Abstract
Purpose
This study aims to predict the effect of cultural distance, perceived risk and electronic word of mouth (eWOM) on higher education institutes' students' destination image. In addition, it examines the mediating role of destination image in relation to students' travel intentions.
Design/methodology/approach
An online survey was employed to collect data from 200 graduate and postgraduate students. The partial least squares was employed to analyse the hypothesised relationships.
Findings
The results of this study found support for the positive effect of cultural distance and eWOM on destination image. Additionally, the mediating effect of destination image was also supported.
Originality/value
This research confirms the vital role of destination image as an antecedent of students' future intention to visit the destination. Moreover, this study contributes to marketing theory by predicting the critical drivers of higher education students' destination image and discussing their applications in the education sector.
Keywords
Citation
Yang, X., Mohammad, J. and Quoquab, F. (2024), "A study of cultural distance, eWOM and perceived risk in shaping higher education students' destination image and future travel plan", Journal of Tourism Futures, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JTF-03-2023-0080
Publisher
:Emerald Publishing Limited
Copyright © 2023, Xia Yang, Jihad Mohammad and Farzana Quoquab
License
Published in Journal of Tourism Futures. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Studies pertaining to tourism and destinations argue that attracting and retaining repeat travellers is essential because it is cost-effective and a necessary strategy for tourism and destination marketing organisations (Syakier and Hanafiah, 2022). Particularly, repeated tourists are considered as one of the fundamental factors in increasing profits and reducing costs in market communication (Zhang et al., 2014), leading to more sustainable destination development (Chi and Qu, 2008). Therefore, it is essential to maintain existing and potential travellers and motivate them to become loyal to make a destination profitable (Sadiq et al., 2022). Thus, factors attracting travellers to a destination have been receiving more attention from researchers and marketers (Roozen and Raedts, 2022; Samala et al., 2022). However, the drivers of students' intentions as travellers need to be investigated further, particularly in the emerging market context, which this study aims to address.
Students are considered as a unique and noteworthy market segment of the tourist market due to their flexibility regarding time and purchasing power (Bai et al., 2004). According to Bicikova (2014, p. 854), the college student market, which is frequently considered to be a multibillion-dollar industry, “represents the single market segment of the youth tourism sector.” The WYSE Travel Confederation (2010) viewed it as an important market with significant economic potential, even during the world economic crisis. Similarly, Cavagnaro and Staffieri (2015) argued that studying youth tourism, especially university students, provides a descriptive and interpretative framework for future travellers in the long run. Although scholars and practitioners recognise the importance and contribution of student travel worldwide, there is a dearth of studies that examine Malaysian higher education students' travel intentions to visit China. Hence, additional studies are needed to better predict the travel behaviour of this tourist segment.
China is a unique destination that draws visitors from all over the world (China Highlight, 2021; Wen et al., 2021). In 2015, it became the fourth-most-visited country in the world, with 56.9 m international tourists per year (Ceoworld Magazine, 2018). In 2019, international arrivals in China reached 145.3 m (National Data Statistics of China, 2022); notwithstanding, this number dropped to 27.5 m in 2020 due to the coronavirus pandemic (Blazyte, 2022). South Korea, Japan, the United States of America, Russia and Malaysia are amongst the top countries for foreign tourists visiting China (Feiyue, 2019). According to the National Data Statistics of China (2022), the number of Malaysian tourists visiting China increased gradually from 107.550 thousand in 2015 to 129.150 thousand in 2019. However, after 2019, Malaysian tourists reduced their visits compared to the first time (Travel China Guide, 2019), and this number is still decreasing even in the post-pandemic area (Travel China Guide, 2019). According to Fan et al. (2023), the recovery stage remains uncertain, and it is likely to continue influencing travel behaviour, including revisits to specific destinations like China. In addition, Abbasi et al. (2021) contended that not all tourists intend to revisit any particular destination since many pull and push factors are associated. Hence, the primary objective of this study is to identify the factors driving Malaysian tourists, specifically students, to choose China as their destination. According to Chen et al. (2021), student tourists stand out from other visitor groups by having distinctive motivations. Recognising and comprehending the travel behaviour and motivations of this segment hold significant interest amongst scholars, practitioners and researchers, irrespective of their country of residence (Bicikova, 2014; Chen et al., 2021).
Past studies have revealed that psychological variables, particularly destination image influence consumer behaviour before, during and after visiting a destination (Chen and Hsu, 2000). Talaee Malmiri et al. (2021) suggested that destination image is one of the most dominant factors that affect tourists' behaviour. Destination image is “the totality of impressions, beliefs, ideas, expectations and feelings accumulated towards a place over time” (Kim and Richardson, 2003, p. 128). Nevertheless, there is a lack of empirical research that examines the relationship between the destination image and students' travel intentions. Accordingly, the first objective of this study is to predict the effect of destination image on students' travel intentions.
In the marketing and tourism literature, it is well established that external factors can influence consumer attitude and behaviour. For example, Donovan and Rossiter (1982) and Bues et al. (2017) suggested that consumer behaviour is a complex phenomenon that must be investigated in relation to internal factors (for example, personality, attitude, emotion, etc.) and external factors. External factors refer to situations where a person has encountered issues relating to the environment (Ibrahim and Harrison, 2019). Grounded in the stimulus–organism–response (S–O–R) theory (Mehrabian and Russell, 1974), this study considered cultural distance, perceived risk and eWOM as external factors that can exert a direct and indirect effect on students' distention image and their intention to visit Chain. Indeed, eWOM can affect consumers' attitude positively/negatively (Hajli et al., 2014), which in turn increases/decreases their behavioural intentions (Quoquab and Mohammad, 2022). The high perceived risk may lead consumers to form negative thoughts and feelings about the destination, which can decrease their intention to visit the destination (Sadiq et al., 2022). Fourie and Santana-Gallego (2013) revealed that cultural differences and similarities affect travellers' destination choices. Particularly, tourists tend to travel to destinations with low cultural distances (Álvarez-Díaz et al., 2022). Nevertheless, a paucity of empirical research examines the combined effect of these external factors on students' destination image. Therefore, the second objective of this study is to predict the effect of eWOM, perceived risk and cultural distances/similarities on students' destination image.
Although past studies found a significant relationship between external factors (e.g. eWOM, perceived risk and cultural distance) and internal factors (e.g. destination image) (Bi and Lehto, 2017; Quoquab et al., 2021) and between destination image and travellers' intention to visit (Hallmann et al., 2015), there is a lack of research that examined the mediating effect of destination image between external factors and travel intention. Considering this gap and guided by the S–O–R theory, the third research objective is formulated, which is to examine the mediating effect of students' destination image in the relationship between external factors and students' travel intention.
This study is expected to contribute to the existing literature in various ways. In particular, it is one of the few studies that predict the combined effects of eWOM, perceived risk and cultural distance on destination image, particularly in the higher education context. Additionally, this is a pioneering study that examines the mediation role of destination image on the relationship between cultural distance, perceived risk, eWOM and students' intention to visit China. The rest of the paper is organised as follows: The next section discusses the research context, followed by the theoretical background and conceptual design. In the following section, the adopted methodology is explained and the analysis and findings are presented. The discussion, contribution, limitations and future research directions are also highlighted.
2. Theoretical framework and hypotheses development
2.1 Student travellers as the research context
Usually, students like to travel, visit various destinations and consume numerous hospitality and tourism products and services, particularly in a foreign land (Sánchez-Torres et al., 2023). Their experience with this amalgam of products and services forms and shapes their visit experience, influencing their future visit intention (Sánchez-Torres et al., 2023). Many scholars have suggested that the student tourist segment is lucrative (Bai et al., 2004; Kim et al., 2007), representing 22% of global market segments (Patwary and Rashid, 2016). It is found that this segment holds different travel needs, travel motives and travel patterns (El Alfy and Abukari, 2020).
The literature review suggests that studies on student travel behaviour were mostly conducted in the Western countries such as the USA, Australia and New Zealand, and less is known from Asian perspectives (Kasim and Wickens, 2020). It provides an opportunity to address the gap by investigating the factors driving Malaysian students' travel intention to visit China. In doing so, this study examines the role of cultural distance, perceived risk, electronic word of mouth (eWOM) and destination image on students' travel intention.
2.2 The S–O–R theory
The S–O–R theory was initially proposed by Mehrabian and Russell (1974) in the context of environmental psychology. This theory suggests that environmental stimuli can affect an individual's cognitive and emotional status, leading to behavioural outcomes (Petrie, 1967). This model has been widely used to understand consumer behaviour and experience of buying halal food (Quoquab et al., 2019), organic food (Saleki et al., 2019), second-hand clothes (Mohammad et al., 2021), revisit intention (Kani et al., 2017) and place attachment (Jiang et al., 2017) but are rarely employed to understand consumers’ intention/behaviour in the higher education industry context (Goi et al., 2018).
In the S–O–R model, “stimulus” represents external factors that influence the individual's internal states (Chang et al., 2011). In this study, the stimuli are the antecedents of destination image, namely: cultural distance, perceived risk and eWOM. “Organism” refers to the emotional state of the human being that mediates the relationship between environment and human action. It represents “internal processes and structures intervening between stimuli external to the person and the final actions, reactions or responses emitted” (Bagozzi, 1986, p. 46). In this study, the organism refers to the destination image (includes cognitive and affective dimensions), which mediates the relationship between cultural differences, risk perception, eWOM and travel intention. The final output, “response,” refers to the approach/avoidance behaviour of the tourist in the S–O–R model (Mehrabian and Russell, 1974). In this study, the Malaysian students’ intention to travel to China is the response (R). The proposed conceptual framework of this study is illustrated in Figure 1.
2.3 Cultural distance and destination image
The cultural distance reflects the differences/similarities in values and shared norms from one country to another (Beugelsdijk et al., 2014). Cultural differences and/or similarities strongly influence individuals' choices (Mohammad et al., 2021). This is consistent with Huang et al.'s (2013) argument that the geographic and cultural distance between two places may affect the way a country's visitors see another country as a destination. Their findings indicated that cultural proximity is likely to form familiarity in tourists' minds. Likewise, Kastenholz (2010) contended that cultural proximity affects the destination image, revealing a different way of perceiving the destination area. San Martín and Rodríguez del Bosque (2008) also claimed that people with shorter cultural distances might have higher certainty and a more favourable image before visiting.
Destination image is a crucial factor in consumer behaviour and tourism studies (Álvarez-Díaz et al., 2022; Quoquab et al., 2021). Visitors rely heavily on destination image to decide their holiday choices; thus, it is essential to examine the factors that form their destination image (Kosmaczewska, 2022). Past studies found that experience with the destination, travel context, sociodemographics, beliefs sought and source of information are the major factors influencing destination image formation (Fourie and Santana-Gallego, 2013; Kastenholz, 2010). However, less attention was given to predicting cultural distances/similarities role in forming students' destination images.
In the Malaysian context, the Malaysian Chinese account for 22.8% of the total population of Malaysia (DOSM, 2019). Moreover, China and Malaysia have the same economic development level and social media prevalence, which can reduce the uncertainties in comparing the behaviour of Chinese and Malaysian individuals (Huang et al., 2020). In addition, Hofstede (2001) argued that Asian societies (e.g. Malaysia, China, etc.) have similar cultural values in terms of high power distance, collectivism, long-term orientation, masculinity and uncertainty avoidance. Similarly, Huang et al. (2013) declared that countries on the same continent may be relatively similar in terms of their culture and customs when compared to other countries. Similarly, Hu and Ritchie (1993) revealed that tourists' familiarity with a destination, which reflects their level of knowledge about a destination, can come from various sources (e.g. past experience, film, newspaper, magazine, TV, travel literature, etc.) can reduce the differences between a tourist and the host.
Based on the previous discussion, this study assumes that the similarities between Malaysian and Chinese culture range from moderate to high, which can positively affect Malaysian travellers' attitudes and behaviour. In addition, considering the huge number of Chinese students in Malaysian universities (28.59 thousand in 2021, Statista, 2021), this study contends that the communication, interaction and sharing of information between local students, regardless of their ethnicity and Chinese students can increase and improve local students knowledge, understanding and familiarity with Chinese culture which may affect their image positively to visit chine. Based on this assumption, this study assumes a positive association between cultural similarity and destination image. Thus, the following hypothesis is developed:
Cultural similarity positively impact on students' destination image
2.4 Perceived risk and destination image
In the tourism industry, the products are mostly intangible and the tourism experience can be subject to risk and danger (Sadiq et al., 2022). Perceived risk refers to individuals' perception of the probability that an act may be subject to a threat, which may impact travel decisions if the perceived danger is comparatively serious (Reichel et al., 2007). This threat can spoil the image of a travel destination (Walters et al., 2017), and increase the difficulty for tourists to assess the attractiveness of a destination (Mohseni et al., 2018). Perceived risks may include fear of natural disasters, sociopolitical instability, terrorism, the spread of diseases, experiencing poor value for money, etc (Lu et al., 2016). Such instances threaten the destination image and subsequent flow of tourists (Lepp et al., 2011).
Poon and Adams (2000) revealed that the security and safety issue had become a concern amongst tourists due to increased natural threats. Remarkably, natural disasters may intensify perceived travel risk and hinder tourist arrival (Lehto et al., 2008). Similarly, Roehl and Fesenmaier (1992) found that perceptions of risks and travel behaviour seem to be embedded in the situation. According to them, tourists perceived risks differently towards different destinations, which calls for studying destination-specific risk perceptions.
In recent years, China's air pollution has been one of the main factors affecting foreign tourists travelling to China. Becken et al. (2017) found that although the outside world has recognized China's cognitive image, potential tourists have expressed negative thoughts about the tourism crisis in China, especially the air quality. More importantly, this view of the air quality crisis has seriously impacted the destination's image and their intention to visit China. In addition, health-related risks, such as viral infection, are another vital factor affecting tourists' choices to visit China (Hong et al., 2020). This perceived risk negatively affects the destination's image, ultimately affecting students' intention to visit China and other destinations worldwide (Hong et al., 2020). Thus, this study proposes a negative correlation between perceived risk and destination image. Grounded in this proposition, the following hypothesis is developed:
Perceived risk will exert a significant negative impact on students' destination image
2.5 Electronic word of mouth (eWOM) and destination image
Technological advancements in communication and the sharing of information have seen the emergence of eWOM (Ismagilova et al., 2019). Due to its greater accessibility, speed and reach, this novel style of communication has become a crucial platform for individuals (travellers, visitors, consumers, students, etc.) to share and exchange their positive/negative experiences, actual/imaginary stories and good/bad thoughts, feelings and emotions (Kim et al., 2020; Yuan et al., 2022). According to Hennig-Thurau et al. (2004, p. 39), eWOM refers to “any positive or negative statement made by potential, actual or former customers about the product or company, which is made available to a multitude of people and institutions via the internet.” Being an effective tool, eWOM is likely to affect tourists' decisions and choices of destinations. It usually takes various formats, modes and timings (Chen and Law, 2016). Viglia et al. (2016) demonstrated that eWOM can influence consumer perceptions, buying behaviour and loyalty towards a destination. Similarly, Hamouda and Yacoub (2018) found that eWOM exerts an effect on cognitive and affective images and intentions to access potential destinations. However, the role of eWOM has been disregarded in the higher education context (Carvalho et al., 2021). Therefore, this study presumes that eWOM positively affects students' destination image. Guided by this presumption, the following hypothesis is developed:
eWOM will exert a significant positive impact on destination image.
2.6 Destination image and future travel intention
Destination image plays a crucial role in affecting tourists' attitudes and behaviour towards a destination (Quoquab et al., 2021). It can be ascribed as “visitors' beliefs, ideas and impressions of a specific destination” (Lee and Lockshin, 2011, p. 18), the more attractive the image of a destination, the greater the possibility that travellers will favour that destination for visiting (Goodrich, 1978). Therefore, a destination image is crucial to marketing success (Nghiêm-Phú and Nguyễn, 2020).
Destination image has been found to be a significant predictor of consumer intention to travel. For example, Tan and Wu (2016) found that cognitive and affective images have a concrete impact on tourists' future visit intention to Hong Kong. Likewise, Biswakarma (2017) found that the tourist destination image of Nepal correlated positively with his/her behavioural intention to visit (Biswakarma, 2017). Oliver (1997) defined behavioural intention as a confirmed chance to involve in certain behaviour. Intention can be perceived as a prediction tool when studying customers' future behaviour. This study assumes that the destination image will influence students' intention to travel to China. Based on this assumption, the following hypothesis is developed:
Destination image will exert a significant positive impact on students' future travel intention.
2.7 The mediation role of destination image between cultural distance, perceived risk, eWOM and future travel intention
Previous research demonstrated a significant correlation between environmental factors (i.e. cultural distance/similarity, perceived risk, eWOM) and psychological factors (i.e. destination image) (Bi and Lehto, 2017; Quoquab et al., 2021). In addition, Hallmann et al. (2015) and Yoon and Uysal (2005) found that psychological variable (e.g. destination image) is an essential factor that influences traveller attitudes and intention towards the destination. Thus, a mediation mechanism of the destination image is expected, and the S–O–R theory can explain this mediation effect. In this study, cultural distance, perceived risk and eWOM may affect students' perceived image (i.e. organism), leading them to visit/revisit distention (response). Therefore, the following hypotheses are being developed:
The relationship between cultural distance and students' future travel intention will be mediated by destination image.
The relationship between perceived risk and students' future travel intention will be mediated by destination image.
The relationship between eWOM and students' future travel intention will be mediated by destination image.
3. Methodology
3.1 Measurement
To measure the study constructs, all items were adapted from past studies (Appendix). To validate the questionnaire further, it was subjected to face and content validity (Cavana et al., 2001). The content validity was conducted by disseminating the draft questionnaire to five academicians in the field of tourism and marketing to check the adequacy and representativeness of the scales (Bowden et al., 2002). In addition, the questionnaire was faced-validated through ten postgraduate students to check the level of clarity and readability of measures (Zikmund et al., 2012). Based on the feedback obtained, the questionnaire was revised accordingly.
The study constructs were measured using a seven-point Likert scale, ranging from (1) strongly disagree to (7) strongly agree. The cultural distance variable was measured by using three items adapted from (Liu et al., 2018). Perceived risk was measured by using three items adapted from (Walters et al., 2017). eWOM was measured via six items adapted from Jalilvand et al. (2012). Cognitive and affective images were measured via seven items adapted from Tan and Wu (2016). Lastly, future travel intention was measured by using three items adapted from Chen et al. (2014).
3.2 Sample and data collection
To test the hypotheses, an online questionnaire survey was designed and the data were collected from undergraduate and postgraduate students, who were studying in business school at five Malaysian research universities (i.e. The Universiti Malaya (UM), Universiti Kebangsaan Malaysia (UKM), Universiti Sains Malaysia (USM), Universiti Putra Malaysia (UPM) and Universiti Teknologi Malaysia (UTM)). The non-probability judgemental sampling technique was used to collect data from respondents due to a lack of a sampling frame (Perla and Provost, 2012). The target respondents for the survey were Malaysian students who have intention to visit China in the nearest future. This criterion was fulfilled by using screening questions on the cover page of the questionnaire. This study utilised a web survey, and the data were collected through the social media channels such as Facebook, Twitter, WhatsApp, etc. Confidentiality and anonymity of provided information were assured to allow the students to express and share their honest opinion and true feelings. The Gpower software was used to calculate the minimum sample size with a predictive power of 0.95, effect size of 0.15 and marginal error of 5% (Chin, 2010; Hair et al., 2022). Calculations suggested that, with a maximum of three predictors, the required sample size was 119.
A total of 300 links were distributed, and after a period of one month, 221 questionnaires were received. The data were cleaned in terms of errors, outliers and concerns related to normality. Specifically, amongst the 21 surveys that were excluded from the analysis, ten exhibited straight-line replies, six were identified as outliers and five violated the normality assumption (Hair et al., 2022). The demographics of respondents in this study include gender, age, education, ethnicity, education, occupation and income (Table 1). In a total of 200, 89 (44.4%) respondents were male and 111 (55.5%) were female. Regarding respondents' age, 85% were less than 40 years old. Out of 200 respondents, 35.5% were Malays, 43.5% were Chinese, 14.5% were Indian and 6.5% were of other ethnicities. Most of the respondents have an income greater than $800 (56%).
4. Analysis and findings
The two stage-approached recommended by Anderson and Gerbing (1988), was used to analyse the data. In the first stage, the measurement model’s reliability and validity was examined followed by testing the structural model through structural equation modelling (SEM) using SmartPLS3 software (Ringle et al., 2015). The PLS-SEM can handle complex model that has higher-order construct and direct and indirect relationships (Hair et al., 2022). In addition, the PLS-SEM provides simultaneous explanation and prediction assessment of the model, which meets the objective of this study.
4.1 Measurement model assessment (first order)
All constructs were measured reflectively; hence, it is essential to assess the indicator reliability, internal consistency reliability and construct validity (Hair et al., 2022). As revealed in Table 2, the indicator loadings are above 0.5 except eWOM4 and it was dropped from further analysis; the Cronbach’s alpha (CA) and composite reliability (CR) values range from 0.736 to 0.903 and the AVE ranges from 0.583 to 0.699. Consequently, all criteria for confirming the reliability and establishing convergent validity of the measures were achieved (Hair et al., 2022). Next, discriminant validity was evaluated based on the heterotrait-monotrait ratio (HTMT) recommended by Henseler et al. (2015). The HTMT ratio of less than 0.85 (Kline, 2011) indicates that the constructs are distinct. As presented in Table 3, all the ratios are less than 0.85; thus, discriminant validity was established.
4.2 Measurement model assessment (second order)
In this study, the destination image is operationalized as a higher-order reflective-reflective construct manifested in the cognitive and affective images (Tan and Wu, 2016) and was measured using a repeated indicator approach. Applying the repeated indicator approach involves assigning all indicators of the lower-order component to the higher-order (Wold, 1982). In this study, the destination image is measured via two lower order components, i.e. cognitive image (measured via three items) and affective image (measured via four items); the higher order would be measured by the same seven items as the lower order components. The evaluation of higher order construct is based on its relationships with its lower order component rather than with its repeated indicators (Hair et al., 2022). The relationship between the destination image and its component is reflective; thus, the standard measurement model for reflective construct will be followed. Mainly, factor loadings, internal consistency reliability, convergent validity and discriminate validly criteria should be assessed for the higher-order destination image. As shown in Table 4, the PLS algorithm result produces a loading of 0.88 for cognitive image and 0.927 for affective image, thereby supporting indicator reliability. By using these indicator loadings and the correlation between the constructs (0.682), other values were calculated manually. As demonstrated in Table 4, Cronbach’s alpha and composite reliability for cognitive and affective images exceeded the recommended value of 0.70. AVE surpassed the suggested value of 0.50, indicating that the second order shared a high portion of variance with its lower components. Consequently, the validity and reliability of higher order was confirmed.
4.3 Structural model assessment
First, the structural model was assessed for collinearity (Hair et al., 2022) by testing the variance inflation factor (VIF) values for all predictors constructed in the model. The PLS algorithm result found that the VIF values were less than 3.3 (Diamantopoulos and Siguwa, 2006). Thus, collinearity was not an issue. Next, the significance and relevance of path coefficients were tested via bootstrapping procedures with 5,000 resamples (Hair et al., 2022). As shown in Table 5 and Figure 2, CD has a significant positive effect on the destination image (β = 0.283, p < 0.01), providing support for H1. In addition, eWOM has a significant positive effect on destination image (β = 0.345, p < 0.01) but no effect on perceived risk. Therefore, support for hypothesis H3 was found, whilst hypothesis H2 was not confirmed. Finally, destination image exerts a significant positive effect on travel intention (β = 0.558, p < 0.01), providing support for hypothesis H4.
Next, the in-sample explanation power of the structural model was assessed using the coefficient of determination (R2) (Hair et al., 2022). R2 values of 0.26, 0.13, and 0.02 are considered substantial, moderate and weak, respectively (Cohen, 1988). The output of the PLS algorithm revealed that R2 values of the destination image were moderate (0.218) and substantial (0.312) for travel intention (Table 5). These results illustrate that the R2 values were considered acceptable for this model.
Out-of-sample predictive power was also examined via PLSpredcit with ten folds and ten repetitions (Hair et al., 2022). The guidelines suggested by Shmueli et al. (2016) were followed, and to evaluate the result, the root mean squared error values (RMSE) for PLS and linear model (LM) as well as the Q2-predict values for the PLS model were focussed. The Q2 values should be positive and the prediction error of PLS-SEM (e.g. RMSE) should be smaller than the prediction error resulting from the LM. The result of PLSpredcit displayed in Table 6 revealed that the Q2 values of the indicators of travel intention were positive. In addition, the RMSE values from the PLS-SEM analysis were less compared to RMSE values of naïve LM benchmarks (Table 6). This indicates that the model has high predictive power (Shmueli et al., 2016).
To examine the mediating effects of destination image, a bootstrapping procedure with 5,000 resampling was performed (Hair et al., 2022). The results reported in Table 7 indicate that destination image mediated the relationships between cultural distance and travel intention (β = 0.144, t = 3.574, p = 0.000) and between eWOM and travel intention (β = 0.212, t = 3.470, p = 0.000). Therefore, H5 and H7 were confirmed. Contrary to expectation, the mediation role of destination image between perceived risk and travel intention was insignificant (β = −0.091, t = 1.442, p = 0.075); hence H6 was rejected.
5. Discussion
The main objectives of this research were to examine the effect of external factors (i.e. cultural distance, perceived risk and eWOM) on Malaysian students' destination image as well as the effect of destination image on their future travel intention and also, to predict the mediation effect of destination image between external factors and travel intention. To carry out these objectives, a conceptual model was developed based on the S–O–R theory and tested empirically using partial least square. The result of PLS bootstrapping using SmarPLS software found support for five out of seven hypotheses. The results are briefly discussed in the following paragraphs.
The cultural distance was able to exert a positive and significant influence on the destination image (β = 0.252, p < 0.01). This is in agreement with past studies (e.g. Huang et al., 2013) that found that if the destination has a similar culture to tourists' home country, tourists will have a good image of the place they plan to go. This result also aligns with the S–O–R theory, which argues that cultural distance (stimulus) can positively affect the destination image (organism), leading him/her to visit the destination. In this study, Malaysian students find similarities between his/her place (Malaysia) and his/her target destination (China) in terms of language, lifestyle, habits, weather, values, food, etc.; therefore, they have developed a good image of the destination's culture.
The output of this study demonstrated that eWOM exerts a strong positive effect on the destination image (β = 0.372, p < 0.01). This result is consistent with past studies that found a positive association between word of mouth and consumer attitude and behaviour (see Hamouda and Yacoub, 2018). This result also agrees with the S–O–R model that argues eWOM is likely to stimulate tourists to form positive/negative ideas, thoughts, feelings and emotions about the destination. This result indicates that eWOM is likely to enhance students' favourable evaluation of destinations resulting in their intention to visit China. This research also found a strong positive correlation between destination image and travel intention (β = 0.569, p < 0.001). This result is congruent with past research that found a positive association between an individual psychological state and his/her intention/behaviour (see Tan and Wu, 2016). The result indicated that Malaysian students with a positive image of China are more likely to develop a positive intention to travel to the destination.
Contrary to expectation, the analysis showed that perceived risk does not affect destination image. According to Roehl and Fesenmaier (1992), perceptions of the risks of a destination can be embedded in the situation, proposing that tourists perceive risks differently towards different destinations and, thus, the need to study destination-specific risk perceptions. For example, Kozak et al. (2007) found that tourists from Malaysia and Singapore were more concerned about terrorist attacks and natural disasters when visiting Hong Kong. However, when visiting Japan, they are more concerned about financial risk rather than physical risk (Chew and Jahari (2014). Likewise, Simpson and Siguaw (2008) stated that Mexican travellers were more concerned about health and well-being. Other tourism researchers argued that differences in risk perception can vary between nationalities and ethnic groups. For example, Money and Crotts (2003) observed that German tourists were more risk-takers than Japanese tourists. Similarly, Reisinger and Mavondo (2006) found that tourists from the United States of America and Australia perceived more travel risks than those from the UK and Canada.
Based on the discussions mentioned above, it can be said that Malaysian travellers hold a low physical risk perception towards China. In Malaysia, there is a big Chinese community and many international Chinese students at public and private universities, which may make them somewhat familiar with the culture. Another plausible explanation is that they are more risk-takers. This explanation aligns with the psychological value and motivation lenses (Baloglu and McCleary, 1999), arguing that young individuals are risk-takers (Gardner and Steinberg, 2005).
Finally, this research demonstrated that destination image was able to mediate the relationship between cultural distance, eWOM and travel intention, confirming H5 and H7. This result is in line with the S–O–R theory. Notably, the S–O–R theory suggests that a tourist's organism (i.e. his/her image of destination) is influenced by the environmental stimuli (i.e. cultural difference and eWOM), which is likely to affect their responses (i.e. intention to visit). More specifically, destination image represents a mechanism that underlies the relationship between external factors and behaviour intention.
6. Theoretical contribution
This study enhances the understanding of the existing literature theoretically in different aspects. First, it strengthens the foundation of the destination image model by improving our understanding of its antecedents and consequences in the tourism context from students' perspectives. By explaining how external factors in terms of cultural distance, perceived risk and eWOM influence destination image and travel intention, this study fills the gap in the existing literature on destination marketing in the higher education context.
Second, this is a pioneer study that considers the mediating role of psychological variables (i.e. destination image) between cultural distance, eWOM, perceived risk and travel intention. Destination image and its related concepts have been well-studied. However, the role of destination image as a mediator is still not well explained. The results of this study revealed that student tourists' cognitive and emotional status is a crucial mediator that receives information from the external environment and translates it into high/low intention and behaviour. The empirical evidence indicates that when stimulating factors lead to positive formation/reformation of destination images, repeat tourists would tend to increase their revisit intentions.
Third, this study provides a unique framework that has integrated external factors (cultural distance, perceived risk and eWOM) and internal factors (destination image) in an attempt to enhance the predictability of students' intention to visit China. The S–O–R model guided this integration, confirming the usability and suitability of this model in a developing context like Malaysia.
Fourth, in this study, the theoretical model and empirical evidence of the second-order factor structures of destination images were confirmed. Given the fact that research on the structural constructs of destination image has been done mostly at the conceptual level and from a developed cultural perspective (see Kim and Yoon, 2003; Llodrà-Riera et al., 2015; Pike, 2002), this study provides empirical evidence from the emerging context like Malaysia supporting the theoretical model of destination image as a higher order construct. Specifically, the study's findings indicate that the image of a tourism destination can be operationalized as the second-order construct that is reflected in both affective and cognitive images. The analysis results have also confirmed the destination image's validity and reliability at both the first and second orders.
Fifth, the findings of this study contend that the effects of risk perception on the formation/reformation of the destination image are likely to be context-specific even when repeat travellers perceive the same risk. Last but not the least, this study's results strengthen past studies' findings (e.g. Chew and Jahari, 2014; Huang et al., 2013; Tasci et al., 2022) concerning cultural differences and their effect on travelers' attitudes and behaviour. Specifically, similarities between tourists and hosts can form positive cognitive and affective images. In contrast, differences can result in a negative image of the destination.
7. Practical implication
This study suggests that to enhance students' intention to visit China, the tourism sector must pay attention to the destination image, eWOM, perceived risk and cultural distance. These factors need to be marketed wisely since these factors are likely to play a vital role in marketing campaigns. In more detail, eWOM positively and significantly impact destination image in this study. The possible reason can be that the internet is an initial tool for tourists to search the suitable destination before travelling. The pictures and comments of the destinations are viewed by the students once browsing the tourism websites. Not only that, but social media also plays a significant role in spreading word of mouth via the net. In this way, eWOM influences students' travel intentions. Therefore, the Chinese tourism department must ensure that the information to attract international students is presented on the official websites.
In addition, the result indicated a positive and significant relationship between cultural distance and destination image. The findings of this study suggest that the more similarities between the host country's culture (e.g. China) and the home country's culture (e.g. Malaysia), the better destination image created in student tourists' minds. The reason for this can be illustrated from several aspects, such as food, religion, language and geographic distance. For example, Malaysian Chinese students have the advantage of speaking the language, and it is easy for them to adopt Chinese foods. On the contrary, Malaysian students may not have the image as Malaysian Chinese since they have to consider some religious issues. Therefore, this study suggests that more attention should be paid to the student tourists' religious needs. The recommendations involve providing information on the tourism website about halal food and other essential religious aspects to reduce the distance between the host country (China) and the home country (Malaysia).
Moreover, this study found a positive link between destination image and students' travel intention. It indicates that the higher the positive destination image, the higher the travel intention to a particular destination in a foreign land. As a result, to attract students to travel to another country, the respective departments, organizations and/or agencies should promote beautiful images of the country (China), e.g. ancient palaces, iconic tourist sites, famous universities museums and temples in order to attract students to visit. Surprisingly, in this study, the perceived risk did not exert an effect on destination image. It might be due to the fact that students are comparatively more risk-takers than the other tourist segments. Students are likely to be more adventurous and not stop visiting any place by being afraid of the perceived risk. Tourism operators may take advantage of this issue and attract international students to visit their destinations by promoting rides, hiking and other activities.
Lastly, the findings supported the mediating role of destination image between cultural distance, eWOM and travel intention. It can be said that the destination image is likely to strengthen the cultural distance and eWOM impact on the travel intention. Thus, it is recommended to focus on forming a positive image in students' minds. Nowadays, the tourism industry is very competitive; thus, promoting a destination needs to be more innovative and attractive for student travellers. The primary tool or strategy in marketing is promotional activities. The content provided and promoted by the tourism operators and the destination organizations will be first seen on the internet through social media or travel websites. Eventually, it will create an image in students' minds from their website browsing.
8. Limitations and future research directions
The current study adopted a cross-sectional research design; this means that the data were collected at specific points of time, which may pose a question about the cause-effect relationships. Therefore, further research may use the experimental and/or longitudinal design to enhance the researcher understanding of causality amongst constructs. Additionally, future studies can incorporate other variables in the model, such as tourism motive and destination facilities, etc., to gain a wider understanding of the phenomenon. In addition, this study was limited to a sample from five public and research universities. Therefore, future research is advised to consider both public and private as well as research and non-research universities. In addition, this study was based on Malaysian students only; future research may consider respondents from different cultures to increase the generalizability of the result. Lastly, future researchers are advised to examine tourist perception of post-COVID-19 as it may impact their future travel intention.
Figures
Demographic profile of the respondents
| Demographics variables | Number of respondents (200) | Percentage (%) |
|---|---|---|
| Gender | ||
| Male | 89 | 44.5 |
| Female | 111 | 55.5 |
| Age | ||
| 20–30 | 86 | 43.0 |
| 31–40 | 84 | 42.0 |
| 41–50 | 26 | 13.0 |
| 51 and 60 | 4 | 2.0 |
| Ethnicity | ||
| Malaysian | 71 | 35.5 |
| Chinese | 87 | 43.5 |
| Indian | 29 | 14.5 |
| Others | 13 | 6.5 |
| Education | ||
| Bachelors' degree | 59 | 29.5 |
| Masters' degree | 109 | 54.5 |
| Doctoral degree | 27 | 13.5 |
| Diploma/other tertiary degree | 5 | 2.5 |
| Monthly Income | ||
| Below RM 2000 | 52 | 26.0 |
| RM 2001–RM 3000 | 27 | 13.5 |
| RM 3001–RM 4000 | 24 | 16.7 |
| RM 4001–RM 5000 | 22 | 20.1 |
| RM 5001–RM 6000 | 26 | 11.5 |
| RM 6001 and above | 49 | 17.8 |
Source(s): Authors’ creation
Assessment of measurement model (first order)
| Construct | Indicators | Loading | Cronbach’s alpha | Composite reliability | AVE |
|---|---|---|---|---|---|
| Cultural distance (CD) | CD1 | 0.934 | 0.736 | 0.851 | 0.666 |
| CD2 | 0.908 | ||||
| CD3 | 0.548 | ||||
| Cognitive image (CI) | DI1 | 0.843 | 0.739 | 0.852 | 0.659 |
| DI2 | 0.842 | ||||
| DI3 | 0.746 | ||||
| Affective image (AI) | DI4 | 0.774 | 0.856 | 0.903 | 0.699 |
| DI5 | 0.85 | ||||
| DI6 | 0.844 | ||||
| DI7 | 0.873 | ||||
| Perceived risk (PR) | PR1 | 0.98 | 0.844 | 0.867 | 0.689 |
| PR2 | 0.793 | ||||
| PR3 | 0.691 | ||||
| Future travel intention (FTI) | FTI1 | 0.852 | 0.779 | 0.869 | 0.688 |
| FTI2 | 0.783 | ||||
| FTI3 | 0.851 | ||||
| eWOM | eWOM1 | 0.802 | 0.82 | 0.874 | 0.585 |
| eWOM2 | 0.883 | ||||
| eWOM3 | 0.596 | ||||
| eWOM4 | 0.831 | ||||
| eWOM6 | 0.676 |
Source(s): Authors’ creation
Assessment of discriminant validity using heterotrait-monotrait (HTMT)
| CI | CD | PR | FTI | AI | eWOM | |
|---|---|---|---|---|---|---|
| CI | ||||||
| CD | 0.259 | |||||
| PR | 0.167 | 0.112 | ||||
| FTI | 0.569 | 0.286 | 0.126 | |||
| AI | 0.856 | 0.375 | 0.083 | 0.659 | ||
| eWOM | 0.402 | 0.138 | 0.196 | 0.421 | 0.365 |
Source(s): Authors’ creation
Assessment of measurement model (second order)
| Construct | Indicators | Loading | Cronbach’s alpha | Composite reliability | AVE |
|---|---|---|---|---|---|
| Destination image | Cognitive image | 0.880 | 0.81 | 0.899 | 0.816 |
| Affective image | 0.927 |
Source(s): Authors’ creation
Structural model result for direct relationships
| Hypotheses | Relationships | Std beta | Std error | t values | R2 | 95%CI | Decision |
|---|---|---|---|---|---|---|---|
| H1 | Culture distance → Destination image | 0.283 | 0.062 | 4.576 | 0.218 | 0.165–0.391 | S |
| H2 | Perceived risk → Destination image | −0.155 | 0.106 | 1.458 | −0.284–0.126 | NS | |
| H3 | eWOM → Destination image | 0.345 | 0.07 | 4.924 | 0.179–0.461 | S | |
| H4 | Destination image → Future travel intention | 0.558 | 0.07 | 7.931 | 0.312 | 0.389–0.671 | S |
Source(s): Authors’ creation
PLSpredict result based on assessing RMSE values
| PLS-SEM LM | ||||
|---|---|---|---|---|
| Items | RMSE | Q2_predict | RMSE | PLS-SEM-LMRMSE |
| TI2 | 1.296 | 0.092 | 1.346 | −0.05 |
| TI3 | 1.333 | 0.073 | 1.413 | −0.08 |
| TI1 | 1.039 | 0.106 | 1.052 | −0.013 |
Source(s): Authors’ creation
Structural model results for indirect effect
| Hypotheses | Relationships | Std beta (a*b) | Std error | t values | 95%CI | Decision |
|---|---|---|---|---|---|---|
| H5 | Culture distance → Destination image → Future travel intention | 0.158 | 0.043 | 3.656 | 0.085–0.25 | S |
| H6 | Perceived risk → Destination image → Future travel intention | −0.086 | 0.063 | 1.367 | −0.173–0.083 | N |
| H7 | eWOM → Destination image → Future travel intention | 0.193 | 0.054 | 3.543 | 0.091–0.0298 | S |
Source(s): Authors’ creation
The supplementary material for this article can be found online.
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Acknowledgements
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Corresponding author
About the authors
Xia Yang is Alumnus of Azman Hashim International Business School, Universiti Teknologi Malaysia. His research focus is consumer behaviour, eWOM, risk management, cultural difference and tourism marketing.
Jihad Mohammad (Dr) is Assistant Professor of Management at Graduate Business School, UCSI University. He has received his DBA degree from Universiti Kebangsaan Malaysia. He has published several articles in peer-reviewed international journals. He has versatile career exposure. He has conducted several workshops for postgraduate students regarding research methodology and structural equation modelling. His area of research interest includes organizational citizenship behaviour, psychological ownership, psychological capital, leadership, innovation and Islamic work ethics, green and sustainability.
Farzana Quoquab (Dr) is Associate Professor of Marketing at Azman Hashim International Business School, UTM. Since 2014, she has been actively working on the issues of green and sustainability marketing. Her works have appeared in high-impact publications such as Asia Pacific Journal of Marketing and Logistics, Journal of Electronic Commerce Research, Internet Research, Employee Relations: The International Journal, SAGE Open, Personnel Review, Cross Cultural and Strategic Management, Journal of Fashion Marketing and Management, and Journal of Product and Brand Management. She is also Prolific Case Writer. Dr Farzana is one of the Associate Editors of “Emerald Emerging Market Case Studies”, and Editor-in-Chief of “International Journal of Innovation and Business Strategies”. She has successfully served as a guest editor for the reputed journals like Young Consumers (Emerald) and Journal of Global Marketing (Routledge Publishing). She is also Member of Editorial Advisory/Review Board of several internationally reputed journals.