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Received: 18 September 2023
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Revised: 10 September 2024
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Accepted: 3 October 2024
DOI: 10.1111/1468-5973.70001
ORIGINAL ARTICLE
Reimagining crisis management with an organizational
learning framework
Erika J. Schneider
Public Relations Department, S.I. Newhouse
School of Public Communications, Syracuse
University, Syracuse, USA
Correspondence
Erika J. Schneider, S.I. Public Relations
Department, Newhouse School of Public
Communications, Syracuse University,
Syracuse, NY, USA.
Email: eschne03@syr.edu
Funding information
None
Abstract
Technological advancements have altered the landscape of crisis management,
making many crises potentially preventable and controllable. Moreover, these
technological advancements have provided opportunities for organizations to
implement an informed learning approach in crisis responses. The interconnected-
ness and complementary aspects of three theories within crisis management,
including the situational crisis communication theory's base crisis response strate-
gies, image repair theory's corrective action, and discourse of renewal theory's
organizational learning, were assessed and integrated into a proposed framework for
understanding a comprehensive approach to crisis management. In this research,
technology is regarded as both an asset for facilitating organizational learning (e.g.,
informed decision‐making through data analytics), and a potential source of
challenges in crisis communication (e.g., Zoombombing and negative social amplifi-
cation). The proposed framework aims to bridge proactive risk and reactive
crisis management efforts through organizational learning. Findings from this 4 × 2
between‐subjects experimental design study explore the effectiveness of organi-
zational learning to address crisis responsibility in an evolving technological
landscape.
KEYWORDS
attribution, crisis management, organizational learning, stakeholder perceptions
1|INTRODUCTION
In the past, a crisis might have been called a coincidence or bad luck,
but advancements in technology, such as artificial intelligence that
enable precise monitoring, provide professionals with an under-
standing of what factors contribute to an adverse event. Since a crisis
is a manifested risk, this research proposes a framework that en-
courages informed decision‐making in public relations practices
through organizational learning. The framework strategies address an
obligation to identify organizational vulnerabilities and prioritize
stakeholder wellbeing, given stakeholder expectations to prevent
crises. As advancements in technologies make organizations capable
of mitigating risks, this research reevaluates the concept of crisis
responsibility provided the new realities of stakeholder expectations.
Derived from crisis and disaster management literature, the
proposed framework includes a time‐delineated response applying
the situational crisis communication theory's (SCCT) base crisis
response (Coombs, 2015), image restoration (IRT) (Benoit, 1995), and
organizational learning, rooted in the discourse of renewal theory
(DOR) (Ulmer et al., 2019). Previous research has differentiated the
J. Contingencies Crisis Manag. 2024;32:e70001. wileyonlinelibrary.com/journal/jccm
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https://doi.org/10.1111/1468-5973.70001
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© 2024 The Author(s). Journal of Contingencies and Crisis Management published by John Wiley & Sons Ltd.
retrospective aspects of SCCT and the prospective vision of DRT in
crisis management (Soares, 2022), addressing how each framework
offers guidance within different crisis phases. This study evaluates
their synergy, backed by empirical data, to assess how stakeholders
respond to an integrated framework. The study presents an ex-
plication and exploratory application of an organizational learning
framework to gain deeper insight into gain deeper insights into the
crisis lifecycle. This research emphasizes the importance of under-
standing appropriate levels of crisis responsibility, as evolutions in
identifying threats have influenced a better understanding of the
nature and contributing factors of a crisis. The purpose of this ex-
ploratory study is to probe the effectiveness of the framework
strategies, compared with matched reputation responses. Findings
provide scholars and professionals with an understanding of how
stakeholders respond to the organizational learning framework and
considers a reconceptualization of crisis management.
2|LITERATURE REVIEW
2.1 |Crisis management
A crisis is conventionally known as a sudden, unpredictable event
that threatens important stakeholder expectancies (Coombs, 2015).
The inherent uncertainty surrounding a situation, such as the cause,
the extent of the damage, and the duration, creates a need for
communication with the public to adequately address those affected
and reduce uncertainty, which is a stressful and uncomfortable state
(Reynolds & Seeger, 2005). Crises can be induced intentionally or
unintentionally and result from a vulnerability or weakness that
went misinterpreted, underestimated, neglected, or ignored by an
organization (Coombs, 2015; Williams et al., 2017). Previous under-
standings of a crisis emphasize the uncontrollable and unpredictable
nature because, in the absence of modern technology, it was chal-
lenging to identify contributing factors. However, with advance-
ments, technology has provided the tools and insights that allow for
organizational learning, which ultimately reshapes an organization's
responsibility to respond to a crisis. Research has investigated how
artificial intelligence, for instance, can be used to inform organiza-
tional learning by revising or creating new processes that strengthen
an organization (Hendriks et al., 2023; Jarrahi et al., 2023). Zhang
et al.'s (2023) research advises that managers be open to acquiring
technology and knowledge for innovation through organizational
learning. While organizational learning has been investigated as a
business strategy, there is an opportunity to apply the concept within
a crisis management framework.
Technology can serve to assist organizational learning, but it can
also be the catalyst for exacerbating crises in the digital age. For
instance, the phenomenon of Zoombombing exemplifies how the
inherent vulnerabilities of digital platforms like video‐conferencing
applications can be exploited. Zoombombing involves third parties
disrupting Zoom meetings with unsettling material, such as deroga-
tory videos and xenophobic language, which can have psychological
and emotional impacts on meeting attendees. This form of cyber
intrusion demonstrates how the ease of access and anonymity af-
forded by technology can be used by malicious actors to inflict harm
on unsuspecting organizations. Zoombombing incidents through
social media can amplify the trauma experienced by victims and
tarnish the reputation of affected organizations. Thus, while digital
technology offers opportunities for connectivity, it also poses sig-
nificant risks, emphasizing the importance of understanding how
technology both assists and complicates crisis management efforts.
2.2 |Attribution of crisis responsibility
Attribution, which is a causal explanation for an event, plays a focal
role in crisis communication. When an adverse event occurs,
Weiner's (1985) attribution theory describes how individuals evaluate
the cause along the dimensions of locus of causality, controllability,
and stability. Attribution theory asserts that individuals will be mo-
tivated to search for answers if a disturbance is important,
unexpected, and negative (Weiner, 1995). The theory is applied in
SCCT's organizational context by including that if the locus is external,
unstable, and uncontrollable, the organization has little attribution of
crisis responsibility (Coombs, 2007a). SCCT is a prescriptive theory
that matches the crisis type (e.g., victim, accidental, preventable) based
on perceived attributions of crisis responsibility to organizational
responses (Coombs, 2007b). When there are minimal attributions of
responsibility, such as natural disasters, it can be considered a victim
crisis. The preventable cluster, such as human errors that cause
accidents, includes high attributions of crisis responsibility with strat-
egies from the rebuilding posture. The reputation responses provide a
generalizable guideline for practitioners to adopt; however, mis-
interpreting crisis responsibility can generate issues when responsi-
bility is incorrectly attributed. While this approach has been effective
in many cases, the evolving technological landscape challenges tradi-
tional notions of crisis attribution, as the emergence of artificial
intelligence and advanced monitoring systems create expectations of
prevention and mitigation. For instance, Tu et al. (2021)sharethat
during CSR crises, firms tend to attribute less responsibility to the
organization than consumers, externalizing responsibility and re-
sponding with strategies like diminishment or denial rather than
responses within the preventable cluster. As technology enables
organizations to better predict and understand the cause(s) of a crisis,
it may contribute to stakeholder expectations to use AI tools and
management systems so crises are mitigated or avoided.
2.3 |Crisis management
The effects of crisis response strategies have been thoroughly
investigated in crisis communication literature and follow the
assumption that responses shape how stakeholders view an organi-
zation (Coombs & Holladay, 1996). Guided by the key premise of
neo‐institutionalism, the assumption advocates for organizations to
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conform to social rules within the external institutional environment
(Fredriksson et al., 2013). Coombs and Holladay's (1996) approach to
public relations understands the violation of norms as a threat to
reputation. Scholars have applied SCCT to investigate the matched
content strategies, spokespersons, dissemination platforms, message
timing, and other variables (e.g., Arpan & Pompper, 2003; Boman
et al., 2023). Although protecting the public may be implied in liter-
ature, the base response is not always applied in crisis communication
scholarship (e.g., Verhoeven et al., 2012).
2.4 |Framework response strategies
Guided by the definition of a crisis as a manifested risk, a framework
composed of three strategies driven by literature was developed to
address ethical considerations in the modern crisis landscape: base
response, corrective action, and organizational learning. The three
layers provide time‐delineated strategies that may be applied
in situations outlined in Table C1. Prior research has distinguished
SCCT and DRT to identify the retrospective and prospective ap-
proaches to crisis management (Soares, 2022), and each theory
presents response strategies within different phases of the crisis
lifecycle. The selected concepts address different stages of crisis
management and align with established theories in crisis management
literature. For instance, Coombs (2007b) emphasizes the importance
of base crisis response to provide critical information to stakeholders
during the onset of a crisis. Similarly, Benoit's IRT addresses correc-
tive action, focusing on correcting issues that directly caused the
crisis and limit the impact of the situation. Organizational learning
underscores the importance of continuous improvement and adap-
tation to institute new measures within the risk management phase.
This research evaluates the complementary aspects of the strategies,
which have been individually supported in empirical research, to offer
a robust foundation for addressing ethical considerations in the
modern crisis landscape (e.g., Cheng, 2018). Prior research within
SCCT, IRT, and DOR provide evidence for the effectiveness of base
crisis response, corrective action, and organizational learning,
respectively, and assessing the strategies in an integrated framework
provides the opportunity to assess how each serves stakeholders
within the crisis lifecycle. This study tests the comparative value of
the crisis communication strategies based on neoinstituionalism to
understand the role of protecting stakeholders during a crisis.
2.4.1 |Base crisis response
When a crisis occurs, organizations must compose a base crisis response,
including instructing and adjusting information (Coombs, 2007b). As
crises result from a manifested risk and can have negative impacts on
stakeholders, it is an organization's responsibility to help protect stake-
holders' wellbeing (Lie & Servaes, 2015). This includes providing infor-
mation that instructs how to protect a stakeholder's physical safety, such
as sheltering‐in‐place, and adjusting information, which provides
communication that assists with psychological coping (Coombs, 2015).
Claeys and Coombs (2019) share how organizations should respond to
crises with the ethical base response, involving informing stakeholders
how to protect themselves physically and psychologically. Slagle et al.
(2021) investigate the base ethical response and note that including
corrective action within adjusting information may pose challenges
considering the time involved in understanding the cause of the crisis.
2.4.2 |Corrective action
Benoit (1995) developed image restoration theory (IRT) in an effort to
provide organizations with strategies to recover from the damage left in
thewakeofacrisis.Ofthestrategies,correctiveactionaddresseshow
an organization can correct a problem to prevent a similar event from
happening in the future (Benoit, 1995). Sellnow et al. (1998)describe
instances where this involvement contributes to positive perceptions of
the organization. Corrective action addresses the specific factors that the
organization did or did not perform that contributed to the effects of the
crisis felt by stakeholders. Benoit's (1995) image repair strategy of cor-
rective action is one of five crisis responses, with others being denial,
evasion of responsibility, mortification, and reducing offensiveness.
Caldiero et al.'s (2009) found corrective action to be the most widely
used IRT strategy to fraud‐related and mismanagement crises, which
emphasizes the need for changes to prevent similar crises from emer-
ging. Early iterations of SCCT termed corrective action as rectification in
the form of a mortification crisis response strategy (Coombs, 1995), and
itwasthenlistedasanaccommodativestrategyandanalyzedasa
response strategy independent of adjusting information in crisis com-
munication research (Coombs, 1998;Coombs&Schmidt,2000;Kim&
Yang, 2009). Many of IRT's response strategies are applied in SCCT crisis
response strategies (e.g., denial, attack accuser, compensation), yet later
SCCT research identified corrective action as a component of instructing
information or adjusting information rather than an independent crisis
response strategy (Coombs, 2006).Thebaseresponseshouldbedis-
seminated immediately and since understanding the cause may take
time,Slagleetal.(2021)add,“discussing corrective action (as part of
adjusting information) is not advised until the cause is known”(p. 659).
There has been a noted discrepancy in the timing of the strategy in IRT
and SCCT research (Zhang & Zhou, 2020) and researchers have invested
in understanding the effectiveness of corrective action as a crisis
response strategy outside of SCCT's base response (e.g., Jin et al., 2020;
Langaro et al., 2024).
2.4.3 |Organizational learning
This strategy, driven by the discourse of renewal (DOR) theory, ap-
proaches a crisis as an opportunity to adjust values and procedures
(Ulmer et al., 2019). DOR advises organizational rhetoric that promotes
ethical considerations and optimism for positive change. Literature
from management sciences supplements research on how organiza-
tional learning can contribute to not only survival but also a competitive
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advantage (Odor, 2017) that strengthens operations by acquiring and
using competencies for changing at the individual and collective levels
(Fiol & Lyles, 1985). For organizations to cope with future challenges,
learning involves initiating a process of identifying, acquiring, devel-
oping, mastering, retaining, managing, evaluating, and improving rele-
vant individual and organizational competencies (Jones & Pfeiffer,
1976). Discourse of renewal research emphasizes relationships to
support stakeholders, and the essence of this approach is that crisis
communication should prioritize ethical communication with forward‐
looking perspectives (du Plessis, 2018; Ulmer et al., 2019;Xu,2018).
Prior crisis communication research has called for studies that apply
DOR to understand how ethical communication strategies can be used
to effectively support stakeholders during a crisis (du Plessis, 2018).
Zhao et al. (2020) add that DOR relies on ethical communication
before, during, and after a crisis, and communicating organizational
changes allows an ethical response to potential crises in the future.
3|STAKEHOLDER RESPONSE
3.1 |Negative perceptions
Crises are socially constructed and emerge when an organization vio-
lates stakeholder expectancies that create negative affect (Estes, 1983).
Coombs and Tachkova's (2019) analysis of scansis, which is the inter-
section of a crisis and scandal, understands how elements of crisis
produce predictable emotions, such as moral outrage and anger. Anger,
for instance, may be arrived at through thoughts that are capable of
producing emotion (Lazarus, 1991). Crises can produce anger in sta-
keholders because they experience an undesirable outcome that could
have been controlled by some actor (Coombs & Tachkova, 2019).
Coombs and Holladay (2007) add that when attributions of crisis
responsibility are high, the event will produce more anger, and that
anger can cause resistance or backlash that translates emotion into
behavior (Watson & Spence, 2007). Moral outrage was found to occur
when participants perceived greed by the organization and unfair
corporate behavior (Antonetti & Maklan, 2016). To evaluate the effects
of the proposed framework on anger and moral outrage, the following
research questions are proposed:
RQ1. How do framework responses to a victim crisis compare
with the matched reputational response on (a)anger and (b)
moral outrage?
RQ2. How do the framework responses to a preventable crisis
compare with the matched reputational response on (a)anger
and (b)moral outrage?
3.2 |Organizational reputation
Since the early 1990s, crisis communication scholars have examined
the conditions in which communication may be used to protect
organizational reputation (Coombs & Holladay, 1996). Reputation is
recognized as an intangible asset to be monitored and protected
(Davies et al., 2005), which can help attract employees and customers
and increase investor confidence (Fombrun & van Riel, 1997).
Coombs and Tachkova's (2019) study found that corrective action
and moral recognition lowered anger and moral outrage, but they did
not find significant impacts on reputation; thus, the following
research questions are posed:
RQ3. How do framework responses to a victim crisis compare
with the matched reputational response on reputation?
RQ4. How do the framework responses to a preventable crisis
compare with the matched reputational response on reputation?
3.3 |Social amplification
As crises involve uncertainty and can threaten public safety,
organizations must use communication platforms that expeditiously
distribute crisis responses, which can contain life‐saving informa-
tion. As social media allows professionals to provide prompt
responses, this speed can also work against organizations as it
may accelerate negative interactions. The social‐mediated crisis
communication model brought an opportunity for scholars to
understand the facilitation of crisis communication on social media
(Jin et al., 2014;Liuetal.,2020). The model recognizes that online
platforms provide an opportunity for organizations to cultivate
stakeholder relationships, inform their audiences, and monitor
crises online. However, users on these platforms can also foster
negative interactions that make it difficult for an organization to
regain control of (Lim, 2017). In essence, social amplification
involves interactions that increase the relevance of the message for
others, which further contributes to the spread (Strekalova, 2017).
To assess how the framework strategies influence intentions to
negatively amplify the message on social media, the following
research questions are posed:
RQ5. How do the framework responses to a victim crisis
compare with the matched reputational response on negative
social amplification?
RQ6. How do the framework responses to a preventable crisis
compare with the matched reputational response on negative
social amplification?
3.4 |The mediating role of organizational learning
Organizational learning is a concept that illustrates how newly gained
knowledge can become a catalyst for improvements by acquiring new
and relevant capacities and skills (Edmondson, 1999; Kale
et al., 2000). Technology can facilitate this process by using digital
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tools to analyze data that informs decisions, similar to management
practices approach through an R&D process (Carmona‐Lavado
et al., 2021; O'Connor et al., 2008; Zhang et al., 2023). Using tech-
nology to overcome challenges through innovation has been studied
as an investment that allows a company to reduce uncertainty and
inform risk management practices (O'Connor et al., 2008). Jarrahi
et al. (2023) argue that AI can be used to facilitate the organizational
learning process, but only realized in partnership with humans. Obeso
et al. (2020) found organizational learning to mediate the relationship
between performance and knowledge management practices, such as
generating new or innovative ideas. Practical implications suggest
that managers should invest in a commitment to promote a shared
vision, culture, and open‐mindedness when it comes to new ideas.
Jain and Moreno (2015) add that literature within organizational
learning, which they refer to as a process of creation and integration
of knowledge, provides “a bridge between the cultivation of knowl-
edge and the organization's effectiveness”(p. 18). Organizational
learning has been found to mediate the relationship of knowledge
management processes and operational performance (Jaber &
Caglar, 2017). Within crisis communication, there remains an
opportunity to explore the mediating role of the organization learning
on organization reputation, and the following research question is
posed:
RQ7. Does organizational learning mediate the relationship
between the conditions on reputation?
4|METHOD
To examine the proposed research questions, a 4 × 2 between‐
subjects experimental design survey was developed with the fol-
lowing conditions: base crisis response; base response with correc-
tive action; base with corrective action and organizational learning;
matched reputational response. Participants were randomly assigned
one of four response messages, to a victim crisis or a preventable
crisis. After receiving the response, feelings of anger, moral outrage,
perceptions of reputation, organizational learning, and social ampli-
fication were measured. An a priori G*Power analysis was conducted,
using estimations of effect sizes (0.25) from prior crisis communica-
tion studies to determine a sample size (Xu, 2020). There were
450 participants were recruited through Amazon's Mechanical Turk.
After removing four participant responses that indicated straightlin-
ing, the final sample size was 446, with 223 participants receiving the
victim crisis and 223 receiving the preventable. There were 53–60
participants per response condition and the Tukey‐Kramer method
was used to provide conservative estimates to account for unequal
sample sizes (Gupta, 2015; Oehlert, 2010). The sample included
56.05% (n= 250) males, 43.27% (n= 193) females, and 0.01% (n=3)
participants who preferred not to share. The average age was
37.72 years old, and they were majority white (72.65%, n= 324) and
married (58.97%, n= 263) with a Bachelor's degree (50.22%, n= 224)
(Table C2).
4.1 |Manipulations
A fictitious higher education organization was utilized with stimuli
based on real crisis scenarios to increase ecological validity. A victim
crisis, which is indicated by lower perceptions of crisis responsibility,
and a preventable crisis, indicated by greater perceptions of crisis
responsibility, were selected to examine how varying levels of
responsibility influence perceptions and the effectiveness of organi-
zational learning framework strategies. The framework response
strategies detailed below consist of three components: the base
response (i.e., instructing and adjusting information), corrective action
(i.e., addressing causes and containment), and organizational learning
(i.e., commitment to ongoing improvement). These manipulations
were developed to explore the effects of the framework in varied
crisis contexts. The manipulations can be found in Supporting Infor-
mation S1: Appendix Aand the results of the manipulation cheques is
reported below.
4.2 |The victim crisis
Zoom has played a significant role in connecting the world during and
after the COVID‐19 pandemic (Bond, 2020). The victim crisis in this
experiment involved students being exposed to derogatory videos
and hateful language when a Zoombomber took over screen‐sharing
capabilities, illustrating external, uncontrollable, and unstable aspects
that assist in classifying the incident as a victim crisis (Coombs &
Holladay, 2002).
4.3 |The preventable crisis
In the early 2020s, issues of xenophobia emerged as disinformed
headlines in the US promoted fear that contributed to discrimination
and normalized racism (Noel, 2020). Although Zoom enabled virtual
meetings, it also facilitated issues like discrimination, which mani-
fested in aspects like student–instructor interactions. The prevent-
able crisis in this experiment involved a college instructor exhibiting
discriminatory behavior toward a group of Asian students during a
course facilitated over Zoom, which is a human error that violated
student expectations by disrupting the learning environment.
4.4 |Framework response strategies
The framework strategies include a three‐part response (i.e., base,
corrective action, organizational learning). The base crisis response
included instructing and adjusting information (Coombs, 2015). After
the base response, participants in the corrective action condition also
received information about the specific processes that contributed to
the event and a solution to prevent it from continuing (Benoit, 1995).
Participants in the organizational learning condition received the base
response, corrective action, and then a response that reflected a
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systematic commitment to ongoing learning that promotes positive
change (Jones & Pfeiffer, 1976;Odor,2017). The reputation responses
were developed from SCCT by providing an apology to the preventable
crisis and a scapegoat/denial response to the victim crisis.
4.5 |Measurements
The following measures, all measured with 7‐point Likert‐type scales,
were adapted from previous research in crisis communication and
can be found in Supporting Information S1: Appendix B.
4.6 |Anger and moral outrage
Anger toward the organization was measured using Coombs and
Holladay's (2007) measure. Three items were used to measure anger
(e.g., “Because of the incident, I feel angry at Chicago College)
(M= 3.46, SD = 1.79, α= .81). Moral outrage was measured using a
three‐item scale used in prior crisis communication studies (e.g.,
Coombs & Tachkova, 2019), adapted from Antonetti and Maklan's
(2016) research. The questions asked participants to indicate
the degree they felt angered, outraged, and mad as a result of reading
the organization's response (M= 3.66, SD = 2.08, α= .96).
4.7 |Organizational reputation
Reputation was assessed using a five‐item reputation scale (Coombs
& Holladay, 2002), with statements such as “The organization is
concerned with the wellbeing of its publics”(M= 5.26, SD = 1.25,
α= .92).
4.8 |Negative social amplification
To measure negative social amplification, participants were asked
how likely they were to negatively engage with the message on a
7‐point Likert scale with the item, “How likely is it that you would
negatively react to the message on Facebook?”(Barger et al., 2016;
M= 3.43, SD = 1.90).
4.9 |Organizational learning
Organizational learning was measured with two items initially deve-
loped by Kale et al. (2000) and two items from Edmondson's (1999)
study on learning behavior. This measure has been applied in com-
munication studies and has been found to be unidimensional with
adequate reliability and validity (García‐Morales et al., 2012). Orga-
nizational learning was measured with statements such as, “At Chi-
cago College, newly gained knowledge influences improvements”
(M= 5.46, SD = 1.14, α= .83).
4.10 |Manipulation cheques
A pretest with 40 participants was performed to assess perceptions
of the manipulations, which is a practice utilized in communication
research (e.g., Hong & Cameron, 2018; Tao, 2023). This is an effec-
tive validation method that shortened the length of the main survey
to reduce participant fatigue (Hauser et al., 2018). To prevent car-
ryover effects, participants from the pretest were not included in the
main experiment by excluding identification numbers from being
eligible for participation. Pretest participants were asked to share
perceptions of four fictitious institution names and logos. Since fic-
titious organizations may still be mistakenly recognized or associated
with real organizations, which is a potential confound, the pretest
determined which organization was perceived most neutral (1 = very
unfavorable,7=very favorable). If participants did not have an opinion,
they were directed to select “Neutral”(4). Of the four colleges and
universities, Chicago College was rated the most neutral (M=4,
SD = 0), followed by West Metro University (M= 3.62, SD = 0.74),
Texas Central University (M= 3.25, SD = 1.08), and Ohio College
(M= 3.17, SD = 1.11). All participants in the sample rated Chicago
College neutral; thus, it was the college name and logo utilized in the
main experiment. Participants then received a message about a col-
lege experiencing the victim or preventable crisis, and asked about
their perceptions of crisis responsibility, followed by the response
strategies.
Five manipulation cheques were created to correspond with
each dimension of the response manipulations and a series of one‐
way analysis of variances (ANOVAs) were performed. To assess
perceptions of the base response, participants were asked to rate the
extent they agree or disagree with the statement, “After reading
the message, the students know what they can do to protect them-
selves.”An ANOVA found significant differences between conditions
(F(3, 36) = 69.38, p< .001), with the base response accurately
perceived (M= 6.60, SD = 0.52). To assess corrective action, the
following statement was provided: “I know what Chicago College is
doing about this specific situation to prevent the event from hap-
pening again.”An ANOVA was performed and found significant
differences between conditions (F(3, 36) = 98.65, p< .001), with cor-
rective action accurately perceived (M= 6.50, SD = 0.53). For orga-
nizational learning, the statement said, “I feel like Chicago College is
committed to ongoing learning to promote positive change.”An
ANOVA was performed and found significant differences between
conditions (F(3, 36) = 97.55, p< .001), with organizational learning
being accurately perceived (M= 6.51, SD = 0.52). The measure for the
preventable matched response, which was an apology, stated, “I feel
like Chicago College apologized for the incident,”and the victim
matched response, which was scapegoating, stated, “I feel like Chi-
cago College blamed the incident on something else.”An ANOVA
was performed to assess the preventable response and the differ-
ences were not significant between conditions (F(3, 36) = 1.49,
p= .20), although the matched apology response was perceived
highest. The apology was adjusted to make the apology clearer (i.e.,
directly stating “we apologize”). For the matched victim response,
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which was a scapegoating strategy, an ANOVA found statistically
significant differences between conditions (F(3, 36) = 100.5, p< .001),
with participants perceiving the scapegoating strategy the highest in
blaming something else for the incident (M= 6.33, SD = 0.48). Per-
ceptions of crisis responsibility, measured using a three‐item scale
(Coombs & Holladay, 1996;α= .81), found that perceptions were
relatively low for the victim crisis (M= 3.02, SD = 0.20) and higher for
the preventable crisis (M= 6.23, SD = 0.11). With the exception of
modifying the apology, the manipulation cheques confirmed per-
ceptions of the stimuli.
5|RESULTS
Analyses were conducted using the R programming language in R
Studio, a software environment for statistical computing (R Core
Team, 2023; R Studio Team, 2020). Research questions 1‐6 were
analyzed with ANOVAs, and the Tukey‐Kramer test was used for
comparisons since sample sizes varied (Salkind, 2007). A post hoc
G*Power 3.1 analysis was conducted, and analyses related to the
preventable crisis surpassed a power of 99%, which confirmed the
adequacy of the sample size. For the victim crisis, three effect sizes
ranged from 0.1 to 0.3 with nonsignificant p‐values.
To assess if organizational learning mediates the relationship
between the conditions on reputation, a mediation analysis was
conducted to detect interactions. The analyses served as an ex-
ploratory process of probing the effects of the organizational learning
framework. Testing the assumption for homogeneity of variance,
Levene's tests for each analysis were not significant, indicating rea-
sonable normality and the assumptions were not violated. Full results
can be found in Appendix C.
To answer the first research question, an ANOVA was conducted
to assess the differences in anger between organizational learning
and reputation responses to a victim crisis. No statistically significant
differences were found among the response strategies regarding
anger (F(3, 219) = 1.88, p= .14, η
2
= 0.02). Similarly, an ANOVA was
employed to examine the impact of different strategies on moral
outrage during a victim crisis. Although differences were again found,
the results were not statistically significant (F(3, 219) = 0.74, p= .52,
η
2
= 0.02).
When assessing responses to a preventable crisis, an ANOVA
revealed statistically significant differences in anger levels between
the conditions (F(3, 219) = 9.55, p< .001, η
2
= 0.08). Participants ex-
pressed the most anger after receiving the base response, followed
by the reputation response, the base+corrective action, and the full
learning response. Comparisons of moral outrage in preventable crisis
scenarios also yielded statistically significant differences (F(3,
219) = 6.28, p< .001, η
2
= 0.08). The base response resulted in the
highest levels of moral outrage, followed by the reputation response.
Assessing the effects on reputation in a victim crisis, an ANOVA
was conducted, approaching statistical significance (F(3, 219) = 2.30,
p= .07, η
2
= 0.03). Participants receiving the full learning strategy
perceived the highest reputation, followed by the base+corrective,
the reputation response, and the base response. For preventable
crisis scenarios, an ANOVA revealed statistically significant differ-
ences in reputation among the conditions (F(3, 219) = 6.25, p< .001,
η
2
= 0.08). Participants receiving the base+corrective strategy per-
ceived the highest reputation, followed by the full learning strategy,
reputation response, and the base response.
To explore intentions to negatively interact with posts on social
media during a victim crisis, an ANOVA was conducted, but no sta-
tistically significant differences were found (F(3, 219) = 0.90, p= .44,
η
2
= 0.01). For preventable crisis scenarios, an ANOVA was con-
ducted to assess differences in social amplification. Statistically sig-
nificant differences were observed (F(3, 219) = 5.99, p< .001,
η
2
= 0.08), with participants in the base response condition indicating
the highest intention to amplify the message negatively on social
media, followed by the reputation strategy, the base+corrective, and
the learning response.
To answer the last research question, which asked if organiza-
tional learning mediates the relationship between the conditions on
reputation, a regression model was fit for the path between each of
the conditions on organizational learning. For the victim crisis, the
learning condition was found to significantly influence the mediator.
The reputation condition yielded a negative coefficient for the
mediator, but only approached conventional levels of statistical sig-
nificance. A second model was fit to assess the effect of the mediator
(i.e., on organizational learning) on reputation, the dependent varia-
ble, and the effect of the full response on the outcome when con-
trolling for the mediator. Organizational learning was found to be
significantly associated with reputation. The effect of the learning
condition on the outcome when controlling for the mediator was not
significant, meaning there was no residual effect. To assess if the
learning condition had an indirect effect on reputation through its
effect on organizational learning, a causal mediation analysis was
conducted using Tingley et al.'s (2014) mediation package in R Studio.
The simulations ran at 10,000 bootstraps and the average causal
mediation effect (ACME) was estimated at 0.30, meaning that with
the average effect observed, the effect of the learning condition on
reputation through organizational learning was estimated at 0.30,
which is a small effect. The lower (0.03) and the upper boundary
(0.54) of the confidence intervals were entirely above zero, which
was loosely interpreted to mean there was 95% confidence that the
true value of the indirect effect was not zero, rejecting the null. The
effect ranged fairly small (0.09–0.30), and the estimate is not very
precise. Ultimately, an indirect effect of the learning condition on
reputation through organizational learning was found, but a direct
effect was not significant. A sensitivity analysis was conducted to
address unobserved variable bias, or if the mediator and dependent
variable have an unexplained variance that is highly correlated, which
would suggest an element unaccounted for that unites the variables.
A sensitivity analysis was conducted using Imai et al.'s (2010) pro-
cedure and guidelines found the indirect effect on reputation was
robust (ρ= 0.68), which is above the 0.20 guideline for a robust
mediation. This procedure was repeated for each condition and
results can be found in Table C17. The organizational learning
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condition was the only condition to meet the threshold for 95%
confidence.
This was repeated for the responses to the preventable crisis.
Organizational learning was significantly associated with reputation
(p< .001), meaning participants had greater perceptions of reputation
as they perceived organizational learning (0.78). The ACME was es-
timated at 0.30, which was a small effect. With the lower (0.03) and
the upper boundary (0.46) entirely above zero, there was 95% con-
fidence that the true value of the indirect effect is not zero, rejecting
the null. The average direct effect was not significant (LLCI: −0.27,
ULCI: 0.17), indicating there was not a residual effect of the full
learning condition on reputation after accounting for organizational
learning. The total effect was also not significant (LLCI: −0.12, ULCI:
0.51), indicating the effect did not show up as an independent direct
effect. Sensitivity analyses were conducted and found the indirect
effect on reputation was robust (ρ= 0.69). The learning and reputa-
tion conditions were the only conditions to meet the thresholds for
95% confidence.
6|DISCUSSION
In light of the emerging challenges faced by crisis and risk commu-
nicators, findings provide insight into a learning approach to crisis
management that integrates of strategies to connect the crisis life-
cycle. SCCT contributes the base crisis response strategies which
provide guidance for protecting stakeholders' physical and psycho-
logical wellbeing, corrective action from IRT shares retrospective
guidance with direct changes to prevent the situation from worsen-
ing, and organization learning from DRT shares the prospective vision
connecting postcrisis outcomes into risk management procedures.
The organizational learning approach addresses how crisis responsi-
bility can be used to address contributing factors and satisfy stake-
holders. In essence, this research contributes to the ongoing
discourse on crisis management in the context of emerging tech-
nologies, emphasizing a shift in crisis management paradigms to
adapt to an evolving technological landscape. This study acknowl-
edges technology as an asset in facilitating organizational learning,
and also acknowledging the role of technology in creating challenges
in crisis communication, as evidenced by occurrences like Zoom-
bombing. Driven by crisis and disaster communication literature, the
framework proposes time‐delineated strategies to address vulner-
abilities that prevent future crises, illustrating a symbiotic relationship
between risk and crisis communication. This experiment found that in
some cases, the organizational learning framework was compara-
tively more effective in satisfying stakeholders, than reputation
response strategies.
The study findings contribute to crisis communication literature
by offering empirical support for the effectiveness of organizational
learning in the crisis lifecycle. By validating the practical application of
the framework's three layers—base response, corrective action, and
organizational learning—the study enhances theoretical under-
standing of crisis management processes. The study's theoretical
contribution extends to its application of relevant theories, namely
SCCT, IRT, and DOR, to provide a theoretical foundation for under-
standing proactive and reactive responses and the cyclical nature of
crisis management. SCCT offers insights into how organizations can
effectively provide immediate information that protects stakeholders,
IRT complements SCCT by emphasizing the importance of corrective
action in mitigating the damage, and DOR underscores the value of
organizational learning in crisis contexts. The framework provides a
comprehensive approach to promote positive change in communi-
cation practices.
Organizational learning was illustrated by the organization
communicating its commitment to finding solutions, such as investing
in new policies, procedures, and training sessions. This involves a
learning approach to analyze and identify sustainable changes for
organizational improvement. Given technological advances, organi-
zational learning may be most effectively facilitated with the assist-
ance of artificial intelligence, as it allows deep learning systems, with
human feedback, to create or modify processes and procedures to
strengthen the organization (Jarrahi et al., 2023). Organizational
learning is a systematic commitment to an ongoing learning process
and provides the organization an opportunity to learn, with a sus-
tainable process that strengthens operations (Fiol & Lyles, 1985). This
process can include acquiring, retaining, and using competencies for
changing thinking and behaviors at the individual and collective lev-
els. Additionally, technology can enhance the organizational learning
process to assist in benchmarking, experimentation, or environmental
scanning. For instance, AI can identify vulnerabilities, VR simulations
can help with scenario planning, and knowledge management sys-
tems can streamline communication and promote a culture of con-
tinuous learning. While this experiment did not assess the different
forms and illustrations of organizational learning, professionals are
advised to integrate technology into the organizational learning
process to foster a dynamic and adaptive learning culture, which may
also translate into a competitive advantage. Emerging technologies
provide ways to analyze and track risks, which may affect stakeholder
expectations.
Crises are violations of stakeholder expectancies and can
generate negative emotions. Generally, the organizational learning
response was most effective at mitigating anger. Feelings of moral
outrage, which could be the result of stakeholders perceiving unfair
behavior, were generated the least in participants who received
the organizational learning response (Antonetti & Maklan, 2016).
The consequences of anger and moral outrage can be damaging to
organizations, such as stakeholders retaliating and boycotting
(Cronin et al., 2012). These results are consistent with Coombs and
Tachkova's (2019) study, which found that lower levels of moral
outrage were generated when an organization provided corrective
action and moral recognition when responding to a crisis that
involved a scandal.
Comparing the effects of the framework strategies with SCCT‐
matched strategies on reputation provides valuable insight into PR
scholarship. As the aim of the reputation management strategies is to
preserve reputation, findings illustrated, comparatively, the
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|
SCHNEIDER
framework was effective at protecting reputation. For the prevent-
able crisis, which had significant differences between conditions, the
base and corrective action response was most effective, followed by
organizational learning. Reputation is regarded as an intangible
investment to protect and can result in favorable outcomes like
attracting employees and customers (Davies et al., 2005). The effects
of the framework responses on reputation share an indication that
organizational learning may translate into positive perceptions,
although the results were not consistent across crisis types. For the
victim crisis, findings showing the framework response as more
effective approached significance.
Social media has impacted the lifespan of a crisis by increasing
the visibility of crisis messaging, and these findings illustrate the
extent of this process. To mitigate negative social media interactions,
organizations should prepare messaging to quickly respond and
prevent crisis escalation on social media, also referred to as “online
firestorms”(Lim, 2017). The framework responses to the preventable
and victim crisis resulted in the least intention for participants to
negatively interact with the message on social media, although
the differences between victim responses approached statistical
significance.
7|LIMITATIONS AND FUTURE
RESEARCH
An important limitation of the study is that the manipulation che-
ques were conducted in a pretest but not measured in the main
experiment, which reduces the ability to interpret the results. There
was an effort to reduce the length of the main survey to minimize
participant fatigue; however, employing manipulation cheques
within the main survey would add confidence in our understanding
of how participants perceived differences between conditions. This
experiment tested message manipulations of the base crisis
response, corrective action, and organization learning as crisis
management strategies. This study did not actually measure how an
organization corrected or adapted procedures over time, but pre-
sented statements, validated through manipulation cheques, that
stated how an organization responded. In practice, actions outlined
within an organizational response must be met with real action,
whichmaynotbefeasibleconsideringthecostsofresourcesand
expertise. Future research should investigate forms of organiza-
tional learning longitudinally and assess the timing of the response
postcrisis. Moreover, while this study focused on moral outrage and
anger as emotional responses, future research should consider
assessing emotions such as fright and sadness, which are commonly
associated with crisis situations, to provide a more comprehensive
understanding of stakeholder reactions. This experiment utilized
experiential learning, or drawing from an organization's own ex-
perience; however, organizational learning can occur experientially
or vicariously. Although crises expose organizational weaknesses
and vulnerabilities, organizational learning should not require a
crisis to stimulate.
8|CONCLUSION
Addressing a crisis as manifested risk is an approach that absorbs
crisis responsibility to develop stronger systems and practices, with
stakeholder wellbeing at the forefront. The organizational learning
framework reevaluates crisis responsibility by recognizing that
technology enables organizations to mitigate risks that have the
potential to manifest into a crisis. When there is a failure of mitiga-
tion, the framework strategies provide a time‐delineated response
that prioritizes public safety through instruction, correction, and a
commitment to changes in response to the exposed organizational
vulnerabilities. Findings promote a line of inquiry within public rela-
tions scholarship that invests in long‐term stakeholder relationships
while recognizing that crisis responsibility becomes even more
accountable in the context of emerging technological developments.
ACKNOWLEDGEMENTS
The author would like to acknowledge the support of Dr. Glen
Cameron and Dr. J. Brian Houston in conducting this research.
CONFLICT OF INTEREST STATEMENT
The author declares no conflict of interest and there are no funding
interests to disclose.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available on
request from the corresponding author. The data are not publicly
available due to privacy or ethical restrictions.
ORCID
Erika J. Schneider https://orcid.org/0000-0002-1799-9688
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SUPPORTING INFORMATION
Additional supporting information can be found online in the Sup-
porting Information section at the end of this article.
How to cite this article: Schneider, E. J. (2024). Reimagining
crisis management with an organizational learning framework.
Journal of Contingencies and Crisis Management,32, e70001.
https://doi.org/10.1111/1468-5973.70001
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TABLE C1 Conceptualization of the organizational learning framework.
Strategy Actions Proposed appropriate situations
Base Response Provide instructing and adjusting information Utilized as an immediate response after a crisis. Can be used as
a solo strategy if there is uncertainty about the cause or if there
are not resources available to investigate the cause.
Corrective Action Provide information that corrects the problem to
prevent a similar event
Utilized after the base crisis response when the cause of the
crisis is recognized. It involves addressing a specific product or
processes that directly contributed to the current crisis. It can
be used if the correction is feasible to execute.
Organizational
Learning
Provide a stated commitment to a learning process (e.g.,
benchmarking, experimentation, environmental
scanning)
Utilized after the base crisis response and corrective action. It
involves a systematic and expeditious commitment to an
ongoing learning process to promote positive change.
TABLE C2 Participant demographics.
n(%)
Gender
Female 193 (43.27%)
Male 250 (56.05%)
Prefer not to say 3 (0.01%)
Race
White or Caucasian 324 (72.65%)
Black or African
American
63 (14.13%)
Asian 49 (10.99%)
American Indian or
Alaska Native
5 (1.12%)
Other 4 (0.90%)
Native Hawaiian or
Pacific Islander
1 (0.22%)
Ethnicity
Spanish/Hispanic/
Latino
36 (8.07%)
Mexican/Mexican
American/Chicano
32 (7.17%)
Preferred not to say 7 (1.57%)
Cuban 4 (0.90%)
Age
Age (M= 37.72, SD = 10.74) 19–76 years old
Marital status
TABLE C2 (Continued)
n(%)
Married 263 (58.97%)
Never married 142 (31.84%)
Divorced 35 (7.85%)
Widowed 4 (0.90%)
Separated 2 (0.45%)
Highest level of education
Less than high school
degree
1 (0.22%)
High school diploma
or GED
25 (5.61%)
Some college, no
degree
49 (10.99%)
Associate degree or
equivalent
39 (8.74%)
Bachelor's degree 224 (50.22%)
Master's degree 96 (21.52%)
Doctorate degree 9 (2.02%)
Professional degree 3 (0.67%)
Household Income
Less than $29,999 55 (12.33%)
$30,000–$59,999 172 (28.57%)
$60,000–$99,999 151 (33.86%)
$100,000 or greater 68 (5.25%)
Note: Cells display counts of each category with percentages in
parentheses in the overall column, except for cells referred to age with the
mean, standard deviation, and the range.
APPENDIX C
Tables C1–C18
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TABLE C3 ANOVA comparisons of the strategies to a victim crisis on anger and moral outrage.
Condition nAnger M(SD) Moral outrage M(SD)
Base 55 3.59 (1.79) 3.60 (1.91)
Base + CorrectiveAction 55 2.95 (1.59) 3.25 (2.05)
Base + CorrectiveAction + OrgLearning 53 2.89 (1.87) 3.11 (2.11)
Reputation Response 60 3.01 (1.77) 3.56 (2.12)
Note: The ANOVAs in the table were not statistically significantly different. (Anger: p= .14; Moral Outrage: p= .61).
Abbreviation: ANOVA, analysis of variance.
TABLE C4 Multiple comparisons on anger during a victim crisis.
BCO compared to reputation response Difference between means (95% CI)
Base and Reputation −0.58 (−1.43 to 0.27)
Base + Corrective and Reputation 0.07 (−0.78 to 0.92)
Base + Corrective + OrgLearning and Reputation 0.12 (−0.78 to 0.92)
Abbreviation: CI, confidence interval.
TABLE C5 Multiple comparisons on moral outrage during a victim crisis.
BCO Conditions compared to Matched Condition Difference between means (95% CI)
Base and Reputation −0.04 (−1.03 to 0.94)
Base + Corrective and Reputation 0.30 (−0.69 to 1.29)
Base + Corrective + OrgLearning and Reputation 0.45 (−0.55 to 1.45)
Abbreviation: CI, confidence interval.
TABLE C6 ANOVA comparisons of the strategies to a preventable crisis on anger and moral outrage.
Condition n
Anger Moral Outrage
M(SD) M(SD)
Base 53 4.46 (1.64) 4.57 (2.04)
Base + CorrectiveAction 58 3.39 (1.68) 3.56 (2.06)
Base + CorrectiveAction + OrgLearning 55 3.11 (1.51) 3.18 (1.95)
Reputation Response 57 4.37 (1.73) 4.47 (2.02)
Note: The ANOVAs in the table were statistically significantly different. (Anger:p< .001; Moral Outrage: p< .001).
Abbreviation: ANOVA, analysis of variance.
TABLE C7 Multiple comparisons on anger during a preventable crisis.
BCO compared to Reputation response Difference between means (95% CI)
Base and Reputation −0.09 (−0.90 to 0.72)
Base + Corrective and Reputation 0.98 (0.12 to 1.78)*
Base + Corrective + OrgLearning and Reputation 1.26 (0.45 to 2.06)*
Abbreviation: CI, confidence interval.
*p< .01.
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TABLE C8 Multiple comparisons on moral outrage during a preventable crisis.
BCO compared to Reputation response
Difference between
means (95% CI)
Base and Reputation Response −0.09 (−1.09 to 0.91)
Base + Corrective and Reputation 0.91 (−0.06 to 1.89)
Base + Corrective + Org Learning and
Reputation
1.29 (0.30 to 2.28)*
Abbreviation: CI, confidence interval.
*p= .004.
TABLE C9 ANOVA comparisons of the strategies to the victim crisis on organizational reputation.
Organizational reputation
Condition nM(SD)
Base 55 5.06 (1.24)
Base + CorrectiveAction 53 5.50 (1.18)
Base + CorrectiveAction + Orglearning 55 5.52 (1.22)
Reputation Response 60 5.07 (1.37)
Note: The ANOVA on Organizational Reputation approached a conventional threshold of statistical significance (p= .07).
Abbreviation: ANOVA, analysis of variance.
T A B L E C10 Multiple comparisons on organizational reputation during a victim crisis.
BCO compared to Reputation response Difference between means (95% CI)
Base and Reputation response 0.01 (−0.60 to 0.62)
Base + Corrective and Reputation response −0.43 (−1.04 to 0.18)
Base + Corrective + Org Learning and Reputation −0.45 (−1.06 to 0.17)
Abbreviation: CI, confidence interval.
*p= .05.
T A B L E C11 ANOVA comparisons of the strategies to the preventable crisis on organizational reputation.
Organizational reputation
Condition nM(SD)
Base 53 4.69 (1.33)
Base + CorrectiveAction 58 5.59 (1.04)
Base + Corrective + OrgLearning 55 5.48 (1.03)
Reputation response 57 5.13 (1.35)
Note: The ANOVA on Organizational Reputation was statistically significantly different (p< .001).
Abbreviation: ANOVA, analysis of variance.
T A B L E C12 Multiple comparisons on organizational reputation during a preventable crisis.
BCO Conditions compared to Matched Condition Difference between means (95% CI)
Base and Reputation response 0.44 (−0.15 to 1.03)
Base + Corrective and Reputation response −0.46 (−1.04 to 0.12)
Base + Corrective + Org Learning and Reputation −0.35 (−0.93 to 0.23)
Abbreviation: CI, confidence interval.
*p= .05.
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T A B L E C13 ANOVA comparisons of the strategies to the victim crisis on negative social amplification.
Social amplification
Condition nM(SD)
Base 55 3.29 (1.75)
Base + CorrectiveAction 55 3.09 (1.88)
Base + CorrectiveAction + OrgLearning 53 2.91 (1.80)
Reputation response 60 3.45 (2.02)
Note: An ANOVA on Negative Social Amplification was not statistically significant (p= .44).
Abbreviation: ANOVA, analysis of variance.
T A B L E C14 Multiple comparisons on negative social amplification during a victim crisis.
BCO compared to Reputation response
Difference between
means (95% CI)
Base and Reputation 0.16 (−0.74 to 1.06)
Base + Corrective and Reputation 0.36 (−0.54 to 1.26)
Base + Corrective + OrgLearning and Reputation 0.54 (−0.37 to 1.46)
Abbreviation: CI, confidence interval.
*p= .05.
T A B L E C15 ANOVA comparisons of the strategies to the preventable crisis on negative social amplification.
Social amplification
Condition nM(SD)
Base 53 4.55 (1.94)
Base + CorrectiveAction 58 3.34 (2.20)
Base + CorrectiveAction + OrgLearning 55 3.05 (1.67)
Reputation response 57 3.77 (1.95)
Note: An ANOVA on Negative Social Amplification was statistically significantly different (p< .001).
Abbreviation: ANOVA, analysis of variance.
T A B L E C16 Multiple Comparisons on Negative Social Amplification during a Preventable Crisis.
BCO compared to Reputation response Difference between means (95% CI)
Base and Reputation response −0.78 (−1.74 to 0.19)
Base + Corrective and Reputation response 0.43 (−0.52 to 1.37)
Base + Corrective + Org Learning and Reputation 0.72 (−0.24 to 1.67)
Abbreviation: CI, confidence interval.
*p= .05.
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T A B L E C17 Indirect effects of message strategies on reputation through organizational learning during a victim crisis.
Average Causal Mediation Effect (ACME)
Coef. LLCI ULCI ρ
B‐> Learning ‐> Reputation −0.09 −0.37 0.16 0.68
BC ‐> Learning ‐> Reputation 0.11 −0.15 0.35 0.68
BCO ‐> Learning ‐> Reputation 0.30* 0.03 0.54 0.68
Rep ‐> Learning ‐> Reputation −0.22 −0.48 0.02 0.68
Note: Average causal mediation effects estimated using Imai et al.'s (2010) algorithms. ρis generated using Imai et al.'s (2010) procedure for sensitivity
analysis. An asterisk (*) indicates significance, or when the LLCU and ULCI are both positive or are both negative.
Abbreviations: Coef., Product of coefficients; LLCU, lower limit confidence interval; ULCI, upper limit confidence interval; ρ, sensitivity statistic.
T A B L E C18 Indirect effects of message strategies on reputation through organizational learning during a preventable crisis.
Average Causal Mediation Effect (ACME)
Coef. LLCI ULCI ρ
B‐> Learning ‐> Reputation −0.07 −0.31 0.19 0.69
BC ‐> Learning ‐> Reputation 0.07 −0.15 0.27 0.69
BCO ‐> Learning ‐> Reputation 0.26* 0.03 0.41 0.69
Rep ‐> Learning ‐> Reputation −0.30* −0.61 −0.04 0.69
Note: Average causal mediation effects estimated using Imai et al.'s (2010) algorithms. ρis generated using Imai et al.'s (2010) procedure for sensitivity
analysis. An asterisk (*) indicates significance, or when the LLCU and ULCI are both positive or are both negative.
Abbreviations: Coef., product of coefficients; LLCU, lower limit confidence interval; ULCI, upper limit confidence interval; ρ, sensitivity statistic.
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