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Article

Real Bounce Forward: Experimental Evidence on Destination Crisis Marketing, Destination Trust, e-WOM and Global Expat’s Willingness to Travel during and after COVID-19

by
Murat Aktan
1,
Umer Zaman
2,*,
Pablo Farías
3,
Syed Hassan Raza
4 and
Emenyeonu C. Ogadimma
5
1
Faculty of Economics and Administrative Sciences, Mugla Sitki Kocman University, Muǧla 88000, Turkey
2
Endicott College of International Studies (ECIS), Woosong University, Daejeon 34606, Korea
3
Departamento de Administración, Facultad de Economía y Negocios, Universidad de Chile, Santiago 8330015, Chile
4
Department of Communication Studies, Bahauddin Zakariya University, Multan 66000, Pakistan
5
College of Communication, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(3), 1111; https://doi.org/10.3390/su14031111
Submission received: 6 December 2021 / Revised: 6 January 2022 / Accepted: 14 January 2022 / Published: 19 January 2022
(This article belongs to the Special Issue Sustainable Tourism in International Context: Solutions during and after the Global Pandemic Crisis)
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Abstract

:
The nexus of global tourism, disasters and sustainability have always been triggered by numerous crises, e.g., political unrest, wars, and pandemics. However, there is still fragmented research on destination crisis marketing, and its impact on willingness to travel remains largely unknown. To address this critical research gap, the present study used an experimental research design by framing destination crisis marketing campaigns (2 × 2 frames including DCM implemented versus DCM not implemented) and electronic word of mouth (2 × 2 frames including positive e-Wom versus negative e-Wom) to examine their impact on destination trust and global expat’s willingness to travel. Based on the experimental settings of global expats (N = 232; representing over 10 nationalities) with four framing groups (Group 1 to Group 4, configured in frames as ± DCM and ± e-Wom), the new evidence suggests that global expats who are provoked by positive crisis marketing campaigns and positive e-Wom (Group 4) have higher levels of destination trust than those who are exposed to either negative crisis marketing scenario and/or negative e-Wom (i.e., Group 1 to Group 3). The findings also revealed that global expat’s willingness to travel is significantly influenced by destination crisis marketing campaigns and e-Wom. Interestingly, for all framing groups (Group 1 to Group 4), the effects of destination crisis marketing and e-WOM on expat’s willingness to travel, was significantly mediated by destination trust. Utilizing prominent theories (i.e., signal theory, image repair theory and trust transfer theory), the study implications highlighted that crisis marketing and positive e-Wom could serve as the cornerstones for destinations to stay relevant, regenerate sustainable practices, as well as create new opportunities out of a crisis.

1. Introduction

Sustainable destination transformations are significantly altered by crises and disasters of various sorts, however, the worst of all the crises has been the COVID-19 pandemic the world has been going through since the end of 2019 [1]. The COVID-19 has brought the global tourism industry almost to a complete halt. As a response, destinations have implemented well-established crisis measures to restore their images, rebuild trust, and re-attracting tourists, globally [2]. Destination crisis marketing is a component of destinations’ overall counter-crisis marketing efforts during times of crisis to restore tourists’ confidence in the viability of destinations [1,3]. When hit by a crisis, destination marketers much like their counterparts in other industries, need to harness different media ubiquitously to promote destinations as safe and attractive [2]. In this respect, destinations’ owned media (DOM) refer to media channels that are largely controlled by quasi-governmental bodies (destination management organizations) [4]. DOM include state-owned web pages and social media accounts that aim to direct and amalgamate the individual promotional efforts of other organizations to ensure coherency in destinations’ overall marketing activities [5]. Nevertheless, the conventional role of DOM has been recently questioned as they are becoming less reflective of the complex relations of contemporary tourism, where tourists tend to ignore intermediaries and want to control their relationships with individual tourism stakeholders [6].
The present COVID-19 pandemic intensified the ongoing debates about what to communicate and how to design marketing messages to regain trust towards destinations in times of crisis [7,8]. In this vein, this study borrows from the image repair theory, which concentrates exclusively on messages that are tailored to enhance images tarnished by suspicion and criticism [9]. Therefore, once a positive destination image is cultivated, destination management organizations are responsible for protecting it from crises by implementing effective crisis communication and recovery marketing strategies [2,10,11]. Despite the fact that destinations need to take preventive and restorative measures when encountering image problems, most destination management organizations are still ill-prepared to deal with unexpected crisis events [7,12,13,14]. Therefore, as an alternative, destinations’ earned media (DEM) offer a significant solution while destinations are trying to get over the crisis-related pitfalls. DEM are categorized as user-generated content shared and consumed within consumers’ own networks (e.g., retweeting a friend’s tweet about a product) [15]. Prior studies in tourism illustrated that DEM (i.e., e-WOM, online review sites, and travel blogs) alleviate tourists’ risk perception and generate a sense of trust when destinations suffer from crises such as terror attacks, and natural disasters, etc. [16,17]. Furthermore, earned media is cited as more influential than owned media platforms to increase consumers’ trust and positive intentions [15,18]. Tourists can be more skeptical of DOM as they might assume that destination marketers provide misleading information in their own media. In contrast, the feeling of trust is intensified for the earned media sources where information is shared on social media and online travel review sites [18,19,20].
Although destination trust and loyalty have been commonly studied under normal conditions, the study of the interrelationships between these concepts in times of crisis has been largely neglected [2,7,21]. The fact that the crises with a major impact on tourism have been commonly witnessed over the past few decades, the urgency of the need to investigate various aspects of destination marketing and management from the perspective of crises has been exacerbated [12,21,22]. To that end, the present study addresses a nascent field of research by contributing to the destination crisis marketing literature [3]. In particular, the present study investigates the impact and relevance of both DOM and DEM in destination recovery efforts during the pandemic for the first time in tourism literature [2,23,24]. Thus, the findings will provide clear-cut strategies to destination management organizations to tackle the negative consequences of the pandemic. Last but not least, the present study also aims to extend the scholarly knowledge about the mediating role of destination trust between tourist behavior and destination crisis marketing activities by applying a quasi-experimental design [7,25,26].

2. Theoretical Background

2.1. Influence of Destination Crisis Marketing on Destination Trust

Destination trust refers to the extent that destinations are perceived as reliable, transparent, risk-free, and able to perform their advertised functions [27,28]. Having been struck by the COVID-19, global destinations have suffered from the erosion of travelers’ trust towards destinations, which induced significant drops in tourism revenues. As a result, tourism destinations’ future has become more dependent on their ability to provide a risk-free, safe, and reliable environment to their guests [29,30]. Also, destination management organizations must contemplate how they should counter risks of various sorts during crises, including their marketing strategy. As a part of the destination’s comprehensive action plan, destination crisis marketing is designed to provide positive messages about the destination, which aim to reduce tourists’ risk perceptions and enhance their sense of trust [31,32]. When individuals think of traveling to a new destination, they assess various information coming from both owned media (i.e., Destination web pages) versus earned media (i.e., previous travelers’ comments). Hence, crisis marketing messages of destination management organizations may act as one of the groups of valuable signals, helping and influencing tourists to make more educated decisions [33].
According to the image repair theory, destinations shouldn’t stick to their regular promotional tools during a time of crisis but have to consider and adopt various strategies to bring tourists back. For instance, destinations can convey messages that everything is functioning, as usual, the situation has been eased, and visiting the destination is safe as opposed to public opinion [10,34]. In contrast, destinations may also choose to accept and publicly refer to the problem to establish rapport with the target audience [35]. Despite the relevance of image repair theory in tourism, there is still limited empirical research on the influence of the crisis on destinations and destinations’ image recovery attempts [22]. In an earlier study that measured the impact of the Fukushima earthquake on tourism found that the psychological and social risks associated with the radioactive contamination caused travelers to develop distrust towards Japan as a tourism destination [36]. In response, the Japanese National Tourism Organization initiated a destination crisis program to reestablish trust. This marketing campaign communicated information about such as Japan’s highly advanced disaster management systems, its world-class health care infrastructure, and the country’s food safety standards, etc. Eventually, these efforts paved the way for Japan to regain travelers’ trust and increase the inbound tourism flow [36].
A review of recent research also suggests that the adoption of crisis marketing strategies tends to mitigate tourists’ perception of risk and inspire trust towards the destinations [37,38]. Aliperti and Cruz [37] emphasized the need for tailor-made marketing communication strategies that take into account of cross-cultural behavioral differences of international travelers [37]. The researchers also recommended not to apply “one size fits all marketing strategies” in case destinations host tourists from different nationals. Similarly, in a most recent study analyzing European destinations’ reactions during crises, Avraham [34] showed that destinations could communicate messages reassuring that the place is safe and locals are continuing their life routine [34]. The above discussion shows that crisis marketing efforts of destination management organizations may act as an important instrument to reestablish tourists’ trust towards destinations in times of crisis. Based on this background, the following hypothesis is formed:
Hypothesis 1 (H1).
Participants provoked by positive crisis marketing campaigns have higher levels of destination trust than those who are shown negative crisis marketing scenarios.

2.2. Influence of Destination e-WOM on Destination Trust

Destination perception has been widely acknowledged as the product of three main sources of information, including destination marketers’ efforts, tourists’ real experiences, and word of mouth (WOM) [39,40]. In other words, destination tourist is an outcome of multiple sources, including tourists’ first-hand experiences and earned media such as WOM. As the typical example of earned media, WOM in tourism refers to the dissemination of destination information between individuals via oral communication. Whilst, the advancement of mobile devices and technologies led the way to the emergence of Electronic Word of Mouth (e-WOM), i.e., system where interaction and communication relating to products, services, and destinations take place in online communities and websites [41]. Although in the traditional WOM information sharing mostly occur between relatives, friends, and peer groups, in e-WOM people may have access to online reviews made by people they do not know or whose identities are mostly unknown. Therefore, compared with WOM, e-WOM may be more likely to provide more objectivity of the information when tourists think about new destinations, relatively freer from interpersonal bias [27]. Another distinct advantage of e-WOM is that as it exists online, it allows access to potentially millions of people at any time in a day and for a longer period of time [42].
Based on the trust transfer theory, trust is cognitively transferred from the source of trust to the unknown target, when the trustor has little to no experience [43,44]. To put it differently, when individuals are to evaluate an entity, a brand, or a destination, etc., that they are not familiar with, they tend to rely on the source of trust and transfer that positive image to the unknown target if these two factors are perceived as related. The pioneering study of Lee et al. [43] delineated that successful mega-event(s) such as festivals led to favorable attitudes towards the whole country (China) as a destination [43]. Furthermore, Pop et al. [45] illustrated that the sense of trust towards social media influencers positively influences each stage of tourists’ decision journey, including the purchase decision and experience sharing [45]. Similarly, tourists’ evaluations of reviews on a worldwide famous online platform may also increase the positive perception and assessment of the destination [46], thus can be instrumental in spreading positive messages about a destination. In line with this perspective, several tourism researchers have investigated the role of e-WOM in the promotion of destinations (e.g., [16,27,47]).
A review of the literature shows that e-WOM has a positive influence on destination image, attitude toward destinations as well as tourists’ visiting intentions [16,41,48]. Also, e-WOM tends to play an important role in restoring the image of the destination following crises such as political disputes, terror attacks, and natural disasters [16,17]. Hence, destinations often spend efforts to increase tourists’ involvement and motivation to establish and distribute positive e-WOM in order to generate better destination mental images [49]. In a study investigating the impact of political turmoil on tourism following the Arab Spring, Avraham [17] found that e-WOM mitigated the tourists’ risk perceptions and increased their intentions to visit positively. In particular, the online campaign launched by the travel bloggers helped Jordan restore its image and allowed it to re-attract the visitors following the crisis [17]. Again, in a more recent study by Assaker and O’Connor [16], it was found that e-WOM platforms such as social media, travel review sites, and online communities were highly effective in alleviating tourists’ negative perceptions of political instability and terrorism threats in relation to a destination [16].
Despite the sufficient evidence for the relevance of e-WOM in promoting destinations [16,40,50,51], the specific relationship between destination e-WOM and trust has been mentioned only in a few studies in the literature [25,27,46]. In a study on Northern Cyprus nationals, respondents suffering from health problems were asked to indicate their extent of reliance on online travel reviews if they were to consider traveling abroad for medical care. The findings demonstrated that the medical tourists’ feelings of trust towards the destinations were positively influenced by the comments posted on well-known online review sites [27]. Also, another study conducted on international patients receiving medical care in Istanbul elucidated the positive influence of e-WOM on destination trust [46], whilst there were gender-based differences in the strength of the relationships. Based on the above discussion, one can argue that when individuals see positive e-WOM in online travel review sites, their trust towards destinations is heightened.
Hypothesis 2 (H2).
Participants who are provoked by the positive e-WOM scenario have higher levels of destination trust than those who are shown the negative e-WOM scenario.

2.3. Mediating Effects of Destination Trust on Destination e-WOM and Willingness to Travel

The mediating role of trust has been empirically tested in prior marketing studies and verified for various contexts. The limited research in the literature has illustrated that trust mediates the relationship between brand loyalty and other concepts such as corporate social responsibility [52], perceived utilitarian and hedonic benefits [53], brand image perceptions [54], and risk aversion [55]. Further studies have validated the role of trust as a mediator on the relationship between corporate citizenship, intention to purchase [56], brand personality and consumer command, etc. [57].
Parallel with the growing body of trust literature in marketing; the trust concept has recently begun to attract the interest of tourism researchers [26]. For instance, Abubakar [46] identified the mediating role of destination trust between e-WOM and tourists’ travel intentions by using a structural model, where the findings also suggested the gender’s moderating role on this relationship. Particularly, while the impact of e-WOM on destination trust was found to be significantly stronger for the male respondents, the relationship between destination trust and travel intention was recognized as stronger for the female participants [46]. In another conceptually similar study, Abubakar and Ilkan [27] tested the mediating roles of destination trust and income as moderating variables on the e-WOM and travel intention relationship. This study revealed that the impact of destination trust on travel intention was weakened along with an increase in respondents’ income levels [27]. Based on the prior literature clarifying the mediating role of destination trust between e-WOM [25], travel, and revisit intentions, the third hypothesis of the current study was established as follows:
Hypothesis 3 (H3).
Destination trust mediates the relationship between e-WOM and the intention to travel for each group.

2.4. Mediating Effects of Destination Trust on Destination Crisis Marketing and Willingness to Travel

The mediating role of trust has been studied from various contextual relationships such as the relationship between the company image and loyalty [58], perceived risk, knowledge, and purchase intentions [59], etc. Also, in the tourism literature, trust has been widely recognized as a mediating variable, influencing the extent to which travel intention is facilitated or hindered [60,61]. Prior studies have empirically shown the mediating role of destination trust between various factors such as visitors’ service quality perceptions and revisit intentions [62], destination social responsibility, and intention to visit [32].
In a most recent study, Hassan and Soliman [26] analyzed the influence of fear perceptions on domestic holidaymakers by using a structural model and acknowledged that social responsibility was an important predictor of tourists’ revisit intentions for a destination [26]. The study showed that destinations operating in an environmentally responsible manner, which complies with health and safety regulations, could create higher levels of trust. Furthermore, destination trust was found to mediate the relationship between destination social responsibility and intention to visit a destination. This finding means that if destinations build a reputation for being socially responsible, they can establish trust, which in turn may help them increase tourists’ visiting intentions. This impact might also be amplified, especially during or after periods of crises when individuals tend to be more risk-averse [26,63]. Consequently, the fourth hypothesis has been developed as follows:
Hypothesis 4 (H4).
Destination trust mediates the relationship between destination crisis marketing and willingness to travel for each group.

3. Methods

3.1. Sampling and Procedure

The present study adopted a quasi-experimental design, where SPSS 26 and Amos 24 software were utilized for data analyses and hypotheses testing. The data were collected from white-collar expats working in the United Arab Emirates by sending invitations directly to their institutional e-mails. After the initial data purifications (i.e., outliers, normality, etc.), the final sample was reduced to 232 observations (see Table 1 for demographics). In particular, the study has used four scenario combinations and 58 participants were involved in each scenario. Therefore, the number of participants for each experimental group was above the minimum recommended sample size of 30 [64,65,66]. During the research, participants were exposed to a unique combination of 2 (crisis marketing positive; crisis marketing negative) × 2 (e-Wom positive; e-Wom negative) scenarios, where the separate and combined impacts of CM and e-Wom on the outcome variables (i.e., destination trust, willingness to travel) were examined. Also, to prevent possible response biases that could result from prejudices and prior negative experiences towards any particular destination, the present study adopted a fictional destination name (i.e., Ambrosia). Therefore, participants were required to evaluate destinations’ CM campaigns and e-WOM scenarios before answering the questions about destination trust and willingness to travel. In the design of CM scenarios, the positive scenario was cultivated to include the most common characteristics of successful crisis marketing campaigns [1,2,3,7,38,67,68,69,70,71]. The positive CM scenario stressed and used the following words in the text: “empathy, transparency, optimism, and supportiveness”, whereas the negative CM scenario was designed not to sound as being transparent, optimist, and supportive, etc. [3,71] Finally, in each scenario, the same scenery was used so as to ensure that cases were perceived identical except the textual contents (Table 2). When it comes to e-WOM, participants were shown two messages in an online travel review site, where the former contained a positive message accompanied with a rating of four out of five and the latter was slightly a negative message along with two ratings. In particular, the positive e-WOM scenario emphasized the health regulations implemented to prevent the spread of the infection, whereas the negative eWOM scenario depicted a case where the regulations were not sufficiently followed (Table 3).

3.2. Measures

The outcome variable of the conceptual model, willingness to travel was assessed by the three items adapted from Moura et al. [72], including; (1) I would like to visit Ambrosia, (2) I would be interested in visiting Ambrosia, and (3) I would recommend others to go to Ambrosia [72]. For destination trust, eight items were adapted from the prior studies [73,74], including; (1) I feel confident that Ambrosia would be a good tourist destination, (2) Ambrosia would be a destination that meets my expectations, (3) Ambrosia would guarantee tourist satisfaction, (4) Ambrosia would be a destination that never disappoints me. These four items measured the reliability dimension of destination trust [73,74]. The additional adapted items for destination trust included; (1) Ambrosia would compensate me in some ways for the problems with the trip, (2) Ambrosia would make a better effort to satisfy tourists, (3) I would rely on Ambrosia to solve any problems with the trip, (4) Ambrosia would be honest and sincere in addressing my concerns. The four (04) items measured the intention dimension of destination trust [73,74]. Hence, the final scale reflected the extent to which destinations are considered reliable and capable of enhancing the tourism experience [73]. While administering the survey, respondents were asked to self-report their level of agreement on a five-point Likert type scale, where number one represented strong disagreement and five stood for a strong agreement.

4. Results

4.1. Descriptive Analysis

During analysis, correlation analyses were initially conducted per each group consisting of each unique combination (i.e., CM + EW +; CM-EW- etc.) (See Table 4). The results indicated that the VIF values for all the relationships remained below 10, hence proving the non-existence of a multicollinearity issue.
The initial MG-CFA findings illustrated that after omitting one item per both from the trust (intention dimension) and E-Wom dimensions, the rest of the loadings achieved the suggested cut-off value (0.6) per each sample group [75]. MG-CFA findings are shown in Table 5. Item loadings per each experimental condition are shown in Figure 1. Furthermore, the goodness of fit values of each group’s measurement was displayed in Table 6.

4.2. Confirmatory Factor Analysis (CFA)

This research employed a structural equation modeling technique (henceforth SEM) and AMOS 24 software was used to test the constructs’ convergent and divergent validities and measurement invariance. First and foremost, SEM is free from the shortcomings of traditional techniques used in experiments such as ANOVA and t-test, as the latter are considered inadequate while dealing with a measurement model. SEM is also useful when an unobserved variable is being measured through numerous observed items, all of which have varying factor loadings on the composite variable. Finally, SEM is capable of accommodating complex designs where mediation or moderation are involved for testing [76,77]. Consequently, the present study adopted SEM to test the suggested conceptual model.
After the constructs were acknowledged as valid, the degree of fit between the proposed conceptual model (i.e., measurement and structural models) and the data was evaluated through goodness-of-fit indexes, and hypotheses proposed in the conceptual model were tested. In this regard, multigroup CFA was conducted for each experimental condition, where the first group (group 1) comprised of participants who were exposed to “crisis marketing negative” and “e-WOM negative” scenarios. Whereas, “crisis marketing negative” and “e-WOM positive” was named as group 2, and “crisis marketing positive” and “e-WOM negative” condition was referred to as group 3. Finally, group 4 represents participants who were exposed to “crisis marketing positive and e-WOM positive scenarios”. Chen et al. [78] suggested implementing measurement invariance tests to ensure that measurement models are equivalent and samples can be compared [78]. Furthermore, for studies having multiple samples, Multi Group-CFA (henceforth MG-CFA) is utilized to analyze the equivalence of measurement and structural parameters across multiple samples.
The present study employed MG-CFA to evaluate whether both the measurement models were the same across the samples representing four experimental conditions. MG-CFA has strengths over traditional comparison tests (i.e., Anova) as it can validate and ensure measurement models’ equivalency across different samples due to it’s more sophisticated procedures [76]. During analysis, MG-CFA stepwise procedure was implemented where distinct CFAs were first conducted for each sample. Afterward, simultaneous tests were conducted to determine the identical factor structure, and equality of factor loadings was examined. Finally, item intercepts’ equality across samples was tested and equal constraints were employed to the factor variances and latent means. To investigate whether the measurement invariance assumption held, the CFI values of the constrained models were compared with the baseline model (e.g., unconstrained model). In this respect, the variation larger than (0.01) in CFI across the constrained and unconstrained models can indicate significant variation in a model fit when examining measurement invariance (MI). The differences between CFI values (i.e., 0.03) revealed that there were no substantial variances across models. Thus, as shown in Table 5, MI was achieved across different models. Having run the MG-CFA, the convergent and discriminant validities of all constructs involved in the research model were assessed respectively by average variance extracted (AVE), composite reliability (CR), and Cronbach’s Alpha tests. The results provided that both the composite reliability and average variance extracted statistics obtained values within their acceptance thresholds (see Table 7).

4.3. Manipulation Checks

In multigroup analytical methods, it is recommended to run a measurement model (See Figure 1) incorporating both the manipulation check questions and the measured constructs to test whether the manipulations have worked [76]. In particular, measurement invariance among different experimental conditions is assessed to see whether the stimulus (manipulation) significantly affects the respondents. Therefore, this study applied a differential invariance test to analyze whether there are inter-group differences in the measurement model. When the paths were constrained, the findings revealed that all the four models were found significantly variant (Δx2: 2.32; Δ degree of freedom:4; p. 001). Nevertheless, also for the case when the paths were unconstrained, measurement models were found to be significantly variant across the four groups (Δx2: 4.78; Δdegree of freedom:4; p. 001). These findings demonstrated a variance across the four experimental conditions, indicating that scenarios worked effectively to stimulate each group as expected.

4.4. Hypothesis Testing

Having empirically verified the validity of the measurement models, the proposed hypotheses in the conceptual model were tested. The findings demonstrated that for participants who were exposed to positive crisis marketing (i.e., Group 3 and 4), crisis marketing has a significant positive influence on the destination trust, whereas the same relationship was found insignificant for those being exposed to negative crisis marketing scenarios (i.e., Group 1 and 2). Hence the first hypothesis was empirically supported. Moreover, the findings also showed that for the participants who were shown the positive e-WOM scenario, e-WOM was found to have a significant positive influence on destination trust (i.e., Group 2 & 4), whereas the same relationship was noted to have a negative direction for the respondents who were provoked by the negative e-WOM scenario (i.e., Group 3 and Group 1). Furthermore, for Group 3, the relationship was insignificant. Based on these findings, the second hypothesis of the conceptual model was empirically approved (see Figure 2 and Table 8).

4.5. Mediation Analysis

Hierarchical linear modeling (HLM) based on multigroup structural equation modeling was applied to verify the mediating role of destination trust between willingness to travel with e-WOM and crisis marketing. Also, the bootstrapping method with maximum likelihood estimation was applied to calculate the direct and indirect influences of crisis marketing and EWOM on willingness to travel. Finally, group-wise comparisons were run to identify the degree of the mediating role of trust across the four subsamples. Along with the direct significant influence of destination trust on willingness to travel across each group (Group1, β = 0.18; Group2, β = 0.21; Group3, β = 0.53 and Group4, β = 0.67), the findings also revealed that trust partially mediates the relationship between e-WOM and willingness to travel in each group. In particular, the indirect influence of e-WOM on willingness to travel via trust was found significant across all groups. Besides the indirect effect, the direct effect of e-WOM on WTT also remained significant. Therefore, e-WOM partially mediated the relationship between destination trust and WTT (H3 accepted). Similarly, the findings revealed that destination trust partially mediates the relationship between crisis marketing and willingness to travel across all groups. In this respect, the indirect influence of crisis marketing on WTT via destination trust was found significant. Furthermore, the direct influence of crisis marketing on WTT was still significant despite the destination trusts’ mediating role across all the groups. Based on these findings, destination trust was considered to partially mediate the relationship between crisis marketing and WTT. Thus, H4 was accepted (please see Table 9 for regression weights and related significance levels). Furthermore, in light of the SEM results, the mediating role of destination trust was found to be intensified for respondents being exposed to positive e-WOM and crisis marketing scenarios (Group 4). The implications of these results are discussed in the next section.

5. Conclusions and Implications

Despite mounting literature on the complex challenges of the COVID-19 pandemic and uncertain demands for global travel [79], there is still rare evidence on how destination crisis marketing campaigns influence people’s willingness to travel [1,2,7,38]. Consequently, the debate about what and how to communicate during the tourism crisis seems to be intensified [8,80]. This study is a preliminary effort that aimed to compare the influence of owned and earned media’s on creating a positive assessment of destinations under the time of the COVID-19 crisis. To do so, the present study examined UAE residents’ willingness to travel (N = 232 with over 10 different nationalities) using experimental evidence of destination crisis marketing campaigns, e-Wom and the mediating role of destination trust [1]. A quasi-experimental between subject research design was applied in the study, where the impacts of “2 destinations’ owned media scenarios (i.e., crisis marketing implemented; crisis marketing not implemented) × 2 destinations’ earned media scenarios (i.e., positive e-Wom; negative e-Wom)” on destination trust and intention to visit were examined. The study findings revealed that respondents exposed to positive crisis marketing campaigns developed significantly higher trust towards destinations than those stimulated by the negative crisis marketing scenario. In a similar vein, respondents when being provoked by the positive e-WOM formed higher levels of destination trust than those primed with the negative e-WOM stimuli. Thus, the study findings confirmed the prior studies, which have highlighted that both owned and earned media’s can be relevant to boost positive perceptions about destinations to help destinations recovery [16,17,27,33,36,37]. Furthermore, the findings illustrated that even though a destination implements a crisis marketing campaign, the impact of negative e-WOM still surpassed the positive effects of the CM. In particular, although the positive crisis marketing scenario was acknowledged to enhance the destination trust, it was still not able to positively influence respondents’ willingness to travel. This may be attributable to the fact that safety cues used in the messages may prime the probability of risk and remind tourists of the threats or dangers [81]. Therefore, a crisis marketing campaign stressing safety measures may scare tourists and increase their risk perceptions [82]. Also, user-generated content is considered an authentic and more reliable source of information than official messages by destination management organizations in crisis [49].
Also, in the case when participants were provoked by the negative DOM scenario (i.e., crisis marketing not implemented), the positive influence of e-WOM appeared to outweigh the negative influence. In particular, the negative effect of DOM (-) on destination trust was found insignificant and the negative relationship between DOM (-) and willingness to travel was very weak although being significant. Therefore DEM (e-WOM) was noted as more effective than DOM (Crisis marketing) to reestablish destination trust, which in turn enhanced participants’ willingness to travel at a greater scale than the DOM. This finding aligns with previous studies that highlighted earned media as a more influential channel than the owned media platforms to strengthen consumers’ positive intentions and trust [15,18]. The present study also suggests earned media sources such as online review sites and social media over DOM to generate destination trust when destinations are suffering from the pandemic [19,20]. Last but not least, this study tested and verified the mediating role of destination trust on the relationship between willingness to travel, crisis marketing and e-WOM. Whereas, in the case that participants were stimulated by the negative crisis scenario, destination trust was noted not to mediate the relationship between crisis marketing and willingness to travel relationship. Thus, the mediating role of destination trust was not affirmed.

5.1. Theoretical Implications

Although destination trust and loyalty have been commonly investigated under normal circumstances, the study of the interrelationships between these concepts in times of crisis has been largely neglected [21]. Therefore, this study makes a novel contribution to tourism literature by empirically testing and validating the direct impact of destination trust on loyalty while destinations still suffer from the global crisis. Besides, the present study also investigates the indirect impacts of e-WOM and crisis marketing on willingness to travel through destination trust, thereby contributing to the scholarly understanding of the role of destination trust [26,46,63]. The findings articulated that tourism behavior is a more dominant factor of e-WOM than crisis marketing due to the stronger indirect impact of e-WOM on willingness to travel. Therefore, the present study for the first-time sheds light on the relative impact of DOM and DEM on destination recovery efforts, where DEM was acknowledged to be more effective in boosting destination trust and favorable tourism behavior. Last but not least, the present study applied an experimental design to validate the research’s hypotheses, thus making a methodological contribution to tourism literature as well. In comparison with other disciplines such as psychology, education and marketing, the experimental design remains under-utilized in tourism literature [83,84,85]. Furthermore, the prior literature also recommended applying an experimental design to elicit the influence of social media to predict tourism behavior [85]. In this vein, this study is a pioneering work that applied experimental design for investigating the impact of social media on tourism behavior in a time of crisis.

5.2. Managerial Implications

Based on the study findings, destination management organizations are advised to invest in both DOM and DEM channels. Nevertheless, e-WOM was found to be substantially more influential than crisis marketing campaigns, thus should be given more emphasis for triggering tourism demand while destinations are still recovering from the crisis. Borrowed from the signal theory, positive e-WOM can serve as a valuable signal, leading tourists to develop trust towards destinations [32,33]. Therefore, destinations should timely respond to negative comments on online platforms (i.e., online review sites, social media, blogs), and spread positive information about the destinations’ positive attributes, including safety and high-quality standards. Besides, destinations should design and host their online communities to foster e-WOM communication, interactivity for a better tourism experience. Destinations are also suggested to take more active roles in generating, distributing, and administering e-WOM information to foster destination image and trigger tourism demand [86]. For instance, destinations can send relevant advertising links or customized offers to the members of online communities, which will create additional value for them and develop an emotional bond with potential visitors [87]. Destinations should also carefully explore and balance the potential inconsistencies between the official promotional materials and e-WOM created in online travel communities, review sites, and blogs, etc. Essentially, the provision of unrealistically positive messages may backfire as tourists visit the destination and experience that the destination is much different in reality than depicted in the promotional messages [88]. Therefore, destination marketers should try to assure image and information coherency across various DOM and DEM platforms so to build destination trust and trigger future tourism demand [89]. In line with this, destination management organizations are suggested to adopt optimist, empathetic, transparent, and supportive attitude in their crisis marketing tools.

5.3. Limitations and Future Research

Despite bringing new perspectives for destination management organizations to deal with the tourism crisis, this study has some limitations that are noteworthy to be highlighted. First, the respondents were mostly from Eastern cultures, whereas the Pakistani nationals constituted nearly one-third of the overall sample. Eastern cultures have mainly low certainty avoidance, where people have a higher propensity to depend on personal information sources such as friends, relatives, online travel reviews, etc. [90]. Therefore, the fact that e-WOM was acknowledged as more influential than destinations owned crisis marketing message could be attributed to the respondents’ cultural backgrounds. However, it must also be noted that the research sample was quite heterogeneous as there were more than twelve nationals participating in the research. In a most recent study, Carvalho [91] enrolled a heterogeneous sample to find the shared patterns across people with diverse cultures, which enhanced the findings’ generalizability [91]. Similarly, the fact that this present study also involved expats with different nationalities is believed to increase the generalizability of the findings [92]. To that end, future studies should concentrate on tourists from particular cultures to verify whether e-WOM or crisis marketing campaigns are more effective in times of crisis. Furthermore, tourists’ attitudes towards destinations’ marketing messages can change during the period of crisis, especially when tourists feel threatened [93,94]. In this vein, future studies should investigate the relative efficacy of destination-owned media or e-WOM for building destination trust and increasing willingness to travel.

Author Contributions

Conceptualization, U.Z. and M.A.; methodology, U.Z. and M.A.; software, S.H.R.; validation, S.H.R.; formal analysis, S.H.R.; investigation, U.Z., E.C.O. and S.H.R.; resources, S.H.R., E.C.O., P.F. and U.Z.; data curation, M.A., U.Z., E.C.O. and S.H.R.; writing—original draft preparation, M.A., U.Z., S.H.R. and P.F.; writing—review and editing, U.Z., M.A., S.H.R. and P.F.; visualization, S.H.R.; supervision, U.Z. and M.A.; project administration, U.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research did not receive any funding.

Informed Consent Statement

Informed consent was initially obtained from all participants who had volunteered to participate in this study.

Data Availability Statement

The study data is available on special request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 14 01111 g001 550
Figure 1. Four Framing Groups’ Measurement Models.
Figure 1. Four Framing Groups’ Measurement Models.
Sustainability 14 01111 g001
Sustainability 14 01111 g002 550
Figure 2. Four Framing Groups’ Structural Models.
Figure 2. Four Framing Groups’ Structural Models.
Sustainability 14 01111 g002
Table
Table 1. Global Expat’s Demographics (N = 232).
Table 1. Global Expat’s Demographics (N = 232).
AgeFreq.%Monthly Income
(UAE Dirham) *		Freq.%
18–25361510,000–20,0007331
26–35693021,000–30,0008637
36–45552431,000–40,0003816
46–55431941,000–50,0002210
≥552912Above 50,000136
Nationality Education
Egyptian239Matriculation/O-Levels2812
Nigerian2611Intermediate/A-Levels4118
Pakistani6328Graduation7432
Palestinian156Masters8436
American125Ph.D.52
Indian104Gender
Filipino73Male12755
Syrian63Female10545
Saudi Arabian52
Sudanese52
Algerian 52
Other Nationalities5525
Note: * 1 Dirham is equal to 0.27 USD.
Table
Table 2. Destination Crisis Marketing Scenarios.
Table 2. Destination Crisis Marketing Scenarios.
Destination Crisis Marketing (Implemented)
Sustainability 14 01111 i001		Welcome to Ambrosia,
The good news is that bad things will end soon 1. We know that our lovely planet as well as Ambrosia is going through difficult times, thus we empathize with your health concerns 2 due to the recent pandemic. Lying at the heart of the Mediterranean Sea, Ambrosia is a unique and exciting destination that offers many cultural and historical attractions and a variety of interesting activities. To ensure a reliable, safe, and healthy holiday, we transparently follow the rules and regulations 3 of International Health and Tourism Authorities. We are committed to providing high standards of quality, hygiene, and safety standards throughout your journey, and fully support you 4 for a memorable and distinguished vacation.
Destination Crisis Marketing (Not Implemented)
Sustainability 14 01111 i002		Welcome to Ambrosia,
We know that our lovely planet as well as Ambrosia is going through difficult times due to the recent pandemic. However, this crisis shouldn’t prevent us from realizing our dreams and exploring our planet. Lying at the heart of the Mediterranean Peninsula, Ambrosia is an exciting and fascinating destination that offers many cultural and historical attractions and a variety of interesting activities. To ensure a joyful holiday for you, we are committed to providing distinguished services as well as memorable experiences while you are our guest.
Note: 1 optimism; 2 empathy; 3 transparent and 4 supportiveness as four key-characteristics of destination campaign.
Table
Table 3. Destination e-WOM scenarios.
Table 3. Destination e-WOM scenarios.
Positive e-WOM about AmbrosiaNegative e-WOM about Ambrosia
Great and Safe Stay in Ambrosia
Sustainability 14 01111 i003		Not a very pleasant stay in Ambrosia
Sustainability 14 01111 i004
I enjoyed every moment of my vacation in Ambrosia. The destination offers a variety of amazing and unique experiences, including Mediterranean cuisine and visiting cultural monuments from ancient civilizations. During my journey, there were very strict regulations to prevent the spread of infectious viral diseases. Social distancing practices were strictly followed in my hotel and other touristic areas. Our body temperatures were measured every time before entering the hotel as well as in tourist places.Although I had enjoyed most of the time during my vacation in Ambrosia, there were some incidences that I felt insecure and vulnerable to the risk of getting an infectious disease. Despite the delicious Mediterranean cuisine and visiting cultural monuments from ancient civilizations, the health measures were loosely implemented. The rule of social distancing was not sometimes ensured at my hotel as well as in other touristic areas. Also, some of the staff seemed to not take the pandemic very seriously.
Table
Table 4. Descriptive and Pearson Correlation Statistics (N = 232).
Table 4. Descriptive and Pearson Correlation Statistics (N = 232).
CM+
EW-		MeanαCMEWDTWTTCM-
EW-		MeanαCMEWDTWTT
CM3.360.931 CM3.580.961
EW3.100.89−0.251 EW3.290.85−0.271
DT3.490.91−0.17−0.601 DT3.710.89−0.230.381
WTT3.500.93−0.13−0.65−0.431WTT3.800.82−0.140.270.361
CM+
EW-		Mean CMEWTRWTTCM+
EW+		Mean CMEWTRWTT
CM3.250.921 CM3.870.941
EW3.660.720.451 EW3.730.860.131
DT3.650.900.190.511 DT3.810.880.370.551
WTT3.790.870.210.490.351WTT3.920.900.290.590.721
Note: CM = Crisis marketing, EW = Electronic Word of Mouth, DT = Destination Trust, and WTT = Willingness to Travel, (each group n = 58, N = 232); bold italic values represent non-significance.
Table
Table 5. Nested Models Comparison (N = 232).
Table 5. Nested Models Comparison (N = 232).
MG-CFA ModelsX2/dfCFITLIRMSEA
Unconstrained2.5800.8070.8680.039
Measurement weights2.5060.8050.8790.038
Measurement intercepts2.4370.8030.8830.036
Measurement residuals2.4120.8040.8850.038
Independence model4.4920.0000.0000.000
Table
Table 6. Confirmatory Factor Analysis (N = 232).
Table 6. Confirmatory Factor Analysis (N = 232).
Measurement Modelsx2/dfGFITLIIFICFIRMSEA
Group1: CNWN2.650.930.930.950.940.044
Group2: CNWP2.470.910.910.980.970.016
Group3: CPWN3.450.880.910.920.900.081
Group4: CPWP2.120.960.910.960.950.028
Structural Modelsx2/dfGFITLIIFICFIRMSEA
Group1: CNWN3.210.930.94 0.890.900.059
Group2: CNWP2.910.950.890.910.930.067
Group3: CPWN4.160.920.960.900.920.021
Group4: CPWP2.980.990.970.920.940.032
Note: CNWN (both destination crisis marketing and e-Wom are negative); CNWP (negative destination crisis marketing and positives e-Wom); CPWN (positive destination crisis marketing and negative e-Wom); CPWP (both destination crisis marketing and e-Wom are positive).
Table
Table 7. Validity Statistics and Standardized Weights (N = 232).
Table 7. Validity Statistics and Standardized Weights (N = 232).
ItemsGroup 1:
CM- & EWOM- 		Group 2:
CM- & EWOM+		Group 3:
CM+ & EWOM-		Group 4:
CM+ & EWOM+
CRAVELCRAVELCRAVELCRAVEL
CM10.940.720.820.920.670.900.950.780.960.950.770.96
CM2 0.90 0.81 0.93 0.82
CM3 0.85 0.75 0.86 0.85
CM4 0.83 0.75 0.79 0.93
CM5 0.81 0.79 0.89 0.84
CM6 0.87 0.91 0.85 0.85
EWM10.900.810.940.800.660.810.860.750.860.890.810.88
EWM2 0.86 0.82 0.87 0.92
IN20.930.630.760.920.600.680.890.540.750.920.610.85
IN3 0.71 0.82 0.66 0.61
IN4 0.89 0.79 0.65 0.87
RL1 0.77 0.68 0.63 0.80
RL2 0.79 0.76 0.77 0.79
RL3 0.78 0.80 0.81 0.83
RL4 0.85 0.86 0.84 0.68
WT10.940.840.990.900.760.660.860.680.680.820.930.85
WT2 0.85 0.93 0.92 0.98
WT3 0.90 0.99 0.85 0.88
Note: CM = Destination Crisis Marketing, EW = Electronic Word of Mouth, DT = Destination Trust, WTT = Willingness to Travel, RL = Reliability Dimenion of Destination Trust, IN = Intention Dimension of Destination Trust, and L = Loading of items.
Table
Table 8. Hypothesis Testing (N = 232).
Table 8. Hypothesis Testing (N = 232).
Direct InfluenceTRUST<---CMTRUST<---EWOM
Group1: CNWN−0.02 (p = 0.11)−0.35 (p = 0.001)
Group2: CNWP−0.09 (p = 0.10)0.31 (p = 0.001)
Group3: CPWN0.41 (p = 0.001)−0.17 (p = 0.069)
Group4: CPWP0.48 (p = 0.001)0.59 (p = 0.001)
Note: CNWN (both destination crisis marketing and e-Wom are negative); CNWP (negative destination crisis marketing and positive e-Wom); CPWN (positive destination crisis marketing and negative e-Wom); CPWP (both destination crisis marketing and e-Wom are positive); H1 and H2 are supported.
Table
Table 9. Meditating Effects of Destination Trust (N = 232).
Table 9. Meditating Effects of Destination Trust (N = 232).
ModelsWTT<--EWOM
Direct Effect β		WTT<--CM Direct Effect βWTT<--TRUST<--EWOM
Indirect Effect β		WTT<--TRUST<--CM Indirect Effect βMediation
G1: CNWN−0.29 (p = 0.001)0.05 (p = 0.001)−0.10 (p = 0.001)−0.04 (p = 0.001)Partial
G2: CNWP0.23 (p = 0.01)−0.19 (p = 0.01)0.19 (p = 0.01)−0.02 (p = 0.01)Partial
G3: CPWN−0.03 (p = 0.001)−0.24 (p = 0.001)−0.14 (p = 0.001)0.25 (p = 0.001)Partial
G4: CPWP0.41 (p = 0.001)0.35 (p = 0.001)0.46 (p = 0.001)0.34 (p = 0.001)Partial
Note: CNWN (both destination crisis marketing and e-Wom are negative); CNWP (negative destination crisis marketing and positive e-Wom); CPWN (positive destination crisis marketing and negative e-Wom); CPWP (both destination crisis marketing and e-Wom are positive); β = Standardized Regression Weight.
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Aktan, M.; Zaman, U.; Farías, P.; Raza, S.H.; Ogadimma, E.C. Real Bounce Forward: Experimental Evidence on Destination Crisis Marketing, Destination Trust, e-WOM and Global Expat’s Willingness to Travel during and after COVID-19. Sustainability 2022, 14, 1111. https://doi.org/10.3390/su14031111

AMA Style

Aktan M, Zaman U, Farías P, Raza SH, Ogadimma EC. Real Bounce Forward: Experimental Evidence on Destination Crisis Marketing, Destination Trust, e-WOM and Global Expat’s Willingness to Travel during and after COVID-19. Sustainability. 2022; 14(3):1111. https://doi.org/10.3390/su14031111

Chicago/Turabian Style

Aktan, Murat, Umer Zaman, Pablo Farías, Syed Hassan Raza, and Emenyeonu C. Ogadimma. 2022. "Real Bounce Forward: Experimental Evidence on Destination Crisis Marketing, Destination Trust, e-WOM and Global Expat’s Willingness to Travel during and after COVID-19" Sustainability 14, no. 3: 1111. https://doi.org/10.3390/su14031111

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