Johns Hopkins Journal Article Review Essay

Please write a one-page review of the attached article, and then write at least two thoughtful open-ended discussion questions. Instruction and a sample are also attached.

Journal of Public Relations Research
ISSN: 1062-726X (Print) 1532-754X (Online) Journal homepage: https://www.tandfonline.com/loi/hprr20
Understanding publics’ perception and behaviors
in crisis communication: Effects of crisis news
framing and publics’ acquisition, selection, and
transmission of information in crisis situations
Young Kim
To cite this article: Young Kim (2016) Understanding publics’ perception and behaviors in
crisis communication: Effects of crisis news framing and publics’ acquisition, selection, and
transmission of information in crisis situations, Journal of Public Relations Research, 28:1, 35-50,
DOI: 10.1080/1062726X.2015.1131697
To link to this article: https://doi.org/10.1080/1062726X.2015.1131697
Published online: 06 Feb 2016.
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JOURNAL OF PUBLIC RELATIONS RESEARCH
2016, VOL. 28, NO. 1, 35–50
http://dx.doi.org/10.1080/1062726X.2015.1131697
Understanding publics’ perception and behaviors in crisis
communication: Effects of crisis news framing and publics’
acquisition, selection, and transmission of information in crisis
situations
Young Kim
Manship School of Mass Communication, Louisiana State University, Baton Rouge, Louisiana, USA
ABSTRACT
ARTICLE HISTORY
This study aims to better understand publics’ perception and communicative behaviors in crisis communication. The extant research has overlooked
how framing factors and different publics’ communicative behaviors
directly influence crisis outcomes, including reputation and behavioral
intentions. An online experiment with 1,113 participants was conducted
to fill the gap. The findings demonstrated that preventable crisis news
framing was a strong negative predictor for crisis outcomes. Another finding based on Communicative Action in Problem Solving (CAPS) in
Situational Theory of Problem Solving (STOPS) revealed that information
attending, forwarding, and seeking are positively associated with reputation
and behavioral intentions.
Received January 30 2015
Accepted November 25 2015
KEYWORDS
Communication Action in
Problem Solving (CAPS);
crisis communication; crisis
news framing; Situational
Theory of Problem Solving
(STOPS)
Various publics arise and respond to crisis situations differently. During a crisis, publics become the
key players in the environment, creating issues that affect them as well as the organization,
government, media, and other parties (Kim, Ni, & Sha, 2008). Understanding the publics and
their communicative behaviors is critical because it can be helpful to determine an organization’s
stance and to develop effective crisis strategies targeted for the different publics (Kim, Kim, &
Cameron, 2012a). Crisis communication researchers have studied how publics perceive, interpret,
and respond to the crisis to better understand the publics and their communicative behaviors in
crisis situations (An & Gower, 2009). In particular, crisis news framing research has illuminated how
news framing can influence publics’ perception and interpretation of the organization, providing
crisis managers with useful insights into the appropriate crisis response strategies for effective crisis
communication (Holladay, 2009; Liu & Kim, 2011).
However, the extant research has focused on how crisis news framing plays an important
role in the publics’ perceived crisis responsibility or attitudes, rather than actual crisis outcomes, reputation, and behavioral intentions (Coombs, 2007b, 2015). Moreover, previous crisis
communication research has failed to identify and examine different publics’ communicative
behaviors (Austin, Liu, & Jin, 2012). To fill the gap, this study examines how crisis news
framing can be connected to reputation and behavioral intentions to better understand the
publics’ perception in crisis communication. Adopting Communicative Action in Problem
Solving (CAPS: a conceptual framework of communicative behaviors), this study investigates
how active communication actions predict the crisis outcomes compared to passive communication behaviors (Kim, Grunig, & Ni, 2010).
CONTACT Young Kim
enteryoung@gmail.com
Journalism Building, Baton Rouge, LA 70803.
© 2016 Taylor & Francis
Manship School of Mass Communication, Louisiana State University, 211
36
KIM
Literature review
Crisis communication and crisis news framing
A crisis is the perception of an unpredictable event negatively affecting an organization’s
performance and reputation, as well as its publics (Coombs, 2015; Fearn-Banks, 2011). If the
publics believe there is a crisis, then the organization is in a crisis (Coombs, 2009). After a crisis,
publics may not only have negative perceptions of the organization’s reputationbut also stop
buying its products and no longer support the organization (Helm & Tolsdorf, 2013). Thus, the
crisis seriously damages the reputation and negatively affects publics’ behavioral intentions
toward the organization (Dowling, 2002; Simon, 2009). To reduce and contain such harm and
further change perceptions of the crisis or the organization in crisis, the organization communicates strategically with the publics (Reynolds & Seeger, 2005; Seeger, 2006). The organization’s
crisis communication includes actual verbal and nonverbal responses to understand and affect
publics’ perceptions in a crisis by collecting, processing, and disseminating information required
to address a crisis situation (Coombs, 2012).
Crisis communication scholars have provided theoretical approaches to guide and help crisis
managers understand how to effectively communicate with publics in response to a crisis (Choi &
Chung, 2013; Seeger, 2006). Coombs (2006, 2007b) proposed Situational Crisis Communication
Theory (SCCT), which recommends appropriate crisis response strategies to crisis managers.
Applying Wiener’s (1986) attribution theory, SCCT draws upon empirical evidence and tests
hypotheses related to how publics’ perceptions of crisis situation affect the crisis response and crisis
outcomes (Coombs, 2007a). The SCCT literature has demonstrated how crisis response strategies
restore an organization’s image and reputation (Choi & Chung, 2013; Claeys, Cauberghe, & Vyncke,
2010; Coombs & Holladay, 2002), as well as improve positive behavioral intentions toward the
organization (Coombs & Holladay, 2007, 2008; Laufer & Jung, 2010). Consequently, the extant SCCT
research illuminated how an organization should choose its crisis response strategies by understanding how the publics perceive crises (Choi & Chung, 2013; Coombs, 2015).
Thus, crisis communication starts with understanding how publics perceive crisis situations
(Coombs, 2007a, 2015; Ulmer, Sellnow, & Seeger, 2014). The perception of a crisis is based upon
a crisis type, and the crisis type is “how the crisis is being framed” (Coombs, 2007b, p. 166). Crisis
events can be framed into one of three clusters (victim, accidental, and preventable); each cluster
entails different levels of reputational threat based on how publics perceive and attribute crisis
responsibility to the organization (Coombs, 1998; Coombs & Holladay, 1996, 2002). The publics
attribute very little crisis responsibility in the victim cluster (e.g., natural disaster) and low crisis
responsibility in the accidental cluster (e.g., technical-error accidents; Coombs, 2015). However, the
publics attribute strong crisis responsibility in the preventable cluster (e.g., human-error accidents)
(Coombs, 2006; Schwarz, 2012). Accordingly, crisis managers choose appropriate response strategies
to not only frame the crisis type but also change publics’ perception of the organization in crisis
(Boin, Hart, & McConnell, 2009; Ulmer et al., 2014). At the same time, the news media frame the
crisis in similar or dissimilar ways (Bowen & Zheng, 2015; Coombs, 2007b). Sometimes, crisis
managers and publics may disagree on the crisis type. The publics tend to seek crisis information,
perceive crisis responsibility, and change their view of reputation of the organization based on media
coverage of the crisis, rather than crisis managers’ strategies (Cho & Gower, 2006; Holladay, 2009;
Liu & Kim, 2011). The publics attempt to reduce uncertainty at the beginning stage of a crisis by
seeking news media information to gain a better understanding of the crisis (Spence, Westernman,
Skalski, Seeger, Sellnow, & Ulmer, 2006). The publics are more likely not only to accept crisis
messages via news media than the messages via social media or word-of-mouth and more likely to
provide supportive messages for the organization when the crisis information comes from journalists
(Liu, Austin, & Jin, 2011). Thus, the news media exert a major force on public discourse online in
JOURNAL OF PUBLIC RELATIONS RESEARCH
37
crisis situations, although the popularity of social media has been growing (Etter & Vestergaard,
2015; Utz, Schultz, & Glocka, 2013).
Nevertheless, the extant research has rarely illuminated the actual effects of crisis news framing on
crisis outcomes, because it has focused on content analyses of crisis news coverage (e.g., An &
Gower, 2009; Bowen & Zheng, 2015; Liu & Kim, 2011; Van Der Meer, Verhoeven, Beentjes, &
Vliegenthart, 2014). Moreover, the previous research has heavily emphasized the relationship
between various crisis types framed differently and crisis responsibility or attitudes (e.g., Cho &
Gower, 2006; Claeys & Cauberghe, 2014; Coombs & Holladay, 2001), not actual crisis outcomes such
as reputation and behavioral intentions based on publics’ perception (Coombs & Holladay, 1996,
2007; Lee, 2005). Hence, it would be a more realistic approach to examine how crisis news framing
directly influences the actual crisis outcomes.
An organizational reputation is a perceptual construct that resides in publics’ heads; that is, what
the publics actually think, say, or evaluate about an organization (Coombs & Holladay, 2007; Helm
& Tolsdorf, 2013; Kim, Hung-Baesecke, Yang, & Grunig, 2013). Many scholars agree that a crisis is a
threat to reputational assets (Gaultier-Gaillard & Louisot, 2006; Jacques, 2014). In this sense,
effective crisis communication is expected to help the organization repair and/or prevent reputational damage, as well as sometimes have a more positive reputation than it had before the crisis
(Coombs, 2007b; Fearn-Banks, 2011; Ulmer et al., 2014; Van Der Meer, 2014). Moreover, a crisis
leads the publics to be less likely to report supportive behavioral intentions such as saying nice things
about the organization and using its products and services (Coombs, 2007b; Coombs & Holladay,
2001, 2007; Siomkos & Kurzbard, 1994). Thus, reputation and behavioral intention toward an
organization are important outcomes in crisis communication.
In the crisis framing research, a recent crisis communication study demonstrates the direct
relationship crisis types framed differently and the crisis outcomes by finding that preventable crises
had the most negative effects on organizational reputation in a hypothetical crisis using fictitious
company (Claeys et al., 2010). More recently, Iannarino, Veil, and Cotton’s (2015) study indicated
that the news framing of the 2011 Japan nuclear crisis from US evening networks may have shaped
publics’ negative perception and not supportive behaviors toward nuclear development in the United
States. To confirm the direct and strong relationship between crisis news framing and crisis outcomes in the actual crisis types helping to enhance ecological validity (Turk, Jin, Stewart, Kim, &
Hipple, 2012), this study proposes the following hypothesis:
H1: Preventable crisis news framing will be a stronger predictor for an organization’s negative crisis
outcomes, reputation, and behavioral intentions, than other news framing (accidental crisis news
framing or no framing).
Communicative action in problem solving (CAPS) in crisis situations
As aforementioned, examining crisis news framing is in an effort to understand public’s perception
of a given crisis to effectively communicate with the publics of the organization (Kim & Cameron,
2011; Kim et al., 2012a). To more effectively communicate, nonetheless, crisis managers need to
identify and understand the key publics who are more likely to influence others by selecting
(permit), transmitting (forward), and acquiring (seeking) crisis information than are other publics
(e.g., passive publics; Ni & Kim, 2009). Nonetheless, identifying and examining different publics’
communicative behaviors in crisis situations have been rarely highlighted in crisis communication
studies (Austin et al., 2012; Kim, Jung, Park, & Dutta, 2009). Dominant crisis communication
theories such as Coombs’s (2007b) SCCT and Benoit’s (1997) image repair theory do not consider
different publics’ communicative behaviors in crisis situations, ultimately influencing the organization’s crisis communication (Austin et al., 2012; Olsson, 2014).
In public relations practice and research, identifying the publics’ communicative behaviors and
predicting impacts have received special attention for several decades (Kim & Krishna, 2014). Grunig’s
38
KIM
(1968, 1997) Situational Theory of Publics (STP) was built to identify who publics are by explaining why
and how they communicate. As an extended and generalized version of STP, Kim and Grunig (2011)
proposed Situational Theory of Problem Solving (STOPS). STOPS explains why and how an individual
communicates during problematic life situations based on a more comprehensive and theoretical
framework, CAPS, which details communicative behaviors in problematic situations (Kim & Krishna,
2014). The CAPS delineates communicative activeness in information taking, selecting, and giving in
terms of active and passive components (Kim et al., 2010). CAPS conceptualizes communication
behaviors in three domains, including information acquisition, selection, and transmission, thus leading
to six communication behavioral variables: seeking (active) and attending (passive) in the information
acquisition, forefending (active) and permitting (passive) in the information selection, and forwarding
(active) and sharing (passive) in the information transmission (Kim et al., 2010).
The CAPS literature demonstrates that more active communicative behaviors have “most of the
strategic potential” because such communicative actions can explain “how problematic situations (e.g.,
crises) arise and are shared and sustained” (Ni & Kim, 2009, p. 220; Vasquez & Taylor, 2001). The extant
research has indicated that the active and aware publics actively transmit their dissatisfaction with the
organization to inactive publics and tend to create a negative reputation (Kim et al., 2013; Kim & Rhee,
2012). The active publics share, forward, and discuss crisis messages via various media channels, including
interpersonal, traditional, and social media (Utz et al., 2013). The communicative behaviors using social
media (e.g., blogs and Facebook) can help the publics reduce uncertainty, maintain support, and achieve
expressive and instrumental communication goals in crisis situations (Liu, Jin, & Austin, 2013; Procopio &
Procopio, 2007). If the active publics become aware of the crisis from such media before the organization
officially notifies them, it can cause tension in the relationship, resulting in negative outcomes in crisis
communication (Coombs, 2015). Even in post-crisis situations, the active communicative actions (i.e.,
forefending, seeking, forwarding) play a critical role in the evolution or devolution of issues and conflicts
(Kim, Kim, Tam, & Kim, 2014; Ni & Kim, 2009). Examining active publics’ communicative actions for
effective crisis communication can help crisis managers strategically learn where to go or how to communicate in a crisis situation (Coombs & Holladay, 2014). To demonstrate the importance of active publics
and their communicative behaviors and elaborate their empirical evidence on crisis outcomes, consequently, this study applied CAPS to a crisis situation. Therefore, this study posits the following hypothesis:
H2: Active communication actions, forefending, forwarding, and seeking of information, will be
significant predictors for crisis outcomes, reputation and behavioral intentions, more than
passive communication actions, permitting, sharing, and attending of information.
In the STP and STOPS literature, publics’ enduring characteristics such as formal membership in
a group, demographics, or psychographics are regarded as cross-situational (static) variables (Kim
et al., 2008). The relevant studies have demonstrated that the cross-situational factors, especially
demographics and socioeconomic status, have some effects on publics’ communicative actions in
problematic situations (Grunig, 1997; Kim et al., 2009; Kim, Ni, S.-H., & Kim, 2012b). Hence, this
study asks the following research question:
RQ1: Controlling for the effects of demographics, including age, education, gender, income, and
race, are preventable crisis news framing and active communication actions still able to predict
a significant amount of the variance in negative crisis outcomes, reputation and behavioral
intentions?
Method
For this study, an online experiment was conducted with the between-subjects groups randomly
assigned, two different news framing groups and a control group. Because many scholars and
practitioners agree that a real crisis is the best textbook for learning crisis communication
JOURNAL OF PUBLIC RELATIONS RESEARCH
39
(Coombs & Holladay, 2001; Park & Hon, 2010), an actual airline crash was used. The airline industry
has recently become one of the most crisis-prone industries (ICM Crisis Report, 2013), and the
airline crash has been frequently investigated in a number of crisis communication studies (Helm &
Tolsdorf, 2013; Lee, 2005). On July 6, 2013, Asiana Airlines (Seoul, South Korea based) Flight 214,
with 307 people on board, crashed as it approached San Francisco International Airport. The
incident killed three teen-aged girls from China and seriously injured 181 others (Karp, 2013).
After investigating for almost a year, the National Transportation Safety Board concluded that the
pilot’s mismanagement caused the crash (ABC News, 2014). Actual news stories covering the crisis
were adopted for this experiment.
Participants
The participants in this study were 1,113 people living in the United States. Excluding missing
data (N = 40), the total sample was 1,073. The ages ranged from 18 to 80 years old, with the
average age of respondents at 35.8. Men accounted for 39.1% (N = 420) and women were 60.9%
(N = 653). Among the participants, 75.1% (N = 804) were White, 9.4% (N = 100) were African
American, 7.1% (N = 76) were Asian American, and other races were 8.4% (N = 90). Participants
in this study were recruited through an online web-based platform (Amazon.com’s Mechanical
Turk; M-Turk) with a diverse subject pool in October, 2013. M-Turk subjects were all volunteers
paid 50 cents to complete the questionnaire. M-Turk is a burgeoning and promising vehicle for
experiment studies in social science, recruiting and paying participants to perform tasks
(Berinsky, Huber, & Lenz, 2012).
Stimulus development
To choose different news framing stories from a real crisis case, each representative story framing
was chosen from national US newspapers (e.g., the New York Times, USA Today) published
during one month after the crisis occurred, from the first day (July 6) to August 5. Three stories
were selected based on (a) technical problems (accidental crisis framing), which can lead to low
attribution of crisis responsibility; (b) pilot’s performance error (preventable crisis framing),
which can lead to strong attribution of crisis responsibility; and (c) no-framed story describing
the crash without any framing. Each stimulus story was cut down to around 260 words to reduce
the participants’ fatigue.
Procedure
Participants were informed by the consent form about the purpose, procedures, statement of privacy,
and benefits, and then asked to indicate their agreement with what they would do to answer after
reading the crisis scenario and each crisis news article. In the experiment, this study had three
conditions with a control group (i.e., no-framed news story group) and two experimental conditions
based on two different news stories framed either with the pilot’s performance error (preventable
crisis) or a technical problem (accidental crisis) leading to the crash. Before the participants were
exposed to the different news stories, they were briefly introduced to the crisis event through a press
release from Asiana Airlines, which included simple factual information about the crash. The
participants then answered questions measuring information forefending, permitting, forwarding,
sharing, seeking, and attending as the independent variables. The participants were randomly
assigned to one of the three conditions: no frame, preventable crisis, and accidental crisis news
framing group. After random assignment, reputation and behavioral intentions toward the organization were measured as the crisis outcomes (dependent variables). The experiment questionnaire was
created on Qualtrics.com, a web-based tool, and the link was launched on M-Turk. The participants
could withdraw from the survey at any time.
40
KIM
Measures
Multiple items were used for each variable and measured on a 7-point bipolar Likert-type scale
(1 = not at all to 7 = very much). To measure situational communication behavioral variables, this
study adopted Kim and Grunig’s (2011) STOPS scales consisting of five items measuring each
variable. Participants answered the questions assessing whether they were active or passive in
information acquisition, selection, and transmission: forefending (active in information acquisition;
e.g., I know where to go when I need updated information regarding this crisis; Cronbach’s α= 0.76),
permitting (passive in information acquisition; e.g., for this crisis, I welcome any information
regardless of where it comes from; α = 0.76), forwarding (active in information transmission; e.g.,
if it is possible, I take time to explain this crisis to others; α = 0.90), sharing (passive in information
transmission; e.g., I may not initiate but willing to have conversation about this crisis; α = 0.88),
attending (passive in information selection; e.g., If I hear someone talking about this crisis, I am
likely to listen; α = 0.89), and seeking (active in information selection; e.g., I am willing to contact
people about this type of crisis to learn what kind of solutions there are; α = 0.88).
Regarding dependent variables, this study used SCCT scales (Coombs, 1998; Coombs & Holladay,
1996). Crisis reputation was measured by five items (e.g., under most circumstance I would be likely
to believe what the organization says; α = 0.79). Positive behavioral intentions were measured by four
items (e.g., saying nice things about the organization to other people) collapsed to one item as well
(α = 0.87). In addition, participants were asked for demographic (age, gender, and race) and
socioeconomic characteristics (income and education level).
Results
Manipulation checks
Each framing group was almost an equal sample size: accidental framing group (N = 361), preventable
framing group (N = 355), no framing group (N = 358), and demographic characteristics in each group
were all balanced without any significant differences at 0.05 (p > 0.05). To check the news framing
manipulation leading to the intended effect on crisis outcomes, participants were asked to rate the
following items with a 7-point scale (1 = not at all, 7 = very much); “the cause of the crisis was something
(accidental crisis) other circumstance or organizations could have controlled,” and “the cause of the
crisis was something the pilot’s error (preventable crisis) could have controlled.” The results of one-way
ANOVA showed that manipulation of different news framing stories was successful. Participants who
read an article framed by preventable crisis (pilot’s error; M = 5.01, SD = 1.26) perceived significantly
higher crisis responsibility on the pilot than those who read article framed by accidental crisis (technical
problem; M = 4.27, SD = 1.25), and no frame (M = 4.12, SD = 1.06), F (2, 1071) = 56.55, p < 0.001. Posthoc comparison using the Tukey Honestly Significant Difference (HSD) test revealed that the mean score of participants who read an article framed by the pilot’s error was significantly higher than the means of those in other framing groups, technical problem and no framing (p < 0.05). In addition, participants reading an article framed by the technical problem (M = 4.21, SD = 1.09) perceived significantly higher crisis responsibility on technical problem or Boeing than those reading article framed by pilot’s error (M = 3.72, SD = 1.32) and no framing (M = 4.03, SD = 0.88), F (2, 1071) = 18.13, p < 0.001. Post-hoc comparison using the Tukey HSD test revealed that the mean score of participants who read an article framed by the technical problem was significantly higher than the means of those who read the news story framed by the pilot’s error, not means in no-framed group (p < 0.05). Overall, the analyses demonstrated that participants perceived different crisis responsibility leading to crisis outcomes between conditions as intended. News framing, communicative behaviors, and crisis outcomes To test hypotheses, a series of multiple ordinary least squares (OLS) regression analyses were conducted in STATA 13 statistical software program. Assumptions were checked to ensure that JOURNAL OF PUBLIC RELATIONS RESEARCH 41 there was no violation. In checking multicollinearity, there were a few high coefficients of pair-wise correlations among variables (i.e., above r = 0.80): Asian and Black race (r = 0.92), Asian and Other race (r = 0.93), and Black and Other race (r = 0.92). However, the variance inflation factor (VIF) and tolerance showed that there was not a violation of multicollinearity in all independent variables (i.e., VIF of each variable < 10 and tolerance of each variable > 0.10). Regarding heteroskedasticity,
Breusch-Pagan/Cook-Weisberg test was conducted and revealed that there was heteroskedasticity as
fitted values of reputation, χ2(1) = 7.60, p < 0.05, and behavioral intention, χ2(1) = 31.06, p < 0.05, were smaller than 0.05. For this reason, White’s heteroskedastic robust standard error was run as a remedial measure, and this study reports the results (i.e., changed standard errors and tests of statistical significance). To run multiple OLS regression analyses, framing factors were recoded as dichotomous variables, and accidental (accidental crisis: 1, others: 0) and preventable (preventable crisis: 1, others: 0) crisis news framing variables were included in the models. Regarding CAPS variables (information forefending, permitting, forwarding, sharing, seeking, and attending), confirmatory factor analysis (CFA) using AMOS 22 was run to check the dimensionality of the measures and the covariance of items (i.e., composite reliability and construct validity). The initial CFA revealed that there was a measurement item for information forefending in a violation of construct validity due to significantly low level standardized loading (β < 0.50) and average variance extracted (AVE < 0.50) (Hair, Black, Babin, & Anderson, 2009). The item was deleted, and CFA was then run again. Construct validity (standardized loading estimate > 0.50, convergent validity: AVE > 0.50, discriminant validity: AVE >
average shared varience), and composite reliability (CR > 0.70) were successfully established in all
measurement items (Hair et al., 2009). The CFA model goodness-of-fit indices also met all of the
joint criteria by Hu and Bentler (1999): χ2(231, N = 1,074) = 687.532, χ2/df = 2.98, p = 0.00,
Comparative Fit Index (CFI) = 0.98, Standardized Root Mean Square Residual (SRMR) = 0.04, Root
Mean Square Error of Approximation (RMSEA) = 0.05 (See Table 1).
Together, all independent variables (CAPS: information forefending, permitting, forwarding,
sharing, seeking, and attending and framing: accidental and preventable) in the model accounted
for a significant portion of the variance in reputation, R2 = 0.06, F(8, 1074) = 8.62, p < 0.001 and behavioral intention, R2 = 0.19, F(8, 1073) = 22.09, p < 0.001. H1 proposed that preventable crisis news framing will be a stronger predictor for an organization’s negative crisis outcomes, reputation, and behavioral intentions, than accidental news framing and no framing. As expected, preventable crisis news framing appeared as a strong predictor for negative crisis outcomes. The results indicated that one unit change in preventable crisis news framing results in a decrease of 0.36 in the organization’s reputation (b = −0.36, t = −4.44) and a decrease of 0.23 in positive behavioral intentions (b = −0.23, t = −2.50), controlling for effects of other independent variables in the models (See Table 2). To estimate how different effects the preventable crisis framing compared to other framing factors have on crisis outcomes, reputation and supportive behavioral intentions, coefficients of all independent variable were applied to the multiple regression equation, Y = a + b1*X1 + b2*X2 + . . . + bp*Xp (e.g., Predicted value of preventable crisis framing on RT[Ŷpreventable-reputation] = 4.36 + [−0.04] *forefending. . .[−0.37]*[1: preventable crisis new framing] + [−0.08]*[0: accidental crisis news framing]. . .+ [−0.08]*Other race). As a result, the predicted value of preventable crisis news framing (Ŷpreventable-reputation) on reputation was 0.37 lower than no-framing (Ŷno-reputation) and 0.39 lower than accidental crisis news framing (Ŷaccidental-reputation); there was a small amount difference (0.08) between Ŷno-reputation and Ŷaccidental-reputation. Regarding supportive behavioral intentions, the predicted value of preventable crisis news framing (Ŷpreventable-behavioral) was 0.24 lower than no-framing (Ŷno-behavioral) and 0.21 lower than accidental crisis news framing (Ŷaccidental-behavioral). However, there was 0.03 difference between Ŷno-behavioral and Ŷaccidental-behavioral. Because the t statistics of preventable crisis framing were −4.50 (reputation) and −2.61 (supportive behavioral intentions), the differences of predicted values were statistically significant. Therefore, H1 is supported. 42 KIM Table 1. Composite reliability and construct validity of CAPS (N = 1,074). Standardized loading Latent estimate variable Measurement items (β) Information forefending Others respect my perspective about 0.72 (IFF) this crisis because it is simple and clear. I know where to go when I need 0.50 updated information regarding this crisis. I feel like resisting some persuasive 0.66 efforts about this crisis. I express my opinions confidently 0.78 about what should be done to deal with this crisis. Information To make better decisions regarding 0.85 permitting this crisis, I listen to views and (IPM) information opposite to my own as long as they are related to the crisis. For this crisis, I welcome any 0.72 information regardless of where it comes from. I am careful in accepting information 0.50 about this crisis because of the hidden interests of those who provide the information. I listen even to opposite views on 0.66 this crisis. At times, I find that I have accepted 0.67 conflicting information about this type of crisis. Information If possible, I will take the time to 0.84 forwarding explain this crisis to others. (IFW) It is worth spending some time to 0.76 persuade others about this crisis. I look for chances to share my 0.86 knowledge and thoughts about this crisis. I actively seek out opportunities to 0.85 participate in public opinion polls about this crisis. I love to start a conversation on this 0.72 crisis with others. Information I may not initiate but willing to have 0.77 sharing (ISH) conversation about this crisis. I talk about this type of crisis when 0.83 others bring up the topic. I am willing to participate in casual 0.66 conversations about this crisis. I would join in a conversation when I 0.81 hear people talking about this crisis. I am sure that I will be quite active in 0.75 passing on information related to this crisis in the near future. Explained variance (R2 ) 0.61 Composite reliability (CR) 0.78 Average variance extracted (AVE) 0.55 Average shared variance (ASV) 0.43 0.81 0.53 0.30 0.90 0.65 0.53 0.88 0.59 0.48 0.43 0.24 0.60 0.44 0.43 0.29 0.52 0.72 0.52 0.72 0.73 0.58 0.70 0.56 0.66 0.44 0.68 0.60 (Continued ) JOURNAL OF PUBLIC RELATIONS RESEARCH 43 Table 1. (Continued). Latent variable Information seeking (ISK) Information attending (IAT) Standardized loading estimate Measurement items (β) I am willing to contact people about 0.83 this type of crisis to learn what kind of solutions there are. I am willing to visit Web sites 0.67 relevant to this crisis. I am willing to check to see if there is 0.65 any new information about this crisis on the Internet. I would request booklets containing 0.78 relevant information about this crisis. I actively search for information on 0.86 this topic. If I hear someone talking about this 0.76 crisis, I am likely to listen. I attend to news when they cover 0.79 this crisis. I paid attention to a news report 0.75 about this kind of crisis recently. I pay attention to this crisis when a 0.89 news report appears on TV news. I may take some time to listen if 0.83 someone tries to give information about this crisis. Explained variance (R2 ) 0.73 Composite reliability (CR) 0.87 Average variance extracted (AVE) 0.58 Average shared variance (ASV) 0.51 0.90 0.65 0.42 0.61 0.42 0.45 0.69 0.68 0.79 0.57 0.62 0.57 Note. Construct validity (standardized loading estimate > .50, convergent validity: AVE > .50, discriminant validity: AVE > ASV), and
composite reliability (CR > .70) were successfully established (Hair et al., 2009). CAPS Confimatory Factor Analysis (CFA) model
goodness-of-fit indices met all of the joint criteria by Hu and Bentler (1999): χ2(231, N = 1,074) = 687.532, χ2/df ratio = 2.98,
p = .00, Comparative Fit Index (CFI) = .98, Standardized Root Mean Square Residual (SRMR) = .04, Root Mean Square Error of
Approximation (RMSEA) = .05.
Inconsistent with H2, all active communication actions, forefending, forwarding, and seeking of
information, were not significant predictors for crisis outcomes, but there were different communication actions present as strong predictors for reputation and behavioral intentions. In reputation,
only one communicative behavior variable, attending (b = 0.18, t = 4.77), was found as a strong
predictor. This result reveals that every one unit change of passive acquisition (attending) results in
an increase of 0.18 in the organization’s reputation, controlling for effects of other independent
variables in the model (Step 1). When it comes to positive behavioral intentions, active information
transmission (forwarding; b = 0.30, t = 6.29) and acquisition (seeking; b = 0.20, t = 3.93) were
positively associated, but a passive communicative behavior (information transmission: sharing)
appeared as a negative predictor (b = −0.13, t = −2.23), controlling for effects of other independent
variables in the model (Step 1). Consequently, H2 is partially supported (See Table 2).
To answer RQ1, demographic and socioeconomic variables (age, education, gender, income, and
race) were added into the regression models (Step 2). Gender (female = 1, male = 0) and race (Asian,
Black, and Other race: non-White but also non-Asian and non-Black) were recoded as dichotomous
variables. Independent variables (two framing variables, six communication actions, and five demographic and socioeconomic factors) in the model accounted for a significant portion of the variance
in reputation, R2 = 0.07, F (15, 1070) = 6.55, p < 0.001 and behavioral intention, R2 = 0.21, F (15, 1070) = 15.93, p < 0.001 (Step 2). There was the increase of 1% (reputation: ΔR2 = 0.01) and 2% (behavioral intention: ΔR2 = 0.02) in variance from previous models (Step1). Controlling for effects of other independent variables in the models, information attending (b = 0.16, t = 4.10) and preventable crisis news framing (b = −0.37, t = −4.50) were still able to strongly predict the 44 KIM Table 2. OLS regression analyses for the relationship between CAPS and crisis outcomes. Reputation (RT) Behavioral intentions (BI) Variables Step 1 Constant Forefending (active selection) Permitting (passive selection) Forwarding (active transmission) Sharing (passive transmission) Seeking (active acquisition) Attending (passive acquisition) Accidental crisis news framing Preventable crisis news framing N R2 F b t b t 4.61 −0.04 0.05 −0.09 −0.07 −0.04 0.18 −0.07 −0.36 1,074 0.06 8.62*** 33.58*** −1.00 1.34 −1.92 −1.65 −1.00 4.77*** −0.95 −4.44*** 1.92 0.07 −0.08 0.30 −0.13 0.20 −0.01 −0.04 −0.23 1,073 0.19 22.09*** 11.70*** 1.48 −1.82 6.29*** −2.33* 3.93*** −0.15 −0.46 −2.50* Step 2 Constant Forefending (active selection) Permitting (passive selection) Forwarding (active transmission) Sharing (passive transmission) Seeking (active acquisition) Attending (passive acquisition) Accidental crisis news framing Preventable crisis news framing Age Gender Education Income Asian race Black race Other race N ΔR2 R2 F 4.36 −0.04 0.04 −0.08 −0.06 −0.04 0.16 −0.08 −0.37 0.01 0.10 0.02 −0.01 0.01 0.01 −0.08 1,070 0.01 0.07 6.55*** 21.64*** −0.97 1.21 −1.75 −1.41 −0.83 4.10*** −1.06 −4.50*** 2.00* 1.46 0.81 −0.78 0.13 0.13 −0.90 2.62 0.05 −0.08 0.28 −0.10 0.20 −0.00 −0.03 −0.24 −0.01 −0.11 −0.08 −0.00 0.10 0.03 −0.10 1,070 0.02 0.21 15.93*** 10.69*** 1.13 −1.90 5.84*** −2.03* 4.09*** −0.11 −0.35 −2.61** −2.00* −1.44 −3.06** −0.09 0.78 0.30 −0.44 Note. ***p < 0.001, **p < 0.01, *p < 0.05. Results were based on White’s heteroskedastic robust standard errors because the Breusch-Pagan/Cook-Weisberg test revealed that there was heteroskadesticity (RT: χ2(1) = 7.89, p < 0.05, BI: χ2(1) = 30.40, p < 0.05). Independent variables were not in a violation of multicollinearity (i.e., VIF of each variable < 10 and Tolerance of each variable > 0.10).
organization’s reputation, and the effects of information forwarding (b = 0.29, t = 6.26), seeking
(b = 0.20, t = 4.18), sharing (b = −0.10, t = −2.03) and preventable crisis news framing (b = −0.24,
t = −2.61) were consistent as significant predictors for behavioral intentions as well. Among
demographic variables, age was a positive predictor (b = 0.01, t = 2.00) for reputation as well as a
negative predictor (b = −0.01, t = −2.08) for behavioral intentions. Education (b = −0.08, t = −3.06)
was negatively associated with only behavioral intentions when controlling for the effect of other
independent variables (See Table 2).
Discussion
Understanding publics’ perception through the framing effect
As H1 anticipated, this study found that preventable crisis news framing was a strong negative predictor
for an organization’s crisis outcomes, controlling for the effect of other variables and communicative
behaviors, as well as demographic and socioeconomic characteristics. This result corroborates the most
negative effect of preventable crisis type on reputation of the organization and publics’ behavioral
intentions because the preventable crises produce strong attribution of crisis responsibility. In addition,
JOURNAL OF PUBLIC RELATIONS RESEARCH
45
the effect of accidental crisis news framing was not statistically significant compared to no-framing
news, although it appeared a negative predictor for crisis outcomes. Such different magnitudes of
preventable and accidental news framing on the crisis outcomes underpin the relationship crisis types
and level of crisis responsibility. Thus, this study supports the SCCT research that accidental crisis types
produce low attribution of crisis responsibility and preventable crises lead to strong attribution of crisis
responsibility. In turn, different crisis types lead crisis managers to choose different crisis response
strategies as more defensive strategies (e.g., attacking the accuser) for accidental crises and more
accommodative strategies (e.g., apology) for preventable crises to change publics’ perceptions of the
crisis or of the organization (Coombs, 1998, 2007b; Schwarz, 2012). The finding provides the actual and
direct evidence demonstrating how news framing is an influential factor in crisis communication as the
final arbitrator of publics’ perception and interpretation of a crisis, thereby leading to reputational threat
and negative behavioral intentions toward the organization.
Applying it to the crisis case of this study, crisis managers in Asiana Airlines may have had to
monitor the media coverage to determine a crisis type the publics were likely to perceive, rather than
focus on their own framing of the crisis. Even if public relations practitioners in the organization put
more effort into framing the crash crisis as an accidental crisis (e.g., technical problem caused by
Boeing) and making their defensive crisis response strategies (e.g., attacking the accuser or justification), their efforts and strategies may not have been successful for the publics who read more
frequently news stories framing the crash crisis as a preventable crisis (e.g., pilot’s error), expecting
the organization’s accommodative response strategies (e.g., apology or compensation). Thus, it is
advisable that crisis communicators should take media coverage of a crisis into consideration when
collecting, processing, and disseminating information required to address a crisis situation (i.e., crisis
communication) (Coombs, 2015; Etter & Vestergaard, 2015). In doing so, the crisis managers can
choose appropriate crisis strategies for more effective crisis communication which helps better
understand publics’ perception, thereby restoring the organization’s reputation and improving
positive behavioral intentions toward the organization.
Predicting and understanding publics’ crisis communication behaviors through CAPS
With regard to the organization’s reputation in a crisis situation, attending (passive acquisition) was
a significant predictor, controlling for the effects of other communicative behaviors. When demographic and socioeconomic characteristics were included in the model, the effect of information
attending was consistent as a positively significant predictor for reputation. This result provides
empirical evidence of the important effect of communicative action (information attending) on crisis
outcomes, although it was an unexpected finding. Information attending refers to less-active communicative behaviors characterized by “unplanned discovery of a message followed by continued
processing of it” (i.e., unintentional discovery of information) (Clarke & Kline, 1974; Kim et al.,
2010, p. 132). Information attending reflects that the publics are less likely to feel the need to acquire
information about the problem because they are likely to perceive a situation to be less problematic
than perceived by others who have active information acquisition (i.e., information seeking publics)
(Kim, 2006).
In addition, the publics who have information attending have built a solution and successfully
tested it, and they do not need further information because they feel to have competence of the
information (Kim et al., 2010). Hence, the publics in attending crisis information tend to be “passive
and reactive in gaining only information that is easily available and accessible” (Kim et al., 2010, p.
130). Further, the information-attending publics are associated with “a chronic or dormant
approach” because they are not engaged in information seeking but mostly processing the information (Ni & Kim, 2009, p. 237). That is, they no longer seek additional information but only rely on
updates available from the mass media in a problematic situation (Kim et al., 2014). In this sense, the
findings of this study indicate the importance of immediate response, as well as accurate information
in crisis communication to reduce the publics’ uncertainty in a crisis (Coombs, 2015; Seeger &
46
KIM
Ulmer, 2001). Accordingly, crisis managers should attempt to make crisis information available and
accessible to publics in order to increase information attending in a positive way, leading to
protecting or restoring their organization’s reputation.
Furthermore, the positive relationship between information attending and reputation in crisis
situation can be supported by the importance of prior reputation for effective crisis communication.
The finding implies that those who have information attending are likely to ignore the crisis if it
contradicts the relevant information to the solution when the information-attending publics had a
positive reputation previously. Thus, the positive relationship between information attending and
reputation supports the positive effect of prior reputation on crisis outcomes as “a reservoir of good
will” or “buffers” sustaining the organization in crisis situations (Helm & Tolsdorf, 2013, p. 145;
Tucker & Melewar, 2005). As Coombs and Holladay (2001, p. 324) explained, the “deflective power
of reputation in times of crisis,” a previous reputation makes the publics interpret the crisis as an
exceptional situation that can be disregarded. Based on the prior reputation, information-attending
publics perceive the crisis as a less serious situation and they do not feel the need to acquire
information. That is, they disregard the crisis information and keep maintaining their positive
view of the reputation on the organization. Therefore, information attending empirically explains
the importance of publics’ previous information and organizational reputation perceived by the
publics, helping shield the organization from reputational threat.
In behavioral intentions, more active information behavioral variables, transmission (forwarding) and acquisition (seeking), were positively significant, controlling the effects of other variables. According to the CAPS literature, the publics who engage in information forwarding and
seeking are classified as activist publics who are more situational and active than other active
publics (Kim, 2006; Kim et al., 2010; Ni & Kim, 2009). In particular, information seeking is
active communication behaviors that are more likely to initiate the collecting of information
proactively because they feel an urge to deal with a problematic situation (Ni & Kim, 2009).
Information transmission allows publics to mobilize resources to resolve the problem and evolve
into a social collectivity from the isolated problem solvers by giving information of problems and
solutions to others (Kim et al., 2010). For this reason, information transmission is “at the heart
of the locating and networking with other individual problem solvers” because transmitting
information about a problematic situation makes a problem produce a group of collective
problem solvers (i.e., an activist group) (Kim, 2006, p. 297).
In this regard, the result of this study helps identify activist groups and explains why crisis
managers primarily communicate with them as the key publics in crisis situations. The OLS
regression results revealed that one unit changes of information forwarding and seeking results in
increases of 28% and 20% in positive behavioral intentions toward the organization respectively. The
activist publics who are actively acquiring (seeking) and transmitting (forwarding) are more likely to
say nice thing about the organization to other people or show public support for the organization in
crisis than other types of publics (Coombs, 2007b). Accordingly, the result indicates that crisis
managers should identify the activist groups’ communicative characteristics and strategically communicate with them for effective crisis communication, improving positive behavioral intentions
toward their organization in crisis situations.
However, it is noteworthy that information sharing (passive transmission) was consistently
negative for supportive behavioral intentions controlling for the effect of others. This result demonstrates how important information transmission plays a critical role in crisis communication even if
it is passive or reactive. The findings also indicate the extent of activeness of communicative actions
in crisis situations that distinguish forwarding and sharing could result in different effects on
supportive behavioral intentions toward an organization. Even though the reactive transmitters
(i.e., information sharers) are less likely to initiate their information giving themselves, their
communicative actions are more likely to engage in negative word-of-mouth. Nonetheless, there
should be more research to bear out the different effects based on activeness of information
transmission. Because the information sharers are formerly active problem solvers who have
JOURNAL OF PUBLIC RELATIONS RESEARCH
47
acquired knowledge from past crisis situations (Kim et al., 2010), the finding in this study could be
attributed to prior reputation or experience with the organization.
Implications
In terms of more realistic crisis communication practice, the results can direct and advise crisis
managers as to how to conduct effective crisis communication when crisis type is ambiguous due to
the uncertainty of the causality. In the real world, an accident produces greater variance in publics’
perceptions. To determine the crisis type, the publics should “look to see what cues are present and
being used to describe the crisis” (Coombs, 2015, p. 157). The publics not only rely on the media
reports for crisis information, but also evaluate the cause of the crisis and the organization’s
responsibility based on the media coverage. For this reason, the publics have a different crisis type
from what the crisis managers intend to frame in a crisis situation. If this is the case, the crisis
managers should seriously consider adopting the publics’ frame based on media coverage of the
crisis and choosing appropriate crisis response strategies according the media framing. In this sense,
this study bears out the importance of media framing effects in crisis communication, providing
crisis managers with a useful direction for more effective crisis response strategies.
As a theoretical implication, this study provides a more comprehensive look into understanding
the role of media shaping publics’ perceptions of a crisis and the effects of publics’ communicative
actions on crisis outcomes. The findings indicate how the crisis communication researchers make
theoretical efforts to fill the gap of current crisis communication theories, which do not consider
different publics but focus on organizational reputation and blame avoidance strategies (Olsson,
2014). The researchers should “move beyond predominantly focusing on image management” (Liu
& Fraustino, 2014, p. 545). Understanding publics’ perceptions and communicative actions in crisis
situations is necessary to help the publics best cope and move forward after crises to manage a crisis
as an opportunity for renewal (i.e., resilience-generating crisis communication theory; Ulmer et al.,
2014). In other words, this study contributes to the theoretical development of crisis communication
by providing empirical evidence of the need for a resilience-generating theory for effective crisis
communication (Liu & Fraustino, 2014; Olsson, 2014; Ulmer et al., 2014).
Limitations and future research
Despite the important findings and implications, this study has certain limitations. First, this study
used an actual crisis case, and it is possible that participants were exposed to the crisis and crisis
communication of the organization via diverse media prior to participation in the study (Utz et al.,
2013). Moreover, other variables, especially emotions, prior reputation and relationship, were not
considered in this study, even though those factors influence crisis outcomes such as reputation and
behavioral intentions (Turk et al., 2012). Omitting those variables may have resulted in low values of
R2 in the reputation variable. Compared to the other dependent variable, behavioral intentions (19%
and 21%), R2 values of the reputation variable, the proportion of the variance explained by the
factors such as CAPS, news framing, and demographics, were relatively lowered, 6% and 7%. Even
though this study makes a step forward in the theoretical efforts of crisis communication research, a
majority of proportion of unexplained variance may lead public relations practitioners or crisis
managers to cast doubt on the generalizability of results. To extend this study and find more
generalizable results, future research should control for the prior exposure to news on the crisis
and examine the relationship crisis outcomes with such influential factors, including organization’s
reputation and relationship. Finally, this study did not include other situational variables such as
situational antecedents, perceptual and cognitive variables, and situational motivations which lead to
CAPS (Kim & Grunig, 2011). Understanding publics’ perceptual variables (problem recognition,
involvement recognition, and constraint recognition), cognitive variable (referent criterion), and
48
KIM
motivation will help enhance theoretical power and utility as well as comprehensively predict
publics’ communicative behaviors in acquiring, selecting, and transmitting crisis information.
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Running head: ARTICLE REVIEW
1
Discussion Leader 2 Article Review
The article focuses on how the impacts of social media on well-being differ from
adolescent to adolescent (Beyens et al., 2020). The researchers were primarily interested in
understanding the relationship between the use of social media and the affective well-being of
each individual adolescent as none of the past studies has assessed whether the impacts are
unique to each individual adolescent, and those that examined such effects have used different
indicators such as depression and life satisfaction. To examine the momentary well-being of
adolescents, the researchers performed a week-long earlier experience sampling (ESM) study
consisting of 63 adolescents aged between 14 and 15 (Beyens et al., 2020). During this study, the
participants were required to use their mobile phones to complete a survey, which they did a total
of six times a day. By the end of the week, the participants had completed a total of 2,155
assessments, as the survey covered 42 assessments per participant.
The adolescents were asked to report on their use of two social media platforms:
Instagram and WhatsApp. In order to understand the link between social media usage and wellbeing, the researchers differentiated between active and passive usage of social media.
Consequently, Beyens et al. (2020) assessed how adolescents’ overall passive and active social
media use is associated with their well-being, especially with regard to Instagram and
WhatsApp.
The research found that many adolescents are more likely to engage in passive usage of
social media platforms than active use (Beyens et al., 2020). The researchers also found that
there is a strong positive relationship between the time adolescents spend using social media
actively and passively. They used several multilevel models to understand the within-person
links between social media use and well-being and how they differed from one person to the
ARTICLE REVIEW
2
other. The study established that the link between passive social media use with well-being was
unique to every adolescent (Beyens et al., 2020).
Discussion Questions
1) Do you think the use of social media affect your well-being?
2) Do the impacts of social media on the well-being of adolescents differ based on how they
use it?
3) As the research was conducted in Holland and all the participants were from Holland, do
you think the demographic factor could have affected the result? Will the results be the
same if it was conducted in another country, like the U.S. or China?
ARTICLE REVIEW
3
References
Beyens, I., Pouwels, J. L., van Driel, I. I., Keijsers, L., & Valkenburg, P. M. (2020). The effect of
social media on well-being differs from adolescent to adolescent. Scientific Reports,
10(1), 1-11.