2. 2 Group & Organization Management
The survival of an organization during times of great stress and uncertainty
relies on the ability of its members to persist and persevere in their work,
despite the adversity they face. In other words, employees must demonstrate
resilience, a construct that is gaining increased attention in the literature as a
key factor in not just surviving a crisis but also actually thriving from it (e.g.,
Bhamra, Dani, & Burnard, 2011; Sutcliffe & Vogus, 2003; Tugade &
Fredrickson, 2004). Examples of recent organizational crises abound, from
the sinking of the Concordia cruise ship, to the vast recall of General Motors
and Toyota vehicles, to the explosion of the British Petroleum oil refinery
platform. In each of these cases, employee resilience was required to marshal
the resources and motivation necessary to respond to and ultimately resolve
the organizational crisis (Shin, Taylor, & Seo, 2012). In the current study, we
examine how the behaviors of team leaders can influence the resilience of
team members during a crisis through affective mechanisms.
An organizational crisis is operationally defined as an event or time period
involving high levels of uncertainty, important issues, and time urgency
(Pearson & Clair, 1998). Recently, scholars have called for more investiga-
tions of how teams and leaders can effectively deal with such crisis condi-
tions and mobilize others to do the same (James, Wooten, & Dushek, 2011).
To date, research on leadership has mainly focused on the senior officials
who make decisions at the top (Yammarino & Dansereau, 2008). However,
the leaders and members of front-line teams are also important because their
decisions and actions influence the resolution of a crisis, especially in health
care settings in which workers minister to the well-being of patients (Klein,
Ziegert, Knight, & Xiao, 2006; Yun, Faraj, & Sims, 2005).
Empirical research conducted during an actual crisis is quite rare (Pillai &
Meindl, 1998; Schoenberg, 2005). This is most likely due to the challenges
associated with finding enterprises or individuals willing to participate in
real-time crisis research, either because of impression management concerns
or because they are wholly absorbed in dealing with the extreme demands
they face (Pearson & Clair, 1998). The limited available research on crises
typically involves qualitative case studies of specific events (e.g., Elliott &
Macpherson, 2010; Useem, Cook, & Sutton, 2005), retrospective field inves-
tigations (e.g., Pillai & Meindl, 1998), and laboratory experiments (e.g.,
Halverson, Murphy, & Riggio, 2004). These investigations, although valu-
able, are nonetheless limited by their single-case, retrospective methodology
or by the artificiality of the crisis context and manipulations involved
(Crichton, Ramsay, & Kelly, 2009; James et al., 2011). Furthermore, it is
exceedingly difficult to find research conducted during an organizational cri-
sis that systematically captures both team-level and individual-level data. By
gaining access to participants and such multilevel data, the current study
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3. Sommer et al. 3
contributes a more complete and layered understanding of crisis dynamics
than existing research provides. Studies such as ours may be especially valu-
able because organizational crises and other disasters are becoming increas-
ingly commonplace in our fast-paced, complex world—while at the same
time, professional work is increasingly being completed in team settings
(James et al., 2011; West, Patera, & Carsten, 2009).
In this article, we first present a review of the existing literature regarding
resilience and affect, leading to our predictions for how they will interrelate
during a crisis. Next, we provide an overview of research on leadership
behavior, including how transformational and transactional leadership at the
team level might affect the resilience of individual team members, both
directly and through the mediating influence of positive and negative affect.
From this review, we develop a set of hypotheses that are presented in a mul-
tilevel framework. Next, we present our methodology and the results of our
multilevel analyses. Finally, we discuss our findings and implications for
resilience, affect, and leadership during a crisis.
Resilience During an Organizational Crisis
An organizational crisis can be devastating for individuals, groups, and orga-
nizations that are not resilient, leading to employee turnover, equipment dam-
age, and financial loss (e.g., Pearson & Clair, 1998). Resilience is defined as
“the maintenance of positive adjustments under challenging conditions”
(Sutcliffe & Vogus, 2003, p. 95). Resilience relies on a psychological sense
of mastery and self-efficacy, as well as an ability to draw on high-quality
resources (Sutcliffe & Vogus, 2003). When facing adversity, individuals who
successfully adapt develop skills to cope, which develop new capabilities;
resilience is a capacity to rebound strengthened with more resources (Sutcliffe
& Vogus, 2003). For example, a nurse leader in a hospital emergency room
conducted lunch meetings, where a challenge for each nurse on her team was
raised and constructively discussed to learn how to improve in the future. As
such, resilience both buffers individuals from the psychological damage
associated with adversity and increases the likelihood that they will resolve
challenging situations satisfactorily (Block & Kremen, 1996). In work envi-
ronments, research suggests that resilience can be included in a collection of
factors (along with hope, optimism, and efficacy) that contribute to higher
order constructs such as “positive psychological capital” (Luthans, Avolio,
Avey, & Norman, 2007) and “core confidence” (Stajkovic, 2006). In combi-
nation with these other attributes in a measure of psychological capital, resil-
ience predicts higher levels of employee performance and satisfaction (e.g.,
Luthans et al., 2007).
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4. 4 Group & Organization Management
The targeted measurement and development of resilience in the work
domain is a nascent area of research and theory (Bhamra et al., 2011;
Stajkovic, 2006). Much of what we know about resilience in organizations to
date is extrapolated from the fields of child development and psychodynam-
ics (Block & Kremen, 1996; Masten, 2001; Sutcliffe & Vogus, 2003). In
those fields, scholars have debated theoretically whether resilience is an
innate personality trait that remains fairly stable across situations (e.g.,
Tugade & Fredrickson, 2004) or a state-like attribute that is more malleable
and variable (e.g., Rutter, 1985). We build our approach on the studies that
suggest that state-like resilience can be developed during emergencies and
disasters, when people are often forced to “rise to the occasion” (Clair &
Dufresne, 2007; Powley, 2009). One goal of the current investigation is to
examine the nature of resilience as it arises specifically among team members
grappling with an organizational crisis. Little is known about the develop-
ment of resilience in team settings, for as Sutcliffe and Vogus (2003) noted in
their review, “groups researchers have not directly investigated resilience per
se” (p. 101). The current investigation thus contributes new knowledge
regarding the nature and development of resilience in work teams.
Affect and Resilience
To find the strength and capability to be resilient in a crisis, team members
must draw on all available resources, including emotional, cognitive, social,
and instrumental ones (Sutcliffe & Vogus, 2003). Recent studies demonstrate
that positive emotions in particular can be a key asset in the development of
resilience (Kaplan, Laport, & Waller, 2013; Tice, Baumeister, Shmueli, &
Muraven, 2007; Tugade & Fredrickson, 2004). Affect is defined as emotions
(enduring object-focused feelings that could be disruptive to regular activities)
and moods (temporary states or feelings that are not as disruptive to regular
activities; Brief & Weiss, 2002). Weiss and Cropanzano (1996) theorized that
people experience discrete emotions at work in reaction to events that occur,
and that these emotions have a major impact on cognition and behavior in
organizations. Positive emotions have been shown to have many organiza-
tional benefits (Brief & Weiss, 2002). Insights into the mechanisms for posi-
tive emotions strengthening one’s resilience in a crisis can be gained from
Fredrickson’s (2001) broaden-and-build theory, which suggests that positive
affect increases cognitive flexibility, or the thought–action repertoires of indi-
viduals, which has been shown to increase the problem-solving efficacy and
creativity of individuals (Fredrickson & Joiner, 2002; Isen, 2000). In a crisis,
such mental fluidity is essential because, by definition, such events involve
unexpected and potentially traumatic situations that require new modes of
operating and understanding (Elliott & Macpherson, 2010).
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5. Sommer et al. 5
Furthermore, it has been shown that positive affect can facilitate coping
and well-being when undergoing stress (Folkman & Moskowitz, 2000;
Tugade & Fredrickson, 2004). Positive affect can also have a motivational
effect on individuals, as it is associated with higher levels of persistence and
effort in the face of adversity as compared with negative affect (Fredrickson,
Tugade, Waugh, & Larkin, 2003). Indeed, it has been shown that employees
who are optimistic rebound quickly after setbacks and persevere (Schulman,
1999). Positive affect can have protective benefits for individuals in stressful
situations physiologically as well. For example, Tugade and Fredrickson
(2004) found that the experience of positive emotions during a threatening
situation led to faster cardiovascular recovery. Therefore, we expect positive
affect to contribute to resilience by increasing the cognitive flexibility of
individuals as well as by restoring their sense of efficacy, motivation, and
composure. Thus,
Hypothesis 1a (H1a): Team members’ positive affect will be positively
related to team members’ resilience in a crisis situation.
Organizational crises are likely to generate widespread negative emotions,
such as fear and frustration, among organizational members (Brockner &
James, 2008). Unfortunately, negative affect is generally associated with psy-
chological states and behaviors that are less likely to be useful to the types of
decision making required during a crisis (Brief & Weiss, 2002). In Staw,
Sandelands, and Dutton’s (1981) classic theory of threat rigidity, stress or
anxiety leads to information-processing restriction and constriction of con-
trol. Consequently, attention is focused on central or primary cues and there
is a tendency to rely on well-learned behavior (Gladstein & Reilly, 1985;
Isen, 2000; Vessey, Barrett, & Mumford, 2011). In many crisis situations,
these well-rehearsed behaviors and thought paradigms may not be sufficient
to address the uncertainty, high stakes, and urgency involved (Elliott &
Macpherson, 2010; Pearson & Clair, 1998). Furthermore, if workers are
unable to break free from the threat-rigidity trap, they may be doomed to
repeat the same failed responses over and over (Muurlink, Wilkinson, Peetz,
& Townsend, 2012). Based on this research, we predict,
Hypothesis 1b (H1b): Team members’ negative affect will be negatively
related to team members’ resilience in a crisis situation.
Although we expect opposite effects from positive and negative affect in
terms of their impact on team member resilience, we do anticipate that both
types of emotion will arise in our study context, based on past research
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6. 6 Group & Organization Management
findings. Indeed, in a field study conducted after the terrorism events of
September 11, 2001 (Bonanno, Rennicke, & Dekel, 2005) as well as some
simulated crisis laboratory experiments (Fredrickson et al., 2003; Tugade &
Fredrickson, 2004), positive affect was found to co-exist with negative affect
even under the most difficult of circumstances. Our study builds on these
findings to measure the level and outcomes of such positive affect, should it
emerge, in contrast to much previous work that focused exclusively on the
role of negative emotions in crisis situations (e.g., Useem et al., 2005).
Leadership and Affect
The role of leaders in managing the emotions of their followers has become
of increasing concern to researchers because of the important proximate out-
comes (e.g., positive affective tone) and ultimate outcomes (e.g., reduced
burnout and strain) that may ensue (Ashkanasy & Humphrey, 2011; Kaplan,
Cortina, Ruark, LaPort, & Nicolaides, 2014). We draw on Bass’s (1985) well-
known full range leadership model to explore how transformational and
transactional leadership might influence the resilience of team members
through affective mechanisms. According to Bass (1985, 1998), transforma-
tional leader behaviors involve four types of behaviors: idealized influence,
inspirational motivation, intellectual stimulation, and individualized consid-
eration. These behaviors can elevate followers beyond their self-interests and
energize them toward a new common vision (Mitchell et al., 2014). In con-
trast, transactional leadership behaviors reflect an exchange relationship with
team members, where leaders provide rewards and punishments to their fol-
lowers in exchange for their work. Two types of transactional leadership
styles are “active” and “passive” types of management by exception (MBE).
Both active MBE and passive MBE forms focus on correcting problems
rather than on inspiring new directions; the main difference is the time hori-
zon and proactive nature of the behaviors. Specifically, active MBE leader-
ship behaviors involve continually monitoring team members’ performance
to anticipate mistakes before they become a problem and taking preventive
action, whereas passive MBE leadership behaviors involve waiting until
problems materialize and then intervening with criticism and reproof after
mistakes are made. MBE leadership is often contrasted to transformational
leadership in terms of triggering unwelcome organizational outcomes (e.g.,
Bass, 1998; Bass, Avolio, Jung, & Berson, 2003; Halverson et al., 2004).
A third form of transactional leadership in Bass’s (1985) model is “contin-
gent reward,” which involves providing recognition, praise, incentives, and
rewards to team members in exchange for their good work. However, both
conceptually and empirically, this form of transactional leadership has been
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7. Sommer et al. 7
found to overlap highly with transformational leadership (e.g., Rafferty &
Griffin, 2004; Tejeda, Scandura, & Pillai, 2001; Yukl, 1999). Heinitz,
Liepmann, and Felfe (2005) noted that the discriminant validity between con-
tingent reward and transformational leadership “has been questioned and
reexamined again and again” (p. 184). In our investigation, we exclude con-
tingent reward leadership from our theorizing and analyses because of the
likely overlap between giving rewards and other transformational behaviors
(e.g., individualized consideration) as well as due to methodological con-
cerns that the measures would violate the assumption of independence needed
for multilevel modeling.
Whereas empirical research on Bass’s (1985) leadership styles has been
extensive (e.g., Bass et al., 2003; Dvir, Eden, Avolio, & Shamir, 2002; Judge
& Piccolo, 2004), little is known about how they influence the resilience of
team members through affective mechanisms. In general, however, prior
research and theory suggest that transformational leadership behaviors will
increase the scope and intensity of positive affect experienced by members,
while contributing to a contrasting drop in negative affect (Bass, 1985;
McColl-Kennedy & Anderson, 2002). Transformational leadership behaviors
may increase positive affect and reduce negative affect simply through con-
tagion effects (Barsade, 2002; Bono & Ilies, 2006). However, the vision and
values embedded in transformational leadership behaviors are likely to
explicitly activate positive emotions as well, such as hope and optimism that
the current crisis will soon be resolved (Brockner & James, 2008; Shamir &
Howell, 1999). Leaders may also inspire followers to have enthusiasm for
accomplishing the challenge at hand through their encouragement and praise
(Bass, 1998). In addition to cultivating positive affect during a crisis, leaders
can help reduce negative affect in followers by allaying fears and mitigating
frustration (James et al., 2011; Kaplan et al., 2014; McColl-Kennedy &
Anderson, 2002). Therefore, we propose,
Hypothesis 2a (H2a): Transformational leadership will be positively
related to team members’ positive affect in a crisis situation.
Hypothesis 2b (H2b): Transformational leadership will be negatively
related to team members’ negative affect in a crisis situation.
In contrast, transactional leadership behaviors are expected to have the
opposite influence on team member affect. In prior research, both the active
and passive forms of MBE leadership have been found to trigger negative
emotional consequences for individuals and teams (e.g., Nederveen Pieterse,
van Knippenberg, Schippers, & Stam, 2010). In particular, the corrective and
punishing consequences used under both types of MBE leadership are likely
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8. 8 Group & Organization Management
to generate negative emotions such as anger, frustration, and stress (Atwater,
Camobreco, Dionne, Avolio, & Lau, 1997). In addition, the transactional
nature of the MBE relationship between leaders and followers, which focuses
either on discipline or on the basics of how to do the task, can undermine
employee motivation and satisfaction (e.g., Bass et al., 2003). The downside
of MBE leadership is likely to be especially salient in a crisis situation, as
prior research has shown that “the transactional leader works most effectively
in a stable and predictable environment” (Heinitz et al., 2005). Thus, we
theorize,
Hypotheses 2c and 2d (H2c and H2d): MBE leadership (both active and
passive) will be negatively related to team members’ positive affect in a
crisis situation.
Hypotheses 2e and 2f (H2e and H2f): MBE leadership (both active and
passive) will be positively related to team members’ negative affect in a
crisis situation.
Affect as a Mediator of the Relationship Between Leadership
and Resilience
In the best-case scenarios, team leaders will provide the type of resources and
direction needed by front-line employees to respond adequately to a crisis.As
described earlier, emotional resources are essential to this effort, and thus we
expect that team members will be more ready and capable to weather the
storm of a crisis to the degree that their leaders help foster positive affect and
minimize negative affect (Shin et al., 2012; Sutcliffe & Vogus, 2003). In par-
ticular, we expect that transformational leadership behaviors will influence
team members’ resilience through the mediation of positive emotion (Bass,
1998; Kaplan et al., 2014; Sutcliffe & Vogus, 2003). As shown in previous
research, transformational leaders embody behaviors such as idealized influ-
ence, inspirational motivation, intellectual stimulation, and individualized
consideration, all of which are likely to boost the emotional states of team
members, both in general and in a crisis (Barsade, 2002; McColl-Kennedy &
Anderson, 2002). For example, a leader who delivers a rousing speech may
elevate the optimism and confidence experienced by employees, an energy
source they can draw on to remain resolute in their determination to over-
come obstacles (Powley, 2009; Tugade & Fredrickson, 2004). Moreover, fol-
lowers may feel less fearful when they see a transformational leader acting
courageously, which may reduce the level of threat they perceive and allow
them to overcome their natural tendency to constrict cognition under duress
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9. Sommer et al. 9
(Fredrickson, 2001; Staw et al., 1981; Sutcliffe & Vogus, 2003). This media-
tional view of affect is consistent with Van Kleef’s (2009) emotions as social
information model, which specifies that individuals look to the emotional
reactions of themselves and others (including their leaders) to determine how
to conceive of and react to a given situation, especially when the circum-
stances themselves are ill-defined or unusual. Therefore,
Hypothesis 3a (H3a): Positive affect will mediate the positive relation-
ship between transformational leadership and team members’resilience in
a crisis situation such that a positive relationship will be found between
transformational leadership and positive affect, and a positive relationship
will be found between positive affect and resilience.
Hypothesis 3b (H3b): Negative affect will mediate transformational
leadership and team members’ resilience in a crisis situation, such that a
negative relationship will be found between transformational leadership
and negative affect, and a negative relationship will be found between
negative affect and resilience.
As noted previously, MBE leadership behaviors focus on identifying and
correcting errors, which may undermine team members’ self-confidence and
trigger negative emotions (Atwater et al., 1997; Bass et al., 2003). Passive
MBE leaders, in contrast, are barely engaged at all until a problem occurs and
therefore may create anxiety and frustration among team members who need
more support to meet the intense demands of a crisis (Howell & Avolio,
1993). Thus, we propose that both active and passive MBE leadership behav-
iors will reduce team member resilience by undermining the positive affect
and increasing the negative affect experienced:
Hypotheses 3c and 3d (H3c and H3d): Positive affect will mediate the
negative relationship between MBE leadership (both active and passive
forms) and team members’resilience in a crisis situation, such that a nega-
tive relationship will be found between MBE leadership (both active and
passive forms) and positive affect, and a positive relationship will be
found between positive affect and resilience.
Hypotheses 3e and 3f (H3e and H3f): Negative affect will mediate the
negative relationship between MBE leadership (both active and passive
forms) and team members’ resilience in a crisis situation, such that a posi-
tive relationship will be found between MBE leadership (both active and
passive forms) and negative affect, and a negative relationship will be
found between negative affect and resilience.
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10. 10 Group & Organization Management
Summary
The present study compares the influence of three different leadership
approaches on resilience during crisis conditions through the meditational
pathway of positive and negative affect.
Method
Research Context
The context for the current investigation is a hospital bed shortage crisis that
crippled the Canadian health care system in 2007-2008 (“Bed Shortages,”
2008). During the data collection period, the health care facilities in our study
sustained 100% bed capacity for months on end, punctuated by climaxes of
120% or 130% bed capacity. The lack of available patient beds became so
problematic that it threatened the ability of hospitals to provide adequate care
for patients (“Hospital Bed Crunch,” 2008). In particular, surgeries had to be
canceled at the last minute or never performed at all due to the lack of surgi-
cal and recovery space (“Shortage of Hospital Beds,” 2007). It is estimated
that hospital wait times cost the Canadian economy $14.8 billion [Canadian
dollars] in 2007 (“Patient Wait Times,” 2008).
We conducted our research at two large hospitals and 17 smaller medical
sites that collectively employed over 15,000 staff in total in the province of
Ontario, Canada. The units that were identified by top leaders as experienc-
ing the most severe hospital bed access problem were surgery (35%), medi-
cine (26%) and other medical sites (39%). Examples of the departments
include cardiology and general surgery (surgery), intensive care and adult
emergency (medicine), stroke rehabilitation, and specialized geriatrics (other
medical sites).
To confirm that the crisis was experienced in the organizations studied, we
contacted 27 leaders (including at least one from each research site) before
beginning data collection. During the interviews, these leaders confirmed
that the bed shortage situation at the medical sites in our study involved (a)
ambiguity of cause and resolution, (b) life-and-death consequences for
patient care, and (c) urgent time pressure to resolve problems and save lives.
For example, as one participant described, teams responded to the bed short-
age crisis by extreme measures such as “doubling up on patients, skipping
breaks, transferring one [patient] upstairs while teammates are admitting
another.” Thus, the organizational context of our study met the three condi-
tions (uncertainty, high stakes, and urgency) that define a crisis according to
Pearson and Clair (1998). When answering questionnaire items, participants
were asked to refer to the hospital bed access problem over recent months.
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11. Sommer et al. 11
Participants
To be included in this study, team members had to have worked with their
team and leader for at least 30 days to ensure sufficient opportunities to
observe each other (cf. George, 1990). In accordance with the criteria for
defining a team (Guzzo & Dickson, 1996), the medical teams were consid-
ered for inclusion in the study if they (a) consisted of at least two members,
(b) worked interdependently within an organization, and (c) were described
as a team by themselves and others. Senior leaders determined who was on
each team for each unit based on the organizational chart. Each team member
was only a member of one team, and the average team size was eight mem-
bers (SD = 4.9).
Team members were on average 43 years old (SD = 10.7), worked in
health care for 19 years (SD = 10.9), were members of their current organiza-
tion for 12 years (SD = 9.8), and worked with their current team for 8 years
(SD = 8.7), and with their leader for 4 years (SD = 4.6). All participants had
a college diploma or university degree. Most hospital team members were
female (92%), as other research conducted in a medical setting has found (cf.
ten Brummelhuis, Oosterwaal, & Bakker, 2012). The job types of partici-
pants were nurses (78%), nurse practitioners (16%), and technicians (6%).
Leaders were on average 43 years old (SD = 5.49), worked in health care
for 18 years (SD = 6.13), were members of their current organization for 12
years (SD = 5.01), and worked with their current team for 8 years (SD = 4.11).
There were 37% women and 63% men.All participants had a college diploma
or university degree. The leaders were mainly nurses, but there was one
doctor.
Materials and Procedure
Completed surveys were returned from leaders of 52 teams (66% response
rate) and 426 team members (38% response rate). Using questionnaire codes,
team members were matched with their leader. Questionnaires were distrib-
uted to team members either by mail or electronically, and were returned
directly to the researchers. The survey package included a $2 coffee voucher
as a token of appreciation. One week after the questionnaires were sent, par-
ticipants were reminded to fill out the survey, followed by a final reminder a
few days prior to the completion date. Participants were assured of the ano-
nymity of their responses and code numbers were used to match members
with their leaders and teammates during data collection and analysis.
In the survey, the term crisis was not used to avoid the cueing effects that
it might have evoked; the term problem was used instead. On the survey, each
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12. 12 Group & Organization Management
team member rated the transformational and transactional style of his or her
leader as observed over the past 6 months of hospital bed shortages. Team
members also assessed their own negative affect, positive affect, and resil-
ience. We attempted to mitigate any biases that might arise from the survey
method in several ways (cf. Podsakoff, MacKenzie, Lee, & Podsakoff, 2003).
First, we used pre-validated scales that have been used successfully in field
research in the past (e.g.,Avolio & Bass, 1985; Tugade & Fredrickson, 2004).
Second, we carefully constructed the questionnaire to reduce the tendency of
participants to respond overly consistently on all scales (e.g., randomized
questions within blocks, counterbalanced order of presentation). Third, team
members, who are best placed to assess their own thoughts and emotions, and
their leaders’ behaviors, evaluated the predictor variables and the resilience
criterion (e.g., Tugade & Fredrickson, 2004; Wagnild & Young, 1993).
Fourth, the predictors and criterion were evaluated using different response
formats (i.e., Likert-type scales and semantic differentials) to separate the
measures methodologically to reduce social desirability and the consistency
motif (Salancik & Pfeffer, 1977).
Measures
Resilience. We used Wagnild and Young’s (1993) 25-item Resilience Scale,
which was developed in a health care context and has been used in other
leadership research (e.g., Luthans et al., 2007). This State Resilience scale is
designed to capture two factors, personal competence and acceptance of self
and life, which can be combined into an overall measure of resilience. The
response scale ranges from 1 (strongly disagree) to 7 (strongly agree). The
instructions asked participants to refer to the previous 6 months (during the
bed shortages) to assess items such as “When I’m in a difficult situation, I can
usually find my way out of it” and “I usually look at a situation in a number
of ways.” Prior to data administration, four items were removed from the
scale, based on an assessment of their fit with the research context as well as
the face validity of the items. After data collection, principal components
analysis with varimax rotation resulted in the deletion of four items that had
cross-loadings on the personal competence and acceptance factors of resil-
ience. These two factors represented one higher order resilience factor, so
they were combined in subsequent analysis (α = .87).
Affect. Using Tugade and Fredrickson’s (2004) modified scale that is Positive
and Negative Affectivity Schedule or PANAS (Watson, Clark, & Tellegen,
1988), participants rated the degree to which they felt an emotion during the
past 2 months on a 5-point Likert-type scale from 1 (very slightly or not at
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13. Sommer et al. 13
all) to 5 (extremely). Eleven items were used to assess negative affect, based
on previous research (Pearson & Clair, 1998; Tugade & Fredrickson, 2004)
and the crisis context of this study. Based on a principal components analysis
with varimax rotation and an assessment of the internal consistency of the
two scales, 2 items were removed from the Negative Affect scale (guilty and
afraid) and 3 items were removed from the Positive Affect scale (surprise,
alert, and relieved). The 9 items used for the Negative Affect scale were dis-
appointed, sad, irritable, tired, angry, discouraged, upset, depressed, and anx-
ious (α = .89). The 8 items used for the Positive Affect scale were attentive,
satisfied, calm, determined, curious, interested, strong, and inspired (α = .83).
Leadership. The Multifactor Leadership Questionnaire (MLQ) Form
5X-Short (Avolio & Bass, 1995) was used to evaluate transformational and
transactional forms of leadership. All MLQ items were assessed on a 5-point
frequency scale ranging from 0 (not at all) to 4 (frequently, if not always). On
the MLQ Form 5X-Short, 20 items capture four components (idealized influ-
ence, individualized consideration, inspirational motivation, and intellectual
stimulation) that are combined as a measure of transformational leadership
(cf. Avolio, Bass, & Jung, 1999; Avolio, Zhu, Koh, & Bhatia, 2004; Tejeda
et al., 2001). A sample transformational leadership item is, “Articulates a
compelling vision of the future.” We collapsed the subscales based on stan-
dard practice and found high internal reliability for the transformational lead-
ership measure (20 items; α = .96).
Transactional leadership is often measured by three separate subscales
(Contingent Reward, Active MBE, Passive MBE), although prior research
has questioned whether contingent reward is distinguishable from transfor-
mational leadership (Tejeda et al., 2001). In our data, we found that the
Contingent Reward subscale was highly inter-correlated with the measure of
transformational leadership (r = .91), which validated our a priori exclusion
of contingent reward from our hypothesizing and analyses. For the two
remaining transactional leadership scales, Active MBE and Passive MBE,
principal components analysis confirmed that they represented two distinct
constructs, so these variables were retained (r = .01). Sample items include
“Keeps track of all mistakes” (active MBE) and “Waits for things to go wrong
before taking action” (passive MBE). The measures showed adequate inter-
nal reliability for active MBE (4 items; α = .79) and passive MBE (4 items; α =
.77). In the final principal components analysis with varimax rotation, all
leadership items were entered and three factors emerged that confirmed our
expectations: transformational, active MBE, and passive MBE.
In the current study, leadership is conceptualized at the team level of anal-
ysis (cf. Avolio et al., 2004; Gavin & Hofmann, 2002). In a crisis or any other
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14. 14 Group & Organization Management
organizational circumstance, leaders and their team members share interac-
tions and experiences. Shared leadership experiences suggest that individuals
on each team will have similar perceptions of their team, so within-team
homogeneity and between-team heterogeneity are expected (Klein &
Kozlowski, 2000). We tested these assumptions before beginning data analy-
sis and found that for transformational leadership, ICC(1) = .22, ICC(2) =
.75, F = 4.01, p < .001; active MBE leadership, ICC(1) = .22, ICC(2) = .75,
F = 4.00, p < .001; and passive MBE leadership, ICC(1) = .19, ICC(2) = .59,
F = 2.46, p < .001), there was sufficient empirical evidence and theoretical
justification to aggregate team members’ leadership scores to the upper level
of analysis (Klein & Kozlowski, 2000). Thus, team members’ ratings at the
individual level were combined into three team-level leadership variables.
Hypothesis Testing
All hypotheses were tested using hierarchical linear modeling (HLM). HLM is
more accurate than traditional ordinary least squares regression techniques for
examining cross-level models because it estimates within- and between-team
effects with the appropriate degrees of freedom, and estimates non-indepen-
dence of error terms within teams (Gavin & Hofmann, 2002). The sample size
of this study is consistent with leadership studies that have used HLM (e.g.,
Avolio et al., 2004). As the hypothesis tests involve cross-level mediation,
grand mean centering was used for the upper level of analysis. This has several
advantages (e.g., Raudenbush & Bryk, 2002), including between-group vari-
ance partialed out of the outcome variable (Hofmann & Gavin, 1998).
To test the multilevel mediation hypotheses, we followed Baron and
Kenny’s (1986) approach. There are three criteria for mediation to occur: (1)
leadership is related to the mediator (positive or negative affect), (2) leader-
ship is related to resilience, and (3) when all variables are entered into the
equation, affect is related to resilience. If the relationship between leadership
and resilience (in Step 3) is no longer significant, then there is full mediation;
but if the relationship between leadership and resilience decreases but remains
significant, then there is partial mediation. According to Kenny, Kashy, and
Bolger (1998), it is not necessary for leadership to be related to resilience
(Step 2) for mediation to occur.
A “null” model was estimated prior to the hypothesis test. The results
demonstrate that the criterion variables had sufficient within-team homoge-
neity and between-team variance (Hofmann, 1997): positive affect, γ = 2.53,
p < .001; negative affect, γ = 1.47, p < .001; and resilience, γ = 5.95, p < .001.
Accordingly, we conducted hypothesis tests with HLM and we present the
findings in the following section.
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15. Sommer et al. 15
Results
The means, standard deviations, correlations, and reliability are displayed in
Table 1. The means for the transformational and transactional leadership
styles are consistent with those found in prior research (Judge & Piccolo,
2004; Lowe, Kroeck, & Sivasubramaniam, 1996).
Direct Relationships
As predicted and as shown in Table 2, positive affect was positively related to
resilience (H1a: γ = .35, p < .001), and negative affect was negatively related
to resilience (H1b: γ = −.16, p < .001). As shown in Tables 3 and 4, H2a and
H2b were also supported: Transformational leadership was positively related
to positive affect (H2a: γ = .33, p < .001) and negatively related to negative
affect (H2b: γ = −.47, p < .001) during the crisis. Unexpectedly, active MBE
leadership was not related to positive affect (H2c: γ = −0.15, ns) or negative
affect (H2e: γ = .06, ns). As hypothesized, passive MBE leadership was nega-
tively related to positive affect (H2d: γ = −.39, p < .001) and positively related
to negative affect (H2f: γ = .54, p < .001) in crisis.
Mediated Relationships
Affect as a mediator. As hypothesized and as shown in Tables 3 and 4, posi-
tive affect mediated the relationship between transformational leadership and
resilience (H3a: Step 3, for transformational leadership on resilience, γ =
Table 1. Descriptive Statistics and Correlations.
Correlations
Variable M SD 1 2 3 4 5 6
1 Transformational leadership 2.13 0.57 (.96)
2 Active MBE leadership 1.94 0.52 −.14 (.79)
3 Passive MBE leadership 1.50 0.43 −.62 .01 (.77)
4 Negative affect for individuals 1.42 0.83 (.89)
5 Positive affect for individuals 2.47 0.66 −.41 (.83)
6 Resilience for individuals 6.01 0.56 −.22 .41 (.87)
Note. Leadership is at the team level of analysis, N = 52. At the individual level of analysis,
N = 426, negative affect, positive affect, and resilience. Correlations greater than .41 were
statistically significant at p < .01; correlations greater than .22 were significant at p < .05, with
a one-tailed test. MBE = management by exception.
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16. 16 Group & Organization Management
−.04, ns; for positive affect on resilience, γ = .56, p < .001). Similarly, nega-
tive affect mediated the transformational leadership and resilience relation-
ship (H3b: Step 3, for transformational leadership on resilience, γ = −.01, ns;
for negative affect on resilience, γ = −.16, p < .001). As the first condition for
mediation was not satisfied for active MBE (active MBE was not related to
affect), further tests for mediation were not conducted on this leadership style
(H3c and H3e). However, as predicted, positive affect did mediate passive
MBE leadership and resilience (H3d: Step 3, for passive MBE leadership on
resilience, γ = .02, ns; for positive affect on resilience, γ = .35, p < .001).
Finally, as hypothesized, negative affect mediated the relationship between
passive MBE leadership and resilience (H3f: Step 3, for passive MBE leader-
ship on resilience, γ = −.01, ns; for negative affect on resilience, γ = −.16,
p < .001). Figure 1 presents a summary of the multilevel modeling results of
the relationships among our variables.
Discussion
As organizational crises become more frequent and increasingly compli-
cated, the ability of employees to withstand the stressors involved and remain
resilient is a growing concern to researchers and practitioners (James et al.,
2011; Sutcliffe & Vogus, 2003). The results of this study contribute to our
understanding of how teams operate in a crisis in several ways. First, we
found that both positive and negative affect can co-exist within individuals
confronting a crisis, demonstrating the emotional complexity of these situa-
tions. Second, we translate these emotional inputs into the important output
of team member resilience, showing how positive affect promotes resilience
Table 2. Hierarchical Linear Modeling Results for Affect and Resilience.
Positive affect Negative affect
Variables γ00 γ01 σ2 τ00 γ00 γ01 σ2 τ00
Affect and resilience
Level1:Resilience = +
Affect)
0 1ij j j
ijr
β β
( +
5.05*** .35*** .25 .10 6.18*** −.16*** .29 .01†
Level 2 : = +
=
0 00 0
1 10
β γ
β γ
j j
j
U (H1a) (H1b)
Note. γ00 = intercept of Level 2 equation predicting β0j; γ01 = slope of Level 2 equation predicting β0j; γ10 =
intercept of Level 2 equation predicting β1j (pooled Level 1 slopes); σ2 = variance in Level 1 residual (variance
in rij); τ00 = variance in Level 2 residual for models predicting β0j (variance in U0j).
†p < .10. ***p < .001.
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19. Sommer et al. 19
whereas negative affect undermines it. Third, we showcase the powerful role
that leaders can have on the emotional states of team members and their cor-
responding resilience. In particular, we found significant and oppositional
effects of transformational and passive MBE leaders’ behaviors on team
member resilience through the mediating mechanism of affect. Finally, our
results confirm that there are multiple levels of influence involved in creating
resilient teams, a multilevel perspective that has largely been absent from the
literature to date (Sutcliffe & Vogus, 2003; Yammarino & Dansereau, 2008).
First, it is intriguing that team members showed positive affect in the face
of a crisis in our study, as negative affect is traditionally thought to be the
primary type of emotion experienced under stressful conditions (e.g., Önder
& Basim, 2008; Useem et al., 2005). These findings add support to the
nascent literature that suggests that positive emotions can co-exist with nega-
tive emotions in a crisis (e.g., Bonanno et al., 2005; Fredrickson et al., 2003).
It also indicates that workplace events cannot be simply stratified into “has-
sles” and “uplifts” as under affective events theory (Weiss & Cropanzano,
1996); in reality, even stressful circumstances may evoke a mixture of posi-
tive and negative feelings.
Figure 1. HLM results for leadership, affect, and resilience in organizational crisis
situations.
Note. Significant paths are depicted with a solid line, whereas non-significant paths are
depicted with a dotted line. HLM = hierarchical linear modeling; MBE = management by
exception. N = 52 team leaders; N = 426 team members.
*p < .05. ***p < .001.
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20. 20 Group & Organization Management
Second, our study shows that not only can positive affect surface during a
crisis, but it may also be a key driver of the development of resilience within
individuals. In an emergent crisis scenario, where many previous lessons
learned are inappropriate, individuals must develop resilience through draw-
ing on a wide range of resources and acting creatively to navigate the context
(Elliott & Macpherson, 2010; Pearson & Sommer, 2011; Sommer & Pearson,
2007). Our results show just how important one form of resource, positive
affect, may be to that effort. Positive affect, as Fredrickson (2001) suggested,
may serve to broaden the thought–action repertoires of individuals, allowing
them to see innovative solutions to the problems they face and increasing
their self-confidence in their ability to resolve the crisis situation. The rela-
tionship between positive affect and resilience is consistent with the results of
studies of burnout, where individuals experience personal accomplishment
by exerting control over a stressful situation (e.g., Maslach & Jackson, 1981;
Önder & Basim, 2008).
In comparison, we found that negative affect does indeed undermine the
ability of team members to be resilience in a crisis (Schulman, 1999). The more
they experienced negative emotions, the less likely the participants in our study
felt ready to be resourceful and persistent. Therefore, our study provides new
evidence for deleterious effects that negative affect may have on the cognition
and motivation of individuals, especially when safety and security are at risk
(Staw et al., 1981). The high levels of negative emotions that typically emerge
under stress is thus all the more concerning, given the team- and organization-
level ramifications we found here (cf. Folkman & Moskowitz, 2000).
Third, for teams, it is clear that the behaviors of the leader play a part in
building the resilience of team members (Mitroff, 2004). We did not find that
transformational leadership behaviors influenced the level of follower resil-
ience directly. Instead, our research showed that the connection between the
behavior of the team leader and the resilience of his or her followers was
mediated by the affective states of those followers. Specifically, results of the
present study indicate that in a crisis situation, transformational leadership
behaviors are associated with higher levels of positive affect and lower levels
of negative affect among team members, which in turn relate to higher resil-
ience. These results are consistent with the argument that transformational
leaders influence team members’feelings by envisioning a positive picture of
the future, expressing confidence in team members’ abilities to meet high
expectations, and conveying shared values (e.g., Ashkanasy & Tse, 2000;
Bass, 1998). In addition, transformational leadership behaviors predicted
lower levels of negative affect during a crisis context, in much the same pat-
tern as has been found in ordinary leadership contexts (e.g., Densten, 2005;
McColl-Kennedy & Anderson, 2002).
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21. Sommer et al. 21
Unexpectedly, the active type of MBE leadership did not significantly
influence team member affect or resilience in our study. This result is in con-
trast to prior research suggesting that the coercion and punishment involved
in active MBE leads to negative emotions such as anger and resentment
among followers (Atwater et al., 1997). Yet it was not the case that the leaders
in our study simply did not exhibit active MBE behaviors; in fact, the level of
active MBE leadership reported in teams was commensurate with that of
transformational leadership and higher than that of passive MBE leadership
(see Table 1). Perhaps the non-significant relationship between active MBE
and affect is an artifact of the health care setting, in that actively seeking out
and preventatively correcting errors may be viewed as the appropriate (i.e.,
affectively neutral) approach when patient health and safety are at risk.
Indeed, it may be that the absence of active MBE behaviors on the part of the
team leaders in a crisis would have been met with more affective reactivity by
followers.
Consistent with this explanation, we found that the passive form of MBE
leadership was associated with significantly higher levels of negative affect
and lower levels of positive affect among team members. Passive MBE
involves leaving team members in the dark about their progress and perfor-
mance until after mistakes are made, which may be deadly in a health care
context. This may explain the reactions of team members in our study, includ-
ing one who commented about her leader’s passive style, “We feel frustrated
with lack of sharing information, lack of gratitude for jobs well done, and
lack of optimism and worth.” Thus, we extend prior research to show that
passive MBE leaders may increase team members’ psychological stress and
feelings of helplessness, feelings which may already be high in a crisis
(Atwater et al., 1997). Through this impact on positive and negative affect,
our results suggest that passive MBE leadership behaviors indirectly weaken
the resilience of team members.
Strengths and Limitations
Our results indicate that positive affect is fundamental to building resilience in
teams in a crisis. However, the results of the study do not necessarily imply
that negative affect, and the leadership behaviors that trigger it, is universally
detrimental to crisis response efforts. For example, prior research has shown
that negative affect during decision-making processes may encourage indi-
viduals to follow well-established protocols and structures (Elsbach & Barr,
1999; Mitchell et al., 2014). This is the potential upside of the cognitive rigid-
ity associated with threatening situations, in that individuals may revert back
to tried-and-true procedures, rather than improvising new and risky approaches
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22. 22 Group & Organization Management
(Staw et al., 1981). Thus, it is possible that the negative affect experienced by
study participants might have had a positive impact on outcomes other than
resilience, such as decision-making effectiveness. This is certainly an area
worthy of future research, although objective measures of effectiveness are
very difficult to capture methodologically, given the uncertainty and volatility
of crisis contexts (Hadley, Pittinsky, Sommer, & Zhu, 2011).
Certainly, when considering the potential for future research, the chal-
lenges associated with gathering data under crisis conditions cannot be over-
stated. Such data are extremely difficult to collect due to the sensitivity of the
issues and the reluctance of senior leaders to open their doors to outsiders
conducting research, due to time pressures or exposure concerns (Clair &
Dufresne, 2007). This study is unique in that we gathered data as the crisis
was unfolding from leaders and intact teams. Capturing the dynamics among
variables as they occurred in the moment is critical for discovering how to
effectively navigate these situations in the future. Moreover, our real-time
crisis data collection enabled us to avoid the common methodological issue
of relying on the recall of past events, which may invite retrospective biases
(Gilovich, Griffin, & Kahneman, 2002). A second strength of the current
study is the nature of our sample. We collected data from 52 teams from 19
different organizations, all united in their confrontation of the same crisis of
hospital bed shortages. Such multiorganizational studies of crisis have been
lacking in the literature to date (Crichton et al., 2009; James et al., 2011).
From our data, we can assert not only what happened within an organization
facing a crisis, as some prior case studies have done (e.g., Useem et al., 2005),
but also what happened across organizations simultaneously. This aggrega-
tion of data and perspectives on the nature of crisis variables is another aspect
that sets our study apart from prior research (Elliott & Macpherson, 2010).
Although our study contributes both theoretically and empirically to the
field, it does reflect some embedded limitations. First, we collected all of our
measures on a survey, which increases the possibility of common method
bias (Podsakoff et al., 2003). We attempted to mitigate those concerns by fol-
lowing recommendations such as counterbalancing the order of measures and
using pre-validated scales, but nonetheless future research should seek to find
alternative methods of capturing the variables studied. A second limitation of
our study relates to our sample, which mainly comprised female health care
providers. This predominance of women is consistent with previous work in
the health care context (Hofmann, Lei, & Grant, 2009; ten Brummelhuis et
al., 2012) and reflects the typical gender ratios found in the front-line patient
care teams we studied. For example, at the time of data collection, men rep-
resented just 6% of registered nurses employed in Canada (Canadian Institute
for Health Information, 2008). It is possible, however, that the findings of the
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23. Sommer et al. 23
current study may have been influenced by the gender profile of our sample.
For example, recent work has found that female leaders tend to use more
transformational behaviors than male leaders (Eagly, Johannesen-Schmidt, &
van Engen, 2003). Thus, these findings could be tested in more male-domi-
nated contexts as an area for future research.
Future Research
Future research would benefit from not only studying other populations but
also measuring variables longitudinally. Even though our HLM model
allowed for more confirmation of causal effects than single-level studies, as
has been common in leadership research (Yammarino & Dansereau, 2008),
the administration of our measures nonetheless does not allow for full causal
conclusions. Research could also supplement our team- and individual-level
findings with the examination of other levels of analysis, such as organiza-
tional and cross-sectorial, which are likely to be relevant in a crisis (Crichton
et al., 2009). For example, an organizational context that is supportive, adap-
tive, and recognizes team members’efforts may provide another path to resil-
ience (e.g., Sutcliffe & Vogus, 2003). Alternatively, the current study could
be extended by examining additional emotional, cognitive, and behavioral
factors within the team or at the individual level which might also predict
resilience, such as social support, learning orientation, and practicing medita-
tion techniques (Sutcliffe & Vogus, 2003). Other research has found, for
example, that self-care and personal accomplishment minimize stress and
burnout and promote resilience in professions with emotional labor (e.g.,
Halbesleben & Buckley, 2004). Although this study is ground with affective
mechanisms to explain the relationship between leadership and resilience in
crisis situations, future research could examine more traditional cognitive
mechanisms such as information processing.
In addition, although it was an achievement to collect data at multiple sites
during the period of crisis, we did conduct our investigation during only one
crisis. It is possible that the nature of the bed shortage crisis itself influenced
our findings, and that different types of crises may incur different patterns
among our variables of interest. For example, James and Wooten (2005) dis-
criminate between the notion of “sudden” crises (e.g., terrorist attacks) and
“smoldering” crises (e.g., product recalls due to defects). The bed shortage cri-
sis evolved over many months and even years in the Canadian hospital system,
which may make it closer to a smoldering form of crisis (“Bed Shortages,”
2008). In such smoldering crises, more engagement and inspiration may be
required from the leader to convince people to preserve and stay resilient over
time. In contrast, it may be that transactional leadership behaviors would be
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24. 24 Group & Organization Management
more effective in promulgating positive affect and resilience under other crisis
circumstances, especially those in which the time pressure is overwhelming
and decisions need to be made quickly.
Implications and Conclusions
Through this empirical study, recommendations can be offered to practitioners
for the effective management of teams in adverse situations. To start, simply
understanding which team-level and individual-level variables positively influ-
ence team members’ affect could help senior management deal with the com-
plexities of a crisis more effectively. To the extent that leaders can display
transformational behaviors during difficult circumstances, their subordinates
should benefit. For example, leaders who seek team members’ ideas about how
to deal with the crisis, who empathize with the stresses and strains experienced by
team members, and who encourage followers to ask for assistance when needed
may help team members constructively interpret current events and respond posi-
tively (Van Kleef, 2009). Organizations could train leaders to display such trans-
formational behaviors to boost the affect and resilience of team members (e.g.,
Dvir et al., 2002). Furthermore, the more exposure to real or simulated crisis
experiences that leaders can provide to employees, the more likely they are to
gain the experience and self-efficacy needed to feel competent in the next crisis
situation. Ideally, positive spirals will emerge so that resilience spreads through
the organization (Fredrickson & Joiner, 2002; Sutcliffe & Vogus, 2003).
Collectively, this study provides clear evidence that transformational lead-
ership behaviors are more likely to trigger positive emotional states among
team members than transactional ones, and that such positive affect is funda-
mental to building resilience in a crisis. This study’s findings thus add to the
growing body of positive organizational scholarship, which examines how
positive leadership and organizing are fostered (Bakker & Schaufeli, 2008).
Such positive processes and organizational dynamics are important for moti-
vating people to perform and thrive (Weick, 2003). We showed that, even in
a crisis where lives were at stake, positive emotions can emerge and have
important outcomes for individuals and teams. Therefore, this study has
helped us understand how and why some teams can rise to the challenge of a
crisis and the role of the leaders in helping them do so. In our complex and
unstable world, we believe that this insight and knowledge are very valuable
to organizations in any field.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
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25. Sommer et al. 25
Funding
The author(s) disclosed receipt of the following financial support for the research,
authorship, and/or publication of this article: This study was partially funded by a
doctoral fellowship from the Social Sciences and Humanities Research Council of
Canada (SSHRC) awarded to Amy Sommer, a standard research grant from SSHRC
(410-2006-1896) awarded to Jane Howell, and HEC Paris.
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Author Biographies
S. Amy Sommer is an Assistant Professor at HEC Paris, School of Management in
France (PhD, Ivey Business School at Western University; Post Doctoral Fellowship
Harvard University). Dr. Sommer’s research interests include how organizational cri-
sis and temporal dynamics influence teams and leaders to foster resilience, adaptation,
and creativity.
Jane M. Howell is a Professor at Ivey Business School at Western University in
Canada (PhD, University of British Columbia) and holds the J. Allyn Taylor & Arthur
H. Mingay Chair in Leadership. Dr. Howell’s research interests include high perform-
ing leaders, teams, and organizations, and champions of innovation.
Constance Noonan Hadley is a Research Assistant Professor at the State University
of New York at Stony Brook in the United States (PhD, Harvard University; MBA,
Wharton School at University of Pennsylvania). Dr. Hadley’s research interests
include crisis leadership, emotions in organizations, work engagement, and group
behavior.
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