ORIGINAL RESEARCH
published: 13 February 2020
doi: 10.3389/fpsyg.2020.00085
Relational Climate in the Workplace:
Dimensions, Measurement, and
Validation
Richard E. Boyatzis 1* and Kylie Rochford 2
1
Organizational Behavior Department, Case Western Reserve University, Cleveland, OH, United States, 2 Department of
Management, The University of Utah, Salt Lake City, UT, United States
Edited by:
Gabriele Giorgi,
Università Europea di Roma, Italy
Reviewed by:
Gabriela Topa,
National University of Distance
Education (UNED), Spain
Vincenzo Cupelli,
Retired, Florence, Italy
*Correspondence:
Richard E. Boyatzis
richard.boyatzis@case.edu
Specialty section:
This article was submitted to
Organizational Psychology,
a section of the journal
Frontiers in Psychology
Received: 15 October 2019
Accepted: 13 January 2020
Published: 13 February 2020
Citation:
Boyatzis RE and Rochford K
(2020) Relational Climate
in the Workplace: Dimensions,
Measurement, and Validation.
Front. Psychol. 11:85.
doi: 10.3389/fpsyg.2020.00085
Relationships are the fundamental building blocks of organizations, yet the field lacks
a validated and comprehensive measure of how employees perceive the quality of
the relationships in their organization. In this paper, we develop and validate a scale
to measure the perceived relational climate in an organization. We operationalize
relational climate as a second-order latent construct reflected by three first-order
constructs: shared vision, compassion, and relational energy. In Study 1, we develop
an item pool consisting of 51 items and then use a Q-sort procedure to assess
content validity. In Study 2, the item pool is further reduced using exploratory factor
analysis. This is followed by a confirmatory factor analysis that finds initial support
for the three-dimensional structure of relational climate. Study 3 provides further
evidence of convergent and discriminant validity and assesses the criterion validity
of the construct in relation to leader–member social exchange (LMSX), perceived
organizational support, and procedural justice (all positive relationships). Finally, in Study
4, the factor structure of the quality-of-relationships scale is successfully replicated, and
criterion validity is further assessed in relation to instrumental ethical climate (negative
relationship) and affective organizational commitment (positive relationship). This paper
contributes a new validated measure to the literature that will allow organizations to
capture an important aspect of their work environment—the nature of the interpersonal
relationships. Implications for theory, limitations, and future research are discussed.
Keywords: workplace relationships, relational climate, scale development organizational behavior and human
performance, shared vision, shared compassion, shared energy
INTRODUCTION
The importance of high-quality relationships in the workplace is agreed among organizational
scholars (Dutton and Ragins, 2007; Heaphy et al., 2018). Benefits of high-quality relationships
span multiple levels: from individual benefits such as enhanced psychological well-being (Reis
and Gable, 2002) and physical health (Uchino et al., 1996; Berscheid, 1999) to organizational
benefits such as enhanced job performance (Gittell et al., 2010), learning (Carmeli et al.,
2009), coordination (Gittel, 2003), and error detection (Weick and Roberts, 1993). However,
despite the host of benefits associated with high-quality relationships, the field is still lacking
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Relational Climate
theoretical rationale for each of the four proposed factors. We
then present the results of a full-scale development process as
outlined by Hinkin (1998), resulting in a psychometrically sound
and validated measure of relational climate.
a comprehensive and validated measure that captures the overall
nature of the relationships in a given environment.
Relational climate is a facet-specific climate defined as “shared
employee perceptions and appraisals of policies, practices,
and behaviors affecting interpersonal relationships in a given
context. . .” (Mossholder et al., 2011: 36). In conceptualizing
relational climate, Mossholder and colleagues integrate the
structuralist and social interactionist approaches to climate.
Specifically, these authors draw on structuralism to argue that
relational climate begins with employees’ subjective experiences
of the structural aspects of the organization designed to impact
interpersonal relationships (i.e., HR policies and practices). They
then draw on social interactionism (Berger and Luckmann, 1967)
to highlight the role of collective sensemaking processes that
facilitate the emergence of shared meanings and perceptions
regarding the structural aspects (Weick, 1979). While Mossholder
and colleagues carefully laid the theoretical underpinnings of
relational climate, to our knowledge, the construct has not yet
been operationalized and empirically validated. In this paper, we
build on these theoretical foundations to develop and validate
a measure of relational climate. In the following section, we
outline the theoretical underpinnings of relational climate as a
latent construct that can be measured indirectly by the perceived
degree of (1) shared vision, (2) compassion, (3) positive mood,
and (4) relational energy in a given dyadic relationship, team,
or organization.
Definitions and Theoretical Rationale for
First-Order Factors
Shared Vision
Shared vision is defined as “the extent to which members of an
organization (or team or dyad) share a common mental image
of a desirable future that provides a basis for action” (adapted
from Pearce and Ensley, 2004: 260–261). The role of shared
vision in relational climate is 2-fold. First, in the context of
the workplace, shared vision creates a sense of belonging, social
identity, and internalization of values and attitudes—all of which
are characteristics of high-quality relationships (Kahn, 2007)
and are also consistent with Fiske’s (1992) notion of communal
sharing and thus Mossholder et al. (2011) communal sharing
model of relational climate. Second, the presence of a shared
vision suggests that the relationships incorporated within a given
dyad, group, or team have moved beyond our initial basic needs
to be liked and to belong (Baumeister and Leary, 1995) to more
profound, meaningful, and sustainable bonds (Allport, 1962).
Compassion
We adopt Boyatzis et al. (2012) definition of compassion as
“an interpersonal process that involves noticing another person
as being in need, empathizing with him or her, and acting to
enhance his or her well-being in response to that need” (pp.
154–155). This definition departs slightly from the traditional
view of compassion in that it replaces the term “suffering,”
which, by definition, requires pain, distress, or hardship, with
the broader term of “being in need,” which allows for both
noticing and acting not only to ease a person’s suffering
but also to enhance their subjective and psychological wellbeing. Consistent with mainstream literature, compassion is
conceptualized as consisting of three components: (a) noticing
or attending to another’s need; (b) other-regard feelings such as
empathic concern; and (c) acting to ease the suffering and/or
enhance well-being (Kanov et al., 2004; Dutton et al., 2006).
Compassion is a mechanism that facilitates a sense of value
and worth in interactions (Frost, 2003; Dutton et al., 2014) and
creates a psychological pull between people that strengthens the
connection between them (Dutton et al., 2002).
OPERATIONAL DEFINITION
Mossholder and colleagues draw on Fiske’s (1992) relational
models theory to identify difference characterizations of
relational climate: market pricing, equality matching, and
communal sharing. These models represent different “types”
of relationship that reflect different motivations and rules
for interrelating. In considering how best to operationalize
relational climate, we depart slightly, but in a compatible way,
from Mossholder et al. (2011) conceptualization of relational
climate by incorporating the growing literature in the domain
of positive organizational scholarship. In doing so, we focus
primarily on measuring the extent to which people perceive the
relational climate in their organization to reflect “high-quality”
relationships. High-quality relationships are “manifested in
shared goals, shared knowledge, and mutual respect” (Carmeli
and Gittell, 2009: 714). Relating this to Mossholder et al. (2011)
different types of relational climate, we are primarily focusing
our efforts on operationalizing a relational climate that reflects
the communal sharing model of relating (see Fiske, 1992, and
Mossholder et al., 2011), which is characterized by relationships
that are based on shared values, affective bonds, and empathetic
concern (Mossholder et al., 2011).
Building off the definition of high-quality relationships and in
line with the communal sharing model of relationships (Fiske,
1992), in this paper, we propose that relational climate can be
operationalized by four first-order latent constructs: the degree
of shared vision, compassion, relational energy, and positive
mood in a given environment. In what follows, we provide a
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Positive Mood
Positive mood is defined as “a transient affective state
characterized by feelings of positive emotions such as enthusiasm,
elation, and excitement that are not focused on any particular
object, event, individual, or behavior” (adapted from Watson
et al., 1988, and George and Brief, 1992). In this paper, we
conceptualize positive mood as a state and therefore as distinct
from generalized positive affect and similar constructs including
optimism and positive outlook (Watson and Pennebaker, 1989).
We contend that when we interact with others in a meaningful
and positive way, the resulting affective response is reflective
of positive mood. Thus, one reflection of the nature of the
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Relational Climate
relationship/s in a dyad, team, or organization is the degree
of positive mood.
All studies were approved by the Institutional Review Board at
Case Western Reserve University (IRB-2015-1067).
Relational Energy
Method
The sense of energy that is derived from high-quality
relationships is a relatively new idea in the organizational
sciences. The concept was introduced into our literature with the
rise of the positive psychology movement in the early 2000s by the
work of Quinn and Dutton (2005), who claimed that perceived
energy in organizations is a result of interactions and, specifically,
conversations among individuals. Scholars drew heavily on Ryan
and Frederick’s (1997) work on subjective vitality, defined as “a
specific psychological experience of possessing enthusiasm and
spirit” (p. 530). In this paper, we are particularly interested in
energy derived from a person’s relationships in an organization.
We draw on the work of Ryan and Frederick (1997) and Quinn
and Dutton (2005) to define relational energy as “the extent to
which relationships in an organization are a source of energy
in that they result in feelings of positive arousal, aliveness, and
eagerness to act. Recent research has linked relational energy to
perceived social support and the quality of the leader–follower
relationship (Owens and Hekman, 2016). For a comprehensive
review, see Baker, 2019).
In sum, theory and prior empirical work suggest that
relational climate can be operationalized as four first-order latent
factors composed of shared vision, compassion, positive mood,
and relational energy. Table 1 provides a definition for each
construct, the rationale for including it, and citations to relevant
supporting literature.
The initial assessment of the content validity of the items
involved a small sample of subject matter experts, who were
asked to assess the face validity of the proposed items based on
the construct definitions and literature. Five doctoral students,
ten practitioners, and four faculty members provided detailed
feedback on the initial items. As a result of this process, the initial
pool of 51 items was developed—14 for shared vision, 13 for
compassion, 12 for positive mood, and 12 for relational energy.
We used the approach recommended by Schriesheim et al.
(1993) to empirically assess content adequacy. Four separate
samples (one per construct) were recruited using Amazon
Mechanical Turk (MTurk). MTurk is an online participant pool
in which individuals voluntarily participate in advertised studies
in return for a small payment (Buhrmester et al., 2011; Goodman
et al., 2013). The screening criteria used were as follows: (1)
currently living in the United States; (2) being 18 years of age
or higher; (3) being able to speak English as their primary
language; (4) holding a bachelor’s degree or higher; and (5)
having at least 20 accepted HITS (tasks previously completed and
submitted on AMT) and an acceptance rate of 95% of previously
submitted tasks. Work experience was not required for this study
as classifying items is primarily a cognitive task (Schriesheim
et al., 1993; Hinkin, 1998). Sample sizes were N = 46, N = 49,
N = 49, and N = 47. Sociodemographic information for this
sample and the samples used in subsequent studies can be found
in Table 3.
Participants were given one construct definition along with
the full item pool and were asked the extent to which each
item corresponds to the construct definition provided. Items
were rated on a 5-point Likert scale ranging from 1 = very
weak fit to 5 = very strong fit. Three attention checks were
included in each survey. Participants who missed more than one
of these checks were not included in the sample. To analyze
the responses, we calculated a Q-correlation matrix and used
STUDY 1: CONSTRUCT DEFINITIONS
AND ITEM GENERATION
The objective of the first study was to assess the content validity
of the proposed item pool. The list of items used in this study was
derived deductively due to the strong theoretical foundations that
existed for each of the four proposed constructs (Hinkin, 1998).
TABLE 1 | Summary of operational construct of relational climate.
Construct name
Definition
Rationale
Theory
Shared vision
The extent to which members of an organization
share a common mental image of a desirable
future that provides a basis for action.
Identity, belonging, purpose, meaning
Pearce and Ensley, 2004; Kahn, 2007
Compassion
An interpersonal process that involves noticing
another person as being in need, empathizing
with him or her, and acting to enhance his or her
well-being in response to that need.
Caring, feeling valued, psychological
connection, mutuality
Miller and Stiver, 1997; Dutton et al., 2014,
2002, 2014; Frost, 2003; Boyatzis et al.,
2012
Positive mood
A transient affective state characterized by
feelings of positive emotions such as enthusiasm,
elation, and excitement that are not focused on
any particular object, event, individual, or
behavior.
Affective response to positive interactions;
attraction to others; broaden and build
Bell, 1978; George and Brief, 1992; Watson
et al., 1988; Fredrickson, 2001
Relational energy
The extent to which relationships in an
organization are a source of energy in that they
result in feelings of positive arousal, aliveness,
and eagerness to act.
Energy in organizations is a result of
interactions and conversation; only “secure”
relationships result in positive energy;
energy is contagious.
Ryan and Frederick, 1997; Baker et al.,
2003; Quinn and Dutton, 2005; Luke et al.,
2012; Owens and Hekman, 2016; Baker,
2019
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each will load significantly on one and only one first-order
factor. Similarly, the first-order factors must converge on the
higher-order relational climate construct.
While the observed variables (items) and the four first-order
factors must converge on their respective higher-order factors,
these higher-order factors must also be empirically distinct in
order to claim that they are capturing unique variance in their
respective indicators. In sum, we hypothesize the following:
principal components analysis. Items that had factor loadings
>0.4 (Ford et al., 1986), with no major cross loadings, were
retained for Study 2. Items with factors loadings <0.4 or items
with major cross loadings were discarded.
Results and Discussion
Due to space limitations, the full Q-sort results are not displayed,
however, they are available on request. As a result of this initial
sorting, six items were discarded from the item pool. These items
and the reason for discarding them are displayed in Table 2.
H1b: Each of the first-order factors will satisfy empirical tests
of convergent and discriminant validity and therefore provide a
unique and meaningful contribution to the second-order factor.
STUDY 2: PSYCHOMETRIC
PROPERTIES OF RELATIONAL CLIMATE
Method
This study utilized two separate samples—one for the exploratory
factor analysis (EFA) and a second for the confirmatory factor
analysis (CFA). Both samples were recruited from Amazon
MTurk. The inclusion criteria were the same as in Study 1 with
the addition of work experience (currently working more than
20 h/week in an organization with more than 10 employees). Both
surveys included three attention checks. Information on the final
samples can be found in Table 3.
The objective of Study 2 was to assess the psychometric properties
of the proposed relational climate construct. Specifically, the
study examined (1) the underlying structure of the latent variable;
(2) the reliability of the proposed factors; (3) convergent validity;
and (4) discriminant validity.
Hypotheses
The rationale for operationalizing relational climate as a latent
construct that can be measured indirectly by shared vision,
compassion, energy, and positive mood is outlined earlier in this
paper. In sum, high-quality and positive relationships require
a sense of belonging, identity, and shared understanding that,
in an organizational setting, can be captured by the degree of
shared vision. Compassion creates a sense of being valued and
cared for and creates a psychological pull between people (Dutton
et al., 2014). Energy and positive mood are indicative of a work
environment characterized by secure relationships (Luke et al.,
2012) and psychologically safe relationships (Kark and Carmeli,
2009). Thus, we hypothesize the following:
Results
To avoid multicollinearity issues, before running the initial EFA,
we had to remove some items due to high correlations. Items were
removed based on the following criteria: (1) a correlation above
0.8 with another item or (2) multiple correlations above 0.75
with other items and (3) conceptual considerations. As a result of
this initial screening, 12 items were removed from the item pool,
leaving a total of 32 items in the first EFA. The correlations for the
final items are displayed in Table 4.
The initial EFA revealed that there are four factors in the
data with eigenvalues greater than 1.00. The four factors together
explained 67% of variance. An examination of the rotated
factor matrix revealed that some items did not load as we
expected them to. Specifically, items that were intended to be
part of the positive mood construct loaded on the compassion
construct. Additionally, the fourth factor extracted appeared
to be composed primarily of the reverse-coded items from all
four constructs.
Based on this initial output, all the positive mood items were
removed due to the cross loadings. The reason for removing
the positive mood items rather than the compassion items was
3-fold. First, the item loadings were stronger for compassion
than for positive mood. Second, the conceptual basis for the
positive mood construct was weak compared to the compassion
construct. Third, positive mood is partly captured through the
relational energy in that relational energy captures positive
energy and hence some degree of positive affect. Aside from
the compassion and positive mood constructs, the two reversecoded items from the shared vision construct that had factor
loadings less that 0.40 (V9_9 and V10_R) and the two reversecoded items from the compassion construct (C_8R ad C_9R)
were also removed.
The second EFA revealed three clean factors with
eigenvalues greater than 1.00. Together, the three factors
H1a: Relational climate is a second-order latent construct
defined by four distinct dimensions of shared vision,
compassion, relational energy, and positive mood.
In order for the first-order factors of shared vision,
compassion, energy, and positive mood to be meaningful, the
observed variables (items) must show evidence of convergent
validity with their respective factors. We expect that the observed
variables will all be positively correlated with each other, however,
TABLE 2 | Items discarded based on Q-sort results.
Item
Reason for
discarding
My organization is proud of its vision.
Cross loading
Members of my organization have compatible goals.
Cross loading
When we work together, my organization is enthusiastic.
Cross loading
My organization encourages each other to build on our
strengths.
Factor loading
< 0.40 (β = 0.31)
Generally, people in my organization are relaxed.
Cross loading
In my organization, we emphasize our current strengths.
Factor loading
< 0.40 (β = 0.25)
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TABLE 3 | Summary of samples.
Study and use
Sample 1 (N = 93)
Sample 2 (N = 287)
Study 1 Q-Sort
Study 2 EFA
Sample 3: CFA (N = 359)
Sample 4 (N = 354)
Study 2 CFA
Study 4 Consequences
Study 3 Antecedents
Demographics
Gender
48% male
52.3% male
64.6% male
56% male
22–64 years (37 years)
19–65 years (35 years)
18–63 years (31 years)
18–64 years (32 years)
Education
100% college degree
61.7% college degree
72.3% college degree
76.2% college degree
Job tenure
N/A
1–5 years
1–5 years
1–5 years
Average organization size
N/A
>100 employees
>100 employees
>100 employees
Age (average)
TABLE 4 | Item correlations for retained items*.
1
2
3
4
5
6
7
8
9
10
11
1. V_3
1.00
2. V_4
0.62
1.00
3. V_7
0.64
0.71
1.00
4. V_8
0.68
0.65
0.69
1.00
5. V_12
0.68
0.53
0.61
0.70
1.00
6. C_2
0.42
0.43
0.44
0.41
0.43
1.00
7. C_4
0.53
0.46
0.46
0.46
0.48
0.74
1.00
8. C_5
0.47
0.38
0.46
0.41
0.43
0.75
0.75
1.00
9. C_12
0.50
0.41
0.35
0.40
0.46
0.62
0.71
0.69
1.00
10. E_2
0.54
0.44
0.44
0.51
0.50
0.65
0.65
0.60
0.57
1.00
11. E_4
0.55
0.47
0.46
0.51
0.54
0.59
0.59
0.53
0.53
0.72
1.00
12. E_10
0.51
0.47
0.48
0.50
0.48
0.59
0.59
0.55
0.50
0.76
0.73
12
1.00
*All correlations are significant at p < 0.001.
explained 62% of variance. The only cross loading that
was cause for concern was E_9, which was subsequently
removed. The final EFA revealed three factors with all item
loadings greater than 0.65 and no significant cross loadings
(see Table 5).
Overall, Hypothesis 1a was partially supported. Relational
climate does appear to be a second-order latent variable,
however, rather than the hypothesized four first-order factors,
it appears the construct can be adequately captured by three
distinct first-order factors: shared vision, compassion, and
relational energy.
Confirmatory Factor Analysis
To test the construct validity of relational climate, CFA was used
as recommended by Floyd and Widaman (1995). We tested the
hypothesized model as well as three competing models. The
hypothesized model demonstrated excellent fit [comparative fit
index (CFI) = 0.98, Tucker–Lewis index (TLI) = 0.97, root mean
TABLE 5 | EFA 3 pattern matrix.
Factor
1
2
V_3
0.74
0.08
0.04
V_4
0.77
0.02
−0.01
V_7
0.85
0.05
−0.09
V_8
0.87
−0.08
0.05
V_12
0.72
0.01
0.09
C_2
−0.06
0.80
C_4
0.05
C_5
C_12
TABLE 6 | Measurement model fit comparisons (Sample 1).
3
Competing models
Model 1:
Hypothesized
Model 2:
1-factor
Model 3:
2-factora
Model 4:
2-factorb
Model 5:
2-factorc
χ2
135.89
512.03
260.87
357.97
400.30
0.10
df
52
39
64
64
64
0.86
−0.02
p
0.00
0.00
0.00
0.00
0.00
0.01
0.94
−0.10
CFI
0.98
0.85
0.94
0.90
0.89
0.05
0.77
−0.02
TLI
0.97
0.82
0.92
0.88
0.87
E_2
−0.01
0.27
0.66
RMSEA
0.06
0.14
0.09
0.11
0.12
E_4
0.07
0.08
0.74
SRMR
0.03
0.06
0.04
0.05
0.06
E_10
0.01
0.07
0.82
a Model
3 combined compassion and energy.
vision. c Model 5 combined energy and vision.
Extraction method: maximum likelihood with promax rotation.
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b Model
5
4 combined compassion and
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TABLE 8 | Final scale items.
square error of approximation (RMSEA) = 0.06] and superior fit
to all competing models (see Table 6).
Construct
Item
Convergent Validity
Shared Vision
My organization’s daily work aligns with our vision.
The first- and second–order factor loadings and factor
correlations for Model 1 are displayed in Table 7. All of the
first-order item loadings were significant (p < 0.00) as were the
second-order factor loadings (p < 0.00). This provides support
for the convergent validity of the items and Hypothesis 1b.
Overall, the first-order constructs demonstrated good
discriminant validity. The shared variance between any
combination of constructs was less than the average variance
extracted (AVE) by each of them (Fornell and Larcker,
1981)—the only exception being the compassion–energy
combination, for which the shared variance between
the constructs (r2 = 0.70) was greater than the AVE by
compassion (AVEcomp = 0.65). Despite this, there was a
significant decrease in model fit when compassion and
energy were paired as one construct (1χ2 = 113.14,
p = 0.00), which suggests that although the two constructs
share variance, they are best modeled as two factors. Thus,
Hypothesis 1b is supported. The final items are included in
the Table 8.
Shared Vision
My organization’s purpose is clear.
Shared Vision
Members of my organization have a shared purpose.
Shared Vision
My organization’s actions are guided by a shared vision.
Shared Vision
Members of my organization have similar visions of the
organization’s future.
Compassion
Members of my organization are empathetic toward each
other.
Compassion
People in my organization notice when others are in need.
Compassion
Members of my organization care about each other’s
well-being.
Compassion
When someone in my organization is in need, my
organization takes action to assist them.
Relational Energy
The relationships in my organization are a source of energy.
Relational Energy
The atmosphere in my organization is vibrant.
Relational Energy
Interactions in my organization are lively
STUDY 3: ORGANIZATIONAL
ANTECEDENTS OF RELATIONAL
CLIMATE
Criterion validity requires that a given construct behave in
a way that is consistent with theory—that is, constructs that
should theoretically predict relational climate should do so, and
relational climate should lead to outcomes that are consistent
with theory. Thus, the objective of this study was to begin
building a nomological net for relational climate.
TABLE 7 | Model 1: Measurement model factor loadings (Sample 1).
Standardized estimate
SE
p-value
V_1
0.78
0.02
0.00
V_2
0.68
0.03
0.00
V_3
0.80
0.02
0.00
V_4
0.86
0.02
0.00
V_5
0.80
0.02
0.00
C_1
0.81
0.02
0.00
C_2
0.83
0.02
0.00
C_3
0.82
0.02
0.00
C_4
0.78
0.02
0.00
E_1
0.82
0.02
0.00
E_2
0.91
0.01
0.00
E_3
0.81
0.02
0.00
Vision
0.83
0.03
0.00
Compassion
0.93
0.02
0.00
Energy
0.91
0.02
0.00
2
3
Factor loadings
Vision to:
Hypotheses
Leader–Follower Relationship
The quality of the relationship between a leader and follower is
commonly captured using the leader–member exchange (LMX)
framework. The LMX framework focuses on the differential
quality of the relationship between leader and follower with lowquality relationships being based on the transactional part of the
employment contract and high-quality relationships being based
on mutual liking, trust, and respect (Graen et al., 1982).
The role of the leader in influencing work climates is
well established in the literature. For example, Sims and
Brinkman (2002) found that unethical work climates are shaped,
and reinforced, by leader behavior. Amabile et al. (2004)
found that leader behavior influences the creative climate,
and Zohar (2002) found that leadership style influences the
safety climate in an organization. Additionally, Schein (1985)
argues that leaders act as role models for employees and,
through their behavior, provide clear signals to employees of
the organization’s priorities, values, and beliefs. Following this
line of thinking, if an employee has a positive relationship
with their leader, they are likely to emulate this type of
relationship with their colleagues, and this will be reflected
in the relational climate of the organization. Thus, we predict
the following:
Compassion to:
Positive energy to:
Second-order factor loadings
Relational climate to:
First-order factor correlations and AVE*
1
1. Vision
(0.89)
2. Compassion
0.77
(0.88)
3. Energy
0.75
0.84
AVE
0.62
0.65
(0.89)
0.73
*Composite reliability in parentheses.
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needs predicts relationship quality (Patrick et al., 2007). Given
this, we expect POS will be positively related to relational
climate. In contrast, an absence of POS would result in
unfulfilled socio-emotional needs and thus a lower quality
relational climate.
H2: Leader–member social exchange (LMSX) is positively
related to perceived relational climate.
Procedural Justice
Procedural justice is concerned with the “fairness of the
procedures used to determine outcome distributions or
allocations” in organizations (Colquitt et al., 2001: 425). There
is a growing body of work that suggests that procedural
justice elicits emotional responses that mediate the relationship
between procedural justice and organizational outcomes (Weiss
et al., 1999; Murphy and Tyler, 2008). A lack of perceived
fairness in an organization leads to feelings of distrust, anxiety,
conflict, retribution, and retaliation (Skarlicki and Folger, 1997;
Aquino et al., 2006)—all of which are known to impede the
development of positive relationships (Cameron et al., 2003).
Conversely, high procedural justice elicits positive emotions
such as happiness and joy (Krehbiel and Cropanzano, 2000),
cheerfulness (de Cremer et al., 2005), and pride (Weiss et al.,
1999)—emotions associated with the facilitation of positive
relationships (Fredrickson, 2001, 2004).
Finally, research suggests that perceived procedural
justice also impacts a person’s sensemaking and attributions
surrounding organizational decisions. For example, Krehbiel
and Cropanzano (2000) found that procedural justice increases
the ability of employees to derive meaning from both favorable
and unfavorable decisions. Additionally, when persons perceive
that they are the victim of wrongdoing, they are more likely
to forgive and move on in climates perceived as having high
procedural justice (Aquino et al., 2006). There is a significant
body of evidence suggesting that forgiveness is important for the
development and maintenance of relationships (for a review, see
Enright and Fitzgibbons, 2000).
In sum, perceptions of procedural justice impact emotional,
cognitive, and behavioral responses to organizational decisions,
which in turn impact the relationships in the organization.
Environments perceived to have high levels of procedural justice
produce trust, positive emotions, and meaning, all of which
facilitate positive relationships. Environments perceived to have
low procedural justice elicit negative emotions, distrust, and
ambiguity, all of which impede positive relationships. Thus,
we expect that procedural justice will be positively related to
relational climate.
H4: POS is positively related to perceived relational climate.
Discriminant Validity of Relational Climate With
Independent Variables
In order to justify the introduction and use of the relational
climate construct and to meet the requirements for nomological
validity, it must be shown that the construct of interest is distinct
from similar constructs. If relational climate is not distinct from
similar constructs, then its use does not add any value. LMSX
refers specifically to the relationship an employee has with a
superior, while relational climate is concerned with a person’s
general assessment of their relationships at work. Procedural
justice is concerned primarily with the procedures used to
make organizational decisions. The reaction of the employees to
those procedures is what influences the relational climate in the
organization. POS is concerned with an individual’s relationship
with the organization, while relational climate is concerned with
the individual’s general perception of the relationships between
individuals within the organization. In sum, we hypothesize
the following:
H5: LMX, procedural justice, and POS are empirically distinct
from perceived relational climate.
Method
We recruited a sample from MTurk using the same criteria used
in Study 2. Sample demographics can be found in Table 3 (see
Sample 3 in Table 3). Structural equation modeling was used
for all analyses.
Measures
Leader–member social exchange
LMSX was measured using Bernerth et al.’s (2007) eightitem measure. Sample items include “If I do something for
my manager, he or she will eventually repay me” and “My
relationship with my manager is composed on comparable
exchanges of giving and taking.”
H3: Procedural justice is positively related to perceived
relational climate.
Procedural justice
Perceived Organizational Support
Procedural justice was measured using Sweeney and McFarlin’s
(1993) four-item scale. Sample items include “In your
organization, how fair or unfair are the procedures used
to communicate performance feedback?” and “In your
organization, how fair or unfair are the procedures used to
determine pay raises?”
Perceived organizational support (POS) refers to “employee
beliefs as to the extent to which the organization values
their contributions and cares about their wellbeing” (Rhoades
and Eisenberger, 2002: 698). POS theory posits that, among
other things, perceptions of organizational support increase
an employee’s felt obligation to the organization; encourages
employees to incorporate organizational membership and roles
into their identity; and influences employees’ general reactions
to their job (Rhoades and Eisenberger, 2002). POS also fulfills
employees’ socio-emotional needs in organizations (Armeli et al.,
1998; Lee and Peccei, 2007), and the fulfillment of these
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Perceived organizational support
POS was measured using the short version of Eisenberger et al.’s
(1986) scale. Sample items include “The organization strongly
considers my goals and values” and “The organization cares about
my opinion.”
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Control Variables
Internal trust
POS (β = 0.14, p = 0.00) were significantly related to relational
climate. Thus, support was found for Hypotheses 2–4.
We used Huff and Kelley (2003) four-item scale to measure
trust. Sample items include “There is a very high level of trust
throughout this organization” and “Managers in this company
trust their subordinates to make good decisions.”
Relational Climate Discriminant Validity With
Independent Variables
The Fornell–Larcker test was used to assess the discriminant
validity of relational climate with the three predictors. The shared
variance between any pair of the four predictors ranged from
0.08 to 0.22 and was less than the AVE by each construct (AVE
ranged from 0.61 to 0.83), which suggests that these constructs
are indeed distinct (Fornell and Larcker, 1981), providing support
for Hypothesis 5.
Big-five personality
Personality was used only as a control variable in this study;
therefore, we used the Gosling et al. (2003) short measure of
the Big-Five Personality domains. While this measure does not
perform as well as the comprehensive measures of the BigFive domains in terms of psychometric properties, it performs
adequately for situations in which personality is not of prime
importance (Gosling et al., 2003). Sample items include “I see
myself as self-disciplined” and “I see myself as reserved.”
STUDY 4: TESTING A PARTIAL
NOMOLOGICAL NETWORK:
CONSEQUENCES
Other controls
The following demographic control variables were also collected:
gender, age, nationality, and level of education. Tenure and
organization size were also collected.
The objective of Study 4 was 2-fold: (1) to replicate the CFA
in an independent sample and (2) to further test the criterion
validity of relational climate by testing its ability to predict
specified outcomes.
Results
Hypotheses
The correlation matrix and reliability statistics for all variables
included in the structural model are displayed in Table 9. In
an attempt to minimize common method variance, all variables
were loaded onto a common latent factor. This technique has
been used extensively in organizational research (for review, see
Podsakoff et al., 2003).
To arrive at the final model, non-significant control variables
were removed sequentially, beginning with the variable with the
highest p-value. The overall model fit was excellent [χ2 = 272.68,
p = 0.00; CFI = 0.97; TLI = 0.96; RMSEA = 0.05; standardized root
mean square residual (SRMR) = 0.03]. Of the control variables,
only internal trust (β = 0.60, p = 0.00) and “agreeableness”
(β = 0.15, p = 0.00) were significant. As hypothesized, LMSX
(β = 0.11, p = 0.03), procedural justice (β = 0.15, p = 0.00), and
Instrumental Ethical Climate
Instrumental ethical climate is defined as “the prevailing
perceptions of employees that they need to look out for
themselves and their interests, regardless of relationships with
other employees, or responsibilities for the organization and
its environment” (Ambrose et al., 2008: 330; see also Cullen
et al., 1993). Instrumental ethical climate by definition is
concerned with self-interest and gain rather than the pursuit of
a shared vision that characterizes a positive relational climate.
Additionally, in a recent meta-analysis (Martin and Cullen,
2006), instrumental ethical climate was found to have a strong
negative correlation with caring (r = -0.34), which suggests
that we can also expect that instrumental ethical climate would
TABLE 9 | Correlation matrix for Study 3—antecedents1 (N = 359).
Mean
SD
1
(0.94)
2
3
4
5
6
7
8
9
10
11
1
Relational climate (scale)
5.00
1.02
2
LMSX
4.65
1.42
0.62
3
Perceived organizational support
3.92
0.42
0.35
0.65
4
Perceived organizational justice
3.41
0.92
0.65
0.65
0.68
5
Internal trust
4.70
1.41
0.78
0.71
0.73
0.69
6
Extraversion
2.87
0.92
0.16
0.12
0.16
0.08
0.15
7
Openness
3.63
0.68
−0.02
0.03
−0.07
0.02
−0.05
0.20
8
Agreeableness
3.66
0.69
0.29
0.10
0.19
0.17
0.16
0.22
0.11
9
Conscientiousness
3.94
0.69
0.20
0.12
0.19
0.15
0.17
0.13
0.14
0.23
(0.70)
10
Emotional stability
3.70
0.84
0.18
0.15
0.16
0.16
0.19
0.13
0.07
0.33
0.46
(0.82)
11
Age
31.44
9.02
−0.06
0.09
0.05
0.02
−0.05
−0.016 −0.06
0.13
0.14
0.09
12
Tenure
3.18
0.82
−0.03
0.09
−0.01
0.01
−0.02
−0.11
−0.11
−0.00
0.03
0.06
0.52
13
Organization size
3.28
0.87
−0.05
0.07
−0.09
−0.02
−0.02
−0.05
−0.00
−0.03
0.07
0.04
0.23
12
13
(0.97)
(0.59)
(0.89)
(0.93)
(0.82)
(0.58)
(0.64)
0.17
1 Cronbach’s
alpha on diagonal. Correlations above 0.10 are significant at p < 0.05. Tenure coded as 1 = less than 6 months, 2 = 6–12 months, 3 = 1–5 years,
4 = 6–10 years, 5 = more than 10 years. Organization size coded as 1 = less than 10, 2 = 11–50, 3 = 51–100, 4 = more than 100. Age is reported in years.
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Relational Climate
sample size was 354: 63% male and 36.4% female. Ages ranged
from 18 to 64 years with average year in job ranging from 1 to
5 years. Structural equation modeling was used for all analyses.
also be negatively correlated with the compassionate nature
of a positive relational climate. Thus, we hypothesize the
following:
H6: Perception of a positive relational climate is negatively
related to perception of an instrumental ethical climate.
Measures
Affective organizational commitment
Meyer and Allen’s (1997) scale was used to measure affective
organizational commitment. Sample items include “I would be
happy to spend the rest of my career with this organization” and
“I really feel this organization’s problems are my own.”
Affective Organizational Commitment
Affective organizational commitment refers to identification
with, involvement in, and emotional attachment to the
organization (Meyer and Allen, 1997). Employees with high
affective organizational commitment remain working for an
organization because they want to, rather than because they need
to (continuance commitment) or because they feel they ought to
(normative commitment). Employees who generate an emotional
attachment to their organization generally do so because they are
having an emotionally (and psychologically) satisfying experience
at work (Rousseau and Aubé, 2010). Emotionally satisfying
experiences require that an individual’s psychological needs are
being met, including the need for belonging and relatedness
(Baumeister and Leary, 1995). Given this, we would expect
that a high-quality relational climate should induce affective
organizational commitment.
Instrumental ethical climate
This variable was measured using a subscale from Victor and
Cullen’s (1988) Ethical Climate Questionnaire. Sample items
include “There is no room for one’s own personal morals or ethics
in my organization” and “In my organization, people are expected
to do anything to further the organization’s interests, regardless of
the consequences.”
Control Variables
Value congruence
Value congruence was measured using two items proposed by
Posner et al. (1985). The items are “My personal values are
generally compatible with the values of my organization” and “I
find that sometimes I have to compromise personal principles to
conform to my organization’s expectations.”
H7: Perception of a positive relational climate is positively
related to affective organizational commitment.
Internal trust, personality, and demographic variables
Discriminant Validity of Relational Climate With
Dependent Variables
This study utilized the same measures for these variables as those
used in Study 3.
As in the previous study, in order to justify the introduction
and use of the relational climate construct and to meet the
requirements for nomological validity, it must be shown that
relational climate is distinct from instrumental ethical climate
and affective organizational commitment. Instrumental ethical
climate is primarily concerned with the way in which ethical
decisions are made in an organization. This is clearly distinct
from relational climate, which is not concerned with decision
making or ethics. Affective organizational commitment is in
the same conceptual realm as relational climate in that it is
concerned with emotional and psychological factors within the
organization, however, the distinction between the different types
of commitment individuals may have to an organization is based
on their motivation for continuing to work for the organization.
Relational climate is not concerned with motivation for work,
rather it is interested in the experience that an employee has in
the workplace with regard to their relationships and interactions.
Results
The model fit indices for the relational climate measurement
model suggest an excellent fit (χ2 = 75.32, df = 52, p = 0.02;
CFI = 0.99; TLI = 0.98; RMSEA = 0.04). Both the firstand second-order factor loadings were greater than 0.70 and
statistically significant (p = 0.00) (see Table 10). This provides
additional evidence of the convergent validity of the relational
climate scale. The composite reliabilities of the first-order
constructs were also encouraging, with all estimates greater than
0.80 (Fornell and Larcker, 1981).
Overall, the three first-order constructs demonstrated good
evidence of discriminant validity. The shared variance between
any combinations of constructs was less than the AVE by each
of them (Fornell and Larcker, 1981). Additionally, there was a
significant decrease in model fit when any two constructs were
forced to be equal (Anderson and Gerbing, 1988).
The correlation matrix and reliability statistics for all variables
entered into the structural model are displayed in Table 11.
As in Study 3, all variables were loaded onto a common
latent factor in an attempt to account for common method
variances (Podsakoff et al., 1990; see also Podsakoff et al.,
2003). The overall model fit was excellent (χ2 = 209.28,
df = 129; CFI = 0.98; TLI = 0.97; RMSEA = 0.04). Of the
control variables considered, only three were significant: value
congruence predicted instrumental ethical climate (β = −0.43,
p = 0.00) and internal trust (β = 0.15, p = 0.03), and
tenure (β = 0.12, p = 0.00) predicted affective organizational
H8: Affective organizational commitment and instrumental
ethical climate are empirically distinct from relational climate.
Method
A sample of 400 participants was recruited using Amazon
MTurk. The inclusion criteria for this sample were the same as
those used in Studies 2 and 3. Participants who participated in
Study 2 or in Study 3 were not eligible to participate in this
study to ensure that there was no overlap between the samples.
The survey included three attention checks. Participants were
excluded if they missed any of these attention checks. The final
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TABLE 10 | Measurement model factor loadings for Model 1A (Sample 2).
Std. Est.
SE
p
procedure as outlined by Hinkin (1998) to provide empirical
evidence of convergent validity, discriminant validity, and
reliability at both the item and first-order factor levels.
Additionally, we theorized and tested a set of antecedents
and consequences of relational climate in order to begin the
development of the nomological network. Figure 1 provides a
summary of these relationships.
First-order factor loadings
Vision to:
V_1
0.78
0.02
0.00
V_2
0.72
0.03
0.00
V_3
0.80
0.02
0.00
V_4
0.87
0.02
0.00
Additional Evidence of Construct Validity
V_5
0.81
0.02
0.00
C_1
0.82
0.02
0.00
C_2
0.76
0.03
0.00
C_3
0.83
0.02
0.00
C_4
0.80
0.02
0.00
E_1
0.84
0.02
0.00
E_2
0.89
0.02
0.00
E_3
0.83
0.02
0.00
0.00
We recognize that a significant limitation in the previous studies
is our reliance on MTurk as a data source. Although we ensured
that our samples were independent by preventing workers to
participate in more than one study, questions have been raised
regarding the quality of data from online participant pools (Smith
et al., 2016). Due to the large number of samples required for scale
development, relying on these data sources was the only practical
option. However, since our initial studies, the scale has been used
in a number of other unpublished studies that utilize a range of
non-MTurk samples that span a number of industries. Table 12
displays the model fit statistics for the relational climate scale and
summarizes the findings of each study. We include this to add
further support for the psychometric properties of this scale and
to show that the scale’s psychometric integrity remains across a
range of samples.
Compassion to:
Positive energy to:
Second-order factor loadings
Relational climate to:
Vision
0.75
0.03
Compassion
0.92
0.03
0.00
Energy
0.86
0.03
0.00
2
3
First-order factor correlations and AVE*
1
The PNEA Scale
1. Vision
(0.90)
2. Compassion
0.69
(0.88)
3. Energy
0.64
0.78
AVE
It should be noted that three of the four factors we proposed in
this paper have been previously theorized as the Positive Negative
Emotional Attractor (PNEA) scale (Boyatzis et al., 2015; Boyatzis,
2018). The PNEA scale was an initial attempt to capture the
quality of relationships within intentional change theory (ICT)
(Boyatzis, 2008). In ICT, resonant relationships are a critical
part of shifting a person from a negative psychophysiological
state [the negative emotional attractor (NEA)] to a positive
psychophysiological state [the positive emotional attractor
(PEA)]. This shift from the NEA to the PEA allows a person to
move through the five stages of change (Boyatzis and McKee,
2005; Boyatzis et al., 2015).
In operationalizing resonant relationships in the context of
ICT, Boyatzis theorized three factors: shared vision, compassion,
and positive mood—together known as the PNEA scale.
However, a more careful examination of the PNEA scale revealed
some concerning psychometric weaknesses (Boyatzis, 2018).
While the shared vision factor in the scale consistently produced
strong empirical results, the items in the compassion construct
confound two constructs–trust and caring–and the positive
mood construct rarely loaded as expected (Boyatzis, 2018). The
original items from the PNEA scale were included in our initial
item pool and put through the same validation process as new
items. As a result of this, none of the items in the new relational
climate measure are identical to any of the PNEA items, however,
some of the items in the shared vision construct are very similar
with minor variations in wording.
0.64
0.65
(0.89)
0.73
*Composite reliability in parentheses.
commitment. As hypothesized, relational climate had a negative
relationship with instrumental ethical climate (β = −0.43,
p = 0.00), providing support for Hypothesis 6. Hypothesis 7
was also supported with a positive relationship between
relational climate and affective organizational commitment
(β = 0.69, p = 0.00).
Relational Climate Discriminant Validity With
Dependent Variables
The Fornell–Larcker test was used to assess the discriminant
validity of relational climate with the two dependent variables.
The shared variance between any pair of the four predictors
ranged from 0.19 to 0.77 and was less than the AVE by each
construct (AVE ranged from 0.88 to 0.96), which suggests that
these constructs are indeed distinct (Fornell and Larcker, 1981).
Thus, Hypothesis 8 was supported.
DISCUSSION AND CONCLUSION
Contributions
The key contribution of this set of studies is the development of
a conceptual and operational definition of relational climate in
the workplace and, based on these definitions, the construction
and validation of a scale. We used a standard scale validation
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Limitations
While the results from this study are encouraging, our work does
suffer from a number of limitations. First, although attempts
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Relational Climate
TABLE 11 | Correlation matrix for Study 4—consequences1 (N = 354).
Mean
SD
1
2
3
4
5
6
7
8
9
10
11
12
1
Relational climate*
5.06
0.90
2
Instrumental ethical climate
3.21
0.91
−0.57
3
Affective commitment
4.20
1.42
0.75
−0.57
(0.91)
4
Value congruence
4.90
1.24
0.53
−0.64
0.51
(0.65)
5
Trust
4.78
1.32
0.74
−0.56
0.70
0.58
6
Extraversion
2.87
0.92
0.22
−0.06
0.20
0.04
0.07
(0.82)
7
Conscientiousness
4.10
0.65
0.21
−0.14
0.15
0.16
0.11
0.20
8
Emotional stability
3.86
0.77
0.23
−0.18
0.14
0.18
0.13
0.23
0.42
9
Openness
3.66
0.70
0.11
−0.08
0.05
0.06
0.06
0.20
0.14
0.17
10
Agreeableness
3.78
0.66
0.30
−0.24
0.24
0.23
0.26
0.17
0.27
0.29
0.09
(0.65)
11
Age
32.53
9.65
0.06
−0.07
0.12
0.12
−0.03
0.09
0.26
0.21
0.08
0.08
1
12
Tenure
3.29
0.79
0.03
−0.05
0.13
0.05
−0.05
0.05
0.08
0.09
−0.05
0.03
0.48
1
13
Org. Size
3.19
0.88
−0.06
0.08
−0.01
−0.03
−0.09
−0.01
−0.05
−0.02
−0.07
−0.05
0.13
0.12
13
(0.93)
(0.84)
(0.93)
(0.74)
(0.82)
(0.64)
1
1 Cronbach’s
alpha in parentheses. Correlations above 0.10 are significant at p < 0.05. Tenure coded as 1 = less than 6 months, 2 = 6–12 months, 3 = 1–5 years,
4 = 6–10 years, 5 = more than 10 years. Organization size coded as 1 = less than 10, 2 = 11–50, 3 = 51–100, 4 = more than 100. Age is reported in years. Gender coded
as 1 = male, 2 = female. *Relational climate was calculated as the composite of the scales or the second order factor.
FIGURE 1 | Combination findings from Study 3 and Study 4. Notes: Standardized betas are reported. ∗∗ p < 0.01; ∗∗∗ p < 0.001. Dotted lines represent control
variables. Independent variables were allowed to covary. Only significant control variables are reported.
were made to minimize common method bias by loading
all observed variables onto a common latent factor, statistical
control is no substitute for multisource data. Thus, there is
likely some inaccuracy in the strength of the relationships,
although not necessarily in an upward direction (Conway and
Lance, 2010). On average, the common latent factor removed
approximately 3% shared variance between observed variables.
The use of multisource data in future studies would increase
our understanding of the strength of the relationships between
relational climate and its antecedents and consequences.
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Second, the cross-sectional design of this study limits our
ability to make claims regarding the causal direction of the
hypothesized relationships to theoretical arguments. Particularly
with a construct such as relational climate, which is likely
to both impact and be impacted by the same variable (i.e.,
relational climate is likely impacted by ethical climate and
also impacts ethical climate), longitudinal designs are needed
to fully grasp the relationships in the nomological network.
Longitudinal research designs would allow us not only to
empirically untangle antecedents from consequences but also
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Relational Climate
TABLE 12 | Summary of relational climate model fit statistics and findings from additional studies.
Source
Sample information
Characteristics
Kendall, 2016
Berg, 2017
Alharbi, 2019
Leah, 2017
Barco, 2019
Leaders in technology
United States-based technology
firms
Leaders in United States-based
for-profit organizations
Nursing students in residency year
in a large public university in
Saudi Arabia
United States-based leaders
across a range of industries
College students in a large public
university
Model fit statistics
Key findings
N
χ2 (df = 51)
CFI
TLI
RMSEA
SRMR
357
190.50
0.97
0.96
0.08
0.03
564
158.15
0.98
0.97
0.06
0.04
93
126.02
0.91
0.89
0.12
0.06
322
126.02
0.97
0.97
0.06
0.04
1,694
422.17
0.98
0.97
0.07
0.03
Relational climate predicts product
innovation (B = 0.33, p < 0.05) and
voice (B = 0.78, p ≤ 0.001)
Relational climate predicts job
engagement (B = 0.59, p < 0.001)
and OCB (B = 0.35, p < 0.0001)
Relational climate predicts work
engagement (B = 0.27, p < 0.001)
Relational climate predicts
economic performance (B = 0.28,
p < 0.001) and weakly predicts
social/environmental performance
(B = 0.10, p = 0.06)
Relational climate predicts student
engagement (B = 0.89, p < 0.001)
All betas are unstandardized.
CONCLUSION
to begin to understand how relational climate emerges and
fluctuates over time.
In conclusion, relationships are, and we believe will continue
to be, a central part of organizations and organizational
research. As such, it is critical that researchers have access
to a measure that captures the how employees experience
relationships in a given organization. This paper took the
first steps toward developing a comprehensive measure of
relational climate that will serve this purpose. We examined
the relationship this new construct has with other established
and consequential constructs in the organizational sciences.
Specifically, we found that relational climate is positively
associated with LMSX, procedural justice, POS, and affective
organizational commitment. Additionally, we found a negative
association with instrumental ethical climate. In other field
data collection efforts, this scale has been used to predict
product innovation, organizational citizenship behavior (OCB)
voice, job engagement, economic performance, and student
engagement (see Table 12 for further details on these studies).
It is hoped that in the future, this measure will assist researchers
in further understanding and advocating for the important role
of relationships in organizational life.
FUTURE RESEARCH
The most pressing area for the future is to address the limitations
discussed above. As part of the continued effort to validate
this measure and place it in the nomological network, future
research will need to consider additionally antecedents to,
and consequences of, relational climate. For example, aside
from surfacing the range of benefits of positive workplace
relationships (Heaphy et al., 2018), this measure could also
help organizations identify and address maladaptive relational
behaviors in the workplace such as bullying (Lutgen-Sandvik
et al., 2007), ostracism (Ferris et al., 2008), and loneliness
(Ozcelik and Barsade, 2018).
Another area of future research closely related to the extension
of the nomological network is establishing relational climate as
a multilevel construct (Kozlowski and Klein, 2000; Kuenzi and
Schminke, 2009; Kozlowski et al., 2013). Multilevel constructs
are constructs that have similar meanings at multiple levels of
analysis (Chen et al., 2005). We suspect that relational climate will
be particularly important at the team level of analysis, however,
it may also have implications for role-based dyadic relationships
(e.g., patient–doctor and coach–coachee).
Finally, as suggested by Kuenzi and Schminke (2009), there is
certainly scope to examine the relationship between the different
types of organizational work climates. In this study, we included
the relationship between relational climate and instrumental
ethical climate, however, this is just one of multiple climates
conceptualized in our literature. It is important that as scholars
start to reduce organizational climate and/or psychological
climate into smaller facets of climate, we continue to address
the discriminant and convergent validity of the different types
of climates and the common and distinct antecedent and
consequences among them.
Frontiers in Psychology | www.frontiersin.org
DATA AVAILABILITY STATEMENT
The datasets generated for this study are available on request to
the corresponding author.
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by the Institutional Review Board, Case Western
Reserve University. The patients/participants provided their
written informed consent to participate in this study.
12
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Relational Climate
AUTHOR CONTRIBUTIONS
FUNDING
RB builded the earlier test of quality of relationships. Both
authors revised the original test and expanded it and wrote the
manuscript. KR collected the data and analyzed it.
Funds from the HR Horvitz Endowed Chair Fund were
used. The HR Horvitz family’s generosity is gratefully
acknowledged.
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Conflict of Interest: The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be construed as a
potential conflict of interest.
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