Travellers’ destination choice among university students in China amid COVID-19: extending the theory of planned behaviour

Lei Wang (Faculty of Hospitality and Tourism, School of Management, Xuzhou University of Technology, Xuzhou, China)
Philip Pong Weng Wong (School of Hospitality, Sunway University, Subang Jaya, Malaysia)
Qi Zhang (School of Management, Xuzhou University of Technology, Xuzhou, China)

Tourism Review

ISSN: 1660-5373

Article publication date: 4 February 2021

Issue publication date: 27 July 2021

2279

Abstract

Purpose

Prior tourism literature neglected the negative motivational or attitudinal elements influencing individuals’ travel destination decisions. This study aims to examine the relationships between animosity, ethnocentrism, attitude, subjective norm (SN), perceived behavioural control (PBC), destination overall image (DOI) and destination visit intention (DVI).

Design/methodology/approach

A quantitative approach was used using a survey methodology involving 402 student responses. The proposed hypotheses were empirically tested with SPSS and AMOS.

Findings

The results demonstrated that animosity and ethnocentrism negatively influenced DOI and DVI. A positive relationship was reported between attitude, DOI and DVI. Additionally, SN and PBC positively influenced DVI. Ethnocentrism, PBC and DOI were also identified with statistically significant differences through gender. Meanwhile, statistically significant differences in attitude, PBC, DOI and DVI were evident between postgraduate students and the counterparts.

Originality/value

This study extends the existing knowledge on how animosity and ethnocentrism influenced DOI and DVI in tourism literature and benefitted Western tourism and key stakeholders in tourism.

目的

以往的旅游文献忽视了影响个人旅游目的地决策的负面动机或态度因素。本研究考察了敌意、民族中心主义、态度、主观规范(SN)、感知行为控制(PBC)、目的地总体形象(DOI)和目的地访问意向(DVI)之间的关系。

设计/方法/方式

本文采用定量方法之中的调查问卷方法, 涉及402名学生的答复。用SPSS和MOS对提议的假设进行了经验测试。

发现

结果表明, 敌意和民族中心主义对多利和DVI产生了负面影响。态度、DOI和DVI之间有积极的关系。此外, SN 和 PBC 对 DVI 产生了积极影响。民族中心主义、PBC 和 DOI 也被确定为通过性别在统计学上显著差异。同时, 研究生与配对物的态度、PBC、DOI、DVI在态度上存在明显差异。

原创性/价值

本研究扩展了关于敌意和民族中心主义如何影响旅游文献中和DVI的现有知识, 并有利于西方旅游业和旅游业主的发展。

Elección de Destino de los Viajeros entre Estudiantes Universitarios en China en medio de COVID-19: Ampliar la Teoría del Comportamiento Planificado

Propósito

La literatura turística anterior descuidó los elementos motivacionales o actitudinales negativos que influyen en las decisiones de destino de viaje de las personas. Este estudio examinó las relaciones entre la animosidad, el etnocentrismo, la actitud, la norma subjetiva (SN), el control de comportamiento percibido (PBC), la imagen general de destino (DOI) y la intención de visita de destino (DVI).

Diseño/metodología/enfoque

Se empleó un enfoque cuantitativo utilizando una metodología de encuesta que implicaba 402 respuestas de los estudiantes. Las hipótesis propuestas se probaron empíricamente con SPSS y AMOS.

Resultados

Los resultados demostraron que la animosidad y el etnocentrismo influyeron negativamente en doi y DVI. Se informó de una relación positiva entre la actitud, doi y DVI. Además, SN y PBC influyeron positivamente en el DVI. El etnocentrismo, el PBC y el DOI también se identificaron con diferencias estadísticamente significativas a través del género. Mientras tanto, las diferencias estadísticamente significativas de actitud, PBC, DOI y DVI eran evidentes entre los estudiantes de posgrado y las contrapartes.

Originalidad/valor

Este estudio amplía los conocimientos existentes sobre cómo la animosidad y el etnocentrismo influyeron en el DOI y la DVI en la literatura turística y beneficiaron al turismo occidental y a las principales partes interesadas en el turismo.

Keywords

Citation

Wang, L., Wong, P.P.W. and Zhang, Q. (2021), "Travellers’ destination choice among university students in China amid COVID-19: extending the theory of planned behaviour", Tourism Review, Vol. 76 No. 4, pp. 749-763. https://doi.org/10.1108/TR-06-2020-0269

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited


1. Introduction

A positive destination overall image (DOI) is a powerful tool (Alcocer and Ruiz, 2019) indicating the tourist–destination relationship and tourist flow (Kim et al., 2019). Nazneen et al. (2020) stated that a positive DOI pertained to a rise in tourism demands and economic advantages. Regardless, tourism is prone to the changes induced by external factors (Wen et al., 2020b), such as wars, terrorism, natural disasters, financial crises, flight accidents, disease outbreaks and negatively impacted destination (Yu et al., 2020) and travel perceptions (Campo and Alvarez, 2019). The COVID-19 pandemic has caused sudden economic downturns and unemployment worldwide (State of Maine Department of Labor, 2020). Additionally, misleading media coverage on the COVID-19 outbreak caused Asian communities, specifically Chinese nationals, to face intense discrimination (Wen et al., 2020a). To date, anti-Chinese xenophobia has been reported in several countries including the USA, UK, Canada, Europe and Australia (Wen et al., 2020a). Hence, Wen et al. (2020b) suggested Chinese travellers be more cautious concerning future travel destinations.

Previous studies identified DOI measurements following the continuum of functional and psychological attributes (Wong and Teoh, 2015). Nevertheless, destination decisions were complex (Durán et al., 2016) and ignored the negative behavioural intention framework (Ulker-Demirel and Ciftci, 2020). Although many studies strived to comprehend attitude components through different variables (Wang, 2020; Wang et al., 2020a), the focus was on traveller behaviour. The impact of negative attitude development components as DOI and destination visit intention (DVI) prerequisites was overlooked. Therefore, an investigation into the theoretical construction of negative behavioural intention perspectives was required to understand tourism literature (Ulker-Demirel and Ciftci, 2020).

Animosity and ethnocentrism exerted similar psychological mechanisms involving attitude (Stepchenkova et al., 2019) with negative emotions towards purchasing foreign products (Al-Hyari et al., 2012; Ahmed et al., 2013). Although the influence of animosity and ethnocentrism on purchasing behaviours was recognised (Campo and Alvarez, 2019; Dursun et al., 2019), several empirical tests on animosity and ethnocentrism as the factors influencing DOI and DVI in destination choice were performed (Campo and Alvarez, 2019; Stepchenkova et al., 2019). Hence, more research was needed to study the effects of negative behavioural attitudes in tourism (Ulker-Demirel and Ciftci, 2020).

The theory of planned behaviour (TPB) was extended from the theory of reasoned action (TRA) (Ajzen, 1991) as a prominent social-psychological human behaviour model in tourism literature (Ulker-Demirel and Ciftci, 2020). The model considers a wider range of factors, such as act belief, normative belief and control belief (Bamberg and Schmidt, 2003), and is extendable with additional constructs denoting a notable portion of the intention variance (Nimri et al., 2019). Although studies investigated the influence of animosity and ethnocentrism on DOI and DVI (Campo and Alvarez, 2019; Stepchenkova et al., 2019), only one causal relationship between animosity, ethnocentrism, DOI and DVI was proposed. Little research incorporated the negative attitude aspects into TPB to justify DOI and DVI. The current study extended the TPB model on DOI and DVI, specifically on how animosity and ethnocentrism influenced DOI and DVI among Chinese university students. This study demonstrated how animosity and ethnocentrism negatively influenced DOI and DVI during COVID-19.

2. Literature review

2.1 Animosity

Animosity refers to the dislike of past or current events (Klein et al., 1998). Studies on international conflicts received particular attention in purchasing attitude and consumer behaviour (Al-Hyari et al., 2012; Sánchez et al., 2018). For example, Stepchenkova et al. (2019) defined animosity as a hostile attitude incorporating beliefs and emotional components towards particular groups (Stepchenkova et al., 2019) and represented belief-based enmity from unjustified and abnormal issues (Sánchez et al., 2018). Thus, consumers possessed negative emotions concerning purchase behaviours from a disliked group or nation (Al-Hyari et al., 2012). Although animosity might not influence product assessment, product purchase decisions were heavily impacted (Klein et al., 1998).

Consumer animosity is new and can be defined as a negative feeling impacting destination choices (Alvarez and Campo, 2020). Sánchez et al. (2018) mentioned that tourism depended on destination characteristics, such as economic stability, place safety and environmental quality. Consequently, animosity impacted tourist behaviour through the influence of affective images on tourist emotions (Alvarez and Campo, 2014). Economic and political events directly impacted tourist activities (Arnegger and Herz, 2016). Additionally, Yu et al. (2020) argued that animosity hindered travel activities. Campo and Alvarez (2019) indicated that animosity significantly influenced consumers’ country evaluation as a tourist destination.

Historical, economic or environmental events led to various crises and animosity if the consequences persisted, thus influencing DOI and DVI despite the end of the incident (Sánchez et al., 2018). Guo et al. (2016) confirmed that the Chinese nationals’ animosity towards the Japanese following the 1937 Nanjing massacre influenced the intention to tour Japan. Besides, animosity could arise from a particular event, situation or an accumulation of incidents experienced by individuals (Sánchez et al., 2018). Resultantly, Chinese travellers would be vigilant in choosing Western countries as tourist destinations because of the political conflicts following COVID-19 (Wen et al., 2020b). Thus, the following hypotheses are established:

H1.

Animosity negatively influences DOI.

H2.

Animosity negatively influences DVI.

2.2 Ethnocentrism

Ethnocentrism and animosity are distinct constructs influencing consumer behaviour and the preference towards local products over foreign ones (Ahmed et al., 2013). Ethnocentrism is defined as consumers’ belief in the appropriateness of purchasing foreign-made products (Shimp and Sharma, 1987). Highly ethnocentric consumers avoided foreign product purchases and felt that such purchasing was wrong (Ahmed et al., 2013; Kock et al., 2019). Consumer ethnocentrism also shared similar psychological mechanisms concerning attitudes and behaviours towards foreign brands, thus reflecting the external norms (Stepchenkova et al., 2019) that provided valuable explanations on consumers’ negative brand orientations (Dursun et al., 2019).

In Stepchenkova et al.’s (2019) study, tourism is perceived as the exported product of a nation. Consequently, DVI can be interpreted as a purchase intention (Campo and Alvarez, 2019). Highly ethnocentric tourists supported the domestic tourism economic developments (Kock et al., 2019), thus determining tourists’ decision-making and behavioural processes (Kock et al., 2019). Chan et al. (2010) reported that ethnocentrism significantly influenced DOI and DVI. The following hypotheses are proposed based on the findings:

H3.

Ethnocentrism negatively influences DOI.

H4.

Ethnocentrism negatively influences DVI.

2.3 Theory of planned behaviour

The TPB model is derived from TRA and is considered to be a popular predictor of the consumer decision-making process (Wang et al., 2019). Although both theories proposed rational decision-making behaviours (Wang and Wong, 2020), the main TRA–TBP distinction was that TPB did not consider consumer behaviour to be purely based on volitional factors (Wang et al., 2020b). Therefore, non-volitional control was incorporated into TPB as an important perceived behavioural control (PBC) predictor that extended TRA boundaries (Wang et al., 2019).

This study adopted and modified TPB as a theoretical framework (Ajzen, 1991) based on Figure 1. The TPB is explained through model modification involving critical constructs (Wang and Wong, 2020). Therefore, TPB reflected a more significant portion of the overall intention and behaviour variance (Ajzen, 1991; Han et al., 2011). The TPB variables to indicate consumer intention and behaviour include attitude and subjective norm (SN), together with PBC (Ajzen, 1991). Individuals with a more positive attitude strengthened behaviour performance intention and vice versa (Wang, 2020). Thus, attitude is central to the consumer decision-making theory (Cohen et al., 2014). Han et al. (2011) reported that attitude positively influenced travellers’ decision-making process and indicated attitude as a factor influencing DVI (Souiden et al., 2017). Therefore, the following hypotheses are proposed:

H5.

Attitude positively influences DOI.

H6.

Attitude positively influences DVI.

The SN can be defined as the perceived social pressure in behavioural performance (Wang et al., 2020c). Furthermore, Han et al. (2011) stated that SN was formed on individuals’ salient referents in approving or disapproving a particular behaviour. For example, previous studies demonstrated that the Chinese were more collective (Chen, 2013; Wang et al., 2020a) in decision-making (Cheng et al., 2006; Han et al., 2011). Consumers who received behavioural approval adopted the particular behaviour. Therefore, the following hypothesis is proposed:

H7.

SN positively influences DVI.

The PBC influences consumer behaviour and is partially under volitional control (Paul et al., 2016). The term is defined as the simplicity or complications in people’s behavioural performance (Ajzen, 1991). Han et al. (2010) argued that PBC was a function of belief control involving the presence or absence of required sources and opportunities in performance behaviour (Wang et al., 2019). Iriobe and Abiola-Oke (2019) extended the TPB model to predict consumer DVI and determined that PBC significantly influenced tourist destination revisit intentions. Additionally, Soliman (2019) revealed the significant positive effect of PBC on consumers’ destination revisit intentions. Thus, the following hypothesis is proposed:

H8.

PBC positively influences DVI.

2.4 Destination overall image

Nazneen et al. (2020) mentioned that the DOI significance in tourism destination success was extensively explored in literature. Nonetheless, the complex and subjective nature of DOI presented no consensus regarding definition, formation and conception (Ragab et al., 2019). The classic definition of destination image involved a set of impressions on non-residential places (Hunt, 1975). The DOI was also described as a set of impressions attached to a place (Hung and Petrick, 2012; Králiková et al., 2020) or destination (Smith et al., 2015; Ragab et al., 2019). Overall, a DOI could be described from two aspects: affective image and cognitive image (Ragab et al., 2019). The DOI significantly influenced tourists’ decision-making processes (Alcocer and Ruiz, 2019; Han et al., 2019b) and intentions to visit or revisit (Han et al., 2009; Ragab et al., 2019; Králiková et al., 2020). Therefore, the following hypothesis is established:

H9.

DOI positively influences DVI.

3. Methods

3.1 Operationalisation

A self-administered four-section questionnaire was adopted as the study instrument. The first section included the added TPB variables (animosity and ethnocentrism). Animosity-related items were modified from Huang et al. (2010) and Dursun et al. (2019). Meanwhile, items related to ethnocentrism were modified from Dursun et al. (2019). Section two included the attitude, SN and PBC variables adapted from Han et al. (2011). The third section assessed the DOI and DVI. The DOI-related aspects were adapted from Ragab et al. (2019) and Alcocer and Ruiz (2019), whereas the DVI-related items were adapted based on Han et al. (2011). Finally, section four elicited relevant demographic characteristics. A five-point Likert scale ranging between “strongly disagree” and “strongly agree” was used to assess the questionnaire items.

3.2 Data collection

A purposive non-probability sampling technique was used to collect data at six undergraduate universities in Xuzhou, Jiangsu, China from 18 May to 10 June 2020. Varsity students were chosen as samples for several reasons: the students represented young vacationers (Han et al., 2019a); advanced use of information technology (Wen et al., 2020b); about 150 million outbound travellers in 2018, between 15 and 35 years old, constituted approximately 55% of the Chinese outbound travel market (World Tourism Organization, 2019); and the undergraduate students in Jiangsu exceeded 1.1 million and ranked third in China (Tsai et al., 2020), whereas Xuzhou occupied almost one-fifth of the student population. Thus, the students from Xuzhou universities were selected as samples.

3.3 Issues in common method bias

Potential common method bias (CMB) issues (Hulland et al., 2018) were addressed through specific mitigating measures. The questionnaire items were evaluated by field experts to eliminate respondents’ misunderstandings. The questionnaire items were initially translated into Chinese with the back-translation method using three bilingual experts to ensure translation accuracy. A pre-test was performed with a total of 40 respondents to ensure instrument suitability and viability and prevent potential data quality issues.

At least three items were applied to each construct for adequate content validity, construct reliability and convergent validity. The respondents were selected from various departments to complete the questionnaires and reduce the CMB impact from the same respondent group. Besides, the internet-savvy participants were invited to respond to the survey questionnaire through Tencent QQ and WeChat for anonymity. Lastly, Harman’s single-factor test was performed to determine the existence of CMB in the results to observe the emergence of one factor in accounting for 50% of the covariance between measures. The results revealed a variance of 32.569% and indicated that CMB was not a pervasive study issue.

4. Data analysis and results

Confirmatory factor analysis (CFA) was performed using AMOS, while SPSS 19 was used for descriptive analysis, exploratory factor analysis (EFA) and the analysis of variance (ANOVA). The 402 valid study questionnaires comprised of 78.2% females and 21.8% males. Furthermore, 86.5% were in a four-year bachelor’s degree programme, 12% were postgraduate students, 1% were three-year diploma candidates and others were 0.5%. Regarding the respondents’ age, 97.5% were between 18 and 30 years, 1% between 31 and 45 years, 1% below 18 years and 0.5% were others.

4.1 Data validity and reliability

The observed distribution was normal if the skewness and kurtosis values were close to zero with a measure of skewness ranging from −2 to +2 and kurtosis from −7 to +7 (Byrne, 2016). The results showed that skewness ranged from −0.897 to +0.767, whereas kurtosis ranged from −0.591 to +2.26, thus preserving normality. The EFA was used to uncover the underpinning structure of the relative constructs together with the relationships between the measured constructs to revalidate the adapted measurement items (Mokhlis, 2006). Furthermore, the Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity showed that the KMO value was at 0.797, p < 0.01, indicating sampling adequacy. The results showed that attitude 1, SN 4 and 5, animosity 3, ethnocentrism 1 and overall image 3, 8 and 9 had cross-loadings. Following the exclusion of cross-loading factors, the remaining factor loadings were above 0.4 with values ranging between 0.602 and 0.93, thus indicating a good fit in EFA (Ford et al., 1986).

4.2 Confirmatory factor analysis

Hair et al. (2010) stated that factor loadings should exceed 0.5 and higher than 0.7 in the measurement model. Although some items with loadings below the threshold are acceptable, items with loadings below 0.5 should be rejected (Hulland et al., 2018). Nevertheless, higher factor loadings for item reliabilities implied the shared variance between construct and measure than error variance (Hulland et al., 2018). Therefore, factor loadings below 0.7 were dropped.

The model fit indices revealed that the measurement model contained an adequate data fit (X2 = 372.645, df = 229, p < 0.001, X2/df = 1.627, root mean square residual (RMR) = 0.066, goodness of fit index (GFI) = 0.928, comparative fit index (CFA) = 0.973, adjusted goodness of fit index (AGFI) = 0.905, Parsimony goodness of fit index (PGFI) = 0.708, Parsimonious normed fit index (PNFI) = 0.775, Parsimony comparative fit index (PCFI) = 0.808, root mean square error of approximation (RMSEA) = 0.04). Ho (2006) mentioned that at least three of the indices should be met to achieve the model fit. Moreover, the results revealed that the composite reliability (CR) value for each variable was higher than the threshold of 0.7 following Hair et al. (2010) (see Table 1). The average variance extracted (AVE) values for the measurement model constructs demonstrated higher AVE values than the minimum criteria of 0.5 following Hair et al. (2010). Based on Table 2, the AVE values were greater than the correlation values between constructs. No correlation value between each variable exceeded 0.9. Hence, proof of convergent and discriminant validity was imparted.

4.3 Structural model estimation

The structural equation modelling (SEM) was performed to test the study hypotheses. The results revealed that the proposed SEM had an adequate level of goodness-of-fit statistics following the model summary: X2 = 685.546, df = 241, p < 0.001, X2/df = 2.845, RMSEA = 0.068, CFI = 0.918, AGFI = 0.886, PGFI = 0.712, PNFI = 0.768, PCFI = 0.801, incremental fit index (IFI) = 0.918 and Tucker-Lewis index (TLI) = 0.906 as illustrated in Figure 2 and Table 3.

Wong and Teoh (2015) stated that a small effect below 0.1 was implied in the path coefficients, 0.3 indicated a medium effect and a large effect exceeded 0.5. The results revealed that: animosity and DOI were negatively correlated (medium effect) (β = −0.253, p < 0.001), accepting H1; animosity and DVI were negatively correlated (medium effect) (β = −0.261, p < 0.001), accepting H2; ethnocentrism and DOI were negatively correlated (medium effect) (β = −0.348, p < 0.001), accepting H3; ethnocentrism and DVI were negatively correlated (medium effect) (β = −0.144, p < 0.05), accepting H4; attitude and DOI were positively correlated (medium effect) (β = 0.356, p < 0.001), accepting H5; attitude and DVI were positively correlated (medium effect) (β = 0.195, p < 0.05), accepting H6; SN and DVI were positively correlated (medium effect) (β = 0.12, p < 0.05), accepting H7; PBC and DVI were positively correlated (medium effect) (β = 0.188, p < 0.001), accepting H8; and DOI and DVI were positively correlated (medium effect) (β = 0.348, p < 0.001), accepting H9.

As many researchers suggested DOI as a mediator influencing DVI or behaviour (Souiden et al., 2017; Nazneen et al., 2020), this study tested the mediating role of DOI through the bootstrapping method. The bias-corrected percentile method results showed that DOI was partially mediated between animosity and DVI (the direct effects at 0.004 and the indirect effects at 0.001, p < 0.05), attitude and DVI (the direct effects at 0.022 and the indirect effects at 0.001, p < 0.05) and ethnocentrism and DVI (the direct effects at 0.019 and the indirect effects at 0.001, p < 0.05).

4.4 Analysis of variance

An independent sample t-test was conducted for gender influence in different constructs, whereas ANOVA was conducted to test the significance of various age and education groups in different study constructs. The results showed that ethnocentrism, PBC and DOI were significantly different. The average ethnocentrism for males was 0.284 higher than females (t105.551 = 3.586, p < 0.001), the average PBC for males was −0.378 lower than females (t106.317 = −0.399, p < 0.001) and the average DOI for males was −0.442 lower than females (t101.822 = −5.299, p < 0.001).

The ANOVA test was performed to differentiate between age and education groups involving all constructs. A Scheffe post-hoc test revealed no statistical difference between age groups. Concerning the education group, postgraduate students attained a higher attitude level compared to bachelor students with a mean difference (I-J) of 1.365, p <* 0.001, a higher PBC level compared to bachelor and other students with a mean difference (I-J) of 1.262 and 1.672, p < 0.05, a higher DOI evaluation compared to bachelor students with a mean difference (I-J) of 0.875, p <* 0.05, and a higher DVI level compared to bachelor students with a mean difference (I-J) of 1.151, p < 0.05.

5. Conclusion and discussion

This study focused on the DOI and DVI among Chinese university students towards Western countries concerning the negative perceptions of China following COVID-19. An extended TPB model incorporating animosity, ethnocentrism and DOI was developed and empirically tested. The findings supported the theoretical underpinning of the research model that revealed tourists’ direct effect of animosity and ethnocentrism on DOI and DVI. The results confirmed that the components (SN and PBC) of TPB significantly influenced DVI. Chinese students were able to overcome the barriers (time and money) in selecting Western countries as travel destinations. Close friends, family members and relatives also encouraged the respondents to visit Western countries. Students with positive destination attitudes would result in positive destination images and more likelihood of visiting the West.

In contrast, the results showed that animosity and ethnocentrism negatively influenced DOI and DVI. Animosity and ethnocentrism did not only influence political conflicts, military contests and economic events, but the components were important antecedents in tourist behaviour such as the COVID-19 outbreak. The respondents expressed high animosity and ethnocentrism towards Western countries that were rejected as travel destinations and influenced DVI. This study also demonstrated that male students exhibited higher ethnocentrism than female students. Female students displayed higher PBC and DOI levels than male students. Additionally, postgraduate students had higher attitude, DOI and DVI levels compared to bachelor students. Postgraduate students had a higher PBC level compared to bachelor and other students. The key study findings are illustrated below:

  • Animosity and ethnocentrism negatively influenced DOI and DVI.

  • Attitude positively influenced DOI and DVI.

  • SN and PBC positively influenced DVI.

  • DOI positively influenced DVI.

  • Male students exhibited a higher ethnocentrism level than female students, whereas female students displayed higher PBC and DOI ratings than male students.

  • Postgraduate students had higher attitude, DOI and DVI levels compared to bachelor students and a higher PBC level compared to bachelor and other students.

5.1 Theoretical implications

The impact of negative aspects concerning attitude development was largely overlooked in tourist decision-making processes. Tourism amid conflicts, animosity and ethnocentrism were insufficiently addressed. Based on the findings, potential outlooks on DOI and DVI were provided with valuable insights into assessing the influence of animosity and ethnocentrism amid COVID-19. Few tourism studies performed in-depth analyses on the effect of ethnocentrism and animosity in Chinese consumers’ behaviours.

The study findings provided alternative perspectives of DOI and DVI towards Western countries for young Chinese travellers. Animosity and ethnocentrism could determine travellers’ DOI and DVI towards less-friendly countries. Moreover, the results confirmed that the TPB model allowed the incorporation of new variables into the model. The findings demonstrated significant relationships between animosity, ethnocentrism, attitude, SN, PBC, DOI and DVI. Negative attitudes (animosity and ethnocentrism) significantly influenced TPB. Therefore, future tourism research needed to consider the current study findings using the TPB model to be replicated in other contexts.

5.2 Practical implications

Fundamental implications are outlined for Western organisations based on the study findings. First, sound background knowledge of Chinese travellers could benefit Western tourism in developing effective marketing strategies to attract potential Chinese visitors. Female students expressed positive DOI towards Western countries and overcoming obstacles (availability of time, money, resources and opportunities). For example, Western tourism could design customisable itineraries and niche tourist activities. Tour operators could also design “female only” tour packages in the current circumstance. As highly educated students had high attitude, PBC, DOI and DVI levels, international collaborations between learning institutions were emphasised to encourage Chinese students to visit Western destinations. Many Chinese students wanted to incorporate educational components into tours (visiting educational establishments) to accomplish educational objectives (International English Language Testing System examination).

Chinese students displayed high animosity and ethnocentrism towards Western countries as travel destinations during the COVID-19 pandemic. The high animosity was because of the proliferation of incendiary and discriminatory news stories by Western media channels. For example, the news stories published in the Guardian stating that “the Chinese government locking millions of people into cities with almost no advance notice should not be considered anything other than terrifying” (Eve, 2020) induced negative emotions and images towards Western countries. Therefore, the Western media needed to monitor content accuracy concerning China in the current circumstance.

Although ethnocentrism may be a complicated study factor because of high consumer ethnocentrism, students still enjoyed visiting foreign destinations. Stepchenkova et al.’s (2019) study reported that despite high ethnocentrism towards Korea (because of the Terminal High Altitude Area Defense conflict), the findings showed that ethnocentrism was positively associated with DVI. Many Chinese tourists viewed South Korea as a country within the Chinese cultural and political influence, thus indicating a willingness to visit foreign destinations.

Therefore, Western organisations should develop unique strategies to attract potential Chinese tourists and advertise unique destinations through multiple dissemination and communication channels. Because of the perception of Western news reports as discriminatory, high animosity and ethnocentrism arose towards Western countries as travel destinations. Regardless, a positive attitude, SN and the confidence to overcome tourism obstacles indicated Western countries as desirable destinations. Given the high social media influence, Western tourism needed to continue promoting destinations through Chinese social media.

5.3 Limitations and future recommendations

The cross-sectional study was inconclusive on the causality of relationships in the research model (Hair et al., 2010). The study sample involved young university students and did not represent the entire Chinese population with non-generalisable results. Future research should examine the effects of animosity and ethnocentrism from the divergent populations on DOI and DVI. Although the Harman’s single-factor test is commonly used to assess CMB, Podsakoff et al. (2003) stated that the method cannot remedy CMB. Future studies should apply other alternatives (CFA marker and measured response style techniques) to assess CMB. Despite particular behavioural intention studies, the actual behaviour did not always reflect the stated behavioural intention (Wang et al., 2019). Hence, the influence of behavioural intention on Chinese tourists’ actual destination selection should be further investigated. Future research may focus on the effect of other negative attitude aspects on DOI and DVI based on TPB as few studies emphasised the negative behavioural intention framework in tourism literature.

Figures

Conceptual research model

Figure 1

Conceptual research model

Results of structural model

Figure 2

Results of structural model

Construct validity

Variables (Cronbach’s alpha) Items Item loadings CR AVE
Animosity (α = 0.861) Experienced COVID-19
1. I dislike Western countries
2. I feel anger towards Western countries
5. Western countries want to gain economic power over China
0.758
0.961
0.753
0.867 0.688
Ethnocentrism (α = 0.908) 2. It is not right to visit Western countries because the Chinese become unemployed
3. We should visit Chinese destinations instead of enabling Western countries to become richer in the tourism industry
4. We should only visit Western countries when we cannot travel locally
5. Chinese travellers visiting Western countries as destinations are responsible for unemployment in the local tourism industry
0.83
0.863
0.841
0.839
0.908 0.711
Attitude (α = 0.757) I think visiting Western countries amid/after COVID-19 would be:
2. Valuable
3. Interesting
4. Desirable
0.703
0.769
0.776
0.794 0.563
SN (α = 0.716) 1. My family think I should visit Western countries
2. My friends would want me to visit Western countries
3. My relatives would prefer me to visit Western countries
0.729
0.855
0.764
0.827 0.615
PBC (α = 0.864) 1. I can choose whether or not to visit Western countries
2. I can certainly visit Western countries if I want to
3. I have resources, time and opportunities to visit Western countries
0.726
0.989
0.751
0.867 0.69
DOI (α = 0.827) The Western countries as a destination left a deep impression because it is:
1. A relaxing destination
2. An arousing destination
4. Natural resource (climate and landscape richness)
5. Tourist infrastructure (restaurants, hotels and accommodations)
7. Culture, history and art (gastronomy, theatre festivals, concerts, crafts and folklore)
0.761
0.75
0.75
0.76
0.779
0.872 0.578
DVI (α = 0.835) 1. I plan to visit Western countries soon
2. I am willing to visit Western countries soon
3. I intent to visit Western countries soon
0.782
0.835
0.766
0.837 0.632
Notes:

DOI 1–4 denote affective image; DOI 4, 5 and 7 denote cognitive image

Discriminant validity and the correlation between variables

Item AVE MSV ASV 1 2 3 4 5 6 7
1. SN 0.615 0.01 0.002 0.784
2. Animosity 0.688 0.437 0.194 −0.002 0.83
3. Ethnocentrism 0.711 0.206 0.083 −0.032 0.259 0.843
4. DVI 0.632 0.347 0.201 0.101 −0.569 −0.383 0.795
5. Attitude 0.563 0.256 0.122 0.009 −0.405 −0.27 0.478 0.75
6. DOI 0.578 0.347 0.167 0.029 −0.415 −0.454 0.589 0.506 0.76
7. PBC 0.69 0.437 0.103 0.013 −0.661 −0.047 0.384 0.095 0.143 0.831
Note:

Items in italic denote the square root of AVE

Results of SEM

Hypothesised paths β C.R Sig Decision
H1: Animosity -> DOI −0.253 −4.771 *** Supported
H2: Animosity -> DVI −0.261 −4.982 *** Supported
H3: Ethnocentrism -> DOI −0.348 −6.113 *** Supported
H4: Ethnocentrism -> DVI −0.144 −2.561 0.01 Supported
H5: Attitude -> DOI 0.356 5.56 *** Supported
H6: Attitude -> DVI 0.195 3.053 0.002 Supported
H7: SN -> DVI 0.12 2.266 0.023 Supported
H8: PBC -> DVI 0.188 4.024 *** Supported
H9: DOI -> DVI 0.348 4.864 *** Supported

References

Ahmed, Z., Anang, R., Othman, N. and Sambasivan, M. (2013), “To purchase or not to purchase US products: role of religiosity, animosity, and ethno-centrism among Malaysian consumers”, Journal of Services Marketing, Vol. 27 No. 7, pp. 551-563.

Ajzen, I. (1991), “The theory of planned behavior”, Organizational Behavior and Human Decision Processes, Vol. 50 No. 2, pp. 179-211.

Alcocer, N.H. and Ruiz, V.R.L. (2019), “The role of destination image in tourist satisfaction: the case of a heritage site”, Economic Research-Ekonomska Istraživanja, pp. 1-18.

Al-Hyari, K., Alnsour, M., Al-Weshah, G. and Haffar, M. (2012), “Religious beliefs and consumer behaviour: from loyalty to boycotts”, Journal of Islamic Marketing, Vol. 3 No. 2, pp. 155-174.

Alvarez, M.D. and Campo, S. (2014), “The influence of political conflicts on country image and intention to visit: a study of Israel’s image”, Tourism Management, Vol. 40, pp. 70-78.

Alvarez, M.D. and Campo, S. (2020), “Consumer animosity and its influence on visiting decisions of US citizens”, Current Issues in Tourism, Vol. 23 No. 9, pp. 1166-1180.

Arnegger, J. and Herz, M. (2016), “Economic and destination image impacts of mega-events in emerging tourist destinations”, Journal of Destination Marketing & Management, Vol. 5 No. 2, pp. 76-85.

Bamberg, S. and Schmidt, P. (2003), “Incentives, morality, or habit? Predicting students’ car use for university routes with the models of Ajzen, Schwartz, and Triandis”, Environment and Behavior, Vol. 35 No. 2, pp. 264-285.

Byrne, B.M. (2016), Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming, Routledge, London.

Campo, S. and Alvarez, M.D. (2019), “Animosity toward a country in the context of destinations as tourism products”, Journal of Hospitality & Tourism Research, Vol. 43 No. 7, pp. 1002-1024.

Chan, T.S., Chan, K.K. and Leung, L-C. (2010), “How consumer ethnocentrism and animosity impair the economic recovery of emerging markets”, Journal of Global Marketing, Vol. 23 No. 3, pp. 208-225.

Chen, L. (2013), “A study of green purchase intention comparing with collectivistic (Chinese) and individualistic (American) consumers in Shanghai, China”, Information Management and Business Review, Vol. 5 No. 7, pp. 342-346.

Cheng, S., Lam, T. and Hsu, C.H.C. (2006), “Negative word-of-mouth communication intention: an application of the theory of planned behavior”, Journal of Hospitality & Tourism Research, Vol. 30 No. 1, pp. 95-116.

Cohen, S.A., Prayag, G. and Moital, M. (2014), “Consumer behaviour in tourism: concepts, influences and opportunities”, Current Issues in Tourism, Vol. 17 No. 10, pp. 872-909.

Durán, M., Ferraces, M.J., Rodríguez, M. and Sabucedo, J.M. (2016), “The role of anticipated emotions in recycling intention: an extension of the theory of planned behaviour”, Psyecology, Vol. 7 No. 1, pp. 89-110.

Dursun, I., Kabadayi, E.T., Ceylan, K.E. and Koksal, C.G. (2019), “Russian consumers’ responses to Turkish products: exploring the roles of country image, consumer ethnocentrism, and animosity”, Business and Economics Research Journal, Vol. 10 No. 2, pp. 499-515.

Eve, F. (2020), “China’s reaction to the coronavirus outbreak violates human rights”, available at: www.theguardian.com/world/2020/feb/02/chinas-reaction-to-the-coronavirus-outbreak-violates-human-rights (accessed 2 February 2020).

Ford, J.K., MacCallum, R.C. and Tait, M. (1986), “The application of exploratory factor analysis in applied psychology: a critical review and analysis”, Personnel Psychology, Vol. 39 No. 2, pp. 291-314.

Guo, G., Zhou, X. and Tu, H. (2016), “Consumer animosity, self-efficacy and willingness-to-visit: an empirical study on young outbound tourism market”, Tourism Tribune, Vol. 31 No. 2, pp. 44-52.

Hair, J.F., Black, W.C., Babin, B.J. and Tatham, R.L. (2010), Multivariate Data Analysis: A Global Perspective, Pearson Prentice Hall, Upper Saddle River, NJ.

Han, H., Hsu, L.-T. and Sheu, C. (2010), “Application of the theory of planned behavior to green hotel choice: testing the effect of environmental friendly activities”, Tourism Management, Vol. 31 No. 3, pp. 325-334.

Han, H., Hsu, L.-T.J. and Lee, J.-S. (2009), “Empirical investigation of the roles of attitudes toward green behaviors, overall image, gender, and age in hotel customers’ eco-friendly decision-making process”, International Journal of Hospitality Management, Vol. 28 No. 4, pp. 519-528.

Han, H., Kiatkawsin, K., Ryu, H.B., Jung, H. and Kim, W. (2019a), “Determinants of young vacationers’ recycling and conservation behavior when traveling”, Social Behavior and Personality: An International Journal, Vol. 47 No. 2, pp. 1-11.

Han, H., Lee, S. and Lee, C.-K. (2011), “Extending the theory of planned behavior: visa exemptions and the traveller decision-making process”, Tourism Geographies, Vol. 13 No. 1, pp. 45-74.

Han, H., Meng, B., Chua, B.-L., Ryu, H.B. and Kim, W. (2019b), “International volunteer tourism and youth travelers - an emerging tourism trend”, Journal of Travel & Tourism Marketing, Vol. 36 No. 5, pp. 549-562.

Ho, R. (2006), Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS, CRC Press, New York, NY.

Huang, Y.A., Phau, I. and Lin, C. (2010), “Consumer animosity, economic hardship, and normative influence: how do they affect consumers’ purchase intention”, European Journal of Marketing, Vol. 44 Nos 7/8, pp. 909-937.

Hulland, J., Baumgartner, H. and Smith, K.M. (2018), “Marketing survey research best practices: evidence and recommendations from a review of JAMS articles”, Journal of the Academy of Marketing Science, Vol. 46 No. 1, pp. 92-108.

Hung, K. and Petrick, J.F. (2012), “Testing the effects of congruity, travel constraints, and self-efficacy on travel intentions: an alternative decision-making model”, Tourism Management, Vol. 33 No. 4, pp. 855-867.

Hunt, J.D. (1975), “Image as a factor in tourism development”, Journal of Travel Research, Vol. 13 No. 3, pp. 1-7.

Iriobe, O.C. and Abiola-Oke, E.O. (2019), “Moderating effect of the use of eWOM on subjective norms, behavioural control and religious tourist revisit intention”, International Journal of Religious Tourism and Pilgrimage, Vol. 7 No. 3, pp. 38-47.

Kim, S., Lehto, X. and Kandampully, J. (2019), “The role of familiarity in consumer destination image formation”, Tourism Review, Vol. 74 No. 4, pp. 885-901.

Klein, J.G., Ettenson, R. and Morris, M.D. (1998), “The animosity model of foreign product purchase: an empirical test in the People’s Republic of China”, Journal of Marketing, Vol. 62 No. 1, pp. 89-100.

Kock, F., Josiassen, A., Assaf, A.G., Karpen, I. and Farrelly, F. (2019), “Tourism ethnocentrism and its effects on tourist and resident behavior”, Journal of Travel Research, Vol. 58 No. 3, pp. 427-439.

Králiková, A., Peruthová, A. and Ryglová, K. (2020), “Impact of destination image on satisfaction and loyalty”, Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Vol. 68 No. 1, pp. 199-209.

Mokhlis, S. (2006), “The influence of religion on retail patronage behaviour in Malaysia”, unpublished manuscript, Safiek Mokhlis papers, University of Stirling.

Nazneen, S., Xu, H. and Ud Din, N. (2020), “Assessment of residents’ destination image and their pro-tourism development behaviour: perspectives on the China–Pakistan economic corridor”, Tourism Review, pp. 1-14.

Nimri, R., Patiar, A., Kensbock, S. and Jin, X. (2019), “Consumers’ intention to stay in green hotels in Australia: theorization and implications”, Journal of Hospitality & Tourism Research, Vol. 44 No. 1, pp. 149-168.

Paul, J., Modi, A. and Patel, J. (2016), “Predicting green product consumption using theory of planned behavior and reasoned action”, Journal of Retailing and Consumer Services, Vol. 29, pp. 123-134.

Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P. (2003), “Common method biases in behavioral research: a critical review of the literature and recommended remedies”, Journal of Applied Psychology, Vol. 88 No. 5, pp. 879-903.

Ragab, H., Mahrous, A.A. and Ghoneim, A. (2019), “Egypt’s perceived destination image and its impact on tourist’s future behavioural intentions”, International Journal of Tourism Cities, Vol. 6 No. 2, pp. 1-35.

Sánchez, M., Campo, S. and Alvarez, M.D. (2018), “The effect of animosity on the intention to visit tourist destinations”, Journal of Destination Marketing & Management, Vol. 7, pp. 182-189.

Shimp, T.A. and Sharma, S. (1987), “Consumer ethnocentrism: construction and validation of the CETSCALE”, Journal of Marketing Research, Vol. 24 No. 3, pp. 280-289.

Smith, W.W., Li, X., Pan, B., Witte, M. and Doherty, S.T. (2015), “Tracking destination image across the trip experience with smartphone technology”, Tourism Management, Vol. 48, pp. 113-122.

Soliman, M. (2019), “Extending the theory of planned behavior to predict tourism destination revisit intention”, International Journal of Hospitality & Tourism Administration, pp. 1-26.

Souiden, N., Ladhari, R. and Chiadmi, N.E. (2017), “Destination personality and destination image”, Journal of Hospitality and Tourism Management, Vol. 32, pp. 54-70.

State of Maine Department of Labor (2020), “Maine department of labor releases initial and weekly unemployment claims data for week ending April 11”, available at: www.maine.gov/labor/news_events/article.shtml?id=2388169 (accessed 16 April 2020).

Stepchenkova, S., Dai, X., Kirilenko, A.P. and Su, L. (2019), “The influence of animosity, ethnocentric tendencies, and national attachment on tourists’ decision-making processes during international conflicts”, Journal of Travel Research, pp. 1-16.

Tsai, W.C., Chen, X. and Yang, C. (2020), “Consumer food waste behavior among emerging adults: evidence from China”, Foods, Vol. 9 No. 7, p. 961.

Ulker-Demirel, E. and Ciftci, G. (2020), “A systematic literature review of the theory of planned behavior in tourism, leisure and hospitality management research”, Journal of Hospitality and Tourism Management, Vol. 43, pp. 209-219.

Wang, L. (2020), “Determinants of consumers purchase attitude and intention toward green hotel selection”, Journal of China Tourism Research, pp. 1-20.

Wang, L. and Wong, P.P.W. (2020), “Marketing of environmentally friendly hotels in China through religious segmentation: a theory of planned behaviour approach”, Tourism Review, pp. 1-16.

Wang, L., Wong, P.P.W. and Elangkovan, N.A. (2020a), “Antecedents of green purchase behaviour: an examination of altruism and environmental knowledge”, International Journal of Culture, Tourism and Hospitality Research, Vol. 14 No. 1, pp. 63-82.

Wang, L., Wong, P.P.W. and Elangkovan, N.A. (2020b), “The demographic impact of consumer green purchase intention toward green hotel selection in China”, Tourism and Hospitality Research, Vol. 20 No. 2, pp. 210-222.

Wang, L., Wong, P.P.W. and Elangkovan, N.A. (2020c), “The influence of religiosity on consumer’s green purchase intention towards green hotel selection in China”, Journal of China Tourism Research, Vol. 16 No. 3, pp. 319-345.

Wang, L., Wong, P.P.W., Elangkovan, N.A. and Chee, W.M. (2019), “Green hotel selection of Chinese consumers: a planned behavior perspective”, Journal of China Tourism Research, Vol. 15 No. 2, pp. 192-212.

Wen, J., Aston, J., Liu, X. and Ying, T. (2020a), “Effects of misleading media coverage on public health crisis: a case of the 2019 novel coronavirus outbreak in China”, Anatolia, Vol. 31 No. 2, pp. 331-336.

Wen, J., Kozak, M., Yang, S. and Liu, F. (2020b), “COVID-19: potential effects on Chinese citizens’ lifestyle and travel”, Tourism Review, pp. 1-14.

Wong, P.P. and Teoh, K. (2015), “The influence of destination competitiveness on customer-based brand equity”, Journal of Destination Marketing & Management, Vol. 4 No. 4, pp. 206-212.

World Tourism Organization (2019), Guidelines for the Success in the Chinese Outbound Tourism Market, UNWTO, Madrid.

Yu, Q., McManus, R., Yen, D.A. and Li, X. (2020), “Tourism boycotts and animosity: a study of seven events”, Annals of Tourism Research, Vol. 80, p. 102792.

Acknowledgements

This research was conducted and supported by Professor Dr Murali Sambasivan who comes from Department of Management Studies, Thiagarajar School of Management, Madurai, India. The authors would like to extend their sincere appreciation to his generous comments and support.Author’s contribution.Lei Wang contributed to the design of the work, data collection, data analysis and interpretation, drafting the article and final approval of the version to be published. Philip Pong Weng Wong contributed to the data interpretation, drafting the article, critical revision of the article and final approval of the version to be published.Qi Zhang contributed to the data collection and data analysis and interpretation.

Corresponding author

Lei Wang can be contacted at: drleiwang@foxmail.com

About the authors

Dr Lei Wang is based at the Faculty of Hospitality and Tourism, School of Management, Xuzhou University of Technology, Xuzhou, China. He is a Lecturer in Faculty of Hospitality and Tourism, School of Management, Xuzhou University of Technology, China. His research focuses on sustainability of tourism management, religion/religiosity, consumer decision-making, consumer loyalty and green purchase behaviour. He has published many journal articles in the areas of hospitality and tourism.

Dr Philip Pong Weng Wong is based at the School of Hospitality, Sunway University, Subang Jaya, Malaysia. He is a Senior Lecturer in School of Hospitality, Sunway University, Malaysia. His research interests are destination marketing, destination branding, destination competitiveness and destination loyalty. He has published many journal articles in the areas of top-tier hospitality and tourism.

Qi Zhang is based at the School of Management, Xuzhou University of Technology, Xuzhou, China. She is an Assistant Lecturer in School of Management, Xuzhou University of Technology, China. She has received her degree of Master in Leisure and Tourism Management at the Limkokwing University of Creative Technology, Malaysia. Her research interests include sustainability of tourism management, destination marketing and consumer decision-making process.

Related articles