Exploring Secondary Crisis Response Strategies for Airlines Experiencing Low-Responsibility Crises: An Extension of the Situational Crisis Communication Theory

Abstract

Previous literature on airline crises has largely ignored low-responsibility crises. The purpose of this study is to explore the underlying mechanism of airlines utilizing secondary crisis response strategies to rebuild their reputations during low-responsibility crises. Extending the situational crisis communication theory, the study develops a research framework and conducts three empirical studies with a multi-method design to test the proposed hypotheses. The results demonstrate that an enhancing response strategy is more effective than a bolstering response strategy in evoking more Twitter likes and higher booking intentions. An enhancing response strategy is especially powerful for travelers low in need for cognition or those with a higher level of other-orientation. The effect of the secondary crisis response strategy on travelers’ booking intentions was mediated by the airline’s reputation. These findings provide airlines with valuable insight into the development of successful social media communication strategies when handling low-responsibility crises.

Keywords

situational crisis communication theory (SCCT)secondary crisis response strategy low-responsibility crisis airline need for cognition other-orientation

Introduction

The global tourism industry is vulnerable to crises, and the airline industry is no exception (Ritchie 2004). From accidents to terrorism, natural disasters to economic recessions, the airline industry faces the industry’s highest level of vulnerability to crises and the many complexities of crisis management (Ray 1999). Crisis communication plays an essential role in effective crisis management. Throughout each phase of a crisis, organizations must provide open and accurate communication in order to protect and rebuild their image and ensure a return to normal operations (Ray 1999). Widespread social media use has created new challenges in crisis communication, as it facilitates two-way conversations and the spread of online word-of-mouth (Wut, Xu, and Wong 2021). Increasingly, the airline industry is adopting social media as an essential communication tool, not only for marketing and customer service purposes, but also for proactive and reactive crisis communication (IATA 2018).

As the airline industry may experience a variety of crises, identifying the correct crisis type is the first step in effective crisis communication (Coombs 2007; Ritchie 2004). Faulkner (2001) classified disruptions in the tourism industry into two categories: crises and disasters. As he defined them, a crisis is an event in which an organization bears a great deal of responsibility, such as plane crashes, while a disaster (or called low-responsibility crisis) is an event in which the organization bears minimal responsibility, such as natural disasters or public health crises. The recent COVID-19 pandemic is an example of a low-responsibility crisis for the global tourism industry. Nonetheless, the COVID-19 crisis has had a catastrophic impact on the global tourism industry (Ou and Wong 2021). The airline industry has been hit the hardest among all tourism industry sectors, with a 60% decline in passenger numbers and a $371 1000000000 operating revenue loss (ICAO 2021). What’s more, COVID-19 has had profound long-term effects on consumer behavior, making the current recovery of the airline industry more difficult than during any other previous crisis (Bouwer, Saxon, and Wittkamp 2021). Given these challenges, effective crisis communication, especially via social media, is imperative for the airline industry to recover from this low-responsibility but prolonged crisis.

A review of the airline crisis communication literature revealed that the majority of research focused on high-responsibility crises such as plane crashes or terrorist attacks (e.g., Greer and Moreland 2003; Haruta and Hallahan 2003; Massey 2005; Ma et al. 2019) while low-responsibility crises have largely been ignored. In addition, the previous literature mainly used the case study method to examine one or several airline companies’ crisis response activities with a lack of generalization and theorization (e.g., Greer and Moreland 2003; Haruta and Hallahan 2003; Massey 2005; Ou and Wong 2021). The situational crisis communication theory (SCCT) proposes that crisis response strategies should be selected based on crisis type in order to achieve favorable crisis management outcomes (Coombs 2007). Thus, further research on low-responsibility crises may help the airline industry to leverage social media for effective crisis communication and expedite the industry’s recovery from COVID-19.

To address this research gap, this study explores how airlines may utilize appropriate crisis response strategies to rebuild their reputations and recover from low-responsibility but prolonged crises such as COVID-19. Building upon the SCCT, the study develops a research framework to compare the effectiveness of two secondary crisis response strategies. In the tourism field, the SCCT has only applied in descriptively categorizing crisis response strategies with a lack of causal evidence (Wut, Xu, and Wong 2021). Therefore, this study conducts three empirical studies with a multi-method approach to identify and test causal relationships proposed in the SCCT. Specifically, the study first content analyzed actual airline tweets to identify crisis response strategies in the context of airline low-responsibility crises. Two online experiments were then conducted to test the relationship between secondary crisis response strategy and travelers’ behavior intentions, and the mediating effect of an airline’s reputation in this relationship.

Moreover, existing research on crisis communication has paid little attention to the moderating role of personality traits that may affect the effectiveness of a crisis response strategy (Coombs 2016). To better understand the boundaries of the SCCT, Coombs (2016) proposed the investigation of these moderating variables as a potential direction for future research. In communication studies, the need for cognition and other-orientation are both personality traits that affect an individual’s information processing (Cacioppo and Petty 1982; De Dreu and Nauta 2009). Therefore, the two experiments conducted in the study investigate the moderating influences of these two personality traits (the need for cognition and other-orientation) in the mechanism of individuals processing crisis communication. The study contributes to the crisis management literature by extending the SCCT to emphasize the role of secondary crisis response strategies in response to low-responsibility crises. The results of this research may help airlines and other tourism businesses to leverage social media for crisis communication and brand image rebuilding.

Literature Review

Crisis Communication in Tourism

Although the importance of crisis management in the tourism industry is widely recognized (Ritchie 2004), research on crisis communication in tourism has only recently begun to attract attention (Wut, Xu, and Wong 2021). The extant literature highlights the role of social media in crisis communication from two aspects: tourists’ discussions and organizations’ responses (Wut, Xu, and Wong 2021). From the tourist’s perspective, scholars have examined their comments and thoughts on tourism crises to describe public crisis communication, such as Hurricane Irma (Park, Kim, and Choi 2019), hotel assault incident (Su, Stepchenkova, and Kirilenko 2019), destination attack incident (Zhai, Zhong, and Luo 2019), and the COVID-19 pandemic (Liu et al. 2021). These studies identified topics, themes, emotions arising from social media communications or public discourse. Based on tourists’ reactions to crises, the studies provide practical implications for businesses/destinations to leverage opinion leaders in crisis communication (Park, Kim, and Choi 2019). Liu et al. (2021) also proposed suggestions for online travel agents to respond to the three main complaints during COVID-19—cancelation barriers, refund barriers, and customer relationship management.

From the organization’s perspective, how they respond to tourism crises via social media has also been examined, such as Arab Spring uprisings (Avraham 2015), Tropical Cyclone Winston (Möller, Wang, and Nguyen 2018), and the COVID-19 pandemic (Wong, Ou, and Wilson 2021). These studies analyze organizational responses from press releases or interviews with managers. Avraham (2015) identified three strategies that Middle Eastern destinations used to repair their negative image during the Arab Spring uprisings—source-focused, message, and audience-focused. Wong, Ou, and Wilson (2021) found that the hotel industry was slow in responding to the pandemic with a communication tone change from focusing on the CEOs themselves to seeking social support and shared responsibility. Although social media were underused in the pre-disaster and response phases, they play an important role in the recovery phase by providing resources for economic development, social capital, information and communication, and community competence (Möller, Wang, and Nguyen 2018). Overall, crisis communication studies in our field are mostly descriptive in nature, with a lack of interest in the airline industry. This study attempts to fill this research gap.

Situational Crisis Communication Theory (SCCT)

Rooted in the attribution theory (Weiner 1985), Coombs (2007) developed situational crisis communication theory (SCCT) as a framework to match crisis response strategies to different crisis situations. The SCCT proposes that crises may threaten the reputation of an organization to varying degrees, depending on crisis type, crisis severity, and performance history (Coombs and Holladay 2002). Crisis response strategies should be carefully selected to repair an organization’s reputation and to prevent negative behavioral intentions (Coombs and Holladay 2002). The SCCT groups primary crisis response strategies into three categories based upon perceptions of crisis responsibility—denial, diminishing, and rebuilding—and identifies one secondary response strategy, bolstering (Coombs 2007). According to Coombs (2007), denial strategy tries to disconnect the organization from the crisis by claiming there is no crisis or the organization is not responsible for the crisis; diminishing strategy attempts to minimize organizational responsibility for the crisis or the damage caused by the crisis; rebuilding strategy aims to rebuild a new reputation for the organization by offering compensation to victims and asking for forgiveness. On the other hand, bolstering strategy reminds stakeholders of the past good works of the organization (Coombs 2007). For crises that attribute little to no responsibility to organizations, such as natural disasters and rumors, the use of denial and diminishing strategies is sufficient. However, for crises in which organizations bear a great deal of responsibility, including human errors and organizational misdeeds, rebuilding strategies should be employed (Coombs 2007).

The SCCT is one of the dominant theories in analyzing effective communication responses to different types of crises (An and Cheng 2010; Cheng 2018), including natural disasters (Liu, Lai, and Xu 2018), public health crises (Kim and Liu 2012; Kwok, Lee, and Han 2021), social media crises (Ott and Theunissen 2015), organizational misdeeds (Jeong 2009; Liu, Kim, and Pennington-Gray 2015), and financial crises (Cooley and Cooley 2011). In the tourism field, the SCCT has been applied to examine hotel crisis responses to bed bugs (Liu, Kim, and Pennington-Gray 2015) and COVID-19 (Kwok, Lee, and Han 2021). As the SCCT emphasizes the three types of primary crisis response strategies, previous studies have largely ignored the role of bolstering strategies as a secondary crisis response strategy. A meta-analysis of 24 SCCT studies found that primary crisis response strategies could not completely mitigate the threat to an organization’s reputation (Ma and Zhan 2016). Thus, further exploration of the effectiveness of secondary crisis response strategies that do not focus on issues of crisis responsibility is needed.

In addition, Kim, Avery, and Lariscy (2011) found that the exclusive use of primary crisis response strategies was problematic, as it ignored the public good or public interest. When analyzing crisis response strategies to the 2009 H1N1 crisis, Kim and Liu (2012) added two secondary crisis response strategies to the SCCT, enhancing and transferring, both of which were related to the organization’s good deeds during the crisis. A study on hotels’ communication strategy to bed bug crisis (as an example of health crisis) identified bolstering and enhancing as the most frequently used crisis response strategies (Liu, Kim, and Pennington-Gray 2015). As this study explores airlines’ secondary crisis response strategies during the COVID-19 pandemic, which is also a public health crisis, airline tweets were coded into two types of secondary crisis response strategies, bolstering and enhancing (Coombs 2007; Kim and Liu 2012). Kim, Avery, and Lariscy (2011) indicated that in crises that attribute little to no responsibility to the organization, crisis response strategies that focus on the public’s well-being should result in better outcomes than strategies focusing on the organization itself. Since responsibility for the COVID-19 pandemic can hardly be attributed to the airlines, this study proposes that an enhancing response strategy that focuses on the airlines’ public good deeds will evoke better customer perceptions and behavioral intentions than a bolstering response strategy that focuses on the airlines themselves. In the COVID-19 pandemic, there is a paradox between physical travel obstacles and continuing travel desire exist (Kim, Seo, and Choi 2021). Thus, we combine social media followers’ reactions to airline tweets with potential travelers’ intention to fly with the airline to reflect the effectiveness of the crisis response strategy. In addition, based on the SCCT, the airlines’ reputations are proposed to mediate this relationship (Coombs 2007). The first two hypotheses are put forward:

Hypothesis 1: Airline tweets that apply an enhancing response strategy trigger (a) more likes and (b) higher booking intentions than those applying a bolstering response strategy.

Hypothesis 2: Airline reputation mediates the relationship between the crisis response strategy and booking intentions.

The Need for Cognition

The need for cognition, as conceptualized by Cacioppo and Petty (1982), refers to an individual’s tendency to engage in and enjoy effortful cognitive activities. Those who score high on this attribute intrinsically enjoy thinking, while those who score lower try to avoid effortful cognitive work (Haugtvedt, Petty, and Cacioppo 1992). Cacioppo and Petty (1982) proposed that the need for cognition accounts for individual differences in processing information in persuasive communications. Considerable marketing research has demonstrated that people with high levels of need for cognition are more likely to process and evaluate advertising information more thoroughly (e.g., Cacioppo, Petty, and Morris 1983), while people with low levels of need for cognition pay more attention to and rely more on peripheral or superficial cues (e.g., Haugtvedt, Petty, and Cacioppo 1992). In other words, individuals with high levels of need for cognition tend to be persuaded by the quality of information (strong vs. weak arguments), whereas individuals with low levels of need for cognition are easily affected by peripheral cues such as attractiveness, credibility, and message framing (Petty et al. 2009).

Compared to the plethora of research on the need for cognition in marketing, few studies have explored this trait in the hospitality and tourism field. Lu, Gursoy, and Lu (2016) tested the need for cognition as one of the antecedents of online tourism information confusion and found that this trait negatively influences travelers’ information ambiguity and overload confusion. Zhang, Gursoy, and Xu (2017) examined the moderating role of the need for cognition on the persuasiveness of associative slogans. The findings indicated that the effects of associative slogans are greater on tourists with higher levels of need for cognition than on those with lower levels. Similarly, Zhang and Hanks (2017) tested the interplay of processing fluency and the need for cognition on travelers’ skepticism of a hotel CSR message. The findings suggested that travelers with low levels (vs. high levels) of need for cognition were more skeptical of messages that are easy to process.

As the need for cognition involves a preference for either thinking or referring to peripheral cues, the two secondary crisis response strategies may impact these two groups differently. On one hand, individuals with higher levels of need for cognition concentrate on the real attributes of the product rather than the way key information is presented to them (Sicilia, Ruiz, and Munuera 2005; Zhang and Buda 1999). As both crisis response strategies share the aim of rebuilding an organization’s reputation, consumers with higher levels of need for cognition may perceive the two response strategies as being equally persuasive. On the other hand, individuals with lower levels of need for cognition rely more on ad framing or peripheral cues (Sicilia, Ruiz, and Munuera 2005). The message frame reflecting a specific crisis response strategy acts as a peripheral cue that influences the information processing of travelers with lower levels of need for cognition. The greater influence of the crisis response strategy on behavior intentions of travelers with lower levels of need for cognition is mediated by the airlines’ reputations, as proposed in the SCCT (Coombs 2007). Therefore, the following two hypotheses are proposed:

Hypothesis 3: Travelers’ need for cognition significantly moderates the relationship between the crisis response strategy and booking intentions, such that travelers who have lower levels of need for cognition express higher booking intentions when exposed to tweets with an enhancing response strategy (v.s. a bolstering strategy), whereas those with higher levels of need for cognition are not influenced by the crisis response strategy.

Hypothesis 4: Travelers’ need for cognition significantly moderates the mediation effects of airline reputation on the relationship between the crisis response strategy and booking intention, such that airline reputation mediates the effect of an enhancing response strategy (vs. a bolstering strategy) on booking intentions among travelers with lower levels of need for cognition, whereas the mediation effect is mitigated among travelers with higher levels of need for cognition.

Other-Orientation

Meglino and Korsgaard (2004) introduced the concept of other-orientation as an addition to classical behavioral theories that assume that individuals will act in accordance with their self-interests. Other-orientation is defined as an individual’s dispositional tendency to be concerned for and helpful to other people (Meglino and Korsgaard 2004). People with higher levels of other-orientation not only exhibit more pro-social or altruistic personality traits and behaviors, but also focus on group-related cues in information processing (De Dreu and Nauta 2009). In the context of organizational science, other-orientation has been found to significantly moderate the relationships between self-evaluations and job performance (Grant and Wrzesniewski 2010); group-level job attributes and pro-social behavior (De Dreu and Nauta 2009); job satisfaction and organizational citizenship behavior (Lester, Meglino, and Korsgaard 2008); and perceptions of overall justice and forgiveness of an unfair event (Bobocel 2013).

In marketing research, other-orientation and self-interest are used to segment consumers, especially when predicting their consumption of sustainable products (Ross and Milne 2021). Ross and Milne (2021) found that consumers high with high levels of other-orientation prefer the sustainability attributes to the price attributes of a product. Grappi, Romani, and Bagozzi (2013) found that other-orientation strengthens the relationship between perceived corporate ethical transgression and consumers’ negative word of mouth and protest behaviors. Similarly, Bridoux, Stofberg, and Den Hartog (2016) found that consumers with high levels of other-orientation prefer an organization’s CSR initiatives that favor society, whereas consumers with high levels of self-interest are more attracted by an organization’s CSR activities that favor its own stakeholder groups. In a similar vein, as the key difference between the two secondary crisis response strategies is their focus on either the self or society, travelers’ levels of other-orientation are expected to moderate the influence of the crisis response strategy on their behavioral intentions. Specifically, travelers with higher levels of other-orientation may appreciate an enhancing response strategy more, as it focuses on the airline’s public good deeds. This moderation effect is again proposed to be mediated by the airlines’ reputations, as proposed in the SCCT (Coombs 2007). Thus, the last two hypotheses are given as follows:

Hypothesis 5: Travelers’ levels of other-orientation significantly moderate the relationship between the crisis response strategy and booking intentions, such that travelers with higher levels of other-orientation express higher booking intentions when exposed to tweets with an enhancing strategy (vs. a bolstering strategy), whereas those with lower levels of other-orientation are not influenced by the crisis response strategy.

Hypothesis 6: Travelers’ levels of other-orientation significantly moderate the mediation effects of the airlines’ reputations on the relationship between the crisis response strategy and booking intentions, such that airline reputation mediates the effect of an enhancing response strategy (vs. a bolstering strategy) on booking intentions among travelers with higher levels of other-orientation, whereas the mediation effect is mitigated among travelers with lower levels of other-orientation.

The research framework (Figure 1) was tested in three studies that used a multi-method design: one secondary data study and two experimental studies. Study 1 content analyzed four airline Twitter pages to test the main effect stated in H1. As a further test of the effects evidenced in Study 1, Study 2 conducted an online experiment to examine both the main and mediation effects in H1 and H2. The moderating effects of the need for cognition (H3) and the moderated psychological mechanism via airline reputation (H4) were also investigated in Study 2. Finally, Study 3 replicated and expanded Study 2 to examine the moderating effects of travelers’ other-orientation (H5) and the corresponding moderated mediation effects via airline reputation (H6).

Figure 1.

Research framework.

Study 1—Airlines’ Twitter Communication Strategies and Likes

Objectives & Data

To examine airlines’ Twitter communication strategies and the effects of enhancing vs. bolstering crisis response strategies on likes (H1), a total of 1,179 tweets posted by four major U.S. airline companies (American, Delta, Southwest, and United; Salas 2021) in 2020 were manually collected from Twitter. The descriptive information of the collected tweets is displayed in Table 1.

Table 1.

Total Tweets Collected.

Month	American	Delta	Southwest	United	Total
Jan	20	16	32	18	86
Feb	25	11	40	27	103
Mar	30	28	29	18	105
Apr	28	21	22	38	109
May	39	14	22	21	96
Jun	25	4	24	10	63
Jul	29	14	30	23	96
Aug	23	16	36	22	97
Sep	23	16	37	29	105
Oct	25	14	34	32	105
Nov	32	12	41	21	106
Dec	32	11	29	36	108
Total	331	177	376	295	1,179

Coding

For each tweet, the collected information included the tweet message, the airline that posted the tweet, the posted date, and the number of likes. The collected tweets were then coded according to the categorization framework in the SCCT (Coombs 2007; Kim and Liu 2012). First, each tweet was coded as either COVID-related or COVID-unrelated based on its content. Each COVID-related tweet was then coded into one of the four response strategies: diminishing, rebuilding, bolstering, and enhancing. The respective definitions, sub-categories, and examples of each of these response strategy categories are given in Table 2. All tweets were coded by two team members and the coding results suggest that inter-rater reliability was satisfactorily high (97.2%).

Table 2.

Crisis Response Strategy Coding Results.

Crisis Response Strategy		Definition and Examples	#
Primary Crisis Response	Diminishing	Argues that the organization lacked control over the crisis (Coombs 2007)	38
	Excuse	High call volume; customer service slow; FAQs	9
	Justification	Schedule adjustment; suspend existing routes; resume routes	29
	Rebuilding	Presents actions that the organization takes to cope with a crisis (Coombs 2007)	318
	Compensation	Waive changing fees; extend loyalty program; promotion of air fare; bonus mileage; extraordinary customer service	94
	Endorsement	Expert endorsement; outside news/research to indicate the low risk of flying during COVID	40
	Prevention	Follow strict cleaning procedures; seat arrangement; touchless technology; mask mandate; rapid testing	184
Secondary Crisis Response	Bolstering	Reminds stakeholders of past good works by the organization (Coombs 2007)	103
	Ingratiation	Current customer testimony; pilot/employee organizational citizenship behaviors	53
	Reminder	Reminder of past travel experiences; call back to fly	44
	Victimage	Call for government relief to support airline jobs	6
	Enhancing	Focuses on the organizations’ public good deeds during the crisis (Kim and Liu 2012)	102
	Appreciation	Showing appreciation for medical service providers	15
	Collaboration	Support other CSR, e.g., Red Cross, Food bank, WHO	36
	Goodwill	Company initiated COVID-related CSR, e.g., deliver medical cargo; bring Americans home; transport medical workers	51
	Total:		561

Note: bold numbers represent category totals.

Analysis & Results

Panel regression analysis was employed to explore the effects of crisis response strategy on the number of likes received. The total number of each airline’s COVID-related tweets and the number of tweets posted within each response strategy were aggregated on a monthly basis. To control for crisis severity (Coombs and Holladay 2002), monthly U.S. COVID case numbers were obtained from the Center for Disease Control and Prevention (data.cdc.gov/Case-Surveillance/United-States-COVID-19-Cases-and-Deaths-by-State-o/9mfq-cb36). A total of four different models were employed. Model 1 imposed no control over the number of diagnosed COVID cases, while Model 2 controlled for the number of diagnosed COVID cases. Model 3 controlled for the month, while Model 4 controlled for both the number of diagnosed COVID cases and month. The output of the analysis is summarized in Table 3.

Table 3.

Effects of Crisis Response Strategies on Airlines’ Tweet Likes.

	Model 1	Model 2	Model 3	Model 4
Diminish	0.01(0.27)	0.01(0.23)	0.05(0.79)	0.05(0.72)
Rebuild	−0.01(−0.62)	−0.01(−0.55)	−0.03(−1.09)	−0.03(−1.10)
Bolstering	−0.11* (−2.26)	−0.11(−1.81)	−0.09(−1.76)	−0.12* (−2.12)
Enhancing	0.06* (2.07)	0.06(2.00)	0.06* (2.23)	0.08* (2.53)
COVID-related	0.01(1.14)	0.01(1.10)	0.00(0.91)	0.01(1.05)
Cases		0.00(0.00)		−0.01(−1.17)
Month			0.03(1.01)	0.07(1.55)
_cons	5.96*** (41.92)	5.96*** (40.23)	5.85*** (31.80)	5.75*** (28.68)
N	48	48	48	48
R-sq	0.18	0.18	0.20	0.23
adj. R-sq	0.01	–0.02	0.01	0.02
AIC	57.66	59.66	58.39	58.65
BIC	68.89	72.76	71.49	73.62

t statistics in parentheses: *p < .05; ** p < .01; *** p < .001.

The results of the analysis suggest that the enhancing strategy is positively related to the number of likes received. At the same time, the bolstering strategy is negatively related to the number of likes received. The rebuilding and diminishing strategies were not significantly related to the number of likes received. These results confirm H1.

Study 2—The Moderating Role of Travelers’ Need for Cognition

Objectives & Design

To test H2 and H3, Study 2 was conducted using a one-factor two-level (secondary response strategy: bolstering vs. enhancing) between-subjects design. Participants were randomly assigned to either a bolstering or an enhancing response strategy condition. The development of the manipulation for the secondary response strategy in the bolstering versus enhancing conditions was inspired by field practices (i.e., airlines tweets collected in Study 1). Travelers’ need for cognition as the moderating variable was measured.

Stimuli

The study asked participants to imagine themselves in a hypothetical travel planning scenario during the peak of the pandemic (summer of 2020). After giving a short briefing that explained the severity of the pandemic, participants were asked to imagine themselves flying with a hypothetical airline company, XYZ Airlines, for an upcoming trip. Participants were then directed to view the Twitter profile of XYZ Airlines, which features several tweets framed using either a bolstering strategy or an enhancing strategy. To ensure field realism, the tweets mimicked the actual tweets of the airlines included in Study 1 (Appendix 1).

Measures

After viewing the Twitter profile page, participants were asked to answer a series of questions, all of which made use of a 7-point Likert-like scale anchored from 1 representing strongly disagree to 7 representing strongly agree. Booking intention was measured using three items adapted from Coombs and Holladay (2007) (Cronbach’s alpha = 0.80). Airline reputation was measured using four items adapted from Ponzi, Fombrun, and Gardberg (2011) (Cronbach’s alpha = 0.65). The need for cognition was measured using four items adapted from Cacioppo, Petty, and Kao (1984) (Cronbach’s alpha = 0.77). The measurement scales are attached in Appendix 2. In addition, participants were also asked to answer a few demographic questions about their age, gender, education, and income. Finally, manipulation check and realism check questions were included, the measures and results of which are reported in the respective sections below.

Sample

Participants of the study were recruited from Amazon Mechanical Turk. To be included in the study, participants must have (1) been U.S.-based, (2) been at least 18 years old, (3) taken a flight in 2020, and (4) used a Twitter account. To ensure that the participants were paying adequate attention to the study, a few choice-based scenario recall questions and attention check questions were employed. Those who failed to correctly answer these questions were filtered out of the study. In the end, a total of 198 complete responses were collected. With an average age of 34 years old, the sample consisted of about 74% males and 25% females and was around 72% Caucasian. About 90% of respondents held a bachelor’s degree, and approximately 73% had an annual household income of $40,000 or more.

Manipulation & Realism Check

To assess if the manipulation successfully yielded the intended difference in self- vs. society-serving perceptions as conceptualized, participants were asked, “In your perception, XYZ Airline seems to be. . .?” This question used a 7-point scale adapted from Bolton and Mattila (2015) (1—Self-serving; 7—Society-serving). Results from the independent t-test suggest that participants in the enhancing condition perceived the airline more society-serving than their counterparts assigned to the bolstering condition (M_enhancing = 5.74, M_bolstering = 5.19; t = 2.66, p < .01). As a result, the manipulation was successful.

To assess the perceived realism of the stimuli, participants were asked about the degree to which they agreed that the scenario was realistic and the ease with which they could project themselves into the scenarios. The results suggest that participants across conditions universally perceived the stimuli as highly realistic (M_enhancing = 5.23, M_bolstering = 4.99; t = 1.28, p = .20) and that it was easy for them to self-project into the scenario (M_enhancing = 5.38, M_bolstering = 1.55; t = 2.66, p = .12).

Main & Mediation Effects

After controlling for previous flight experience (Coombs and Holladay 2002), the ANCOVA results revealed a significant main effect for response strategy on booking intention (F = 5.06, p < .05). As proposed in H1, participants who were exposed to tweets with an enhancing response strategy expressed higher booking intentions (M_enhancing = 4.84) than those exposed to tweets with a bolstering response strategy (M_enhancing = 4.57).

To test the mediation effect of airline reputation, PROCESS Model 4 (Hayes 2018) was conducted by controlling for previous flight experience. The model specified response strategy (i.e., bolstering vs. enhancing) as the independent variable, booking intention as the outcome variable, and airline reputation as the mediating variable. The results indicated that airline reputation fully mediated the effect of response strategy on booking intention (indirect effect = 0.19, 95% CI [0.05, 0.34]). Thus, both H1 and H2 were supported.

Moderation & Moderated Mediation

To test H3, a moderation analysis was conducted using PROCESS Model 1 (Hayes 2018). The model specified response strategy (i.e., bolstering vs. enhancing) as the independent variable, booking intention as the outcome variable, and travelers’ need for cognition (measured continuous variable) as the moderating variable. Although the interaction effect was not significant at the conventional criteria 0.05 level, conditional effects suggest that the positive effect of an enhancing (vs. bolstering) response strategy on booking intention was significant only among participants with low levels of need for cognition (−1SD from the mean) (effect = 0.56, t = 2.32, p < .05). Among participants with high levels of need for cognition (+1SD from the mean), the positive effect of an enhancing (vs. bolstering) response strategy was attenuated (effect = 0.15, t = 0.61, p = .55). Therefore, H3 was supported.

Next, to test H4, a moderated mediation analysis was conducted using PROCESS Model 8 (Hayes 2018) using response strategy (i.e., bolstering vs. enhancing) as the independent variable, booking intention as the outcome variable, travelers’ need for cognition (measured continuous variable) as the moderating variable, and airline reputation as the conditional mediating variable. The results of the analysis suggest that the indirect effect via the airline’s reputation was significant only among participants with low levels of need for cognition (−1SD from the mean) (effect = 0.33, 95% CI [0.11, 0.57]) but attenuated among participants with low levels of need for cognition (+1SD from the mean) (effect = −0.01, 95% CI [−0.24, 0.17]). As a result, H4 was supported as well.

Study 3—The Moderating Role of Travelers’ Other-Orientation

Objectives & Design

As Study 2 explored the impacts of secondary crisis response strategies on travelers’ intentions during a crisis, Study 3 replicated and expanded the experiment design to examine this relationship in a post-pandemic world. Similarly, Study 3 employed a one-factor two-level (secondary response strategy: bolstering vs. enhancing) between-subjects design. As in Study 2, participants were randomly assigned to either a bolstering or an enhancing response strategy condition. Travelers’ other-orientation was then measured as the moderating variable.

Stimuli

In this study, participants were asked to imagine themselves in a hypothetical travel planning scenario during the last phase of a pandemic. In this phase of the pandemic, considerable numbers of vaccine doses have been administered. Participants were asked to consider flying with a hypothetical airline company, XYZ Airlines, for an upcoming trip. They were then shown a tweet from this airline that was framed in either a bolstering strategy or an enhancing strategy. The bolstering condition tweet highlighted XYZ Airlines’ commitment to service in 2020, while the enhancing condition tweet featured the airline’s society-serving efforts in 2020. The study stimuli are attached as Appendix 3.

Measures

After viewing the Twitter profile page, participants were asked to answer a series of questions. Booking intention (Cronbach’s alpha = 0.72) and airline reputation (Cronbach’s alpha = 0.78) made use of the same measurement scales as those in Study 2. Four items were used to measure other-orientation. These questions made use of a 7-point Likert scale and were adapted from Agle, Mitchell, and Sonnenfeld (1999) (Cronbach’s alpha = 0.79). The measurement scales are attached in Appendix 2. As in Study 2, participants were also asked about their age, gender, education, and income. Manipulation- and realism-check questions were also administered, and the results are reported in the respective sections below.

Sample

Participants of the study were recruited from Amazon Mechanical Turk and subjected to the same qualification criteria as devised in Study 2. A few choice-based scenario recall questions and attention check questions were employed to ensure that the participants were adequately attentive in the study process. As in Study 2, those who failed to correctly answer these questions were filtered out of the study. In total, 207 complete responses were collected. On average, participants were 35 years old. The gender distribution of the sample was approximately 66% male and 34% female. In addition, around 74% of the sample was Caucasian, with about 91% having obtained a Bachelor’s degree and about 80% with an annual household income of $40,000 or more.

Manipulation & Realism Check

The same manipulation check question in Study 2 was used to assess if the manipulation of crisis response strategy yielded the intended difference in self- versus society-serving perceptions as conceptualized. The results suggest that participants in the enhancing condition perceived the airline more society-serving than their counterparts assigned to the bolstering condition (M_enhancing = 5.92, M_bolstering = 5.17; t = 3.89, p < .001). Therefore, the manipulation was successful.

The realism check questions were the same as those adopted in Study 2. The results suggest that participants across conditions universally perceived the stimuli as highly realistic (M_enhancing = 5.31, M_bolstering = 5.14; t = 1.11, p = .27) and that it was easy for them to project themselves into the scenario (M_enhancing = 5.41, M_bolstering = 5.23; t = 1.10, p = .28).

Main & Mediation Effects

After controlling for previous flight experience (Coombs and Holladay 2002), the ANCOVA results revealed a marginally significant main effect for response strategy on booking intention (F = 3.29, p < .1). As proposed in H1, participants who were exposed to tweets with an enhancing response strategy expressed higher booking intentions (M_enhancing = 5.36) than those exposed to tweets with a bolstering response strategy (M_enhancing = 5.14).

To test the mediation effect of airline reputation, PROCESS Model 4 (Hayes 2018) was conducted by controlling for previous flight experience. The results indicated a non-significant mediating effect of airline reputation (indirect effect = 0.12, 95% CI [−0.05, 0.28]). Thus, H1 was supported while H2 was rejected.

Moderation & Moderated Mediation

To test H5, a moderation analysis was conducted using PROCESS Model 1 (Hayes 2018). The interaction effect was significant (coefficient = 0.27; t = 2.63, p < .01). Further, the conditional effects indicated that the positive effect of an enhancing (vs. bolstering) response strategy on booking intention was significant only among participants with high levels of other-orientation (+1SD from the mean) (effect = 0.46, t = 3.35, p < .01). Among participants with low levels of other-orientation (−1SD from the mean), the positive effect of an enhancing (vs. bolstering) response strategy was attenuated (effect = −0.08, t = −0.54, p = .59). Therefore, H5 was supported.

Finally, to test H6, a moderated mediation analysis was conducted using PROCESS Model 8 (Hayes 2018). The results of the analysis suggest that the indirect effect via the airline’s reputation was significant only among participants with high levels of other-orientation (+1SD from the mean) (effect = 0.19, 95% CI [0.06, 0.34]). On the other hand, this indirect effect was attenuated among participants with low levels of other-orientation (−1SD from the mean) (effect = −0.01, 95% CI [−0.22, 0.21]). Therefore, H6 was supported as well.

Discussion and Conclusion

General Discussion

The ongoing COVID-19 pandemic is an unprecedented and full-fledged global crisis for air transportation. Since the beginning of the crisis, the airline sector has been one of the most severely-impacted industries (Airports Council International 2021). However, few studies have investigated the airlines’ crisis response strategies to recover from COVID-19. Drawing on the SCCT, the current research focuses on the airlines’ crisis communication via social media platforms when facing low-responsibility crises and explores the underlying mechanism through which secondary crisis response strategies affect airlines’ reputations and travelers’ behavior intentions. A multi-method design consisting of three studies was conducted to improve the validity and strengthen causal inferences of the study results. The hypothesis testing results are summarized in Table 4.

Table 4.

Summary of Hypothesis Testing.

Hypothesis		Study 1	Study 2	Study 3
H1	Enhancing strategy → a. More likes, b. Higher booking intention	Supported	Supported	Supported
H2	Response strategy → Airline reputation → Booking intention	--	Supported	Rejected
H3	Response strategy × need for cognition → Booking intention	--	Supported	--
H4	Response strategy × need for cognition → Airline reputation → Booking intention	--	Supported	--
H5	Response strategy × Other-orientation → Booking intention	--	--	Supported
H6	Response strategy × Other-orientation → Airline reputation → Booking intention	--	--	Supported

This study first investigated travelers’ responses toward two secondary response strategies (bolstering vs. enhancing) adopted by airlines when experiencing low-responsibility crises. The results revealed that, when compared to a bolstering response strategy, an enhancing response strategy is more effective at eliciting Twitter likes and generating higher booking intentions. This study corroborates the results of previous studies that explored the effects of crisis communication via social media (e.g., Avraham 2015; Möller, Wang, and Nguyen 2018). It also empirically supports the SCCT, which suggests that businesses should match their crisis response strategies with different crisis types (Coombs and Holladay 2002) in the context of airline crisis communication. As expected, since COVID-19 attributes little responsibility to the airlines, an enhancing response strategy that emphasizes airlines’ contribution to the public’s well-being results in more favorable attitudinal and behavioral responses (Kim, Avery, and Lariscy 2011). However, the results of the mediating effect of airline reputation were mixed. Specifically, the results of Study 2 confirmed that airline reputation mediates the relationship between the secondary crisis response strategies and travelers’ booking intentions, as suggested by the SCCT (Coombs 2007), but the mediating role of airline reputation was not found in Study 3. In Study 2, respondents imagined themselves in a travel planning scenario during the peak of a pandemic, whereas those participating in Study 3 imaged themselves in a scenario during the tail phase of a pandemic in which the majority of the population is fully vaccinated. Cairns, de Andrade, and MacDonald (2013) tested that the role of organizational reputation on the effectiveness of crisis communication is moderated by the timing of communication. Therefore, different phases of the pandemic tested in Study 2 and Study 3 could explain why the results varied. At the tail phase of a pandemic, people’s depression and anxiety levels toward COVID-19 have declined (Shuster et al. 2021). Since people are adapting to the COVID-19 “new normal” (Corpuz 2021), the influence of airline reputation on crisis communication is limited as the severity of the crisis decreases.

Furthermore, this study examined the role of two moderators: the need for cognition and other-orientation. Previous studies indicated that people’s need for cognition affects the effectiveness of persuasive communications due to different information processing approaches (Cacioppo and Petty 1982). This study furthers this research by demonstrating that the way travelers perceive online crisis communication messages is conditioned by their need for cognition. As in other studies (e.g., Sicilia, Ruiz, and Munuera 2005; Zhang and Buda 1999), this study illustrates that individuals who are low in need for cognition process information more heuristically and are greatly influenced by peripheral cues. These findings suggest that an enhancing response strategy (vs. a bolstering strategy) triggers more favorable behavioral outcomes among those with a lower level of need for cognition since the crisis response strategy acts as a peripheral cue that helps them quickly recognize how well airlines respond to this unprecedented crisis. On the other hand, individuals exhibiting a greater need for cognition tend to think critically and focus more on the real attributes of the response messages (Lu, Gursoy, and Lu 2016; Sicilia, Ruiz, and Munuera 2005), which causes them to have no preference for either an enhancing or bolstering response strategy. Moreover, the indirect influence of an enhancing response strategy on behavior intentions via airline reputation is significantly higher for travelers exhibiting less need for cognition, which is in line with SCCT (Coombs 2007).

This study also uncovers that other-orientation moderates the direct and indirect relationships between the crisis response strategy and booking intention. The booking intention of travelers with higher levels of other-orientation is significantly higher when they are exposed to tweets with an enhancing response strategy that focuses on airlines’ acts of kindness in the era of COVID-19. For those who care less about others, this effect is not significant. The findings confirm previous research that found that other-oriented people focus more on group-level attributes and prioritize society-focused messages (De Dreu and Nauta 2009), while less other-oriented people focus more on themselves, with little attention paid to others (Bridoux, Stofberg, and Den Hartog 2016). As suggested in the SCCT (Coombs 2007), the moderation effect of other-orientation is found to be mediated by airline reputation.

Theoretical Implications

The current research highlights the value of crisis response strategies and contributes to several streams of the hospitality and tourism literature in general and the airline context in particular. First, this study innovatively incorporates and extends the SCCT by exploring the role of secondary crisis response strategies in responding to low-responsibility crises. The SCCT emphasizes three types of primary crisis response strategies: denial, diminishing, and rebuilding (Coombs 2007). However, as primary crisis response strategies ignore the public’s well-being (Kim, Avery, and Lariscy 2011), these strategies do not completely alleviate the negative influence of crises (Ma and Zhan 2016). Thus, this study broadens the scope of the SCCT by examining and comparing the effectiveness of two secondary crisis response strategies: bolstering and enhancing. Moreover, the current study shifts the focus of the analysis away from high-responsibility crises (e.g., Greer and Moreland 2003; Haruta and Hallahan 2003; Massey 2005; Ma et al. 2019) to assess airlines’ responses in a low-responsibility crisis setting like COVID-19.

Second, this study expands the boundary of the SCCT and contributes to the discussion on the influence of crisis response strategies on travelers’ behavioral responses by investigating two moderators: the need for cognition and other-orientation. Previous crisis management research has mostly overlooked the moderating role of personality traits in influencing the effectiveness of crisis response strategies (Coombs 2016). As a result, by integrating the need for cognition and other-orientation as moderators, this study examined relationships that were previously overlooked and deepened our understanding by offering a holistic view of the effect of crisis communication.

The third contribution of the current research was the use of a multi-method design. Three studies with an exploratory sequential design were used to answer the postulated research questions. Little prior research had investigated the application of secondary crisis response strategies in airline crisis communication, justifying the exploratory qualitative portion of this research. Qualitative data was collected in the exploratory stage and was followed up by a quantitative portion, allowing for the generalization of the findings (Cresswell and Plano Clark 2007).

Managerial Implications

The findings may guide airline managers who are in charge of crisis management and social media marketing. From a managerial perspective, airline managers should be aware of the various effects that secondary crisis response strategies may have on travelers. Particularly, the findings of the current research confirm that travelers respond more favorably to an enhancing crisis strategy than to a bolstering strategy. Therefore, when posting a social media message for pandemic relief, airline managers should primarily utilize enhancing crisis response strategies. Essential workers, including healthcare and first responders, are widely thought of as COVID-19 heroes since they offer care and other services to the public during this tough time (Crane and Matten 2020). Thus, posting messages that incorporate an enhancing crisis response strategy to support these frontline heroes may evoke travelers’ good impressions toward airlines, and eventually increase the number of tweet likes and their intentions to book tickets.

The mediating role of airline reputation reveals that creating and maintaining a good reputation is beneficial for airlines’ crisis communication. To minimize the impact of the crisis, developing response messages aimed at triggering airline reputation is a promising strategy for eliciting positive responses from travelers. As a result, airlines should tailor the textual and visual contents of social media messages that protect and build their reputations. As a consequence, airlines may be perceived by travelers as a stable and reliable entity (Aula and Mantere 2008), which convinces travelers to trust them at this very critical moment and in turn rewards airlines with positive behavioral responses.

Additionally, the results suggest that the effect of crisis response strategies is conditioned by two personality traits of travelers. Specifically, those with less need for cognition and more other-orientation tend to be affected more by an enhancing response strategy and a better airline reputation, and subsequently, generate a greater intention to book airline tickets. Thus, airline managers should have an in-depth understanding of their target customers and strategically align their crisis communication strategies with the population they intend to attract. The use of an enhancing response strategy is recommended if the airline intends to deliver their online crisis communication in cultural environments that tolerate ambiguity but encourage other-orientation. However, efforts may be wasted when airlines want to attract future passengers in cultures that foster cognitive thinking and self-focus, because there appears to be no difference in their responses toward different secondary crisis response strategies. Furthermore, since the main effect of enhancing response strategies on travelers’ booking intentions is significantly higher, airline managers should prioritize the use of an enhancing response strategy in cultures that do not clearly favor or discourage either of these two personality traits.

Limitations and Future Research

The current research has several limitations. This study selected tweets from four major U.S. airlines, and then created hypothetical tweets as stimuli in the two experiments. However, many businesses, including airlines, post-crisis response messages in responding to COVID-19 on various social media platforms, such as Facebook, Twitter, and Instagram (Arora et al. 2019). The posts on other platforms may require different strategies to capture followers’ attention and positively influence them (Lee and Theokary 2021). Thus, future studies might conduct follow-up studies that include more domestic and international airlines, and examine crisis response strategies on different social media platforms. Our study uses airlines experiencing COVID-19 as an example of a low-responsibility crisis and exclusively tests the effects of secondary crisis response strategies. Future research could extend the proposed framework to the context of other tourism sectors as well as other types of low-responsibility crises, such as inclement weather. In addition, travelers’ reactions to airlines’ social media posts can be affected by various factors. Tan et al. (2021) indicated that one’s information processing method shapes their reaction toward the social media post. As a result, studying the effect of social media users’ information processing approaches, such as different types of heuristics, could be a future research direction. This topic is especially important as individuals are in “information overload” during crises (Imran et al. 2015). Finally, this study employed booking intention as a proxy of travelers’ actual behavior to book an airline ticket. Nevertheless, several studies argued that travelers’ behavioral intention is not a reliable predictor for their actual behavior (e.g., McKercher and Tse 2012). Besides, during the pandemic, travelers’ intention is influenced by their health concerns and the measures to slow the spread of COVID-19, including social distancing, stay-at-home order, and travel restrictions (Shin et al. 2022). Thus, future studies that use sale data as a measure of actual behavior may improve the validity of this study.

Footnotes

Appendix

Appendix 2.

Measurement Items for Study 2 and Study 3.

Constructs & Measurement Items	Cronbach’s Alpha
Constructs & Measurement Items	Study 2	Study 3
Booking intention (Coombs and Holladay 2007)	0.80	0.72
It is very likely that I would fly with XYZ Airline.
The probability that I would consider flying with XYZ Airline is very high.
I am willing to fly with XYZ Airline.
Airline reputation (Ponzi, Fombrun, and Gardberg 2011)	0.65	0.78
Airline XYZ is a company I have a good feeling about.
Airline XYZ is a company that I trust.
Airline XYZ is a company that I admire and respect.
Airline XYZ has a good overall reputation.
Need for cognition (Cacioppo, Petty, and Kao 1984)	0.77	N/A
I would prefer complex to simple problems.
I like to have the responsibility of handling a situation that requires a lot of thinking.
I really enjoy a task that involves coming up with new solutions to problems.
I would prefer a task that is intellectual, difficult, and important to one that is somewhat important but does not require much thought.
Other-orientation (Agle, Mitchell, and Sonnenfeld 1999)	N/A	0.79
working for the welfare of others
feeling empathy for others
equal opportunity for all
being affectionate

Acknowledgements

We thank Montserrat Diaz Reyes, Marthina Orso Tondo, Natalie Tran, and Le Bich Ngoc Vo for their manual data collection from Twitter.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Xi Y. Leung

Author Biographies

Xi Y. Leung, Ph.D., is an assistant professor in the Department of Hospitality and Tourism Management at the University of North Texas. Her fields of expertise include destination marketing, social media, consumer behavior, hospitality management, and experiment design.

Laurie Wu, Ph.D., is an associate professor in the School of Sport, Tourism and Hospitality Management at Temple University. Her research focuses on service experience design & marketing as well as service technology & innovation in the tourism and hospitality industry.

Jie Sun, Ph.D., is an assistant professor in the Collins College of Hospitality Management at California State Polytechnic University, Pomona. Her research focuses on consumers’ perceptions and behavioral response to various marketing strategies, particularly in the context of meetings and events.

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