only 3.6% of the variance across these items was due to an
unmeasured common factor. Furthermore, the association between the study variables is still
highly significant (p < .001) when the unmeasured latent method factor is included in the model.
Thus, it is unlikely that these findings are explained by common method variance.
General Discussion
As early as 1956, psychologists were making distinctions between the exchange of
information and the transfer of energy in interpersonal interactions (Newcomb, 1956, pp. 577–
578). Though there is a large literature comprising theoretical and empirical examinations of
information exchange (see Borgatti & Cross, 2003 for a review), empirical studies of
interpersonal energy transfer are scant. As human energy is a critical organizational resource, our
findings help build theoretical knowledge of how human energy can be derived from
interpersonal interactions. In line with this purpose, we introduced the construct of relational
energy, discussed its theoretical relevance to the work context, offered rationale and empirical
evidence supporting its conceptual uniqueness, and provided evidence for its predictive validity.
The results suggest that relational energy is a psychometrically robust, reliable, and valid
construct that occupies unique conceptual space relative to similar constructs. Our results also
provide support for relational energy being positively associated with job performance and job
engagement.
Theoretical and Empirical Contributions
Relational energy links theoretical insights from interaction ritual, contagion, and
conservation of resource theories to produce a clearer understanding of how interpersonal
interactions at work can be energizing. We highlight three important contributions of this
research: (1) theory and operationalization of a novel relational mechanism with implications for
RELATIONAL ENERGY AT WORK 26
desired work outcomes, (2) empirical support for interaction ritual theory situated in a work
setting, and (3) insight into supervisor-employee influence processes.
Relational mechanism of energy. This study carefully defines and operationalizes
relational energy from the perspective of the individual receiving energy from an interaction
partner. Despite the fact that human energy has been cited as the fundamental resource of
organizations (Katz & Kahn, 1966) and human interaction (Newcomb, 1956), few scholars have
explored the mechanisms of the energizing influence of human interactions at work. For
example, preliminary research implies that increased energy and vitalization are attained through
interpersonal interactions (Fritz, Lam, & Spreitzer, 2011; Grant & Parker, 2009), but the
mechanisms by which this transpires are seldom directly tested. In other words, existing theory
suggests that employees are energized by emotive or stimulating interaction partners, but the
nature of this social energy exchange and how these factors energize individuals have not been
directly examined, as we do here.
Thus, the current study contributes to the theory on the role of energy in relational
interactions in organizations by providing a theoretical explanation and operationalization of
relational energy. The construct of relational energy explains why workplace interactions
stimulate attitudinal and behavioral outcomes: they provide helpful psychological resources
which can be allocated towards the doing of work. In line with COR theory, these psychological
resources enhance employees’ ability to be fully engaged in their work, leading to higher
performance. COR theory also suggests that the enhanced psychological resources resulting from
relational energy would enable greater coping with workplace stressors and burnout, enhancing
workplace well-being (Sonnentag, Mojza, Demerouti, & Bakker, 2012). Such topics would be
worthwhile to explore in future research.
Empirical support of interaction ritual theory. While interaction ritual theory has had
decades of theoretical development in the sociological literature, this study represents one of the
RELATIONAL ENERGY AT WORK 27
few attempts to empirically assess this theory and to test its precepts across a series of workplace
settings. Interaction ritual theory helps to explain why individuals seek certain social
interactions (that generate feelings of excitement, enthusiasm, and positivity) but avoid others
(that do not).
Here, we extend interaction ritual theory in two ways. First, we provide empirical
support for interaction ritual theory as applied to a workplace context. Our relational energy
scale measures the extent to which an employee is invigorated, feeling increased vitality,
stamina, and energy to do work, after an interaction with a particular interaction partner. This is
consistent with Collins’ (2004) description of the effects of receiving energy from an interaction.
Our scale development and predictive validity analyses provide perhaps the first measure that
can be used to quantitatively assess received relational energy. Second, our study and scale
items are employed in workplace settings. Thus, while Collins studied the receipt of emotional
energy in generalized social environments (such as taverns and ladies’ social groups), we situate
this theory in an organizational setting where enhancing work effectiveness is a salient and
desired outcome. Our finding that interactions which generate received psychological resources
yield desired work outcomes provides a compelling reason for the significance of this theory to
organizations.
Leader influence processes. Though relational energy is a construct that could
characterize many types of relationships, our use of the leader-follower relationship in Study 2
specifically contributes to the leadership literature. Existing leadership constructs imply that
leadership is largely synonymous with influence, as leaders influence followers using
mechanisms such as persuasion, charisma, providing resources, or exchanging information
(DeRue & Ashford, 2010). The mechanisms that account for the transfer of influence, however,
have not been adequately articulated nor tested (Atwater & Carmeli, 2009).
Our research shows that the energy resulting from leader-follower dyadic interactions is
RELATIONAL ENERGY AT WORK 28
associated with changes in follower job engagement and performance. That is, leaders are cast
in a novel, expansive role as energy brokers who may enhance follower work functioning. The
leader-follower relationship has also been studied with the construct of LMX, which has yielded
understanding of the reciprocal or two-way nature of leader-follower relationships. Conceptually,
however, LMX focuses more on the perceptions of trust and understanding in a dyad, while
relational energy captures the actual transfer of resources in a dyad. This adds a new facet to our
understanding of both the value of leader-follower relationships, as well as the magnitude of the
responsibility and opportunity leaders have to transfer such resources to employees on a regular
basis. We note that the correlation of relational energy was .45 in Study 2, and .67 in Study 4—
results which may be explained by contextual differences across samples and highlight the need
to explore potential moderating variables to this relationship. Overall, our approach expands the
role of leaders to include the provision of energy in addition to being information sources,
extrinsic reward-brokers, or vision-givers. This adds to the leadership literature by identifying
specific interpersonal effects that leaders can have on followers through the transfer of
psychological resources.
Lastly, this study highlights the need for complementarity between leader approaches and
follower individual differences or preferences (dominance complementarity theory; Carson,
1969; Grant, Gino, & Hofmann, 2011; Perry, Witt, Penney, & Atwater, 2010). For example,
given the varied energizing stimuli we observed in the qualitative data, leaders who behave
charismatically by being intellectually stimulating or modeling extraordinary behaviors may not
energize all followers. The advantage of this measure of relational energy is that it captures the
perceived result of the interaction and is measured from the perspective of the follower, rather
than assuming effective influence from leader behaviors. That is, the specific content of a
leader’s behavior is secondary to whether or not a follower personally perceives interactions with
the leader as energizing. Thus, relational energy more directly captures follower perspectives and
RELATIONAL ENERGY AT WORK 29
interpretations, helping to address a commonly cited weakness of extant behavioral leadership
research (Howell & Shamir, 2005; Kellerman, 2008).
Empirical contributions. Several important empirical contributions of this research are
noteworthy. First, we developed a new relational energy scale and replicated the factor structure
across five different samples. The factor structure and reliability remained consistent whether
participants were rating coworkers (i.e., Study 2, Sample A) or work leaders. Second, we
conceptually and empirically differentiated our construct from related constructs to support our
claim that relational energy occupies unique space in the nomological network of existing
constructs. Third, as a usefulness test, we show that relational energy is associated with variance
in employee job engagement beyond the common predictors of perceived social support and
LMX and that relational energy predicts employee job performance beyond LMX. Fourth, this
research provides initial evidence that relational energy is associated with employee job
performance through employee job engagement.
Limitations and Future Research
We note several limitations to be considered when interpreting these results. First,
though the job performance measure was obtained through a unique source, common method
variance may be inflating the relationship between relational energy, perceived social support,
and job engagement in Study 3 and relational energy, leader-member exchange, and job
engagement in Study 4, since these variables were assessed by employees. To mitigate concerns
of common method variance (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003), we employed
several recommended strategies. We used temporal separation, inserting four weeks between
Time 1 and Time 2 surveys. We sought to reduce evaluation apprehension and social desirability
bias by emphasizing in all communications and in survey instructions that all responses would be
kept confidential and evaluated in aggregate form only. Finally, we used several post-hoc tests
listed in the results sections of Studies 3 and 4 to demonstrate the likelihood that our findings are
RELATIONAL ENERGY AT WORK 30
not explained by common method variance.
Second, the leader-follower dyadic relationships included in Studies 3 and 4 may limit
generalizability to other types of workplace relationships. Future research should assess this
validated relational energy scale to see if similar associations are found with other types of
relationships, such as employees receiving relational energy from peers or leaders receiving
relational energy from subordinates.
Third, due to our study’s cross-sectional nature, we cannot rule out the possibility of
reverse causality, even though we gathered data in two stages. For example, individuals who are
higher performers might be more prone to more easily receive relational energy. However, to
begin to address this issue, we reran our bootstrapped indirect effect analysis in reverse order
with performance predicting relational energy through job engagement. The 95% confidence
interval included zero [-.12, .34], which provides some support for the causal direction of our
model. Future research should employ a longitudinal design or manipulate relational energy in a
controlled lab experiment to reinforce the causal direction of our model.
Fourth, due to survey space restrictions, we were unable to control for additional
potential rival constructs in Studies 3 and 4. Though relational energy predicted variance in job
engagement beyond perceived social support and LMX and showed a stronger relationship with
job engagement (Study 3: r = .40; Study 4: r = .43) than past studies have shown for coworker
social support (r = .16; Schaufeli & Bakker, 2004, p. 306), supervisor social support (r = .21;
Hakanen, Bakker, & Shaufeli, 2006, p. 503; r = .25; Saks, 2006) or LMX (r = .26; Schaufeli &
Bakker, 2004, p. 306),1 future research should examine the degree to which relational energy
explains unique variance in a variety of organizational outcomes beyond additional existing
constructs.
More work remains to further understand energy transfer between individuals. In the
1 For comparison purposes, correlational values were averaged for the three dimensions of job engagement.
RELATIONAL ENERGY AT WORK 31
spirit of multi-trait, multi-method construct validation, future research should compare relational
energy assessments from self- and other-report sources to examine the degree to which
energizers are aware of their ability to energize others. For example, a study could compare the
intent of one interaction partner in sending energy, and how those energetic resources are
received through the course of an interpersonal interaction. Future research should also examine
whether relational energy is stable over time (i.e., test-retest reliability).
While our model focused on the relational energy construct and its outcomes, future
research might also examine antecedents of relational energy both at the individual level (i.e.,
personal well-being, self-esteem, extroversion) and at the dyadic level (i.e., demographic
similarity, power status, relationship tenure). This type of investigation could provide practical
insight about what forms of energizer stimuli may match particular individual differences,
potentially informing selection processes (e.g., relational energizers for key positions), and
interpersonal or team effectiveness (e.g., harmonizing team member work styles).
It could be important to explore any possible “dark side” of relational energy. Spreitzer et
al. (2011) proposed that, unlike forms of energy that are depleted when expended, energy
generated interpersonally is enhanced and renewed when used. It may be important to further
understand the extent to which being an “energizer” to others is sustainable. Are energizers able
to maintain their ability to energize others over time? Or is the act of energizing others on a
routine basis depleting over time? It may be that expending personal energy to give relational
energy to others results in a decreased ability to self-regulate (Baumeister, 2002). Longitudinal
dyadic data could help address these questions. Future research could explore whether relational
energizers experience workflow disruption or decreased performance due to frequent visits from
depleted co-workers, and whether workers may also fail to develop their own methods of
reenergizing, if they become too dependent on relational energizers.
Conclusion
RELATIONAL ENERGY AT WORK 32
The construct and theoretical development of relational energy provides a theory-driven
operationalization of how relationships can be energizing and how this leads to more engaged,
better performing workers. As the average worker is becoming increasingly energy depleted due
to working longer and more intense hours (Fry & Cohen, 2009) and interest in employee burnout
continues to burgeon (Halbesleben & Buckley, 2004), relational energy represents an important
construct in human organizing. More fully understanding the different sources from which
employees can derive energy to offset this burnout becomes increasingly important. This
research provides additional understanding of how individuals can derive and maintain energy
from others at work, providing important foundational support for the internal, discriminant, and
predictive validity of the relational energy construct and setting the groundwork for additional
research.
RELATIONAL ENERGY AT WORK 33
References
Agashae, Z., & Bratton, J. (2001). Leader-follower dynamics: Developing a learning
environment. Journal of Workplace Learning, 13, 89–103.
Arbuckle J. 2010. BM SPSS AMOS 19 User’s Guide. Chicago, IL: SPSS Inc.
Atwater, L., & Carmeli, A. (2009). Leader-member exchange, feelings of energy, and
involvement in creative work. The Leadership Quarterly, 20, 264–275.
Baker, W., Cross, R., & Wooten, M. (2003). Positive organizational network analysis and
energizing relationships. In K. S. Cameron, J. E. Dutton, & R. E. Quinn (Eds.), Positive
organizational scholarship: Foundations of a new discipline (pp. 328–342). San Francisco,
CA: Berrett-Koehler.
Barsade, S. G. (2002). The ripple effect: Emotional contagion and its influence on group
behavior. Administrative Science Quarterly, 47, 644–675.
Baumeister, R. F. (2002). Ego depletion and self-control failure: An energy model of the self's
executive function. Self and Identity, 1, 129–136.
Borgatti, S. P., & Cross, R. (2003). A relational view of information seeking and learning in
social networks. Management Science, 49, 432–445.
Bradbury, H. & Lichtenstein, B. M. B. (2000). Relationality in organizational research:
Exploring the space between. Organization Science, 11, 551–564.
RELATIONAL ENERGY AT WORK 34
Brief, A. P., & Weiss, H. M. (2002). Organizational behavior: Affect in the workplace. Annual
Review of Psychology, 53, 279–307.
Carmeli, A., Ben-Hador, B., Waldman, D. A., & Rupp, D. E. (2009). How leaders cultivate
social capital and nurture employee vigor: Implications for job performance. Journal of
Applied Psychology, 94, 1553–1561.
Carson, R. C. (1969). Interaction concepts of personality. Chicago, IL: Aldine de Gruyter.
Casciaro, T., & Lobo, M. S. (2008). When competence is irrelevant: The role of interpersonal
affect in task-related ties. Administrative Science Quarterly, 53, 655–684.
Cole, M. S., Bruch, H., & Vogel, B. (2012). Energy at work: A measurement validation and
linkage to unit effectiveness. Journal of Organizational Behavior, 33, 445–467.
Collins, R. (1993). Emotional energy as the common denominator of rational action. Rationality
and Society, 5, 203–230.
Collins, R. (2004). Interaction ritual chains. Princeton, NJ: Princeton University Press.
Conger, J. A., Kanungo, R. N., & Menon, S. T. (2000). Charismatic leadership and follower
effects. Journal of Organizational Behavior, 21, 747–767.
Crandall, C. S. (1988). Social contagion of binge eating. Journal of Personality and Social
Psychology, 55, 588–598.
Cross, R., & Parker, A. (2004). The hidden power of social networks: Understanding how work
really gets done in organizations. Boston, MA: Harvard Business School Press.
RELATIONAL ENERGY AT WORK 35
Demerouti, E., Bakker, A. B., de Jonge, J., Janssen, P. P. M., & Schaufeli, W.B. (2001). Burnout
and engagement at work as a function of demands and control. Scandinavian Journal of
Work, Environment & Health, 27, 279–286.
Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands
resources model of burnout. Journal of Applied Psychology, 86, 499–512.
DeRue, D. S., & Ashford, S. J. (2010). Who will lead and who will follow? A social process of
leadership identity construction in organizations. Academy of Management Review, 35,
627–647.
Edmondson, A. (1999). Psychological safety and learning behavior in work teams.
Administrative Science Quarterly, 44, 350-383.
Fritz, C., Lam, C. F., & Spreitzer, G. (2011). It’s the little things that matter: An examination of
knowledge workers’ energy management. Academy of Management Perspectives, 25, 28–39.
Fry, L. W., & Cohen, M. P. (2009). Spiritual leadership as a paradigm for organizational
transformation and recovery from extended work hours cultures. Journal of Business
Ethics, 84, 265–278.
Gaines, S. O., Jr., Marelich, W. D., Bledsoe, K. L., Steers, W. N., Henderson, M. C., Granrose,
C. S., . . . Page, M. S. (1997). Links between race/ethnicity and cultural values as mediated
by racial/ethnic identity and moderated by gender. Journal of Personality and Social
Psychology, 72, 1460–1476.
RELATIONAL ENERGY AT WORK 36
Gephart, R. P. (1993). The textual approach: Risk and blame in disaster sensemaking. Academy
of Management Journal, 36, 1465–1514.
Glick, W. H. (1985). Conceptualizing and measuring organizational and psychological climate:
Pitfalls in multilevel research. Academy of Management Review, 10, 601–616.
Graen, G. B., & Uhl-Bien, M. (1995). Relationship-based approach to leadership: Development
of leader-member exchange (LMX) theory of leadership over 25 years: Applying a multi-
level multi-domain perspective. The Leadership Quarterly, 6, 219–247.
Grant, A. M., Gino, F., & Hofmann, D. A. (2011). Reversing the extraverted leadership
advantage: The role of employee proactivity. Academy of Management Journal, 54, 528–
550.
Grant, A. M. & Parker, S. K. (2009). Redesigning work design theories: The rise of relational
and proactive perspectives. Academy of Management Annals, 3, 317–375.
Griffin, M. A., Neal, A., & Parker, S. K. (2007). A new model of work role performance:
Positive behavior in uncertain and interdependent contexts. Academy of Management
Journal, 50, 327–347.
Hakanen, J. J., Bakker, A. B., & Schaufeli, W. B. (2006). Burnout and work engagement among
teachers. Journal of School Psychology, 43, 495–513.
Halbesleben, J. R. (2006). Sources of social support and burnout: A meta-analytic test of the
conservation of resources model. Journal of Applied Psychology, 91, 1134–1145.
RELATIONAL ENERGY AT WORK 37
Halbesleben, J. R. B., & Buckley, M. R. (2004). Burnout in organizational life. Journal of
Management, 30, 859–879.
Halbesleben, J. R. B., & Wheeler, A. R. (2008). The relative roles of engagement and
embeddedness in predicting job performance and intention to leave. Work & Stress, 22,
242–256.
Hatfield, E., Cacioppo, J. T., & Rapson, R. L. (1994). Emotional Contagion. New York, NY:
Cambridge University Press.
Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new
millennium. Communication Monographs, 76, 408–420.
Hinkin, T. R. (1995). A review of scale development practices in the study of organizations.
Journal of Management, 21, 967–988.
Hirshleifer, D., & Teoh, S. H. (2009). Thought and behavior contagion in capital markets.
Handbook of financial markets: Dynamics and evolution.
Hobfoll, S. E. (1989). Conservation of resources: A new attempt at conceptualizing
stress. American Psychologist, 44, 513–524.
Hobfoll, S. E., & Shirom, A. (2001). Conservation of resources theory: Applications to stress and
management in the workplace. In R. T. Golembiewski (Ed.), Handbook of organizational
behavior (pp. 57–80). New York, NY: Marcel Dekker.
Homans, G. C. (1961). Social Behavior. New York, NY: Harcourt, Brace & World.
RELATIONAL ENERGY AT WORK 38
Howell, J. M., & Shamir, B. (2005). The role of followers in the charismatic leadership process:
Relationships and their consequences. Academy of Management Review, 30, 96–112.
Kahn, W. A. (1990). Psychological conditions of personal engagement and disengagement at
work. Academy of Management Journal, 33, 692–724.
Katz, D., & Kahn, R. L. (1966). The social psychology of organizations. New York, NY: Wiley.
Kellerman, B. (2008). Followership. Cambridge, MA: Harvard Business School Press.
Kiesler, D. J. (1983). The 1982 interpersonal circle: A taxonomy for complementarity in human
transactions. Psychological Review, 90, 185–214.
Kish, L. (1965). Survey sampling. New York, NY: Wiley.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical
data. Biometrics, 33, 159–174.
Loehr, J. E., & Schwartz, T. (2003). On form: Managing energy, not time, is the key to high
performance, health and happiness. Boston, MA: Nicholas Brealey.
McDaniel. D. M. (2011). Energy at work: A multinational, cross-situational investigation of
relational energy (Doctoral dissertation). Retrieved from ProQuest Dissertation and Theses
databases (UMI No. 3456982).
Mossholder, K. W., Settoon, R. P., Harris, S. G., & Armenakis, A. A. (1995). Measuring
emotion in open-ended survey responses: An application of textual data analysis. Journal
of Management, 21, 335–355.
RELATIONAL ENERGY AT WORK 39
Muthen, B. & Satorra, A. (1995). Complex sample data in structural equation
modeling. Sociological Methodology, 25, 267–316.
Newcomb, T. M. (1956). The prediction of interpersonal attraction. American Psychologist, 11,
575–586.
Parker, A., Gerbasi, A., & Porath, C. L. (2013). The effects of de-energizing ties in organizations
and how to manage them. Organizational Dynamics, 42, 110–118.
Paxton, S. J., Schutz, H. K., Wertheim, E. H., & Muir, S. L. (1999). Friendship clique and peer
influences on body image concerns, dietary restraint, extreme weight-loss behaviors, and
binge eating in adolescent girls. Journal of Abnormal Psychology, 108, 255–266.
Perry, S. J., Witt, L. A., Penney, L. M., & Atwater, L. (2010). The downside of goal-focused
leadership: The role of personality in subordinate exhaustion. Journal of Applied
Psychology, 95, 1145–1153.
Pfeffer, J. (2010). Building sustainable organizations: The human factor. Academy of
Management Perspectives, 24, 34-45
Pinder, C. C. (2008). Work motivation in organizational behavior (2nd ed.). New York, NY:
Psychology Press.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method
biases in behavioral research: A critical review of the literature and recommended
remedies. Journal of Applied Psychology, 88, 879–903.
RELATIONAL ENERGY AT WORK 40
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and
comparing indirect effects in multiple mediator models. Behavior Research Methods, 40,
879–891.
Quinn, R. W., Spreitzer, G. M., & Lam, C. F. (2012). Building a sustainable model of human
energy in organizations: Exploring the critical role of resources. Academy of Management
Annals, 6, 337–396.
Radel, R., Sarrazin, P., Legrain, P., & Wild, T. C. (2010). Social contagion of motivation
between teacher and student: Analyzing underlying processes. Journal of Educational
Psychology, 102, 577–587.
Rhoades, L., Eisenberger, R., & Armeli, S. (2001). Affective commitment to the organization:
The contribution of perceived organizational support. Journal of Applied Psychology, 86,
825–836.
Rich, B. L., Lepine, J. A., & Crawford, E. R. (2010). Job engagement: Antecedents and effects
on job performance. Academy of Management Journal, 53, 617–635.
Rothbard, N. P. (2001). Enriching or depleting? The dynamics of engagement in work and
family roles. Administrative Science Quarterly, 46, 655–684.
Saks, A. M. (2006). Antecedents and consequences of employee engagement. Journal of
Managerial Psychology, 21, 600–619.
RELATIONAL ENERGY AT WORK 41
Scandura, T. A., & Graen, G. B. (1984). Moderating effects of initial leader-member exchange
status on the effects of a leadership intervention. Journal of Applied Psychology, 69, 428–
436.
Schaufeli, W. B., & Bakker, A. B. (2004). Job demands, job resources, and their relationship
with burnout and engagement: A multi-sample study. Journal of Organizational Behavior,
25, 293–315.
Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The measurement of work engagement
with a short questionnaire: A cross-national study. Educational and Psychological
Measurement, 66(4), 701–716.
Schaufeli, W. B., Bakker, A. B., & Van Rhenen, W. (2009). How changes in job demands and
resources predict burnout, work engagement, and sickness absenteeism. Journal of
Organizational Behavior, 30, 893–917.
Shirom, A. (2004). Feeling vigorous at work? The construct of vigor and the study of positive
affect in organizations. In D. Ganster & P. L. Perrewe (Eds.). Research in occupational
stress and well-being (Vol. 3, pp. 135–165). Greenwich, CN: JAI press.
Shraga, O., & Shirom, A. (2009). The construct validity of vigor and its antecedents: A
qualitative study. Human Relations, 62, 271–291.
Skirbekk, V. (2008). Age and productivity capacity: Descriptions, causes and policy
options. Ageing Horizons, 8, 4–12.
RELATIONAL ENERGY AT WORK 42
Sonnentag, S., Kuttler, I., & Fritz, C. (2010). Job stressors, emotional exhaustion, and need for
recovery: A multi-source study on the benefits of psychological detachment. Journal of
Vocational Behavior, 76, 355–365.
Sonnentag, S., Mojza, E. J., Demerouti, E., & Bakker, A. B. (2012). Reciprocal relations
between recovery and work engagement: The moderating role of job stressors. Journal of
Applied Psychology, 97(4), 842–853.
Spreitzer, G. M., Lam, C. F., & Quinn, R. (2011). Human energy in organizations: Implications
for POS from six interdisciplinary streams. In K. Cameron & G. Spreitzer (Eds.),
Handbook of positive organizational scholarship (pp. 155–167). New York, NY: Oxford
University Press.
Spreitzer, G., Sutcliffe, K., Dutton, J., Sonenshein, S., & Grant, A. M. (2005). A socially
embedded model of thriving at work. Organizational Science, 16, 537–549.
Wiesenfeld, B. M., Raghuram, S., & Garud, R. (2001). Organizational identification among
virtual workers: The role of need for affiliation and perceived work-based social support.
Journal of Management, 27, 213–229.
Zhang, S., Chen, G., Chen, X. P., Liu, D., & Johnson, M. D. (2014). Relational versus collective
identification within workgroups: Conceptualization, measurement development, and
nomological network building. Journal of Management, 40(6), 1700-1731.
RELATIONAL ENERGY AT WORK 43
Table 1
Study 1 Exemplary Quotes
Motivational Arousal Type
Stimuli from Energizer
Relational Energya
Positive Affect
“She energized me because she loved her job
and was in general, a very happy person. She
always came in with a smile on her face which
created a positive atmosphere.”
“Having [this] energizing boss made me feel
motivated…to work. Working with this
person gave me energy to get my job done. It
helped encourage me to work my hardest and
take pride in my work. I wanted to do well so
that she was happy and proud of me.”
Cognitive Stimulation
“His energy made me feel…that my feedback
was very factual and useful. This person
motivated me to work harder and I also paid
more attention to detail. He brought to the
room…knowledge and a different perspective I
found very interesting.”
“On days after having meetings with him I got
twice as much work done because of
motivational energy that he brought to the
room.”
Behavioral Modeling
“She was involved in a lot of research and
developed her own blog where she gathered her
own thoughts and personal research in specific
topics of sociology. Her clear ambition of
knowing what she wants to do, standing up to
do what she really loved and her commitment to
the field really inspired me.”
“I felt inspired, motivated, and energetic. I felt
like I became more interested in the topics that
we researched and I was also more
responsible in doing my work in the project.”
Note. Quotes from each row came from the same respondent.
a Psychological resources gained from energizer stimuli
à
à
à
RELATIONAL ENERGY AT WORK 44
Table 2
Study 2 Samples
Sample
Source
Purpose
n
%
Female
%
Caucasian
Mean
Age
SD Age
Mean
Tenurea
A
Commercial
subject pool
Exploratory
factor analysis
184
75
81
45
11.45
--
B
Commercial
subject pool
Exploratory
factor and
discriminant
validity analysis
200
67
77
38
7.25
3.66
C
Health
services
organization
Confirmatory
factor and
discriminant
validity analysis
266
64
72
36
10.13
.83
a years working with energizer
RELATIONAL ENERGY AT WORK 45
Table 3
Study 2: Sample A Relational Energy Scale Descriptive Statistics, Loadings, and Reliability
Survey Statement
Item mean
Item SD
Factor loadings
1
I feel invigorated when I interact with this person.
5.18
1.47
.61
2
After interacting with this person I feel more
energy to do my work.
5.01
1.49
.69
3
I feel increased vitality when I interact with this
person.
4.72
1.51
.76
4
I would go to this person when I need to be
“pepped up”.
4.85
1.72
.73
5
After an exchange with this person I feel more
stamina to do my work.
4.75
1.45
.72
RELATIONAL ENERGY AT WORK 46
Table 4
Study 2: Sample B Correlation Matrix of Relational Energy and Related Constructs
Mean
SD
1
2
3
4
5
1 Relational Energy
4.02
.91
(.95)
2 Perceived Social Support
3.69
1.02
.49
(.87)
3 Leader-Member Exchange
3.09
.63
.45
.75
(.92)
4 Productive Energy
3.67
.82
.54
.54
.51
(.96)
5 Emotional Energy
3.99
.78
.50
.42
.32
.49
(.93)
6 Relational Identification
3.63
.78
.55
.54
.52
.77
.56
(.86)
Note. N = 200. All coefficients significant at p < .001.
RELATIONAL ENERGY AT WORK 47
Table 5
Study 2: Sample C Confirmatory Factor Analyses
Model and Structure
χ2
df
∆χ2
∆df
RMSEA
SRMR
CFI
TLI
1. Three factors: Relational
Energy, Perceived Social
Support, and Leader Member
Exchange
169.83
98
.05
.03
.98
.98
2. Two factors: Relational Energy
and Perceived Social Support
combined
896.82
100
726.99***(2 vs. 1)
2
.17
.13
.82
.78
3. Two factors: Relational Energy
and Leader-Member Exchange
combined
833.39
100
663.56*** (3 vs. 1)
2
.17
.13
.83
.80
4. One factor: All combined
1143.41
101
973.58***(4 vs. 1)
3
.20
.09
.76
.72
RELATIONAL ENERGY AT WORK 48
Table 6
Study 3 Correlation Matrix
Mean
SD
1
2
3
4
5
6
7
8
1. Employee Job Engagement
4.99
.84
(.94)
2. Relational Energy
5.25
.98
.40***
(.96)
3. Perceived Social Support
4.04
.91
.40***
.58***
(.87)
4. Leader Gender a
1.44
.50
.02
-.07
-.04
5. Leader Race b
.88
.32
.04
-.04
.03
-.08
6. Employee Gender a
1.37
.48
.04
-.07
.05
.15*
-.06
7. Employee Race b
.83
.37
-.05
.02
.02
-.10
.03
.07
8. Employee Age
55.22
58.60
.06
.01
.11
.02
.16*
-.17*
.06
9. Employee Tenure
34.19
9.17
.21**
.01
.07
.09
.05
.11
.06
.32***
Note. N = 157.
a Gender: 1 = male, 0 = female. b Race: 1 = Caucasian, 0 = Minority.
p < .10, * p < .05, ** p < .01, *** p < .001.
RELATIONAL ENERGY AT WORK 49
Table 7
Study 3: Regression of Relational Energy on Employee Job Engagement, Controlling for Perceived Social Support
Model 1!
Model 2!
Model 3!
Dependent Variable!
Job Engagement!
Job Engagement!
Job Engagement!
Controls!
Leader Gender a!
-.00[-.24,.24]!
.04[-.18,.25]!
.06[-.15,.26]!
Leader Race b!
.23[-.17,.64]!
.20[-.16,.56]!
.29[-.05,.63]!
Employee Gender a!
.00[-.25,.25]!
-.08[-.31,.14]!
-.01[-.23,.21]!
Employee Race b!
-.29[-.62,.04]!†!
-.24[-.53,.05]!
-.31[-.59,-03]*!
Employee Age !
.02[.01,.04]**!
.02[.01,.04]**!
.02[.01,.03]**!
Employee Tenure
-.00[-.00,.00]!
-.00[-.00,.00]*!
-.00[-.00,.00]!†!
Predictors!
]!
]!
Perceived Social Support!
.42[.29,.55]***!
.22[.07,.38]**!
Relational Energy!
.27[.14,.40]***!
F!
2.66*!
8.71***!
10.40***!
R2!
.10!
.29!
.36!
∆R2!
.19***!
.07***!
Note. N = 157. All values reflect unstandardized beta coefficients with 95% confidence intervals in parentheses.
a Gender coded as 1 = male, 0 = female. b Race coded as 0 = minority, 1 = white.
†!p < .10, * p < .05, ** p < .01, *** p < .001
Relational Energy 50
Table 8
Study 4 Bivariate Correlation Analysis
Mean
SD
1
2
3
4
5
6
7
8
9
1. Employee
Performance a
-.34
.47
2. Employee Job
Engagement
4.76
.92
.37**
(.96)
3. Relational Energy
5.13
1.00
.27**
.43**
(.93)
4. Leader-Member
Exchange
3.41
.99
.23*
.46**
.67**
(.94)
5. Leader Gender b
.34
.48
.04
.09
-.12
-.17*
6. Leader Race c
.62
.49
-.20
-.13
.09
.01
.10
7. Employee Gender b
.27
.45
-.03
-.05
.05
.20*
.02
.04
8. Employee Race c
.65
.48
-.16
-.09
.09
.07
-.20*
.20
.21*
9. Employee Age
37.19
9.80
-.21†
.15
-.04
-.01
-.10
.11
.12
.04
10. Employee Tenure
(months)
51.93
43.85
-.05
.26**
-.04
.08
-.04
-.16
.01
-.24**
.42**
Note. N = 123.
a For objective employee performance, N = 78. b Gender coded as 1 = male, 0 = female. c Race coded as 1 = white, 0 = minority.
† p < .10, * p < .05, ** p < .01.
Relational Energy 51
Table 9
Study 4: Regression of Relational Energy on Employee Job Engagement and Job Performance, Controlling for Leader-Member
Exchange
Dependent Variable
Job Engagement a
Job Performance b
Model 1
Model 2
Model 3
Model 4
Model 5
Model 6
Model 7
Controls
Leader Gender c
.18[-.16,.52]
.43[.13,.73]
.44[.15,.74]**
.09[-.12,.29]
.16[-.04,.36]
.14[-.06,.34]
.02[-.18,.21]
Leader Race d
-.15[-.48,.18]
-.24[-.53,.05]
-.27[-.55,.01] †
-.15[-.35,.05]
-.16[-.35,.03]
-.19[-.38,-.01]
-.13[-.31,.04] †
Employee Gender c
-.03[-.39,.32]
-.26[-.58,.05]
-.20[-.51,.11]
-.02[-.26,.21]
-.11[-.34,.12]
-.07[-.30,.16]
-.02[-.23,.19]
Employee Race d
.04[-.33,.40]
.09[-.23,.40]
.07[-.24,.37]
-.02[-.23,.19]
-.00[-.20,.20]
-.03[-.22,.17]
-.02[-.20,.17]
Employee Age
.01[-.01,.03]
.01[-.00,.03]†
.02[-.00,.03]*
-.01[-.03,.00] †
-.01[-.02,.00] †
-.01[-.03,-.00]*
-.02[-.03,-.00]*
Employee Tenure
.00 [.00,.01]*
.00[.00,.01]†
.00[.00,.01]
.00[-.00,.00]
.00[-.00,.00]
.00[-.00,.00]
.00[-.00,.00]
Predictors
Leader Member
Exchange
.46[.32,.60]***
.30[.11,.48]*
.14[.05,.23]**
.05[-.07,.17]
-.03[-.15,.09]
Relational Energy
.24[.06,.41]*
.13[.01,.25]*
.09[-.03,.21] †
Job Engagement
.21[.09,.32]*
F
1.91†
8.08***
8.38***
1.34
2.57*
2.91**
4.43***
R2
.09
.33
.37
.10
.20
.25
.37
∆R2
.24***
.04*
.10**
.05*
.12**
95% CI e
[.002,.128]
Note. All values reflect unstandardized beta coefficients with 95% confidence intervals in parentheses.
aN = 123. bN = 78. cGender coded as 0 = female, 1 = male. dRace coded as 0 = minority, 1 = white. eRepresents a biased corrected and
accelerated confidence interval for indirect effects based on 5,000 bootstrapped samples (see Preacher & Hayes, 2008).
†!p < .10, * p ≤!.05, ** p < .01; *** p < .001
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