Matching Crisis Event With Destination Response Strategy

Abstract

A conceptual model is tested across four studies that examine how tourist destination crisis types (external/internal) impact the information processing mode (heuristic/systematic), internal state (empathy/animosity), and boycott intentions of tourists. The matching effect between destination crisis event type and response strategy (defensive/accommodative) are also examined. Results suggest that internally attributed destination crisis events may be more likely to lead to boycott, and tourists tend to employ a heuristic information processing mode for externally attributed crises but a systematic mode for internally attributed crises. The matching effect of destination crisis type with response strategy indicated that a defensive (accommodative) strategy may effectively weaken the negative effects of externally (internally) attributed crises. Discerning the nature and perceived causes of crisis events offers a means to pinpoint approaches for guiding response strategies to mitigate the likelihood of boycotts and inform effective strategies for handling a destination crisis.

Keywords

crisis event tourism destination heuristic/systematic mode crisis response strategy matching effect

There continue to be crisis events worldwide (e.g., natural disasters associated with climate change, COVID-19, regional conflicts) reported to result in negative economic, social, and environmental impacts (Alvarez et al., 2022; Duan et al., 2022; Su, Pan, & Huang, 2023). Tourist destinations are not immune to crisis events, which are unavoidable and becoming more frequent (Farmaki, 2021). Jin et al. (2019) suggest that anything unforeseen that impacts the sustained routine operation of, or threatens tourists’ confidence in, a destination would qualify as a destination crisis event. These events can severely disrupt the sustainable operation of tourism destinations, threatening the development of related industries and even entire regions, making crisis management an important area of tourism research (Wut et al., 2021).

Crisis events can act to weaken the emotional ties between tourists and a destination, resulting in travel changes, including boycotts (Q. Luo & Zhai, 2017). As such, Pan et al. (2021) suggest that there is a practical and theoretical need for further investigations into the relationship between destination crisis events and tourists’ behavioral responses. If individuals perceive that the responsibility for a crisis is outside (within) the boundaries of an organization, they would be more likely to perceive it as an external (internal) crisis. Following recent suggestions (Su et al., 2022; Su, Pan, & Huang, 2023), attribution theory is utilized to categorize tourism destination crisis events (external/internal) to examine the differential impact of crisis event type on the information processing mode and boycott intentions of tourists.

The Heuristic/Systematic Information Processing Model

Information processing mode is defined as “the behavioral path that information users [use to] process the acquired information, which determines the way they use and make decisions” (Aliperti & Cruz, 2019, p. 3). In crisis situations, how an individual processes crisis-related information acts as a prerequisite for the formation of an internal response and subsequent behavioral intentions (Tan et al., 2018). Dunwoody and Griffin (2015) note that according to the dual-process paradigm of decision making, individuals will engage in one of two distinct information processing modes: heuristic or systematic. Under the heuristic mode, individuals rely on intuitive cues, memories, experiences, feelings, and other readily available signals to arrive at judgment results (Dunwoody & Griffin, 2015). Under the systematic mode, individuals actively try to evaluate and understand the opinions and content of information from multiple perspectives (Cahyanto et al., 2016). The heuristic/systematic information processing model (HSM) provides a theoretical framework for understanding individual information processing, internal states, and behavioral responses (P. Luo et al., 2021; Ryu & Kim, 2015; Zhang et al., 2023). This model emphasizes an individual’s ability to switch between information processing modes by mobilizing varying degrees of cognitive processing capacity in different contexts (Chaiken, 1980). When individuals use fewer cognitive resources, they are more inclined to activate the heuristic information processing mode. When individuals utilize greater cognitive processing capacity, they are more inclined to rely on systematic information processing. The HSM suggests that when faced with different types of crises, individuals will choose either a heuristic or systematic information processing mode, which will impact that individual's internal state and behavioral response(s) (Aliperti & Cruz, 2019; Zhang et al., 2023). The dual-pathway influence mechanism of tourists’ acceptance and processing of different types of crisis incident information on their internal states and behavioral intentions deserves further investigation as a way to provide new insights for managing destination crises (Aliperti & Cruz, 2019; P. Luo et al., 2021; Zhang et al., 2023).

Internal Affective States

The examination of individual affect is crucial for understanding individual behavioral changes related to crisis situations (Tan et al., 2018). Su et al. (2022) point out that rather than a general focus, it is important that researchers shift to a more detailed examination of the potential mediating effects that factors such as betrayal, animosity, sympathy, and empathy may play in the relationship between crisis events and subsequent behavioral reactions. From organizational studies, it has been reported that when a person perceives that an organization bears little responsibility for a crisis situation, that individual is more likely to adopt a heuristic information processing mode which leads to an automated affective response (Dhar & Corlin, 2013). Empathy, an automatic and uncontrollable mental process that allows individuals to understand the situation of others, has been identified as arising from the heuristic information processing mode (Lee et al., 2014). If an individual attributes primary responsibility to an organization for a crisis, they are more inclined to adopt a systematic mode of information processing (Zhao et al., 2019). Animosity, a strong feeling of opposition or dislike, is a common outcome of someone following a systematic information processing mode (Breitsoh & Garrod, 2016). Thus, the systematic mode and animosity might also have the serial mediating role between crisis events and tourist behavior. According to the HSM, information processing mode impacts affect, both of which act to mediate the effects of external stimuli on individual behavior (Zhang et al., 2023). However, the relationship between information processing mode and individual internal affective states, and the role they play between destination-based crisis events and the intentions of tourists, including boycotts, have not been fully explored.

Crisis Response Strategies

No organization is immune to experiencing a crisis, making it important to match the most effective response strategy with a specific crisis type (Wei et al., 2020). Crisis response strategy has been defined as “what management says and does after a crisis” to diminish negative impacts and outcomes (Coombs, 2007, p. 170). By adopting a variety of response strategies based on the principle of the more the better, organizations may be expending resources inefficiently while not effectively addressing the negative outcomes associated with mismanaging a crisis situation (Coombs, 2018). If response strategies are not properly aligned with the type of crisis event being faced, it is difficult to fundamentally eliminate the negative impacts of a destination-based crisis on tourists (Q. Luo & Zhai, 2017). Crisis response strategies can include defensive and accommodative approaches (Jeon & Baeck, 2016; Marcus & Goodman, 1991). A defensive strategy can convey that an organization is not at fault, whereas an accommodative approach demonstrates the determination to atone. While both approaches may be effective, Kähr et al. (2016) suggest that outcomes to an implemented strategy will vary based on the type of crisis event being responded to.

The Matching Effect

Prior studies have suggested that sincere apologies and economic compensation after a crisis are likely to alleviate consumer anger, achieve consumer understanding, and reduce individual extreme behavior (Wei et al., 2020). However, for some crisis types (i.e., external) a destination could be regarded as a victim. In such situations, apologies and compensation might be viewed as a sign of organizational incompetence which could result in consumer disgust or extreme negative behavior (Ma & Zhan, 2016). Thus, response strategies that fail to match attributions of responsibility for crisis situations may lead to individuals incorrectly interpreting crisis-related information, making it difficult to achieve the desired effect of the implemented response strategy (Zhang et al., 2023). Therefore, it is also important to explore the matching effect of destination crisis events and response strategies, as well as the mechanism of their interaction on tourists’ behaviors, which is lacking in existing research (M. Yu et al., 2022).

Research Approach and Contributions

This study employs the HSM framework to create and validate a conceptual model aimed at investigating the influence of various types of destination crisis events (external/internal) on factors such as information processing approach (heuristic/systematic), internal emotional state (empathy/animosity), and tourists’ intentions to boycott. Additionally, the study examines how the compatibility between the type of destination crisis event and the chosen response strategy (defensive/accommodative) plays a role. The research comprised four separate experiments. The first two studies employed distinct destination crisis event scenarios and participant samples to analyze how different types of crisis events impact tourists’ chosen information processing approaches, internal emotional states, and intentions to boycott. Studies 3 and 4 delve into the alignment between destination crisis events and response strategies to further enhance the understanding of these dynamics.

This research offers multifaceted contributions to the body of literature concerning destination crisis management. First, it employs attribution theory to classify crisis events in tourism destinations as either externally or internally attributed. This categorization serves as a means to investigate the distinct effects of each crisis event type on intentions to boycott. Secondly, the research delves into the sequential mediation mechanisms enacted by information processing modes (heuristic/systematic) and internal states (empathy/animosity) in the relationship between destination crisis events and tourism boycott intentions, using the HSM framework. Serial mediation is used to examine how an independent variable traverses multiple mediators before impacting a dependent variable. Exploring serial mediating mechanisms provides a comprehensive and systematic way to better understand the relationship between independent and dependent variables. Notably, this exploration is guided by prior studies (e.g., Wei et al., 2020; Zhang et al., 2023). Moreover, the study identifies a matching effect between crisis response strategies (defensive/accommodative), destination crisis even types (external/internal), and the moderating impact of crisis response strategies on tourists’ information processing modes, internal states, and behavioral intentions. This investigation not only provides valuable theoretical insights but also furnishes practical implications for destination management organizations (DMOs) on crisis mitigation strategies.

Theoretical Framework, Literature Review, and Hypotheses Development

Heuristic/Systematic Information Processing Model (HSM)

The manner in which an individual processes information “determines the way they use and make decisions” (Aliperti & Cruz, 2019, p. 3). The dual-process paradigm of decision making suggests that there are two different information processing modes that are commonly used (Dunwoody & Griffin, 2015): heuristic and systematic (Chaiken, 1980). Eagly and Chaiken (1993) deﬁned the heuristic mode as “a limited mode of information processing that requires less cognitive resources” (p. 327). The systematic mode has been described as an information processing mode in which “recipients exert considerable cognitive effort” as “they actively attempt to comprehend and evaluate the message’s arguments” (Chaiken, 1980, p. 752).

The heuristic/systematic information processing model (HSM) is a persuasion-based dual-process theoretical framework for understanding individual information processing (Ryu & Kim, 2015). The model suggests that individuals can process information in one of two ways: heuristically or systematically. Thus, information processing acts as an antecedent to an individual’s internal states, and behavioral responses. An important strength of the HSM is that it is not a theoretical model with a fixed structure composed of a few specific variables; rather, it provides a general framework to explain individual information seeking, information processing, internal states and behavioral intentions, which has strong theoretical scalability and explanatory power (Zhang et al., 2023).

The HSM has been shown to have good applicability for experiential products (Ryu & Kim, 2015) and has been previously applied to understanding individuals’ processing modes and behavioral responses to crisis situations (Zhang et al., 2023). Ryu and Kim (2015) used the HSM to explore individual information processing modes during the Fukushima nuclear accident in Japan. Their findings indicated that a heuristic or systematic information processing mode will be selected based on the nature and type of crisis information provided. Zhang et al. (2023) used the HSM to explore the relationship between different crisis communication sources and intentions to travel. Findings suggested that the mode utilized (i.e., heuristic/systematic) can act to mediate the relationship of shared information about a crisis and respondent perceptions and intentions.

Individuals seek information to make decisions that are beneficial to themselves (Zhang et al., 2023). When presented with different types of information, individuals will utilize a crisis information processing mode (heuristic mode/systematic mode) to help them make decisions. Their feelings, beliefs, and perceptions will also be impacted depending on the mode of information processing chosen, which ultimately influences an individual’s behavioral response (Aliperti & Cruz, 2019; Zhang et al., 2023).

In this research, the HSM is utilized to examine the influence of tourism destination crisis events on tourist boycott intentions. It is proposed that the characteristics of provided information about a crisis at a destination will influence the choice of information processing mode (i.e., heuristic/systematic) followed by tourists. The different information processing mode selected will differentially impact tourists’ affects and boycott intentions.

Destination Crisis Events and Attribution Theory

Coombs (2019) defines a crisis as “an unpredictable event that threatens important expectancies of stakeholders related to health, safety, environmental, and economic issues, which can seriously impact an organization’s performance and generate negative comments” (p. 3). Crisis events have been found to be created by unforeseen events in the external environment, as well as self-errors, both of which may result in serious negative consequences (Wut et al., 2021). The suddenness of occurrence and uncertainty surrounding crisis events may result in relevant stakeholders having to take extraordinary measures to deal with their effects (Ritchie & Jiang, 2019).

Tourism-based industries must frequently respond to crisis events (Farmaki, 2021), resulting in more focus on this topic by tourism scholars (Duan et al., 2022). Sönmez et al. (1994) specify that an incident that compromises the usual operations taking place at a destination, its business functions, and/or visitors’ behaviors/intentions, would represent a crisis. Negative consequences are likely to be the result of a tourism crisis event (Faulkner, 2001).

Different crisis event types may bring about varying effects on tourists’ attitudes and subsequent behaviors toward a destination (M. Yu et al., 2022). Faulkner (2001) divided tourism-based crises into a natural versus man-made dichotomy. Pullig et al. (2006) classify a crisis event based on whether it was due to incompetence or unethical behavior, whereas Duan et al.’s (2022) analysis of “302 articles related to tourism crises from 1991 to 2020” found that “the types of tourism crises are diverse and have multiple subcategories” (p. 667). The lack of a standardized framework to classify crisis events at tourism destinations make interpreting findings from research in this area difficult (Duan et al., 2022).

Negative events are defined as incidents that have “a strong and extensive negative impact” triggered by “the internal products or services of the enterprise, the entire enterprise or individual employees in the marketing process” (Geeta et al., 1999, p. 325). While negative events could be considered a type of crisis event (Su, Chen, & Chen, 2023; Su, Chen, & Lin, 2023), the concept of crisis events is broader and includes incidents triggered by external or internal factors to an organization (Su et al., 2022). Attribution theory has been proposed as a useful guiding framework for looking at crisis events (Su et al., 2022, Su, Pan, & Huang, 2023). External crises would be induced from factors outside the control of a DMO (e.g., natural disasters, pandemics, terrorist attacks), whereas an internal crisis would be attributed to factors perceived to be under the control of a DMO (e.g., service failures, management disruptions). This research addresses the call by Su, Pan, and Huang (2023) for investigating the impact of destination crisis event attributions (internal/external) on tourists’ responses in a more detailed, comprehensive, and in-depth manner that includes tourists’ emotional responses and tourist boycott intentions.

Destination Crisis Event Type Impact on Tourism Boycott Intentions

Friedman (1985) defined a boycott as “an attempt by one or more parties to achieve certain objectives by urging individual consumers to refrain from making selected purchases in the marketplace” (p. 79). In general, a boycott occurs when there is an individual or collective effort to stop purchasing a product. Boycotts are not just the opposite of purchasing behavior. Rather, boycotts are a non-violent passive behavior engaged in by individuals or collectives to force organizations to change what is perceived to be unjust behavior (Su et al., 2022, 2024). Due in part to the widespread use of social media, boycotts have been identified as increasing in frequency as a response to crisis events (Q. Yu et al., 2020).

Boycotts of tourist destinations are becoming more common and can result in significant negative impacts, yet research on tourism boycotting is still in its developmental stage (Q. Yu et al., 2020). Tourism-based boycotts focus on the refusal of tourists, organizations, and/or governmental agencies to support a particular destination (Q. Luo & Zhai, 2017). Su et al. (2022) explicitly define a tourism boycott as “a behavioral intention that tourists stop travelling to a tourism destination and cease communication with the suppliers of tourism products and services they would otherwise have purchased” (p. 3).

Tourists may boycott a destination for crisis events caused by external uncontrollable factors or internal misbehavior (Palacios Florencio et al., 2019). However, an individual may have different response patterns depending on the types of crisis event. For example, boycott behaviors directed toward organizations may vary depending on if a crisis was attributed to organizational failings, or uncontrollable factors in the external environment (Kübler et al., 2020). As such, when attributions change, individuals’ behavioral responses may also change. It is suggested here that there may be differences in the likelihood of supporting a boycott of a tourist destination based on the type of destination crisis event.

External destination crises might be viewed as less controllable as they are triggered by factors outside an organization. Individuals may be more likely to view the destination as a victim, similar to themselves. Perceptions of reduced responsibility thus would act to reduce the willingness to support a boycott of a destination under such circumstances. Destination crises perceived to be due to internal reasons might be viewed by tourists as more controllable and hence assign greater responsibility to the destination for the crisis situation. Increased responsibility for the crisis should increase intentions to boycott.

Hypothesis 1a (H1a): Internally attributed destination crisis events will lead to greater boycott intentions by tourists.

Hypothesis 1b (H1b): Externally attributed destination crisis events will lead to lesser boycott intentions by tourists.

Destination Crisis Event Type and Heuristic/Systematic Information Processing Model

Based on the heuristic/systematic processing framework, it is proposed that differentially attributed types of crisis events (external/internal) may result in tourists choosing different information processing modes (heuristic mode/systematic mode) that then impact their behavioral intentions (Zhang et al., 2023). Receiver motivation is an important antecedent for the information processing mode chosen (Ryu & Kim, 2015). Individuals who choose the heuristic mode have lower motivation to process information and are more inclined to rely on experience and feelings for rapid processing (Dunwoody & Griffin, 2015). Previous research has pointed out that tourists score lower in information seeking and exhibit lower motivation to process information by adopting a heuristic information processing mode for crises generated by uncontrollable factors (Comyns & Franklin-Johnson, 2018). Therefore, it is predicted that tourists will tend to adopt a heuristic information processing mode for externally attributed destination crisis events. Specifically, external crises can be triggered by factors beyond the control of the tourism destination resulting in tourists perceiving the destination to be less responsible for the crisis (Barcelos et al., 2019). As such, tourists may be more likely to view the destination as a victim, have lower processing information motivation, which results in them utilizing a low-level, automated heuristic processing mode (Comyns & Franklin-Johnson, 2018).

Systematic mode is the information processing mode that requires greater cognitive resources. Individuals who choose a systematic mode have greater motivation to process information and actively try to evaluate and understand the views and content of the gathered information from multiple perspectives (Cahyanto et al., 2016). Zhang et al. (2023) point out that for preventable crises (i.e., crises generated by factors under the control of the destination), tourists have greater motivation to process information and tend to adopt a systematic mode. Thus, for internally attributed crises, tourists are more inclined to perceive the destination to have greater responsibility for the negative experiences and be more motivated to process information related to the crisis, thus adopting a systematic information processing approach (Dhar & Corlin, 2013). Overall, it is predicted that the content characteristics of provided information about a crisis at a destination will lead to attributions (external/internal) that influence the information processing mode (heuristic/systematic) utilized by tourists.

Hypothesis 2a (H2a): Tourists are more likely to utilize a heuristic information processing mode for externally attributed destination crisis events.

Hypothesis 2b (H2b): Tourists are more likely to utilize a systematic information processing mode for internally attributed destination crisis events.

The Serial Mediation Effect of Heuristic Mode and Empathy

Xu et al. (2021) define empathy as an “other-oriented emotion elicited by and congruent with the perceived welfare of someone in need” (p. 79). It is our general ability to identify with the emotional state of another, often leading to a sense of connection and compassion that can act to reduce the possibility of engaging in negative behaviors (Lee et al., 2014). Kirmani et al. (2017) report that for product crisis situations, consumers were more likely to demonstrate empathy if responsibility for the crisis was externally attributed. Empathy has also been found to be reduced if one is thought to be responsible for a predicament (Reich et al., 2020). Lee et al. (2014) suggest that empathy can be a common response to crisis situations and may act to mediate the relationship between the attribution of responsibility for a crisis and tourists’ behaviors.

In crisis situations, tourists’ behavioral intentions are based, in part, on how they process perceived risks associated with a destination (Aliperti & Cruz, 2019). Based on the HSM, information processing mode precedes behavioral response. Ryu and Kim (2015) suggest that individual internal states are a direct antecedent to boycott intentions. Both information processing mode and internal states constitute evaluative responses based on an experienced incident, thus playing a serial mediating role between crisis events and behavioral intentions (Zhang et al., 2023). More specifically, when tourists receive information about a crisis at a destination, they will utilize a particular information processing mode and form an affective reaction that influences their intentions to boycott that location.

For externally attributed crises, tourists may be more likely to choose the heuristic processing mode which may be more likely to produce positive affective responses toward the destination (Comyns & Franklin-Johnson, 2018). In situations where the destination is perceived as a victim, empathy can be an automatic, uncontrollable, and intuitive result (Xu et al., 2021). A greater understanding of another’s situation has been found to result in more positive attitudes and weaken tourism boycott intentions (Price et al., 2018). Based on the HSM and extant literature, it is predicted that there will be a serial mediating effect of heuristic information processing mode and empathy as follows.

Hypothesis 3a (H3a): The destination crisis event type relationship with tourism boycott intentions will be serially mediated by the heuristic information processing mode and empathy.

The Serial Mediation Effect of Systematic Mode and Animosity

Klein et al. (1998) define consumer animosity as “antipathy related to previous or ongoing political, military, economic, or diplomatic events” (p. 90). Animosity has also been reported to be a comprehensive understanding that is formed by individuals after thinking about organizational misbehavior (Breitsoh & Garrod, 2016). Studies of animosity have gradually extended from country-specific, to organizations, to general products, including hedonic intangible products such as tourism (Moufakkir, 2014). These studies reflect the universality and breadth of the application of animosity as a negative emotion that may affect one’s consumption experience.

In crisis situations, animosity has also been reported to play an important role in individual behavioral decision-making processes, including the boycotting of products (Alvarez et al., 2022). As the scope of research on animosity has expanded, some researchers have begun to focus on the impact of animosity on tourists’ behavioral decisions (Unger et al., 2021). Misbehavior in the production and operation process of a tourism destination may be more likely to prompt tourists to form stronger feelings of animosity (Stepchenkova et al., 2018). In fact, animosity has been reported to result in more negative attitudes, prompt tourism boycott intentions, and be associated with the systematic information processing mode (Q. Yu et al., 2020).

When a crisis at a destination is internally attributed, that destination may be viewed as more responsible and deserving of condemnation and punishment (Shiv & Fedorikhin, 1999). As such, tourists may be more inclined to adopt a systematic mode to analyze crisis information more deeply in such situations (Su et al., 2022). As previously mentioned, according to the HSM, information processing mode and internal states can act to serially mediate the impact of external stimuli on behavioral responses (Zhang et al., 2023). As such, it is predicted that the impact of a destination crisis event on tourist boycott intentions will be serially mediated by the systematic information processing mode and animosity.

Hypothesis 3b (H3b): The destination crisis event type relationship with tourism boycott intentions will be serially mediated by the systematic information processing mode and animosity.

Crisis Response Strategy as Moderator

There is a growing interest in how service industries such as hospitality and tourism can mitigate the negative impact of crisis events through appropriate response strategies (Wut et al., 2021). Several scholars have classified response strategies as being either defensive or accommodative (e.g., Jeon & Baeck, 2016; Xu et al., 2021). A defensive strategy focuses on avoiding or shifting responsibility away from the organization by conveying a positive message that the organization is not at fault and might include denial, making excuses, or attacking the accuser (M. Yu et al., 2022). An accommodative strategy implies that the destination recognizes its role in a crisis and takes responsibility to proactively address the mistakes it has made. Accommodative strategies might include providing an apology, adjustment, and/or compensation.

Previous studies have focused on functional products and examined the effectiveness of defensive and accommodative strategies in the context of brand transgression, service failure, and product harm, with inconsistent results across crises (Kähr et al., 2016). Using a defensive strategy conveys that the organization is not at fault. Dawar and Pillutla (2000) suggest a defensive strategy that avoids responsibility is more effective than admitting mistakes, which could result in stakeholders forming a negative perception of the organization. Other studies suggest that accommodative strategies convey a sincere commitment to repentance and when supported with concrete actions by the perpetrator, helps consumers form positive expectations and judgments about the organization’s future restorative actions (Kim et al., 2004). Coombs (2018) points out that organizations ought to coordinate their response strategies based on their level of responsibility in a crisis. Without a clear classification of attribution of responsibility for different crisis events, it can be difficult for organizations to know how to respond effectively. Thus, “a crisis with higher attributions of responsibility should be matched with a response strategy that accepts more responsibility, and a crisis with lower situational attributions of responsibility should be matched with a response strategy that accepts less responsibility” (Raithel & Hock, 2021, p. 174). This research follows the suggestion of Ritchie and Jiang (2019) that the relationship between different response strategies and crisis types should be tested.

A defensive strategy may be best suited when dealing with crisis events where there is no apparent organizational responsibility, or where the attribution of responsibility is ambiguous (Dawar & Pillutla, 2000). As such, a defensive strategy might be more effective when matched to a crisis event with lower situational attribution of responsibility, such as an external crisis (Raithel & Hock, 2021). Although an externally attributed crisis will likely still negatively impact the tourist experience, it should be more likely to be perceived as being caused by uncontrollable factors outside the destination. The destination is seen as a victim as they are not perceived to be significantly responsible for the crisis, having less attribution of responsibility (Comyns & Franklin-Johnson, 2018). Adopting a defensive response strategy might include the destination downplaying responsibility for the crisis by providing a clear account of the fact that the impacted destination is also a victim to discourage tourists from developing negative attitudes toward the destination (Comyns & Franklin-Johnson, 2018; Dawar & Pillutla, 2000). When dealing with an internal crisis, adoption of a defensive coping strategy could be perceived by tourists as a destination shirking its responsibilities, resulting in negative perceptions (Q. Yu et al., 2020).

When a destination adopts an accommodative strategy, it may be signaling a willingness to take the initiative to address mistakes and/or expressing sincere repentance which may act to facilitate tourists’ positive perceptions of the destination’s future restoration actions (Kim et al., 2004). An accommodative strategy may be more appropriate for dealing with crisis events with clear attributions of responsibility (Raithel & Hock, 2021) such as internal crises, where tourists are more likely to assign responsibility to controllable factors within the organization. Internally attributed crises are perceived to be associated with controllable factors, making the destination primarily responsible for the crisis with a strong attribution of responsibility so that they are viewed as a perpetrator that has put visitors at risk (Kübler et al., 2020). The accommodative strategy expresses both an acknowledgement of responsibility and sincere action to try and correct mistakes (Kirmani et al., 2017). However, when dealing with an external crisis, an accommodative strategic approach might lead to a lack of understanding of the facts by the consumer and/or create the perception that the crisis was indeed caused by the destination’s own mistakes. It is predicted that the destination crisis response strategy moderates the effect of the destination crisis type on tourist boycott intentions toward a destination.

Hypothesis 4a (H4a): Destination boycott intentions by tourists are reduced when utilizing a defensive response strategy in response to an external crisis event, relative to an internal crisis event.

Hypothesis 4b (H4b): Destination boycott intentions by tourists are reduced when utilizing an accommodative response strategy in response to an internal crisis event, relative to an external crisis event.

As noted previously, there are likely to be differences in the relationship between heuristic and systematic information processing modes and behavioral responses across different crisis types. In addition, the adoption of different types of response strategies by tourism destinations may have differential impacts on how tourists process information and evaluate, and respond toward a destination (Ryu & Kim, 2015). Therefore, it is hypothesized that the destination crisis event response strategy will act to moderate the relationship between tourism destination crisis event type, tourists’ information processing modes, internal states, and behavioral intentions.

It is proposed here that a defensive response strategy can be more effective in reducing the negative impact of external crises by emphasizing responsibility away from the destination to trigger greater empathy and reduce boycott intentions. Conversely, an accommodative response strategy is predicted to be more effective in reducing the negative impacts associated with an internal crisis. For example, an accommodative strategy can provide useful cues for tourists that will be more deeply processed via the systematic mode resulting in reduced feelings of animosity and consequently fewer intentions to boycott. Specifically, the interaction between crisis event type and response strategy of a destination has a serial mediation effect on tourist boycott intentions toward a destination.

Hypothesis 5a (H5a): Utilizing a defensive strategy to address an external crisis with heuristic information processing will prompt greater empathy and fewer destination boycott intentions by tourists.

Hypothesis 5b (H5b): Utilizing an accommodative strategy to address an internal crisis with systematic information processing will prompt less animosity and fewer destination boycott intentions by tourists.

Methodology

Four experiments are conducted to test the hypotheses as presented in the developed conceptual model (see Figure 1). Study 1 examines the predicted (H1a-b, H2a-b, H3a-b) impact of crisis event type (external/internal) on the utilized processing modes (heuristic/systematic), internal states (empathy/animosity), and boycott intentions of tourists. Study 2 surveys tourists while adopting different destination crisis event stimuli to enhance the external validity of the initial findings. The predicted moderating impact of the response strategy to a crisis on the event type and responses of tourists relationship is explored in Studies 3 and 4 (H4a-b, H5a-b). The different experiment stimuli and multiple data sources employed here improve the robustness of the research findings, avoiding the inherent weaknesses of a single method or data source.

Figure 1.

Theoretical model.

All of the developed scenarios were grounded in actual crises reported in the news media (cf. Li et al., 2021), but to reduce the possible confounding effect of using actual tourist destinations in the experimental stimuli, all scenarios reference the fictitious S scenic area. All scenarios were pretested to verify acceptability for use in the main experiments. After reading their assigned scenario, each respondent was asked two manipulation check questions: “Based on the materials you read reporting events at destination S, do you agree that the reported event is an external (internal) tourist destination crisis event?” Participants also indicated whether the situation provided in the received scenario would be likely to occur in real life (yes/no) (Su et al., 2020). Event strength was measured across the dimensions of novelty, disruption, and criticality. Event strength novelty and disruption were assessed using 4-item scales (event strength novelty: “There is a clear, known way to respond to this crisis event,” “There is an understandable sequence of steps that can be followed by the destination in responding to this crisis event,” “Destination members can rely on established procedures and practices in responding to this crisis event,” “The destination had rules, procedures, or guidelines to follow when this crisis event occurred”; event strength disruption: “This crisis event disrupted the destination’s ability to get its work done,” “This crisis event caused the destination to stop and think about how to respond,” “This crisis event altered the destination’s normal way of responding,” “This crisis event required the destination to change the way it does its work”) adopted from Morgeson (2005). Event strength criticality was measured with a 3-item scale (“This crisis event is critical for the long-term success of the destination,” “This is an important crisis event for the destination,” “This is a priority crisis event to the destination”) adopted from Morgeson and DeRue (2006). The internal/external and event strength scales employed 7-point response options (1 = Strongly disagree, 7 = Strongly agree).

One-way ANOVA findings suggested that responsibility for the presented crises were all successfully attributed, with respondents who were provided with the external (internal) crisis scenarios being significantly (p < .05) more likely to report that the provided description represented an external (internal) crisis event. Participants affirmed scenario realism, with no significant differences (p > .05) in authenticity identified between scenarios. The event strength measures demonstrated acceptable reliability (α > .89 for all strength measures across all pretests) and did not significantly differ (p > .05) by crisis event.

Study 1

The external crisis event was derived from problems due to heavy rainstorms that took place in Zhengzhou, China, and the internal crisis event was adapted from a stranded tourist situation that occurred at Mount Huangshan (see Table 1). Study 1 respondents were comprised of 100 self-identified tourists obtained from an online survey panel (https://www.wjx.cn/) (see Table 2 for participant characteristics). After being randomly assigned to the external or internal crisis event group, participants were told to: “Imagine that you are now looking for a suitable tourism destination for the upcoming weekend. At this time, you happen to see a crisis event report about destination S.” Subjects then completed scales on information processing (heuristic mode, systematic mode), empathy, animosity, and tourism boycott intentions.

Table 1.

Experimental Conditions for Study 1 and Study 3.

S scenic area is a national nature reserve and one of China’s 5A-level scenic spots. The landscape is beautiful and pleasant. S scenic area is famous for its unique natural scenery, attracting millions of domestic and foreign tourists every year.
External crisis event scenario Recently, there have been severe local storms associated with thunder, lightning, heavy rain, hail, strong winds, and sudden temperature changes in the location of S scenic area. The hourly rainfall at the destination had reached 50 mm. Affected by the heavy rain, there was a large amount of water on the roads, and public transportation such as railways, highways, civil aviation, and subways were blocked. Eighty-one tourists were trapped at the S scenic area, with more than 2,000 tourists being negatively affected to varying degrees. The heavy precipitation has led to several secondary disasters such as river flooding and landslides in the S scenic area. Infrastructure such as buildings, bridges, and roads have been damaged to varying degrees, as have some of the natural landscapes of the destination. This has resulted in some local businesses being forced to close, resulting in a slowing of development at the destination.	Internal crisis event scenario Recently, the S scenic area has faced an unexpected surge in tourists, which the destination failed to accurately estimate. The greater number of tourists far exceeded the transportation capacity of S scenic area, resulting in more than 2,000 tourists waiting at pick-up points for up to 6 hours at a time. The number of visiting tourists also created logistical problems as food and beverage services were limited and parking was insufficient. One result of the shortage of services at the destination included traffic jams and overcrowding of the transportation options available. Due to the inability of S scenic area to adequately deal with the number of visitors, it was ordered by governmental offices to suspend business operations until such time that the destination could make changes to correct its deficiencies when dealing with the increasing number of tourists, resulting in a slowing of development at the destination.

S scenic area is a national nature reserve and one of China’s 5A-level scenic spots. The landscape is beautiful and pleasant. S scenic area is famous for its unique natural scenery, attracting millions of domestic and foreign tourists every year.

External crisis event scenario
Recently, there have been severe local storms associated with thunder, lightning, heavy rain, hail, strong winds, and sudden temperature changes in the location of S scenic area. The hourly rainfall at the destination had reached 50 mm. Affected by the heavy rain, there was a large amount of water on the roads, and public transportation such as railways, highways, civil aviation, and subways were blocked. Eighty-one tourists were trapped at the S scenic area, with more than 2,000 tourists being negatively affected to varying degrees. The heavy precipitation has led to several secondary disasters such as river flooding and landslides in the S scenic area. Infrastructure such as buildings, bridges, and roads have been damaged to varying degrees, as have some of the natural landscapes of the destination. This has resulted in some local businesses being forced to close, resulting in a slowing of development at the destination.

Internal crisis event scenario
Recently, the S scenic area has faced an unexpected surge in tourists, which the destination failed to accurately estimate. The greater number of tourists far exceeded the transportation capacity of S scenic area, resulting in more than 2,000 tourists waiting at pick-up points for up to 6 hours at a time. The number of visiting tourists also created logistical problems as food and beverage services were limited and parking was insufficient. One result of the shortage of services at the destination included traffic jams and overcrowding of the transportation options available. Due to the inability of S scenic area to adequately deal with the number of visitors, it was ordered by governmental offices to suspend business operations until such time that the destination could make changes to correct its deficiencies when dealing with the increasing number of tourists, resulting in a slowing of development at the destination.

Table 2.

Participant Characteristics.

	Study 1		Study 2		Study 3		Study 4
	n	%	n	%	n	%	n	%
Gender
Female	48	48	54	54	134	55.8	126	52.5
Male	52	52	46	46	106	44.2	114	47.5
Monthly income
Less than 3,000¥	23	23	17	17	38	15.8	30	12.5
3,000–4,999¥	13	13	4	4	27	11.3	34	14.2
5,000–6,999¥	33	33	34	34	100	41.7	107	44.6
7,000–9,999¥	25	25	32	32	57	23.8	60	25.0
10,000¥ or more	6	6	13	13	18	7.5	9	3.8
Age in years
18–24	40	40	30	30	75	31.2	73	30.4
25–40	35	35	39	39	100	41.7	98	40.8
41–60	20	20	23	23	52	21.7	57	23.8
61 and older	5	5	8	8	13	5.4	12	5.0
Level of education
Less than high school	9	9	11	11	17	7.1	24	10.0
High school/Technical school	23	23	20	20	79	32.9	74	30.8
Undergraduate/Associates degree	45	45	52	52	113	47.1	110	45.8
Postgraduate degree	23	23	17	17	31	12.9	32	13.3

Information processing was measured with 2 items each adapted from Zhang et al. (2023) (heuristic processing: “I accepted all of the facts presented without hesitation,” “I accept all information without filtering”; systematic processing: “I approached the crisis information with a cautious and diverse stance,” “I tried to judge this crisis based on objective data”). Empathy was measured with 3 items adapted from Wei et al. (2020) (“Though I am upset at the destination, I still try to understand the destination’s point of view,” “I would describe myself as a pretty soft-hearted person, and I can understand the trouble of the destination,” “I believe that there are two sides to every question and try to look at them both”). Animosity was measured with a two-item scale adapted from Campo and Alvarez (2019) (“In general, I dislike destination S”, “In general, I have negative feelings toward destination S”) and intentions to boycott a tourist destination assessed with 6 items (e.g., “I will temporarily choose a different tourism destination,” “From now on I will choose an alternative tourism destination,” “I will temporarily stop going to destination S,”) adapted from Su et al. (2022). The scales all included 7-point Likert (1 = Strongly disagree, 7 = Strongly agree) response options. All the scales demonstrated acceptable levels of reliability (heuristic α = .856; systematic α = .873; empathy α = .921; animosity α = .903; tourism boycott α = .846).

Based on the suggestion of Su et al. (2022), emotional state and perceived outside interference were both controlled in the study. Specifically, respondents were asked what “Your current emotional state is” with a 7-point Likert-type question (1 = Very calm, 7 = Very excited), and “Do you think your decision of boycotting the destination is affected by outside influences or interference?” (1 = Yes, 2 = No). Findings indicated no significant differences in emotional state or perceived outside interference (p > .05) between participants in the two experiment scenarios.

Main Effect Analysis

H1a, H1b, H2a, and H2b were tested utilizing a one-way ANOVA. A statistically significant difference in tourism boycott intentions was identified with participants exposed to the internal crisis event reporting a higher level of tourism boycott intentions than those in the external crisis group (M_internal = 5.55, SD = 0.95 vs. M_external = 3.44, SD = 0.79; F (1,96) = 48.53, p < .001, partial η² = .59). Results also indicated that a heuristic processing mode may be more likely to be adopted in response to an external crisis event (M_external = 5.39, SD = 1.49 vs. M_internal = 2.36, SD = 1.51; F (1,96) = 33.45, p < .001, partial η² = .50). There was also a significant difference between the two groups in systematic processing mode, with those placed in the internal crisis event group being more likely to adopt a systematic processing mode than those in the external crisis group (M_internal = 5.61, SD = 1.33 vs. M_external = 2.17, SD = 1.18; F (1,96) = 60.80, p < .001, partial η² = .64). H1a, H1b, H2a, and H2b are confirmed (see Figure 2).

Figure 2.

Study 1: The impact of destination crisis event on heuristic mode, systematic mode, and tourism boycott intentions.

Serial Mediation Effect Analysis

To test the hypothesized pathways (crisis event → heuristic mode → empathy → tourism boycott intentions; crisis event → systematic mode → animosity → tourism boycott intentions), a serial mediation analysis was conducted (Model 82, Hayes, 2013). Destination crisis event (external vs. internal) was used as the independent variable, with heuristic mode, empathy, systematic mode, and animosity as mediators, and tourism boycott intentions as the dependent variable. Emotional state and perceived outside interference were included as covariates.

The pathway (crisis event → heuristic mode → empathy → tourism boycott) was significant (indirect effect = 0.236, SE = 0.116, 95% CI: [0.037, 0.497]). Moreover, the crisis event → systematic mode → animosity → tourism boycott intentions pathway was also significant (indirect effect = 0.287, SE = 0.150, 95% CI: [0.033, 0.618]). Thus, the proposed serial mediation model supported H3a and H3b. Figure 3 and Table 3, in normalized data, provide additional information regarding the mediations.

Figure 3.

Study 1: The impact of tourism destination crisis event on tourism boycott intentions toward the destination.

Table 3.

Mediation Analysis Results.

Study 1
	Heuristic mode			Systematic mode			Empathy			Animosity			Tourism boycott intentions
	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]
Constant	5.39	0.69	[4.02, 6.76]	2.24	0.58	[1.09, 3.39]	3.59	0.73	[2.15, 5.04]	1.21	0.55	[0.12, 2.29]	5.57	0.47	[4.64, 6.51]
Crisis event	−3.06	0.31	[−3.37, −2.44]	3.43	0.26	[2.91, 3.94]	−1.40	0.36	[−2.12, −0.68]	2.08	0.38	[1.32, 2.84]	0.94	0.22	[0.49, 1.38]
Heuristic mode							0.40	0.08	[0.23, 0.57]				−0.23	0.05	[−0.31, −0.08]
Systematic mode										0.34	0.09	[0.16, 0.52]	0.20	0.07	[0.07, 0.33]
Empathy													−0.19	0.06	[−0.31, −0.08]
Animosity													0.25	0.07	[0.11, 0.38]
R	0.71			0.81			0.76			0.84			0.86
R ²	0.51			0.66			0.58			0.70			0.74
F	33.45			60.81			33.26			56.36			53.62
p	<.001			<.001			<.001			<.001			<.001
Serial mediation effect													b	SE	[95% CI]
Crisis event → Heuristic mode → Empathy → Tourism boycott intentions													0.24	0.12	[0.04, 0.50]
Crisis event → Systematic mode → Animosity → Tourism boycott intentions													0.29	0.15	[0.03, 0.62]
Study 2
	Heuristic mode			Systematic mode			Empathy			Animosity			Tourism boycott intentions
	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]
Constant	9.42	0.75	[7.93, 10.90]	0.01	0.85	[−1.67, 1.69]	3.78	1.17	[1.46, 610]	0.23	0.64	[−1.04, 1.49]	5.16	0.42	[4.33, 5.99]
Crisis event	−3.29	0.28	[−3.86, −2.73]	2.81	0.32	[2.17, 3.45]	−1.15	0.42	[−1.98, −0.31]	2.07	0.32	[1.43, 2.71]	0.49	0.15	[0.20, 0.79]
Heuristic mode							0.44	0.10	[0.24, 0.63]				−0.09	0.04	[−0.16, −0.02]
Systematic mode										0.37	0.08	[0.22, 0.53]	−0.08	0.03	[−0.15, −0.01]
Empathy													−0.01	0.01	[0.01, 0.02]
Animosity													0.12	0.03	[0.06, 0.19]
R	0.76			0.67			0.73			0.82			0.77
R ²	0.58			0.45			0.54			0.68			0.60
F	44.88			25.78			27.41			49.84			27.65
p	<.001			<.001			<.001			<.001			<.001
Serial mediation effect													b	SE	[95% CI]
Crisis event → Heuristic mode → Empathy → Tourism boycott intentions													0.12	0.06	[0.02, 0.26]
Crisis event → Systematic mode → Animosity → Tourism boycott intentions													0.13	0.06	[0.04, 0.27]

Study 2

Study 2 replicated Study 1 utilizing new scenarios (see Table 4) and an intercept sample of visitors to a tourist destination. The external crisis event was based on the COVID-19 outbreak in Wuhan, China; the internal crisis event was tailored from a price gouging incident that took place in Yunnan. A total of 100 tourists visiting Dalian Xinghai Square located in Liaoning, China, volunteered to take part in Study 2 and were randomly given one of the crisis event scenarios to read. Measured constructs were the same as those utilized in Study 1 (heuristic α = .874; systematic α = .895; empathy α = .917; animosity α = .935; tourism boycott intentions α = .877). Findings indicate no significant differences in emotional state or perceived outside interference (p > .05) between participants in the two experiment scenarios. Table 2 provides a description of the participants’ characteristics.

Table 4.

Experimental Conditions for Study 2 and Study 4.

S scenic area is a national key cultural relic protection unit in China This is the highest level of cultural heritage register in China at the national level. S scenic area is famous for its historical and cultural relics, attracting millions of domestic and foreign tourists every year.
External crisis event scenarioRecently, 48 new confirmed cases of COVID-19 and 308 asymptomatic infections were identified at the S scenic area, with the average daily number of cases in the local area showing an upward trend of additional cases. Due to this public health emergency that is demonstrating growing infection rates across a wide geographic area, making prevention and control difficult, more than 890 tourists from 8 provinces and 13 tour groups were quarantined at the destination. The rapid growth in cases caused S scenic area to take measures to shut down local travel agencies and tourism companies, close shops located at the destination, and suspend all performing arts activities to help prevent the spread of the epidemic. Closure of businesses at the S scenic area are resulting in a slowing of development at the destination.	Internal crisis event scenarioRecently, the S scenic area has faced a surge in tourist complaints regarding perceptions of being unfairly overcharged while visiting the destination. For example, visitors report that it is common to pay 20 yuan for a bottle of water, 68 yuan for a small container of instant noodles, an ice cream treat can cost as much as 108 yuan, with a serving of hot and sour potato shreds priced at 188 yuan. A meal for a family of three is reported to cost upwards of 800 yuan. The unexpectedly high prices have led to arguments, threats, and even instances of physical altercations between visitors and the local service providers as tourists have no recourse but to pay the inflated prices. It is unclear if these problems are due to poor supervision of service providers located at the destination, or if such behaviors are viewed as acceptable at the S scenic area. Due to the large number of complaints by visitors to the S scenic area, it was ordered by governmental offices to suspend business operations until such time that the destination could make changes to correct its deficiencies, resulting in a slowing of development at the destination.

S scenic area is a national key cultural relic protection unit in China This is the highest level of cultural heritage register in China at the national level. S scenic area is famous for its historical and cultural relics, attracting millions of domestic and foreign tourists every year.

External crisis event scenarioRecently, 48 new confirmed cases of COVID-19 and 308 asymptomatic infections were identified at the S scenic area, with the average daily number of cases in the local area showing an upward trend of additional cases. Due to this public health emergency that is demonstrating growing infection rates across a wide geographic area, making prevention and control difficult, more than 890 tourists from 8 provinces and 13 tour groups were quarantined at the destination. The rapid growth in cases caused S scenic area to take measures to shut down local travel agencies and tourism companies, close shops located at the destination, and suspend all performing arts activities to help prevent the spread of the epidemic. Closure of businesses at the S scenic area are resulting in a slowing of development at the destination.

Internal crisis event scenarioRecently, the S scenic area has faced a surge in tourist complaints regarding perceptions of being unfairly overcharged while visiting the destination. For example, visitors report that it is common to pay 20 yuan for a bottle of water, 68 yuan for a small container of instant noodles, an ice cream treat can cost as much as 108 yuan, with a serving of hot and sour potato shreds priced at 188 yuan. A meal for a family of three is reported to cost upwards of 800 yuan. The unexpectedly high prices have led to arguments, threats, and even instances of physical altercations between visitors and the local service providers as tourists have no recourse but to pay the inflated prices. It is unclear if these problems are due to poor supervision of service providers located at the destination, or if such behaviors are viewed as acceptable at the S scenic area. Due to the large number of complaints by visitors to the S scenic area, it was ordered by governmental offices to suspend business operations until such time that the destination could make changes to correct its deficiencies, resulting in a slowing of development at the destination.

H1a, H1b, H2a, and H2b were tested utilizing a one-way ANOVA. A statistically significant difference in tourism boycott intentions was identified, with participants exposed to the internal crisis event reporting a higher level of tourism boycott intentions than those in the external crisis group (M_internal = 5.63, SD = 0.44 vs. M_external = 4.63, SD = 0.56; F (1,96) = 33.14, p < .001, partial η² = .50). Results indicated that a heuristic processing mode may be more likely to be adopted in response to an external crisis event (M_external = 5.30, SD = 1.50 vs. M_internal = 2.03, SD = 1.34; F (1,96) = 44.87, p < .001, partial η² = .58). There was also a significant difference between the two groups in systematic processing mode, with those placed in the internal crisis event group being more likely to adopt a systematic processing mode than those in the external crisis group (M_internal = 5.45, SD = 1.46 vs. M_external = 2.63, SD = 1.73; F (1,96) = 25.78, p < .001, partial η² = .44). H1a, H1b, H2a, and H2b are re-confirmed (seeFigure 4).

Figure 4.

Study 2: The impact of destination crisis event on heuristic mode, systematic mode, and tourism boycott.

Serial Mediation Effect Analysis

Serial mediation analysis (Model 82, Hayes, 2013) was conducted to test the hypothesized pathways using the same variables as in Study 1. Results suggested that the two sequential mediations were both significant (crisis event → heuristic mode → empathy → tourism boycott, indirect effect = 0.119, SE = 0.059, 95% CI: [0.023, 0.256]; crisis event → systematic mode → animosity → tourism boycott, indirect effect = 0.131, SE = 0.057, 95% CI: [0.038, 0.265]). Thus, the proposed serial mediation model again supports H3a and H3b. Figure 5 and Table 3, in normalized data, provide additional information regarding the mediations.

Figure 5.

Study 2: The impact of tourism destination crisis event on tourism boycott intentions toward the destination.

Study 3

Study 3 examined the predicted moderating effect of destination response strategy on the serial mediation effects identified in Study 1 that were replicated in Study 2. Specifically, it is proposed that a defensive strategy (relative to an accommodative strategy) will weaken the negative effects of an external crisis, while an accommodative strategy (relative to a defensive strategy) will weaken the negative effects of an internal crisis (H4a-b, H5a-b). The crisis event scenarios used in Study 1 were updated with descriptions of destination response strategies (accommodative and defensive), resulting in four scenario versions (see Table 5). Participants were given the definitions of what constitutes accommodative and defensive strategies and asked: “Do you agree that the response strategy of destination S is a defensive strategy?” and “Do you agree that the response strategy of destination S is an accommodative strategy?” (1 = Strongly disagree, 7 = Strongly agree). The manipulation check questions were adapted from Wei et al. (2020).

Table 5.

Experimental Conditions for Crisis Event Type With Strategy for Study 3.

External crisis event
Accommodative strategy	Defensive strategy
In response to the rainstorms, the S scenic area issued the following announcement: It is our great honor and a point of pride that tourists come to S scenic area from all over the world to enjoy its beautiful and unique natural scenery. Due to the recent unprecedented severe local storms, many of our visitors experienced a variety of inconveniences, which we at S scenic area deeply regret. All the staff at S scenic area sincerely apologize to you for any caused inconveniences! For anyone who purchased tickets during this time, you do not need to do anything, the S scenic area will provide you with a full refund within 5 working days. Again, sorry for any inconvenience brought to you!	In response to the rainstorms, the S scenic area issued the following announcement: Unfortunately, we did not receive any advance warning from the meteorological department about the recent unprecedented severe local storms which unfortunately resulted in some visitors being trapped at the destination. S scenic area is in the process of making every effort to mobilize all available resources to address this emergency, including mobilizing rescue personnel, working to control flooding, and working with the appropriate agencies to restore the damaged landscapes at the destination.
Internal crisis event
Accommodative strategy	Defensive strategy
In the face of the unexpected surge in tourists which the destination failed to accurately estimate, S scenic spot issued the following announcement: It is our great honor and a point of pride that tourists come to S scenic area from all over the world to enjoy its beautiful and unique natural scenery. Due to the recent increase in visitors, many of our guests experienced a variety of delays and inconveniences, which we at S scenic area deeply regret. All the staff at S scenic area sincerely apologize to you for any caused inconveniences! We take full responsibility for not carefully planning ahead and have made changes in the number of personnel we have available to help current and future visitors. This includes addressing transportation issues, having adequate food and beverage services available throughout S scenic area, and working with local travel agencies to better guarantee that such problems are avoided in the future. For those visitors that were negatively affected you can expect compensation. Again, sorry for any inconveniences brought to you!	In the face of the unexpected surge in tourists which the destination failed to accurately estimate, S scenic spot issued the following announcement: It is difficult to estimate the number of tourists that will visit S scenic area on any given day, which can result in situations where the destination reaches or exceeds its maximum acceptable capacity. Due to the popularity of the S scenic area, there are times when visitors can overly concentrate at the destination for short periods of time which can create long delays and shortages of available services. It has also been rumored that the overcrowding at the destination may have been the result of illegal sales of entrance tickets in large numbers through online purchases.

A 2 (crisis event type: external/internal) × 2 (response strategy: defensive/accommodative) between-subjects design was used for Study 3. Respondents were comprised of 240 self-identified tourists obtained from an online survey platform (https://www.wjx.cn/). Participants were randomly given one of the four scenarios (n = 60 for each scenario) and asked to respond to the measurement scales utilized in Studies 1 and 2 (heuristic α = .898; systematic α = .887; empathy α = .901; animosity α = .945; tourism boycott intentions α = .874). Findings indicated no significant differences in emotional state or perceived outside interference (p > .05) between participants in the four experimental groups. Table 2 provides a description of the participants’ characteristics.

A two-way ANOVA was used to test the matching effect. A significant interaction between destination crisis event and response strategy on tourism boycott intentions was identified, F(1, 234) = 38.44, p < .001, η² = .438. The results (see Figure 6) indicate that a defensive strategy might reduce (increase) boycott intentions in external (internal) crisis situations, M_external = 3.51 versus M_internal = 4.95; F(1, 116) = 40.977, p < .001, η² = .513, while an accommodative strategy might act to reduce (increase) boycott intentions in internal (external) crisis situations, M_external = 4.69 versus M_internal = 3.71; F(1, 116) = 22.213, p < .001, η² = .335. H4a-b were supported.

Figure 6.

Study 3: The interactive effect of destination crisis event type and response strategy on tourism boycott intentions.

Two-way ANOVA findings suggested that there may be a significant interaction effect between the two destination crisis event types and response strategy conditions on the heuristic, F(1, 234) = 43.165, p < .05, η² = .019, and systematic, F(1, 234) = 28.256, p < .05, η² = .027, information processing modes. The results (see Figure 7) demonstrate that utilizing a defensive strategy with an external (internal) destination crisis event resulted in participants being more (less) likely to employ a heuristic information processing mode, M_external = 4.59 versus M_internal = 1.98; F(1, 116) = 45.231, p < .001, η² = .537. Utilizing an accommodative strategy in an internal (external) crisis event resulted in a greater (lesser) likelihood of adopting a systematic information processing mode, M_external = 4.65 versus M_internal = 5.87; F(1, 116) = 35.761, p < .001, η² = .454.

Figure 7.

Study 3: The interactive effect of destination crisis event type and response strategy on information processing modes.

Serial mediation analysis was conducted (Model 82, Hayes, 2013) to assess the posited pathway for defensive strategy (crisis event → heuristic mode → empathy → tourism boycott) The sequential mediation was significant (indirect effect = 0.1918, SE = 0.1018, 95% CI: [0.0266, 0.4251]). The alternative pathway (crisis event → systematic mode → animosity → tourism boycott) was not found to be significant (indirect effect = −0.0278, SE = 0.0352; 95% CI: [−0.0992, 0.0430]).

A serial mediation of systematic mode and animosity in the relationship between destination crisis event and tourism boycott intentions was hypothesized for the accommodative strategy condition. Results (Model 82, Hayes, 2013) indicate that the serial mediation effect of systematic mode and animosity was significant (indirect effect = 0.1758, SE = 0.0511; 95% CI: [0.0816, 0.2896]). The alternative pathway (crisis event → heuristic mode → empathy → tourism boycott) was not significant (indirect effect = −0.0222, SE = 0.0272; 95% CI: [−0.0807, 0.0285]). H5a and H5b was supported (see Figure 8 and Table 6).

Figure 8.

Study 3: The moderated mediation effects of response strategy and crisis event.

Table 6.

Moderated-Mediation Analysis Results for Study 3.

Defensive response strategy
	Heuristic mode			Systematic mode			Empathy			Animosity			Tourism boycott intentions
	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]
Constant	6.66	0.63	[5.42, 7.90]	4.17	0.35	[3.48, 4.86]	6.15	0.55	[5.07, 7.24]	−3.89	0.64	[−5.17, −2.62]	0.77	0.61	[−0.43, 1.97]
Crisis event	−2.63	0.23	[−3.08, −2.18]	0.76	0.13	[0.51, 1.01]	−2.54	0.21	[−2.95, −2.13]	3.07	0.18	[2.78, 3.42]	0.22	0.26	[−0.30, 0.74]
Heuristic mode							0.25	0.06	[0.14, 0.37]				−0.11	0.05	[−0.21, −0.01]
Systematic mode										0.64	0.11	[0.41, 0.86]	0.27	0.11	[0.06, 0.47]
Empathy													−0.29	0.08	[−0.44, −0.14]
Animosity													−0.06	0.08	[−0.21, 0.09]
R	0.73			0.49			0.91			0.91			0.74
R ²	0.54			0.24			0.82			0.83			0.54
F	45.23			12.48			133.30			4.00			26.83
p	<.001			<.001			<.001			<.001			<.001
Serial mediation effect													b	SE	[95% CI]
Crisis event → Heuristic mode → Empathy → Tourism boycott intentions													0.19	0.10	[0.03, 0.43]
Crisis event → Systematic mode → Animosity → Tourism boycott intentions													−0.03	0.04	[−0.10, 0.04]
Accommodative response strategy
	Heuristic mode			Systematic mode			Empathy			Animosity			Tourism boycott intentions
	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]
Constant	6.64	0.65	[5.36, 7.93]	4.05	0.33	[3.39, 4.70]	2.71	0.41	[1.89, 3.52]	4.22	0.46	[3.31, 5.13]	5.27	0.53	[4.22, 6.32]
Crisis event	−1.89	0.25	[−2.38, −1.40]	1.24	0.13	[0.99, 1.50]	0.06	0.14	[−.22, 0.33]	−1.35	0.16	[−1.66, −1.04]	−0.83	0.15	[−1.13, −0.52]
Heuristic mode							0.13	0.04	[0.05, 0.22]				0.06	0.05	[−0.03, 0.16]
Systematic mode										0.35	0.09	[0.18, 0.52]	0.02	0.09	[−0.16, 0.20]
Empathy													0.09	0.10	[−0.11, 0.29]
Animosity													0.40	0.09	[0.22, 0.59]
R	0.58			0.69			0.82			0.65			0.62
R ²	0.34			0.48			0.14			0.43			0.38
F	19.96			35.76			4.85			21.46			14.12
p	<.001			<.001			<.01			<.001			<.001
Serial mediation effect													b	SE	[95% CI]
Crisis event → Heuristic mode → Empathy → Tourism boycott intentions													−0.02	0.03	[−0.08, 0.03]
Crisis event → Systematic mode → Animosity → Tourism boycott intentions													0.18	0.05	[0.08, 0.29]

Study 4

The crisis event scenarios used in Study 3 were updated with descriptions of destination response strategies (accommodative and defensive) resulting in four versions (see Table 7). Study 4 used the same experimental design and measurement scales (heuristic α = .898; systematic α = .887; empathy α = .901; animosity α = .945; tourism boycott intentions α = .874) as Study 3, but respondents were comprised of 240 visiting tourists to Laohutan Ocean Park, China. Findings indicated no significant differences in emotional state or perceived outside interference (p > .05) between the participants in the four experiment groups. Table 2 provides a description of the participants’ characteristics.

Table 7.

Experimental Conditions for Crisis Event Type With Strategy for Study 4.

External crisis event
Accommodative strategy	Defensive strategy
In the face of the public health emergency, S scenic spot issued the following announcement: It is our great honor and a point of pride that tourists come to S scenic area from all over the world to enjoy its historical and cultural relics. It is regretful that S scenic area has had to quarantine many of our visitors and not allow other tourists the opportunity to visit at this time. All the staff at S scenic area sincerely apologize to you for any caused inconveniences! For anyone who purchased tickets during this time, you do not need to do anything, the S scenic area will provide you with a full refund within 5 working days. Again, sorry for any inconveniences brought to you!	In the face of the public health emergency, S scenic spot issued the following announcement: Affected by recent increasing infection rates, outside agencies have instituted COVID-19 prevention and control measures in the surrounding provinces to slow the movement of people and reduce the risk of epidemic transmission. As there have been local clusters of cases near the S scenic area, some visitors have also been forced to stay at the destination at this time, and we are not allowed to accept additional guests to the location. In accordance with COVID-19 prevention protocols, S scenic area will inform the public on any changes to this policy or recovery options to visitors as they are provided to us by the appropriate departments.
Internal crisis event
Accommodative strategy	Defensive strategy
In the face of the overcharging of visiting tourists, S scenic spot issued the following announcement: It is our great honor and a point of pride that tourists come to S scenic area from all over the world to enjoy its historical and cultural relics. Due to the recent instances of visitors to S scenic area being deceived and overcharged at this destination, we sincerely apologize to anyone that was impacted. We take full responsibility for these actions and are actively cooperating with relevant departments to investigate what happened, accept any recommended punishments, and to communicate with affected consumers quickly and effectively about compensation for their poor experience. We strive to improve how the destination is managed to avoid these problems in the future. Again, sorry for any inconveniences brought to you!	In the face of the overcharging of visiting tourists, S scenic spot issued the following announcement: S scenic area management has been made aware of concerns about pricing at the destination. Please note that enterprises located around and in S scenic area have the autonomy to adjust prices at any time based on a variety of factors that can impact their product costs or demand for their services. This is within the scope of the rules. The independent behavior of local enterprises has nothing to do with the S scenic area. Although S scenic area does not condone predatory pricing by vendors, this is a difficult problem to track, supervise, and/or enforce as the investigation and handling of such cases is exceedingly difficult.

Findings from a two-way ANOVA replicated the Study 3 results of a significant interaction between destination crisis event type and response strategy on tourist boycott intentions, F(1, 234) = 25.35, p < .001, η² = .350. The results (see Figure 9) indicate that a defensive strategy might reduce (increase) boycott intentions in external (internal) crisis situations, M_external = 3.70 versus M_internal = 4.75; F(1, 116) = 14.12, p < .001, η² = .265, while an accommodative strategy might act to reduce (increase) boycott intentions in internal (external) crisis situations, M_external = 4.83 versus M_internal = 3.68; F(1, 116) = 36.36, p < .001, η² = .478. H4a and H4b were again supported.

Figure 9.

Study 4: The interactive effect of destination crisis event type and response strategy on tourism boycott intentions.

Utilizing a two-way ANOVA, a significant interaction between the two destination crisis event types and response strategy conditions on heuristic mode, F(1, 234) = 58.622, p < .05, η² = .025, and systematic mode, F(1, 234) = 29.044, p < .05, η² = .027, were identified. The results (see Figure 10) demonstrate that utilizing a defensive strategy with an external (internal) destination crisis event resulted in participants indicating that they would be more (less) likely to utilize a heuristic information processing mode, M_external = 5.26 versus M_internal = 1.92; F(1, 116) = 66.727, p < .001, η² = .632. Utilizing an accommodative strategy in an internal (external) crisis event results in a greater (lesser) likelihood of adopting systematic information processing mode, M_external = 5.02 versus M_internal = 6.15; F(1, 116) = 42.930, p < .001, η² = .526.

Figure 10.

Study 4: The interactive effect of destination crisis event type and response strategy on information processing modes.

The sequential mediation (Model 82, Hayes, 2013) was significant for the posited pathway for defensive strategy (indirect effect = 0.3140, SE = 0.1038, 95% CI: [0.1383, 0.5502]), but not the alternative pathway (indirect effect = 0.0114, SE = 0.0199, 95% CI: [−0.0259, 0.0567]). The serial mediation effect of systematic mode and animosity in the relationship between destination crisis event and tourism boycott intentions was significant (indirect effect = 0.1165, SE = 0.0580, 95% CI: [0.0140, 0.2401]). The alternative pathway (crisis event → heuristic mode → empathy → tourism boycott) was not significant (indirect effect = 0.0094, SE = 0.0271, 95% CI: [−0.0398, 0.0731]). H5a and H5b were supported (see Figure 11 and Table 8). Results support that the effect of crisis event type on tourism boycott intentions was moderated by the crisis response strategy.

Figure 11.

Study 4: The moderated mediation effects of response strategy and crisis event.

Table 8.

Moderated-Mediation Analysis Results for Study 4.

Defensive response strategy
	Heuristic mode			Systematic mode			Empathy			Animosity			Tourism boycott intentions
	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]
Constant	8.96	0.70	[7.58, 10.34]	3.92	0.37	[3.18, 4.66]	3.16	0.77	[1.62, 4.69]	3.08	0.76	[1.57, 4.58]	5.84	0.69	[4.47, 7.22]
Crisis event	−3.34	0.24	[−3.81, −2.87]	0.71	0.13	[0.46, 0.97]	−0.72	0.28	[−1.27, −0.17]	0.95	0.21	[0.54, 1.36]	−0.02	0.24	[−0.49, 0.46]
Heuristic mode							0.27	0.07	[0.14, 0.41]				−0.15	0.06	[−0.27, −0.03]
Systematic mode										0.11	0.14	[−0.16, 0.37]	0.26	0.12	[0.03, 0.49]
Empathy													−0.34	0.08	[−0.50, −0.19]
Animosity													0.15	0.08	[−0.01, 0.31]
R	0.80			0.48			0.70			0.49			0.67
R ²	0.63			0.23			0.49			0.24			0.45
F	66.73			11.53			28.04			9.14			18.94
p	<.001			<.001			<.001			<.001			<.001
Serial mediation effect													b	SE	[95% CI]
Crisis event → Heuristic mode → Empathy → Tourism boycott intentions													0.31	0.10	[0.14, 0.55]
Crisis event → Systematic mode → Animosity → Tourism boycott intentions													0.01	0.02	[−0.03, 0.06]
Accommodative response strategy
	Heuristic mode			Systematic mode			Empathy			Animosity			Tourism boycott intentions
	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]	b	SE	[95% CI]
Constant	6.81		[5.38, 8.24]	3.90	0.29	[3.34, 4.47]	6.58	0.67	[5.26, 7.90]	5.27	0.75	[3.79, 6.76]	3.98	0.56	[2.86, 5.09]
Crisis event	−2.49	0.25	[−3.00, −1.99]	1.14	0.10	[0.94, 1.34]	−2.00	0.24	[−2.48, −1.53]	−2.27	0.24	[−2.74, −1.80]	−1.18	0.20	[−1.57, −0.78]
Heuristic mode							0.03	0.06	[−0.10, 0.16]				0.02	0.04	[−0.06, 0.10]
Systematic mode										0.51	0.15	[0.21, 0.81]	0.27	0.10	[0.08, 0.47]
Empathy													−0.12	0.06	[−0.24, −0.01]
Animosity													0.17	0.06	[0.05, 0.28]
R	0.68			0.73			0.74			0.71			0.75
R ²	0.47			0.53			0.55			0.51			0.57
F	33.75			42.93			34.53			30.00			30.20
p	<.001			<.001			<.001			<.001			<.001
Serial mediation effect													b	SE	[95% CI]
Crisis event → Heuristic mode → Empathy → Tourism boycott intentions													0.01	0.03	[−0.04, 0.07]
Crisis event → Systematic mode → Animosity → Tourism boycott intentions													0.12	0.06	[0.01, 0.24]

Conclusion

Drawing from attribution theory and the heuristic/systematic information processing model, a conceptual model was proposed and tested examining the relationship between crisis events at tourism destinations, tourist information processing mode (heuristic/systematic), tourist internal state (empathy/animosity), and boycott intentions. Findings from two studies support that boycott intentions toward a destination may be greater (lesser) for internal (external) crisis events. What is more, findings indicate that for externally attributed destination crisis events, tourists may be more inclined to adopt a heuristic information processing mode, feel more empathy, and have reduced intentions to boycott a destination. However, for internal destination crisis events, tourists might be more likely to adopt a systematic information processing approach, experience a heightened sense of animosity, and have greater intentions to boycott a destination. Findings regarding the moderating effect of destination crisis event response strategies on the relationship between such events and tourist responses indicated that a defensive (accommodative) strategy could effectively weaken some of the negative effects a destination might experience when dealing with an external (internal) crisis.

Theoretical Contributions

This research provides three primary contributions to tourism literature. First, this research constructed and tested a theoretical model based on the HSM that was applied to a destination crisis context. Based on the HSM, this study confirmed a serial mediation effect for information processing modes (heuristic/systematic) and internal states (empathy/animosity) between destination crisis events and tourist boycott intentions. Previous studies have examined the direct negative effects of crisis events on tourists’ behaviors (Aliperti & Cruz, 2019), but the role of tourists’ information processing modes and affective evaluations in crisis situations have not been fully explored. In particular, others (e.g., Farmaki, 2021; Schoofs & Claeys, 2021) had called for future research to examine the role of tourists’ affects in crisis events, including empathy and animosity. As such, this study expands prior research on empathy as a prosocial behavior (Allard et al., 2020) to an important aspect of tourism destination crisis event management. Similarly, animosity research has tended to focus on individual perceptions of functional products (Q. Yu et al., 2020), which the current research extends to a hedonic product (i.e., destination tourism). Overall, the use of different crisis situations expanded the application of the HSM to new contexts while providing useful insights for researchers interested in the relationship of information processing modes under crisis management situations.

Second, based on attribution theory, this study identified tourism destination crisis events as being externally or internally attributed, while simultaneously exploring the differential impact of attributions on tourism boycott intentions across different contexts. Prior studies have pointed out that consumers’ purchase intentions for functional products may vary in relation to different types of crisis events (Baghi & Gabrielli, 2019), but this research addressed calls to explore how destination crisis event attributions might impact tourists’ intentions (Coombs, 2018; Karl et al., 2021; Su et al., 2022). The findings support that for externally attributed crises, tourists have less motivation to process crisis information thereby utilizing a heuristic information processing mode and generating positive affective responses (empathy) while reducing possible negative effects (boycott). For an internally attributed crisis, destinations may have a greater attribution of responsibility, which results in tourists having more motivation to think about the crisis (i.e., systematic information processing) and react negatively (i.e., animosity) prompting unwanted behaviors such as boycotting the destination. Applying attribution theory to a destination crisis context, the research findings provided support for the usefulness of the theory to the important area of crisis event management and, more specifically, the management of tourist destinations.

Finally, although response strategies perform a key role in the management of crises, there has been confusion over which response strategies are more effective to weaken the negative effect of destination crisis events (Xu et al., 2021). Crisis response strategies solely based on the principle of the more the better without considering the specific situation will not only be difficult to mitigate and eliminate the negative impact of a crisis event but could also create a secondary crisis based on the communication strategy utilized (Q. Luo & Zhai, 2017). This research highlighted the importance of the matching effect (Coombs, 2018) between destination crisis types (external/internal) and response strategies (defensive/accommodative). Results indicated that a defensive (accommodative) strategy matched in response to an externally (internally) attributed crisis may result in more positive outcomes for a destination. This research also examined response strategy as a moderating variable which provided insights into the relationships of tourist information processing modes, tourist internal states, and behavioral intentions. In addition, previous research has considered crisis response strategies as antecedent to constructs such as empathy (Liu-Lastres et al., 2019). As suggested by M. Yu et al. (2022), this research examined response strategy as a moderating variable, which provided insight into the relationship of different strategies with tourist information processing modes, affective evaluations, and behavioral intentions. As such, this research provided empirical support for the relevance of matching (Zhang et al., 2023) and understanding the information processing mode utilized in a particular tourism destination crisis situation.

Managerial Implications

Study findings point to some possible management implications for DMOs. First, as global instability and uncertainty persist, crisis events, both internal and external, will likely continue to have substantial impacts on tourism (Alvarez et al., 2022). Findings from this research suggest that identifying tourists’ perceived causes of these events may provide a way to better identify approaches to limit unwanted behaviors such as destination boycotts. Specifically, internally attributed tourism destination crises could result in more negative impacts, relative to those crises with external attributions. As such, from an external guidance perspective, DMOs are an integral part of socio-economic development and should be subject to business supervision and normative guidance from local governmental units. This may help DMOs identify potential crisis situations more quickly and provide a partner in addressing these negative incidents. From an internal management perspective, DMOs bear primary responsibility for sustainable tourism destination development. They can minimize the occurrence of internal crises by standardizing service processes and establishing appropriate reward and punishment mechanisms. Furthermore, encouraging multi-departmental collaboration and utilizing dynamic monitoring of potential external risks with big data, DMOs may be able to more effectively identify and quickly respond to crises.

Second, destination managers should recognize that when tourists experience a crisis event, the type of event may impact how information is processed, which could then result in varying affective and cognitive responses. Thus, the information processing mode, tourists' affective evaluations, and cognitive efforts might play an important role in the approaches utilized to manage a destination crisis. For example, when a crisis occurs, a heuristic-based crisis communication mode might be used to promote more positive tourist affect and reduce negative perceptions of the destination. Tourism destination managers could monitor social data platforms to track the affective state and cognitive changes of potential tourists, allowing managers to potentially engage in timely interventions to reduce the likelihood of boycotts occurring.

Finally, this research investigated the matching effect between crisis response strategy and destination crisis event type. Understanding the type of crisis event and the overall attribution of responsibility for such event may provide insights into the most appropriate response strategy. When dealing with an externally attributed crisis, findings suggested that a defensive strategy might be most appropriate. The manager could clearly communicate reasons for the crisis and the harm brought to the destination so that tourists may be more likely to support the destination in its recovery efforts. When dealing with an internally based crisis, the destination may not want to justify the situation but actively engage in recovery efforts (e.g., apology, compensation) in an effort to reduce any animosity or threat of a boycott. A proper crisis response strategy may be able to effectively reduce the negative impact of a crisis event, rebuild the confidence of tourists, and help a tourism destination achieve positive and sustainable development.

Research Limitations and Future Research Directions

This research validated the proposed conceptual model using four studies. However, there are limitations that provide direction for future research. First, this research categorized crisis events based on attribution theory as being external or internal in four different crisis situations. However, crisis events occur in a variety of contexts and may not be as easily classified as was done in the current study. Secondly, although our findings supported that externally attributed crises resulted in tourists utilizing a heuristic information processing mode, there may be situations where a systematic mode would take precedence due to the nature of a crisis or information being disseminated regarding a crisis via social media. Boundary conditions on the findings from this research need to be identified. Third, this study focused on empathy and animosity, leaving opportunities for future research to examine the important role played by other emotions and cognitions experienced by tourists experiencing crisis events. Fourth, this study provided an initial exploration of the matching effect between crisis types and destination response strategies. Real life crises are often more dynamic and fluid than what was portrayed in the created scenarios in this research, suggesting that relevant response strategies may have to be adapted throughout different stages of a developing crisis. Future researchers are encouraged to explore the impact on tourists of single versus combined strategies at various stages of responding to crises across different contexts.

Footnotes

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Natural Science Foundation of China (No. 72174213; 71974206; 71774176).

ORCID iDs

Lujun Su

Scott R. Swanson

Author Biographies

Lujun Su (PhD, Xiamen University) is a professor of marketing at the School of Business at the Central South University, China. Dr. Su’s research interests include tourist loyalty behavior, destination marketing, and destination management. He has published more than 100 referred articles in scholarly journals, such as Tourism Management, Journal of Business Research, Journal of Sustainable Tourism, International Journal of Contemporary Hospitality Management, Journal of Hospitality & Tourism Research, and Journal of Travel Research.

Bocong Jia is an associate professor in the School of Tourism and Hotel Management at Dongbei University of Finance and Economics, China. He received his Ph.D in Business Administration from Central South University, China. Dr Jia’s research interests include tourist behaviour, destination marketing, and destination crisis management.

Scott R. Swanson (PhD, University of Kentucky) is a Professor of Marketing at the University of Wisconsin-Eau Claire. His research interests include sports and hospitality/tourism marketing, service recovery issues, and pedagogy. Dr. Swanson has published more than 100 papers in journals such as the Journal of the Academy of Marketing Science, Tourism Management, Journal of Marketing Theory and Practice, Journal of Services Marketing, and Journal of Travel Research, among others.

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