Every storm will pass: Examining expat’s host country-destination image, cultural intelligence and renewed destination loyalty in COVID-19 tourism

Abstract

The massive cultural transformation in the pandemic-paused tourism industry has revamped loyalty towards destinations, thus prompting scholarly attention towards global expats who were rarely considered in tourism research. Drawing on data from 266 expats in South Korea, the study examined the effects of country image (CYI), destination image (DNI), and expat’s cultural intelligence (ECLI) on expat’s renewed destination loyalty (EDLY) in COVID-19 tourism. Using partial least squares structural modeling (PLS-SEM), we show that expat’s cultural intelligence has a significant influence on destination image and expat’s destination loyalty. Moreover, the study provides new empirical evidence that destination image mediates country image and expat’s destination loyalty in the COVID-19 tourism. The study findings underpin policy interventions to rescue tourism destinations under COVID-19 crisis, as well as restore loyalty towards destinations in the post-COVID-19 global tourism.

Keywords:

• Country image
• destination image
• cultural intelligence
• destination loyalty
• global expats and COVID-19 tourism

PUBLIC INTEREST STATEMENT

The COVID-19 pandemic with its emerging new “delta” variant outbreaks has almost paralyzed the global travel and tourism industry. The highly changing tourism landscape has created new and unprecedented challenges for tourism destinations to lead their strategic response under the increasing threats and constraints of the pandemic. The present study focused on the dominant role of global expats to explore the paradigm shift in the country image, destination image, and renewed destination loyalty under the COVID-19 tourism. Importantly, the present study specifically focused on the changing cultural dynamics across tourism destinations, by examining the role of expats cultural intelligence in influencing their evaluation of destination image and renewed destination loyalty under COVID-19 tourism. The study implications offer significant advancements in theoretical and practical insights for dealing with the emerging challenges, and creating new opportunities for the survival and growth of tourism under and beyond COVID-19 pandemic.

1. Introduction

In the midst of an unprecedented downturn faced by the global tourism industry, destinations are currently preparing themselves for the next wave of international visitors once travel becomes safe and less restricted (Gössling et al., 2020; Zenker & Kock, 2020). Such underlying conditions have created opportunities for many countries and host destinations to re-assess and re-align themselves with the changing international tourism landscape (Gössling et al., 2020). Because the coronavirus pandemic has altered nearly everything in tourism industry from traveling rules and regulations to past tourism habits, the tourism industry during the pandemic (i.e., COVID-19 tourism) needs new deliberate perspectives (Zhang et al., 2021). To that end, repositioning of the CYI and DNI can renew tourism efforts and modernize destinations to host massive numbers of international travelers in the COVID-19 tourism (Brouder, 2020; Gössling et al., 2020). Hence, international tourism destinations need to consolidate their efforts and adopt a holistic approach involving each and every stakeholder to enhance loyalty, as well as dispel any doubts about the host destinations (Brouder, 2020; Stylidis et al., 2020).

Drawing upon the stakeholder’s theory, this study investigates expats as a key partner to help destinations’ image recovery efforts amidst the pandemic. According to stakeholder’s theory destinations need the collaboration of all stakeholders (i.e., tourism businesses, local communities and tourists) while designing destination promotional campaigns (Erul et al., 2020; Zaman & Aktan, 2021). Surprisingly, global expats’ voices have been largely missing in the tourism literature, although they currently represent 3.4 % of the world population (Dutt et al., 2018). In essence, expats live, travel, work and retire in overseas, creating a long-term symbiotic relationship with their host destinations (Frías-Jamilena et al., 2018a). Thus, the presence of expat communities can send positive messages to international travelers about destinations’ friendliness, multiculturalism, safety, and trust (Abuhjeeleh et al., 2019; Dutt et al., 2018). In this respect, expat groups can help destinations to facilitate inbound tourism and aid destination recovery, despite the continuing global pessimism about traveling (Brouder, 2020). Also, the fact that expats have heightened levels of cultural tolerance and capability to work in a culturally diverse environment, their assessment of CYI and DNI can provide meaningful insights for destination marketers (Lee & Xue, 2020). In contrast to occasional general tourists with inadequate short-travel experiences, expats are more credible and marketable source for destinations’ self-evaluation (Abooali et al., 2016; Frías-Jamilena et al., 2018a).

Furthermore, this study concentrated on expats residing in South Korea. Despite the fact that South Korea has been mostly famous for its technologically advanced products, it has become a major tourism hotspot receiving nearly 30 million tourists in 2019 (Gurung, 2021). Also, in contrast to many nations, South Korea well-managed to control the spread of the virus and flattened the dissemination curve in a shorter-period. Hence, the pandemic did not have a substantial impact on the South Korean economy especially at the early phases of the pandemic (Lim et al., 2021). South Korea is a flourishing tourism destination and it positively differentiates from other tourism destinations, especially during the pandemic. Hence, the present study selectively focused on the unique COVID-19 tourism perspective of South Korea, to explore the hypothesized relationships in a newly developed novel research model.

Although the relationship between CYI and DNI has been very recently mentioned in a few studies (Chaulagain et al., 2019; Dedeoğlu, 2019; Palau-Saumell et al., 2016; Zhang et al., 2018), a large majority of tourism research has downplayed the role of individuals’ cultural background in their evaluation of destinations. In essence, cultural intelligence can significantly alter DNI perceptions as well as visitors’ feelings towards destinations (Aktan et al., 2021; Frías-Jamilena et al., 2018a). Tourist’s cultural intelligence (involving their cultural knowledge, cross-cultural skills, and cultural metacognition) goes beyond simply being emotionally mature, intelligent, and/or socially alive. Culturally intelligent individuals reveal to be highly interactive while navigating across cultural boundaries, and to realistically assess the host DNI and CYI (Abooali et al., 2016; Frías-Jamilena et al., 2018a).

Destination loyalty becomes especially more fragile in times of crisis due to the travelers’ aroused fears, massive competition and emergence of safer places as new touristic destination brands (Gössling et al., 2020; Stylidis et al., 2020). To that end, this study for the first time investigates the relationships between CYI, DNI, and EDLY while the COVID-19 crisis is still continuing (e.g., emergence of the COVID-19 “delta variant” leading the highly-contagious outbreaks). Also, this study comprises an initial effort that includes the influence of cultural intelligence on DNI perceptions and EDLY, thus shedding light on an under-researched area in tourism (Aktan et al., 2021; Frías-Jamilena et al., 2018a). Since the “cultural intelligence” concept was just recently introduced to tourism literature (Frías-Jamilena et al., 2018a,b), there is a lack of research about how tourists’ cultural intelligence can reshape well-accepted relationships between concepts such as country image, destination image, and destination loyalty etc. Last but not least, the tourism literature has surprisingly overlooked the roles of expats in destination marketing strategies, by confining the destination loyalty canvas to only general tourists (Dutt et al., 2018; Lee & Xue, 2020). Addressing this potential research gap and the dramatic shift in global tourism affected by the COVID-19 pandemic (Gössling et al., 2020), the present study analyzed the perceptions of expats residing in South Korea to test the proposed relationships via structural equation modeling.

2. Literature review

2.1. CYI and DNI under COVID-19

Globally affected by the COVID-19 crisis, countries and destinations are being categorized into groups (i.e. green, yellow, orange or red) to facilitate a deemed safe travel across international borders (Gössling et al., 2020; Higgins-Desbiolles, 2020). Consequently, CYI and DNI have re-gained huge attention and importance than ever before, especially in times of increased travel restrictions, growing safety concerns and battling mandatory quarantine during international travel (Chaulagain et al., 2019; Gössling et al., 2020; Zenker & Kock, 2020). CYI is a generic concept defined as one’s overall information and belief about a particular country (Hahm et al., 2018; Martin & Eroglu, 1993). Due to this broad definition, the CYI concept has encompassed a variety of related or unrelated elements including culture, traditions, history, economy, politics, and technology, etc. (J. Zhang et al., 2018). As a consequence, although CYI has frequently been operationalized as a multi-dimensional construct in the literature, there are some inconsistencies and differences in its interpretation. For instance, while Lindblom et al. (2018) pointed to a three-dimensional construct to measure CYI by integrating the conative, cognitive, and affective image elements, Chaulagain et al. (2019) treated CYI as a bi-dimensional construct comprising cognitive and affective evaluations. Apart from that, different factors such as political stability, cultural diversity (Hahm et al., 2018); people and country character (Nadeau et al., 2008) and events taking place in a country (Mossberg & Kleppe, 2005) have also been utilized to measure overall CYI.

Mainstream studies in international marketing have provided solid evidence that CYI can impede or facilitate the sales of domestically produced intangible and tangible products abroad (Aktan, 2020; Aktan & Chao, 2016; Chaulagain et al., 2019; Ozretic-Dosen et al., 2018), or hosting universal events like Olympic games (Hahm et al., 2018). Similarly, because visiting a tourism destination can be considered a product of the host country, tourist behavior can be affected by peoples’ CYI preconceptions (Hahm & Tasci, 2019; Hahm et al., 2018). Especially, for the ones who have not visited the destinations within the country, this effect will be magnified and CYI significantly impacts prospective tourists’ DNI perceptions (Chaulagain et al., 2019; Palau-Saumell et al., 2016; Soonsan & Sukahbot, 2019; J. Zhang et al., 2018). DNI refers to individuals’ overall belief, ideas, and impressions about a destination (Crompton, 1979) and is identified as a multidimensional construct involving cognitive, affective, and conative image dimensions (Tasci et al., 2007) as well as functional and psychological elements related to destinations (Echtner & Ritchie, 1993; J. Zhang et al., 2018). To ensure effective positioning for destinations, destination marketers have to develop unique and positive images and associations to attract tourists (Palau-Saumell et al., 2016).

Although CYI and DNI literature have progressed independently on discrete avenues (Elliot et al., 2011), there has been a growing body of research recently, which manifests that these two constructs are interrelated and positively related (Chaulagain et al., 2019; Palau-Saumell et al., 2016; Soonsan & Sukahbot, 2019; J. Zhang et al., 2018). The recent destination marketing literature has postulated that CYI plays an important role in tourists’ destination choices as an antecedent factor (Nadeau et al., 2008), especially when the prospective visitors are not familiar with the destinations (Dedeoğlu, 2019). Furthermore, recent studies have also provided evidence that the CYI has a varying impact on DNI depending on how both concepts are conceptualized. For instance, in their study measuring CYI by country and people character dimensions, Palau-Saumell et al. (2016) revealed that “people character” has a stronger direct effect on DNI than the “country character” dimension. This finding implies that tourists give more importance to the affective factors, when they assess destinations. However, J. Zhang et al. (2018), illustrated that cognitive CYI has a stronger influence on destination’s psychological image (affective) than the functional dimension (cognitive). These findings in the literature suggest that cognitive and affective dimensions of CYI do not necessarily have a similar effect on the DNI’s cognitive and affective components, rather there is a varying degree of relationship between CYI and DNI dimensions depending on the country and destination under study (Lindblom et al., 2018). Based on the theoretical discussions above, the following hypothesis is proposed.

H₁: CYI has a significant and positive effect on DNI in the COVID-19 tourism.

2.2. DNI and EDLY under COVID-19

The COVID-19 tourism has prompted new sets of travelers’ expectations, changed priorities and destination choices compared to pre-pandemic tourism (Osti & Nava, 2020; Zenker & Kock, 2020). Consequently, loyalty towards once renowned destinations has been mostly ruined during the pandemic. To address this change, this study uses the term renewed destination loyalty to reflect expats feelings towards a destination in COVID-19 tourism (Osti & Nava, 2020). A strong DNI can naturally create a decisive advantage in safeguarding destination loyalty in post COVID-19 tourism (Chaulagain et al., 2019; Gössling et al., 2020; Zenker & Kock, 2020). The destination loyalty concept has been attracting tourism researchers’ interest for the last decades with a special focus given to its conceptualization (Prayag & Ryan, 2012) and antecedents (Lindblom et al., 2018; Hasan et al., 2020. Although destination loyalty has frequently been conceptualized with attitudinal and behavioral loyalty dimensions (Kumar et al., 2020; Liu et al., 2019), behavioral loyalty has been criticized due to only focusing on the actual outcome of tourist’s decision-making process while overlooking tourist intentions and motives (Yoon & Uysal, 2005). Therefore, previous studies have measured loyalty considerably with attitudinal loyalty elements such as positive WOM (word-of-mouth) about destinations, revisit intentions (Dedeoğlu, 2019; Králiková et al., 2020; Prayag & Ryan, 2012) rather than the actual tourist behavior.

Establishing and maintaining a positive image is an essential element for destination promotion (Hahm & Tasci, 2019) because tourists’ behavioral intentions are largely driven by DNI perceptions amongst other factors (Aktan et al., 2021; Hasan et al., 2020; Palau-Saumell et al., 2016). Previous studies have sufficiently postulated that DNI has a significant positive effect on destination loyalty including tourists’ travel intention (Lindblom et al., 2018), destination visit and revisit intentions (Chaulagain et al., 2019; Hahm & Tasci, 2019), and attitude towards destinations (Hasan et al., 2020). Despite the solid evidence in the literature for the relationship between DNI on destination loyalty (Hasan et al., 2020; Jeong & Kim, 2019; Prayag & Ryan, 2012), some studies have also revealed that the DNI components have a varying degree of influence on destination loyalty. For instance, Králiková et al. (2020) posited that tourists’ sense of security felt in a destination (cognitive dimension) is the most influential DNI component for tourists’ recommendation intentions, whereas, affective elements (i.e. uniqueness of the food, suitability for year-round vacations) have a more substantial influence on tourists’ revisit intentions. Further, on a recent study conducted on Chinese tourists visiting Seoul City (Korea), Chiu et al. (2016) depicted that affective DNI has a direct positive effect on destination loyalty, whereas cognitive DNI was found to indirectly impact loyalty through affective image and tourist satisfaction. Despite these differences in the degree of relationships, the following hypothesis is developed based on the above theoretical discussions.

H₂: DNI has a significant and positive effect on EDLY in the COVID-19 tourism.

2.3. Mediating role of DNI under COVID-19

The relationship between CYI and DNI has been highlighted by many tourism scholars (Chaulagain et al., 2019; Chung & Chen, 2018; Hahm et al., 2018; Palau-Saumell et al., 2016; Soonsan & Sukahbot, 2019) in addition to studies postulating that both CYI and DNI are significant predictors of tourist’s behavior, attitudes, and intentions (R. Lee & Lockshin, 2012; Stepchenkova & Shichkova, 2017). However, the impact of country and DNI on tourist behavior may not always be parallel despite their conceptual similarities (Chaulagain et al., 2019). For instance, although the individuals have poor country perceptions due to negative economic, social, and political problems happening in the country, they might still have positive images regarding the destinations within the country (Hahm et al., 2018). Therefore, DNI has a potential role in mitigating the harm of CYI on destination evaluations, while reinforcing tourists’ loyalty to destinations, while (Palau-Saumell et al., 2016).

In a recent study focusing on Japanese citizens’ evaluation of Nordic countries (i.e., Finland, Denmark, Sweden) as tourism destinations, Lindblom et al. (2018) acknowledged that beliefs about destinations mediate the relationship between CYI and respondents’ intention to visit these countries within the next 12 months. In another study assessing American citizens’ evaluation of Cuba as a tourism destination, Chaulagain et al. (2019) examined the relationships between intention to visit, DNI, familiarity, and CYI. Their findings revealed that CYI directly impacts participants’ intention to visit Cuba, in addition to its indirect influence through Cuba’s perceived DNI. Further, respondents’ familiarity with Cuba was also noted to moderate the mediating effect of DNI on the relationship between CYI and intention to visit. Finally, J. Zhang et al. (2018) connoted that the DNI of Beijing mediates the relationship between the CYI of China and international tourists’ evaluations of Beijing as a destination. Their findings also revealed that the mediating effect of the psychological component of Beijing’s DNI is stronger than Beijing’s functional image. In line with the theoretical propositions above, the third hypothesis of the research model is generated.

H₃: DNI mediates the relationship between CYI and EDLY in the COVID-19 tourism.

2.4. ECLI, DNI, and EDLY under COVID-19

The survival of destinations in the post COVID-19 global tourism requires reinforcement of a strong DNI to re-engage international travelers, and to build as well as restore their loyalty towards destinations (Brouder, 2020; Chaulagain et al., 2019). Importantly, the traveler’s cultural intelligence has become vital to re-discover the aftermath of COVID-19 on global tourism, especially to comprehend the massive cultural change that follows after the pandemic (Brouder, 2020; Frías-Jamilena et al., 2018a; Zenker & Kock, 2020). The impact of culture on consumer behavior (De Mooij, 2019) has also been heightened for the tourism industry as tourism space requires more intercultural communication between the travelers and service providers (Alshaibani & Bakir, 2017; Darvishmotevali et al., 2018). Described first by Earley and Ang (2003), cultural intelligence refers to individuals’ ability to communicate effectively with individuals from diverse cultures. Most of the studies about cultural intelligence in tourism have indicated that tourism professionals should be trained as culturally intelligent individuals to be capable to have empathy towards tourists from different cultures (Alshaibani & Bakir, 2017; Darvishmotevali et al., 2018; Ljubica & Dulcic, 2012; Teimouri et al., 2015). However, these studies have a one-sided approach because they have mainly focused on tourism professionals while largely overlooking other tourism stakeholders such as residents and expats (C. S. Dutt et al., 2018; Stylidis et al., 2016).

Cultural intelligence is conceptualized with four dimensions including metacognitive, cognitive, motivational, and behavioral components (Earley, 2002; Earley & Ang, 2003). The metacognitive dimension refers to individuals’ cognitive capacity to understand and interpret cultural knowledge (Ang et al., 2007, 2006). The cognitive component is defined as individuals’ general knowledge regarding traditions, norms, and values, etc. of different cultures (Ang et al., 2006). The motivational component stands for individuals’ motives and intentions to adapt to an unfamiliar cultural environment (Ang et al., 2006; Earley, 2002). Lastly, behavioral intelligence is defined as an individual’s ability to take verbal and non-verbal actions under diverse cultural requirements rather than their judgments (Ang et al., 2007; Earley & Ang, 2003).

The cultural intelligence concept was adapted into tourism first by Frías-Jamilena et al. (2018a,b) who postulated that cultural intelligence improves tourists’ capability to adapt to diverse cultures, and, as a result, enhances destination evaluations. Frías-Jamilena et al. (2018a) demonstrated that tourists’ cultural intelligence levels positively impact destination’s perceived value that encompasses functional attributes such as destination risk and cost figures in addition to emotional and social values offered by destinations. Therefore, tourists who are more culturally intelligent are inclined to value destinations more highly than ordinary tourists. Similarly, in a study concentrating on tourists visiting the Tenerife island of Spain, Beerli-Palacio and Martín-Santana (2018) depicted that tourists who self-reported that they are self-confident and know how to behave when they interact with people from other cultures tend to have more positive DNI evaluations. Finally, in their study focusing on tourists visiting Spain, Frías-Jamilena et al. (2018b) illustrated that cultural intelligence is a significant predictor of a destination’s perceived brand equity. More specifically, higher tourist cultural intelligence exerts a significant positive impact on destination equity that encompasses destination “image, loyalty, quality, and perceived value” factors. Also, in a most recent study, while destinations were still suffering from the COVID-19, cultural intelligence was acknowledged to positively moderate the impact of destination personality on its brand equity. In particular, the strength of the mentioned relationship was amplified with an increase in expats’ cultural intelligence levels (Aktan et al., 2021). Therefore, conforming to the previous literature, individuals’ cultural background can shape their destination perceptions and evaluations (McCartney, 2008; Stepchenkova et al., 2015; Zaman & Aktan, 2021). Based on these theoretical discussions, the following two hypotheses are developed.

H₄: ECLI has a significant and positive effect on DNI in the COVID-19 tourism.

H₅: ECLI has a significant and positive effect on EDLY in the COVID-19 tourism.

3. Methods

3.1. Sampling and procedure

This study used a quantitative approach to assess the proposed framework of EDLY and its significant predictors (i.e. CYI, DNI, and ECLI) during the COVID-19 tourism. The sampling frame included expats living in South Korea and data were collected online during January till May, 2020 (i.e. peak-outbreak period of Covid-19), through a Google survey form. As foreign expats are scattered across different regions in South Korea and work in various business fields from construction to education, the overall population of foreigners with work permits (approx. 40 thousand persons) was not fully-accessible (Statistics Korea, 2020). Consequently, a non-probability sampling method, namely “convenience sampling” was chosen as the appropriate sampling method. During data collection, the survey link was shared on social media platforms for expats in South Korea which required moderator authorization to become a member. Also, the survey link was shared individually with expats living in South Korea who are in the researchers’ networks to increase the number of participants. Before opting in, participants were shown an elimination question to understand if the participants visited touristic destinations in South Korea during the COVID-19 outbreak, which aimed to ensure the suitability of the respondents for the research design. Also, to tackle response bias, participants were informed that their information and identities would be kept strictly confidential. Further, they were not provided any information about the research conceptual model along with research objectives to overcome common method bias (Zaman, 2020). Lastly, a total number of 260 completed survey forms were utilized for the PLS-SEM analysis, which conformed with the recommended sample size for structural equation modeling (Chumney, 2013; Hair et al., 2016; Kline, 2015).

3.2. Measures

The survey form comprised two parts where the former included scale items to measure DNI, CYI, EDLY, and ECLI, and the latter consisted of demographic questions. To assess expat’s perceived DNI five items were adapted from Prayag and Ryan (2012). Expat’s perceived CYI was assessed with six items adapted from Nadeau et al. (2008). Moreover, ECLI was operationalized by six items adapted from the shortened version of cultural intelligence scale (Aktan et al., 2021; Thomas et al., 2015; Zaman & Aktan, 2021). Lastly, destination loyalty was measured by three adapted items based on prominent studies on tourism destinations (Oppermann, 2000; Pike et al., 2010; Yoon & Uysal, 2005). All the scales were evaluated on a 5-point Likert-type scale ranging from not at all (1) to extremely well (5). In the second part of the survey respondents were asked questions about their demographics. The length of residency was evaluated with 4 options: Less than 1 year, 1 to 5 years, 6 to 10 years, and more than 10 years. The education level of respondents was categorized into four levels namely Ph.D., master’s degree (or equivalent), bachelor’s degree (or equivalent), and high school degree. Finally, respondents’ age was coded in four separate categories: below 30, 30–39, 40–49, and 50 years and above. Table 1 presents the expat’s demographic details that were examined using IBM SPSS software version 20.

Table 1. Expat’s demographics

	Profile Category	n	%
Age	Below 30 years	110	41.3
	30 to 39 years	72	27
	40 to 49 years	54	20.3
	50 years and above	30	11.2
Gender	Male	173	65
	Female	88	33
	Prefer not to say	5	1.8
Educational Level	High School Degree	11	4.1
	Bachelor’s Degree (or equivalent)	110	41.3
	Master’s Degree (or equivalent)	99	37.2
	PhD. Degree	46	17.2
Length of Residency	Less than 1 year	28	10.5
	1 to 5 years	133	50
	6 to 10 years	41	15.4
	Over 10 years	64	24

*N = 266.

3.3. Data analysis

The empirical investigation of hypothesized relationships of CYI, DNI, and ECLI with EDLY, were tested using the latest software version of SmartPLS . The variance-based PLS-SEM approach has received wide recognition across academic disciplines, including tourism as the technique is more convergent towards simplicity, fewer normality restrictions, and superior predictive capabilities over CB-SEM (i.e., covariance based structural equation modeling) (Hair et al., 2016; Zaman, 2020; Zaman et al., 2019). PLS-SEM technique has also gained recognition for its suitability for complex theoretical models involving direct effects as well as mediating effects (Zaman, 2020). The technique also offers the stability of PLS-SEM estimates using the bootstrapping procedure (Hair et al., 2016). In conformance with the PLS-SEM guidelines (Hair et al., 2016), the bootstrapping procedure (using 500-subsamples) provided the path-coefficients of the hypothesized relationships and their corresponding significance levels (Hair et al., 2011).

4. Results

4.1. Measurement model

PLS-SEM measurement model (represented as Figure 1) provided assessments for hypothesized path coefficients, as well as the R-square value for DNI (predicted by CYI and ECLI) and EDLY (predicted by DNI and ECLI) respectively. Moreover, the PLS measurement model also facilitated the assessment of the reliability and validity of the adapted scale for CYI (Cronbach’s alpha = 0.760; composite reliability = 0.836; AVE = 0.507), DNI (Cronbach’s alpha = 0.866; composite reliability = 0.895; AVE = 0.517), expats cultural intelligence (Cronbach’s alpha = 0.855; composite reliability = 0.892; AVE = 0.580) and expats destination loyalty (Cronbach’s alpha = 0.863; composite reliability = 0.916; AVE = 0.785) respectively. As presented in Table 2, all of the study constructs showed adequate scale reliability and convergent validity, as the calculated values exceeded minimum threshold (i.e. CA > 0.70; CR > 0.70; AVE > 0.50) (Hair et al., 2011). Moreover, the study used two-established criteria’s i.e. Fornell and Larcker (1981) and heterotrait–monotrait relationship (HTMT) approach to evaluate the discriminant validity of the adapted measures. As presented in Table 3, the inter-construct correlation was lower than the square root value of the average variance extracted (AVE) shown diagonally in bold, whereas HTMT between the study constructs was within the recommended range (i.e., HTMT < 0.90) as shown in Table 4 (Hair et al., 2016; Zaman, 2020).

Figure 1. Measurement model of EDLY in COVID-19 tourism

Table 2. Construct reliability and validity

Constructs/Indicators	Mean	Loadings
Country image Cronbach’s Alpha = 0.760; Composite Reliability = 0.836; AVE = 0.507
CYI1	4.33	0.790
CYI2	4.58	0.700
CYI3	3.56	0.665
CYI4	4.30	0.643
CYI5	4.23	0.749
Destination image Cronbach’s Alpha = 0.866; Composite Reliability = 0.895; AVE = 0.517
DNI1	3.92	0.771
DNI2	4.00	0.715
DNI4	4.13	0.776
DHI5	3.84	0.748
DNI8	3.83	0.696
DNI9	3.97	0.688
DNI10	3.91	0.712
DNI12	3.89	0.638
Expat’s Cultural intelligence Cronbach’s Alpha = 0.855; Composite Reliability = 0.892; AVE = 0.580
ECLI1	4.32	0.598
ECLI2	4.02	0.786
ECLI3	4.12	0.795
ECLI4	4.11	0.793
ECLI5	4.01	0.807
ECLI6	4.18	0.773
Expat’s Destination loyalty Cronbach’s Alpha = 0.863; Composite Reliability = 0.916; AVE = 0.785
EDLY1	4.20	0.888
EDLY2	4.08	0.909
EDLY3	4.18	0.860

Table 3. Discriminant validity (Fornell-Larcker criterion)

	CYI	DNI	ECLI	EDLY
CYI	0.712
DNI	0.567	0.719
ECLI	0.235	0.262	0.762
EDLY	0.457	0.574	0.304	0.886

Table 4. Discriminant validity (HTMT criterion)

	CYI	DNI	ECLI	EDLY
CYI
DNI	0.667
ECLI	0.293	0.284
EDLY	0.553	0.655	0.342

4.2. Structural model

Using the bootstrapping method (5,000 sub-samples), the PLS-SEM structural model (represented as Figure 2) assessed the significance of the path coefficients for the hypothesized relationships of CYI, DNI, and ECLI with EDLY, as presented in Table 5 (Sarsted et al., 2017). The variance inflation factor (VIF) values for the study constructs were lower than the maximum level (i.e., VIF< 0.5) hence, ensuring non-existence of any multicollinearity issues. The coefficient of determination (i.e., R² value) was calculated for the mediating variable i.e., DNI (R² = .338) as well as the endogenous variable i.e., EDLY (R² = .355), both being greater than the minimum level (i.e., R² > 0.10) (Falk and Miller, 1992).

Table 5. Structural model assessments

	β	S.D	t-values	p-values	Result
CYI -> DNI	0.535	0.048	11.226	0.000	Supported
DNI -> EDLY	0.530	0.060	8.824	0.000	Supported
ECLI -> DNI	0.135	0.063	2.126	0.034	Supported
ECLI -> EDLY	0.166	0.059	2.820	0.005	Supported

Coefficient of determination (R² = .338 for DNI; R² = .355 for EDLY); Model fit (SRMR = 0.077; Q² = 0.266).

The predictive capability of the structural model of EDLY depending on CYI, DNI, and ECLI was measured through the blindfolding procedure by calculating Stone-Geisser’s Q² value (omission distance = 6). The calculated Q² values for DNI (Q² = 0.166) and EDLY (Q² = 0.266) were greater than the minimum threshold (i.e., Q² > 0) that showed adequate predictive capability of the structural model of EDLY involving CYI, DNI, and ECLI as the significant predictors (Hair et al., 2016). In addition, the effect size showed the impact of the independent variables i.e., CYI (f² = 0.034), DNI (f² = 0.202) and ECLI (f² = 0.033) on the endogenous variable i.e., EDLY. Moreover, CYI (f² = 0.40) and ECLI (f² = 0.026) also showed an effect on DNI. Finally, the standardized root-mean square residual (SMRM) confirmed adequacy for the model fit as the calculated value (i.e., SRMR = 0.077) was within the recommended range (i.e., SRMR<0.80).

Figure 2. Structural model of EDLY in COVID-19 tourism

PLS-SEM results for the bootstrapping procedure provide acceptance of the first hypothesis, as CYI has a significant and positive impact on DNI (β = 0.535, t = 11.226, p < 0.01) as shown in Table 3. The results also provide significant support for the positive impact of DNI on EDLY (β = 0.530, t = 8.824, p < 0.01), hence supporting the second hypothesis. Moreover, ECLI revealed a significantly positive impact on DNI (β = 0.135, t = 2.126, p < 0.05) and EDLY (β = 0.166, t = 2.820, p < 0.01). As shown in Table 6, PLS-SEM assessments for the mediating influence of DNI on the relationship between CYI and EDLY has been statistically confirmed. Hence, the results support the acceptance of the third hypothesis that showed that DNI partially mediates the relationship between CYI and EDLY (direct effect = 0.176; indirect effect = 0.284; total effect = 0.460 ; variance accounted for = 0.617).

Table 6. Mediating effects of DNI

	Direct Effect (DE)	Indirect Effect (IE)	Total Effect (TE)	VAF	Mediation Type	Result
CYI -> DNI -> EDLY	0.176	0.284	0.460	0.617	Partial Mediation	Supported

5. Discussion

Recent studies in destination marketing and loyalty have indicated country wise differences in the relationships among CYI, DNI and loyalty (Aktan & Anjam, 2021; Králiková et al., 2020; Zhang et al., 2018). These evolving differences could be more evident across countries and destinations, especially when it is coupled with unprecedented crisis such as COVID-19 (Avraham, 2015; Zenker & Kock, 2020). COVID-19 has hit some countries harder than others, devastating their economy, health-system, and tourism (Zenker & Kock, 2020). COVID-19 risk perceptions have also altered the CYI’s and DNI’s more recently. As a result, each country and destination require unique remedies to tackle the prolonging effect of the crisis on their inbound and outbound tourism. To overcome the everlasting effect of COVID-19, the relationships between CYI, DNI and loyalty has to be re-assessed to address nascent problems and offer destination specific marketing solutions (Avraham, 2015; Farajat, 2018; Zenker & Kock, 2020). Furthermore, certain groups who are culturally more intelligent could be more relevant to target to recover from the crisis as culturally rich individuals tend to value destinations more highly and objectively than normal tourists (McCartney, 2008; Stepchenkova et al., 2015).

The present study serves to extend previous research in destination marketing studies while addressing the recent call to investigate expats’ tourist behavior (Dutt et al., 2018). While there has been a considerable amount of research on destinations, expats have not been sufficiently reckoned with as tourists visiting destinations in their host country (Dutt et al., 2018; Valek & Fotiadis, 2018). Additionally, despite being one of the potential predictors of tourist’s host destination evaluations, tourist’s cultural intelligence has largely been overlooked in tourism literature (Frías-Jamilena et al., 2018a, 2018b). To address these gaps, the present study analyzed expat’s perception to measure the impact of CYI on destination loyalty, where DNI fully mediates the relationships between these constructs. Further, ECLI was incorporated into the model as an exogenous variable influencing both DNI and destination loyalty. Utilizing structural equation modeling, the findings revealed that CYI has a strong positive impact on DNI, which in turn affected EDLY. This finding confirms earlier observations raised by prior research that suggests that there is a strong connection between CYI and DNI, where positive CYI affects perceived DNI positively (Chaulagain et al., 2019; Hahm et al., 2018; Palau-Saumell et al., 2016; Soonsan & Sukahbot, 2019; Zhang et al., 2018). Also, this study complements the findings ofChaulagain et al. (2019) who indicated the mediating role of DNI between CYI and post-visit intentions. Further, the finding is also line with other studies demonstrating the mediating role of DNI between destination loyalty, and other antecedents of loyalty such as tourism service quality (Akroush et al., 2016), tourism experiences (Kim, 2018), and perceived value (Moon et al., 2013).

DNI and loyalty have long been considered factors of destination brand equity along with other factors such as awareness, quality, and perceived value (Chekalina et al., 2018; Ferns & Walls, 2012; Gartner & Ruzzier, 2011; Pike et al., 2010). As an important contribution, this study revealed that expats’ cultural intelligence significantly and positively affects two dimensions of destination brand equity namely, DNI and destination loyalty. Therefore, this study partially supports the prior research that highlights the positive influence of cultural intelligence on destination brand equity (Frías-Jamilena et al., 2018a). In other words, expats who can easily put themselves in other’s shoes in a cultural context appeared to have more positive evaluation of destinations, which in turn lead to positive post-visit behaviors and intentions. As a relatively new concept to investigate tourist behavior, cultural intelligence becomes more important when destination marketers position destinations to address the needs and expectations of specific tourist profiles (Frías-Jamilena et al., 2018a, 2018b).

Due to the rapid expansion of multi-national companies across borders and migration of global talent, an overwhelming majority of professionals have settled in more developed countries. Host countries provide once-in-a-lifetime experience of better living standards, opportunities for career growth and professional development. Consequently, this trend has positioned expats as invaluable partners for destination branding marketers because expats can be considered long-term tourists whose information about destinations is more reliable than occasional tourists. Consequently, expats can encourage prospective tourists (i.e. relatives, friends, colleagues) from inside and outside of their home countries to visit expat’s host destinations (Gu et al., 2010; Stylidis et al., 2016). In essence, expats may attend tours and provide specific information about destinations while hosting their visitors, which helps them discover new things about destinations and deeply understand local cultures (Dutt et al., 2016). Overall, this study put forwards that DNI mediates the relationship between CYI and destination loyalty (Chaulagain et al., 2019; De Nisco et al., 2015; Soonsan & Sukahbot, 2019), where ECLI levels both affect DNI and expat’s loyalty to destinations in a positive way (Frías-Jamilena et al., 2018a).

5.1. Theoretical and practical implications

In the aftermath of COVID-19 crisis and recent calls to incorporate expat’s role in tourism research (C. S. Dutt et al., 2018; Zenker & Kock, 2020), the study explored CYI, DNI and ECLI as significant predictors of EDLY. The tourism environment comprises a group of actors including tourism professionals, residents, and tourists, where mutually coordinated and integrated efforts are necessary to achieve common destination goals (Sánchez Cañizares et al., 2016; Yu et al., 2018). The study makes the initial attempt to construct a conceptual model linking CYI, DNI, and destination loyalty, while incorporating of cultural intelligence, which has been largely neglected in tourism literature (Frías-Jamilena et al., 2018a, 2018b). Recent studies have linked CYI to DNI, articulating empirical support that CYI acts as an antecedent of DNI (Chaulagain et al., 2019; Hahm et al., 2018; J. Zhang et al., 2018). In addition, other studies have manifested a significant impact of DNI on loyalty with varying degrees (Zhang et al., 2014). However, the present study offers a new model that integrates the concept of cultural intelligence into destination marketing literature and examines the mediating role of DNI between CYI and EDLY. To the author’s knowledge, fewer scholarly attempts have examined the mediating role of DNI between CYI and destination loyalty (Chaulagain et al., 2019; De Nisco et al., 2015). In this regard, this study provides empirical support to the mediating role of DNI between cognitive CYI and post-visit intentions and/or destination loyalty. In essence, destination loyalty can be regarded as an outcome of both DNI and CYI. Therefore, destination marketers should adopt a holistic approach and take the CYI into consideration to boost positive associations between DNI and destination loyalty (Dedeoğlu, 2019).

Equally important, this study contributes to the lacking literature about the impact of cultural intelligence (Frías-Jamilena et al., 2018a, 2018b) in assessing DNI and loyalty, especially from the expat’s viewpoint (C. S. Dutt et al., 2018). Tourism is highly associated with culture due to its reliance on human-to-human interaction. Consequently, cultural interaction of tourist with locals and/or service providers constitutes a major element of tourism experiences (Beerli-Palacio & Martín-Santana, 2018) and DNI perceptions (Richards, 2020). Confirming support to prior research, this study provides evidence that ECLI also has a significant potential to strengthen and/or weaken DNI and destination loyalty. In other words, expats who are culturally intelligent were found to have more positive evaluation of DNI which in turn leads to a stronger destination loyalty. Therefore, destination marketers could benefit from expats to supplement and facilitate effective implementation of destination marketing targets (C. Dutt et al., 2016; Jeuring & Haartsen, 2017; Salehzadeh et al., 2016). Especially, in order to tackle crisis affecting world tourism (i.e., terrorism, and pandemic’s etc.) expats’ views will become more reliable for prospective tourists, and provide a fresh perspective for destination marketers about destination recovery strategies and tourism management. Therefore, expats should be integrated into destination marketing plans as invaluable partners likewise tourists, host residents and tourism professionals (C. S. Dutt et al., 2018; Yu et al., 2018). For instance, expat’s knowledge about their host destinations could be improved through specific cross-cultural trainings, and special events targeting expats which are organized and/or supported by tourism institutions and governmental agencies. As a consequence, expats could feel themselves as more connected and emotionally attached to host destinations, which could turn them to life-time destination ambassadors. Importantly, the global expats real time knowledge about their host destinations, especially experiencing the different phases of destination recovery i.e. during and after a crisis (e.g., COVID-19 pandemic, political and/or civil unrests, and wars etc.) can facilitate policy makers and destination marketers to effectively communicate the ground realities of tourism destinations, that can significantly help to build and restore trust, as well as ensure loyalty of international travelers (Gössling et al., 2020; C. S. Dutt et al., 2018).

5.2. Limitations and future recommendations

Although this study is a pioneering effort that explored the role of CYI, DNI and ECLI in assessing EDLY in COVID-19 tourism, there are some limitations worth highlighting. The primary limitation of this study is the generalizability of the findings because the conceptual model was empirically tested among expats in South Korea. Due to the uneasiness of reaching out to the overall expat communities in South Korea, this study adopted a non-probability sampling approach (i.e. convenience sampling), which lessens the generalizability of the findings to a wider sample. Therefore, future studies could concentrate on larger sample of expats as well as collecting data in other countries for the sake of enhancing the generalizability. Also, the findings may not reflect the perceptions of other groups, such as occasional tourists and/or individuals visiting tourist attractions during their business trips to South Korea. Thus, future studies could involve different tourist types to assess the relevance of cultural intelligence in destination marketing, which may improve and modify the hypothesized relationships in the present research model. Future research could also further explore the interplay between cultural intelligence and other antecedents of destination loyalty which have been postulated in destination marketing literature recently such as service quality, destination attachment, involvement, familiarity, perceived value, and tourist satisfaction (Chi & Qu, 2008; Gursoy et al., 2014, 2014). Lastly, cross-country and longitudinal studies can enrich scientific evidence about EDLY and behavioral changes toward destinations over time.

5.3. Conclusions

As international tourism destinations wrestle to find a rationale to reopen, destination marketers are experimenting with various options to re-engage international travelers and renew their loyalty towards destinations. The present study highlights the emerging role and importance of global expats, by exploring the effects of CYI, DNI, and ECLI on EDLY in COVID-19 tourism. The present study reconfigures findings of prior research on CYI, DNI and destination loyalty (Chaulagain et al., 2019; Dedeoğlu, 2019; Soonsan & Sukahbot, 2019), by introducing ECLI as a significant predictor of DNI and EDLY (Chaulagain et al., 2019; Frías-Jamilena et al., 2018a; C. S. Dutt et al., 2018). Importantly, the study findings provide new evidence that DNI significantly mediates CYI and EDLY (Chaulagain et al., 2019), besides the direct influence of ECLI on DNI and EDLY (Chaulagain et al., 2019; Frías-Jamilena et al., 2018b). In today’s polarized world of open or closed tourism (Zenker & Kock, 2020), destination marketers should re-invent marketing models to include expat groups (C. S. Dutt et al., 2018), and carefully reassess the implications of CYI, DNI, and tourist’s cultural intelligence on destination loyalty in the post COVID-19 global tourism (Gössling et al., 2020).

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Umer Zaman

Umer Zaman is currently working as an Assistant Professor at the Endicott College of International Studies, Woosong University, Daejeon, Republic of Korea. Dr. Zaman has recently published in top-tier international tourism journals (including JHTM and APJTR), also in the International Journal of Project Management (IJPM) based on his interdisciplinary research interest. He has extensive experience working in action-based research projects under various international/regional organizations and donor agencies including the UNODC (Vienna) and ADB-OECD. Dr. Zaman has chaired various academic research conferences at national and international level. He also serves as a reviewer for the Journal of Hospitality and Tourism Management (JHTM), Journal of Retailing and Consumer Services (JRCS), and the Sustainability journal.