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Article

The Mechanism of Tourism Risk Perception in Severe Epidemic—The Antecedent Effect of Place Image Depicted in Anti-Epidemic Music Videos and the Moderating Effect of Visiting History

by
Fang Wang
1,
Tao Xue
2,*,
Ting Wang
3 and
Bihu Wu
3
1
College of Tourism, Huaqiao University, Quanzhou, Fujian 362021, China
2
College of Tourism and Service, Nankai University, Tianjin 300350, China
3
College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(13), 5454; https://0-doi-org.brum.beds.ac.uk/10.3390/su12135454
Submission received: 11 June 2020 / Revised: 2 July 2020 / Accepted: 3 July 2020 / Published: 6 July 2020
(This article belongs to the Special Issue Sustainability vs Uncontrollability: COVID-19 and Crisis Impact on the Hospitality and Tourism Community)
Browse Figures
Review Reports Versions Notes

Abstract

:
Tourism risk perception is proven to have significant influence on tourists’ decision-making behaviors, however, the impact of the place image depicted in the cultural media of destinations on it needs to be further studied. The study explores the mechanism of potential tourists’ risk perception in severe COVID-19 epidemics with the antecedent effects of the place image depicted in anti-epidemic music videos, and the impact of risk perception on potential tourists’ place attachment and travel intention, based on the risk perception theory. This study also explores the moderating effect of the visiting history on balancing risk perception, place attachment, and travel intention. With empirical research, the study result indicates that in severe epidemics: (1). The place image depicted in anti-epidemic music videos has a significant negative effect on tourism risk perception; tourism risk perception has a significant negative effect on potential tourists’ place attachment and travel intention; (2). The tourism risk perception mediates between the place image depicted in the music videos and potential tourists’ place attachment and travel intention; (3). Visiting history modulates the influence of tourism risk perception, potential tourists’ place attachment, and travel intention. This research would be helpful if it enriches the theoretical content of risk perception, expands the theoretical foundation of tourists’ decision making, promotes the application of music videos in tourism research, and proposes empirical risk management countermeasures of tourism destination.

1. Introduction

On 30 January 2020, the World Health Organization confirmed the novel coronavirus pneumonia epidemic to be a public health event of international concern (statement on the second meeting of the International Health Regulations (IHR) emergency committee regarding the outbreak of the 2019- nCoV: https://www.who.int/news-room/detail/30-01-2020 statement-on the-second-meeting-of-the-international healthregulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov)). This is the sixth time that the World Health Organization has promulgated the International Health Regulations for the management of a global health emergency measures since 2007, which means that the world has entered a stage of emergency crisis. Until the 9 May 2020, the epidemic has spread to almost all countries around the world, leading to a total of about 4 million infections and about 270,000 deaths. It has had a huge impact on the world economy and tourism industry, which rarely happens in the case of other major historical public health events. The epidemic has caused both international and domestic tourist arrivals to plummet. According to the report of the China Tourism Research Institute, due to the impact of the novel coronavirus pneumonia epidemic, domestic tourist arrivals in the first quarter of 2020 and the whole year will decrease by 56% and 15.5%, respectively, and a total of 932 million person-fold decrease is forecasted for the year (Source: China Tourism Research Institute, https://ncstatic.clewm.net/rsrc/2020/0315/20/d993dadc05e3e80a35cc5020b3c7be7f.pdf). The sluggish travel intention has caused tremendous impacts on the Chinese tourism industry.
In the context of consumer behaviors, risk is defined as a subjective sense of uncertainty about the quality of purchases [1]. The studies have shown that the perceived risk, as an important factor affecting consumer decision making [2], will have an effect on consumer willingness and behavioral intention [3]. With regard to this new global outbreak crisis, the travel risks of tourists are objective. Higher risk perception will have a negative impact on tourists’ travel intention [4] and even allow tourists to make evasive decisions to avoid specific destinations [5].
In the past, tourism research, the studies on the relationship among place image, emotional attitude, and behavioral intention are relatively well established [6,7,8] and the studies on the relationship between place attachment and travel intention are also common [9]. However, in the special situation of a severe epidemic like COVID-19, tourists’ perceptions of destination risk have significantly changed, and the potential tourists’ travel intention and decision-making processes for destinations have become more complicated and unstable. It is unclear whether the mechanism of place image transmission to place attachment and travel intention under normalized situations is equally effective in severe epidemics or not, and the mechanism of tourism risk perception is still unknown. At the same time, the traditional tourism risk perception is mostly from the perspective of rational decision-making, ignoring the emotional perspective of “person–place” interaction. Even though related research mainly focuses on the management paradigm and investigates the concept, dimensions, influencing factors, and the measurement of risk perception [10], few scholars have studied tourism risk perception from the perspective of the “person–place” relationship in geography. From the perspective of human geography, although these studies have recognized concepts related to risk perception, such as “the fear landscape” [11], more research remains on the description level of people’s psychological response to the landscape, and there is a lack of discussion on the mechanism of potential tourists’ risk perception from the perspective of a “person–place” relationship. In addition, there is inadequate research on the place image depicted in anti-epidemic music videos as the antecedent variable of tourism risk perception. There is also a lack of research on the joint effect of tourism risk perception on the potential tourists’ attitude and behavior.
Therefore, based on the interdisciplinary research perspectives of management, geography, and tourism science, this study uses the place image depicted in anti-epidemic music videos as a starting point to explore the mechanism of tourism risk perception on place attachment and travel intention in order to enrich the theoretical research on tourism risk perception in the special situation of a severe epidemic situation from the perspective of “person–place” relationship.

2. Literature Review and Hypotheses

2.1. Perceived Risk Theory

The perceived risk theory, as an important theoretical basis for explaining consumer decision-making behavior, was first proposed by Bauer in 1960. Bauer (1960) [12] showed that perceived risk is a subjective risk based on subjective personal evaluation, the perception of failure possibility and adverse results purchasing/using goods or services, and he believed that due to the unknown and uncertainty in the consumer purchase process, some purchase results cannot meet expectations and make consumers unhappy. Since then, the perceived risk theory has been widely applied and expanded. Kaplan, Szybillo, and Jacoby (1974) [13] constructed five dimensions of perceived risk: financial risk, functional risk, physical risk, psychological risk, and social risk. Later Stone and Gronhaug (1993) [14] added time risk, which formed the sixth dimension of the perceived risk theory. Subsequent scholars have supplemented and expanded the dimensions of the perceived risk theory based on their research situation [10].
Tourism products have the characteristics of intangibility and instant consumption, and tourist experience is difficult to standardize, both of which lead tourists to have a higher perception of their risks [15]. Roehl conducted an exploratory study on tourism risk perception with perceived the risk theory in 1992, using a psychometrics scaling method and multivariate analysis to determine three basic dimensions of tourists’ perceived risk: physical equipment risk, vacation risk, and destination risk [16]. As the study of tourism risk perception becomes more mature, the current factor identification of tourism risk perception has covered equipment, finance, physical, psychological, satisfaction, social, time, political [17] and cultural differences and barriers [18] and other perception factors, providing a relatively complete measurement dimension for studying the relationship between tourism risk perception and decision-making.
In short, perceived risk theory has become one of the core theories for exploring tourists’ travel decisions, focusing on explaining the interaction between tourists and destinations and effectively predicting tourists’ travel attitudes and choice behaviors to tourist destinations when they encounter a major crisis. The theory also provides theoretical support for destination risk management.

2.2. The Impact of Place Image Depicted in Anti-Epidemic Music Videos on Tourism Risk Perception

Place image is usually defined as the sum of beliefs, ideas, and impressions held by an individual concerning a particular place [19]. It is a psychological impression based on a large amount of informational choice [20]. In the field of destination marketing, exploring the emotional needs of tourists in time and in an accurate manner and disseminating unique destination images that can touch the souls of tourists are conducive to strengthening tourists’ perceived gains and weakening risk perception [21]. Snepenger and Snepenger (1994) [22] found that delivering more information through the media can effectively reduce consumers’ risk perception. Qu, Kim, and Im (2011) [23] believed that spreading positive destination images could help reduce tourists’ concerns about potential risks. Gursoy and Gavcar (2003) [24] found that risk perception promotes tourists’ understanding of travel destinations. Ke (2010) [25] believed that after the Wenchuan earthquake, the promotion video of the travel destination can increase the potential tourists’ understanding of the destination’s recovery status and guide the potential tourists to correctly understand the destination’s tourism environment, thereby reducing risk perception. Music videos with the theme of combating severe epidemics, especially music videos showing place images of epidemic areas, can increase destination awareness and arouse emotional resonance, thus effectively reducing tourism risk perception. Therefore, the study puts forward the following assumption:
Hypothesis 1 (H1).
Place image depicted in anti-epidemic music videos has a negative effect on tourism risk perception.

2.3. The Effect of Tourism Risk Perception on Place Attachment and Travel Intention during Severe Epidemics

Place attachment is an individual’s tendency to be emotionally close to a specific place, it is the emotional connection resulting from the interaction between a person and a place [26] and falls into the category of emotional attitudes [27]. Travel intention is the tendency of persons to judge their future tourism behaviors [28] and the willingness of tourists to participate in certain tourism activities [29]. Risk perception is based on the understanding of information in a specific situation and the assessment of external risks. It significantly affects the individual’s emotional attitude and behavioral tendency [24]. A large number of studies have shown that risk perception is the basis of individual attitude and behavior prediction [10,27]. Cox (1967) [30] studied the risk perception and the specific mechanisms of individual behavior patterns and decision-making behavior from the perspective of consumer behavior. Pidgeon, Hood, and Jones (1992) [31] explored the impact of risk perception on risk behavior by studying the relationship mechanism between risk assessment and management. Their empirical study result indicates that risk perception is a direct determinant of individual attitudes and decision-making behavior. Quintal et al. (2010) [2] proposed that the perceived risk affects the attitude of South Korean and Japanese tourists visiting Australia. Bonaiuto, Alves, De Dominicis, and Petruccelli (2016) [32] found that the perception of natural disaster risks (earthquakes, volcanoes, etc.) have a negative effect on place attachment. Xin-hui, Yao-feng, Jun-sheng, and Kun-fang (2016) [33] conducted research on residents in the two hardest-hit areas of the Wenchuan earthquake in China, confirming that perceived risk can negatively affect place attachment. Chen and Chang (2012) [34] proposed that the overall risk perception of tourists negatively affects travel intention to a significant extent. Dengming, Biao, Jiangying, Xuan, and Qiang (2020) [35] verified that the perceived risk of potential visitors to forest health has a significant negative impact on behavioral attitudes and intentions. The higher the potential tourists’ level of risk perception of a place, the less likely they are to choose to travel there [36]. Therefore, the study puts forward the following hypotheses:
Hypothesis 2 (H2).
Tourism risk perception has a negative effect on potential tourists’ place attachment in a severe epidemic.
Hypothesis 3 (H3).
Tourism risk perception has a negative effect on potential tourists’ travel intention in a severe epidemic.

2.4. Intermediary Role of Tourism Risk Perception

Tourism risk perception is of great significance for understanding tourism decision making [17], and it can be used as a transmitting intermediary to influence tourists’ attitudes and behaviors. Yuetiao, Qian, and Jiangchi (2019) [37] showed that negative public opinion has an effect on revisiting intention through the transmission effect of tourists’ safety perception. Larsen, Brun, and Ogaard (2009) [38] believed that the academic field should pay attention to the relationship between risk judgment and the emotional state by researching on the relationship between risk perception and tourist anxiety. Johnson and Tversky (1983) [39] studied tourism risk perception and coping behavior based on cognition and emotion. A positive destination image can help reduce tourists’ concerns about potential risks [23], while the negative image will increase tourists’ perception of travel risk and reduce their travel intention [40]. Lerner and Keltner (2001) [41] pointed out that positive emotions make people’s prediction of risks more optimistic, while negative emotions make people pessimistically estimate risks. Strong emotions have a significant impact on risk perception and form different decision-making behaviors [41,42]. Therefore, place image in a severe epidemic can have an impact on tourists’ emotional connections and decision-making behaviors through the intermediary role of risk perception. Therefore, the study puts forward the following assumptions:
Hypothesis 4 (H4).
Tourism risk perception is an intermediary between the place image depicted in anti-epidemic music videos and potential tourists’ place attachment.
Hypothesis 5 (H5).
Tourism risk perception serves as an intermediary between the place image depicted in anti-epidemic music videos and potential tourists’ travel intention.

2.5. Effect of Visiting History on Tourism Risk Perception in Severe Epidemics

Visiting history is an important factor affecting tourists’ behavior [43]. Liyun and Haiyan (2012) [44] drew upon that there is an obvious difference between the formation mechanism of first-time tourists and revisiting tourists. Konecnik and Ruzzier (2006) [45] found that the previous travel experience has a significant impact on the destination assessment of perception, image, quality, loyalty, and other dimensions. Travel experience will affect the perception of the destination’s image and value. Ultimately, it will affect the destination’s assessment and decision-making behavior [46,47]. Qingin and Chaowu (2019) [48] showed that tourism experience has a moderating effect on the relationship between hospitality and satisfaction. Xin-hui et al. (2016) [33] showed that “place dependence” is a core reason that the visiting experience affects the perception of supply, and it is also the main driving factor for revisiting behavior. Compared with the “new arrivals” of first-time visitors, repeat visitors who choose to “revisit old places” have more emotional factors. However, in severe epidemics, tourists with rich experiences can better identify the severity of the crisis, observe the impact of a severe epidemic [48], and buffer and enhance the emotional connection between tourists and places. From this, the study obtained Hypothesis 6:
Hypothesis 6a (H6a).
Visiting history has a moderating effect between tourism risk perception and place attachment.
Hypothesis 6b (H6b).
Visiting history has a moderating effect between tourism risk perception and travel intention.
Based on the above literature review and hypothesis, the conceptual model of this study is shown in Figure 1.

3. Research Design

3.1. Selection of Research Materials

There were dozens of anti-epidemic music videos that have been presented to the public since the outbreak of COVID-19. “Wuhan Ya” (Source: https://haokan.baidu.com/v?vid=12640396385345260724&pd=bjh&fr=bjhauthor&type=video), as one of the most widely-spread and well known Chinese anti-epidemic music video, was selected in this study as a test sample to study the place image depicted in anti-epidemic music videos. “Wuhan Ya” was created by 17 artists in Wuhan, Hubei, China, and was released on 27 January 2020. Then, it was broadcasted through China’s Official government media—China Central Television, and was widely spread. The iconic landscapes such as the Yangtze River Bridge, Jianghan Road, and Yellow Crane Tower were selected in the music video of “Wuhan Ya”. While conveying the mighty power of anti-epidemic approaches, the music video enabled the public to understand the unique place image of Wuhan and shows the charming natural landscape and cultural scenery of Wuhan.

3.2. Design of Measuring Scale

This research mainly used the existing mature scale as a measurement tool, and the items were measured by the Likert 7-point scoring method. The place image depicted in anti-epidemic music videos was measured with the scales of Lew (1987) [49], Russell (1980) [50], and Chen, Lai, Petrick, and Lin (2016) [51], and combining the music video pictures and barrages of “Wuhan Ya”, and extracts eight aspects: street scenes, urban landscapes, geographical landscapes, regional characteristics, full of love, full of power, good overall impression, and arouse longing. Tourism risk perception, according to the research of Kaplan et al. (1974) [13], is mainly measured from four aspects: physical risk, functional risk, psychological risk, and social risk. Place attachment, according to Williams and Roggenbuck (1989) [52], is mainly measured from six factors: “more desirable tourist destinations”, “tourism more intoxicating”, “better travel experience”, “know oneself”, “one of them”, “emotional connection”. Travel intention is mainly measured from three aspects: willingness to visit, willingness to recommend/talk and prior choice [53]. In addition, according to the research design, the visiting history of Wuhan was investigated. Basic demographic characteristics were also designed, including gender, age, education, income, and occupation.

3.3. Optimization of the Initial Questionnaires and Collection of Formal Data

In the questionnaire survey, the first participants were guided to watch the “Wuhan Ya” music video for at least 90 s, then they were measured on the items. The initial questionnaires were distributed through the Internet. A total of 111 questionnaires were collected, among which 107 questionnaires were valid. The effective recollecting rate was 96.4%. The survey excluded those who were born and raised in Wuhan or currently lived in Wuhan. The study used SPSS 22.0 to perform reliability test and exploratory factor analysis on the initial questionnaire. The reliability test results showed that the Cronbach’s α coefficients of the four dimensions of place image depicted in the anti-epidemic music videos, tourism risk perception, place attachment, and travel intention are 0.897, 0.825, 0.901, and 0.741. respectively, and the reliability scores were all greater than 0.7, demonstrating the questionnaire’s reliability. Then, an exploratory factor analysis of the preliminary questionnaire data was carried out. The KMO (Kaiser-Meyer-Olkin) value was 0.798, and the above five factors were successfully extracted, which explained 69.96% of the variance in the data. According to the results of the extraction of the common factors, in order to fit the place image conveyed by the music video of “Wuhan Ya”, the items with lower values of common factors were removed, and finally four factors measured by 18 items were obtained. The formal questionnaire was modified and designed based on that. The formal survey used the form of an online questionnaire during the period 23–31 March 2020. A total of 1184 questionnaires were collected, excluding questionnaires with a fill-in time of less than 120 s and a large number of questionnaires with obviously the same option chosen. Finally, 945 valid questionnaires were obtained with an effective recovery rate of 79.81%. The demographic characteristics of the sample are shown in Table 1. In the sample data, the proportion of male and female participants was relatively balanced, accounting for 47.62% and 52.38%, respectively; 82.33% of them were among 18–40 years old. This phenomenon was related to the young people’s willingness to pay attention to online information. Among the participants, 67.09% had a bachelor degree or above. This was in line with the reality that highly educated people might pay more attention to tourism activities and music videos. The income level distribution was relatively balanced. Moreover, 47.41% of the respondents had been to Wuhan and had a certain understanding of Wuhan. In general, the sample data were suitable for this study.

4. Data Analysis and Model Checking

4.1. Measurement Model Checking

4.1.1. Descriptive Statistics and Factor Analysis

This study first performed a statistical analysis of the mean (M) and standard deviation (SD) of each variable. The results showed that the degree of respondents agreeing with the place image depicted in anti-epidemic music videos in a severe epidemic was (M = 5.72, SD = 1.277); The approval degree of tourism risk perception was (M = 4.48, SD = 1.517), and the approval degree of place attachment and travel intention were (M = 3.52, SD = 1.700), (M = 3.72, SD = 1.738). Generally speaking, the respondents’ agreement with the place image depicted in anti-epidemic music videos was the strongest, and their agreement with the tourism risk perception was relatively high, and their agreement with the place attachment and travel intention was relatively low.
The study conducted a factor analysis on each dimension. The results showed that the Cronbach’s α coefficients of all variables reached the 0.7 level, and the combined reliability was also above 0.7, indicating that the questionnaire had good reliability. According to the CFA (Confirmatory Factor Analysis) validity test results, each CFA factor load was greater than 0.5, and the latent variable average variation extraction (AVE) was greater than 0.5, indicating that the measurement items in this article had a high convergence validity (see Table 2).

4.1.2. Correlation and Differentiation Validity Test

The correlation analysis of the variables is shown in Table 3. There was a strong correlation between the main variables. The study continued to calculate the square root of AVE, and further verified the distinguishing validity of the variable by comparing the correlation coefficient between the AVE and the variable. The results showed that the square root of AVE between any two variables in this study was higher than the correlation coefficient between the two, so the discrimination validity of the data was better. In general, the questionnaire data had high reliability and validity.

4.2. Hypothesis Testing

4.2.1. The Direct Effect Testing

The hierarchical regression analysis method was used to test the direct effect. The regression analysis showed that under the 95% confidence interval, the linear relationship and coefficients of each regression equation in the F and t tests were both significant (Table 4). The place image depicted in the anti-epidemic music videos in severe epidemics had a significant negative impact on tourism risk perception (β = −0.359, p < 0.001). Hypothesis H1 was verified. The tourism risk perception had a significant negative effect on place attachment (β = −0.479, p < 0.001), hypothesis H2 was verified. The tourism risk perception had a significant negative effect on travel intention (β = −0.571, p < 0.001), and hypothesis H3 was verified. Therefore, hypotheses H1, H2 and H3 were all verified.

4.2.2. The Intermediary Effect Testing

This study mainly used the SPSS PROCESS macro program for the intermediary effect test, using the Bootstrap test method with a sampling number of 5000 and a deviation corrected by a 95% confidence interval. The intermediary effect testing took tourism risk perception as an intermediary variable (M) and examined the influence of independent variable (X) of the place image depicted in anti-epidemic music videos on dependent variable with place attachment (Y1) and travel intention (Y2).
According to the model’s total direct and indirect effects (see Table 5 and Figure 2), the results indicated that the total effect between the place image depicted in anti-epidemic music videos and place attachment was 0.405 (p < 0.001), the direct effect was 0.265 (p < 0.001), and the total indirect effect was 0.140 (p < 0.001). It showed that tourism risk perception had a partial intermediary role between the place image depicted in anti-epidemic music videos and place attachment. Therefore, hypothesis H4 was verified. The total effect between the place image depicted in anti-epidemic music videos and travel intention was 0.379 (p < 0.001), the direct effect was 0.203 (p < 0.001), and the total indirect effect was 0.175 (p < 0.001). Thus, the risk perception had a partial intermediary role between the place image depicted in anti-epidemic music videos and travel intention. Hypothesis H5 was verified. The overall model testing results are shown in Figure 3:

4.2.3. Moderating Effect Testing

According to current theoretical studies, if the independent variable is a continuous variable and the adjustment variable is a categorical variable, then the group regression method should be used to verify the regulatory effect, rather than the usual multiplication of the independent variable and the regulated variable. In this study, the independent variable of tourism risk perception was a continuous variable, and the adjustment variable of visiting history was a categorical variable, so a grouped regression method was used to perform the regression analysis on the two sets of samples, one with visiting history and the other without, to test the effect of tourism risk perception on place attachment and travel intention in each set of samples.
Table 6 showed that after the tourism risk perception was added to the regression equation, the explanatory role of model 5 on tourism risk perception in the group without visiting history increased by 13.0% compared with model 4 (ΔF = 18.190, p < 0.001); while the explanatory role of model 7 on tourism risk perception in the group with visiting history increased by 27.9% compared with model 6 (ΔF = 29.316, p < 0.001). The standardized regression coefficients of tourism risk perception on place attachment were 0.391 (p < 0.001) for the sample group with visiting history and 0.611 (p < 0.001) for the group without. In addition, the variance ability of explaining tourism risk perception of the no experience group (17.7%) was smaller than that of the visiting history group (32.6%). The regression testing result showed that the R2, ΔR2 and F values significantly increased after tourism risk perception was added to the basic model, indicating that the model was ideal. The impact coefficient of tourism risk perception indicated that visiting history had a non-linear adjustment effect on the relationship structure of tourism risk perception to place attachment. Tourism risk perception of the without visiting history group had less influence on place attachment, while that of the group with visiting history had greater influence on place attachment. Therefore, H6a was verified.
It could be shown from Table 7 that, in the group without visiting history, after the tourism risk perception was added to the regression equation, model 9’s capacity of explaining the tourism risk perception increased by 14.4% compared with model 8 (ΔF = 27.123, p < 0.001); while in the group with visiting history, after the tourism risk perception was added to the regression equation, model 11’s capacity of explaining tourism risk perception increased by 31.8% compared to model 10 (ΔF = 33.793, p < 0.001). According to the revisiting testing result, the standardized regression coefficients of tourism risk perception on travel intention for the group with and without a visiting history were 0.498 (p < 0.001) and 0.680 (p < 0.001) respectively. In addition, the variance explanation role of tourism risk perception without visiting history group (18.7%) was smaller than that with the visiting history group (33.8%). The regression test showed that the R2, ΔR2, and F values of the basic model significantly increased after the tourism risk perception was added, indicating that the model was ideal. The influence coefficient of tourism risk perception indicated that visiting history non-linearly regulated the effect of tourism risk perception and travel intention. The travel risk perception of the none-visiting-experience group had less influence on travel intention, and that of the visiting-experience group had the greater influence on the travel intention. Therefore, H6b was verified.
Therefore, through the two sets of samples—without visiting history and with visiting history —testing the relationship effects of tourism risk perception on place attachment and travel intention, the regulatory effects of visiting history were established. Hypothesis H6 was supported.

5. Research Conclusions and Discussions

5.1. Research Conclusions

In the context of the COVID-19 outbreak, based on the perceived risk theory, this study takes the perspective of the “person–place” relationship to discuss the mechanism of potential tourists’ risk perception in the severe epidemics. The study also discusses the antecedent effect of the place image depicted in anti-epidemic music videos on tourism risk perception, the effect of tourism risk perception on the potential tourists’ place attachment and travel intention, and the moderating effect of visiting history. It enriches the theoretical content of risk perception, expands the theoretical sources of tourist decision making, and promotes the application of music videos in tourism research. The conclusion of this study is as follows.
First, in severe epidemics, the place image depicted in anti-epidemic music videos has a significant negative effect on tourism risk perception (β = −0.359, p < 0.001), and tourism risk perception has a significant negative effect on potential tourists’ place attachment (β = −0.479, p < 0.001). Tourism risk perception has a significant negative effect on the potential tourists’ travel intention (β = −0.571, p < 0.001), where the potential tourists’ risk perception has a greater effect on place attachment than travel intentions. This conclusion confirms that place image depicted in anti-epidemic music videos helps to reduce tourism risk perception in severe epidemic. The conclusion of the study is consistent with the results of Qu et al. (2011) [23] that spreading a positive travel destination image can help reduce tourists’ potential risk concerns. In severe epidemics, the lower the tourism risk perception, the stronger the potential tourists’ place attachment and travel intention. The conclusion of the study is consistent with that of Xin-hui et al. (2016) [33], Zheng, Zhang, Guo, Zhang, and Qian (2019) [54], Bonaiuto et al. (2016) [32], Tavitiyaman and Qu (2013) [55] and Dengming et al. (2020) [35]: the higher the tourism risk perception, the lower the tourists’ place attachment and travel intention. The conclusion of this study confirms that place image based on anti-epidemic music videos has a strong infectivity and influence in severe epidemics, which provides a new perspective for music video research, and also verifies that tourism risk perception greatly influences tourists’ attitudes and behaviors, and provides theoretical support for the risk management and marketing of tourism destinations during epidemics.
Second, in severe epidemics, tourism risk perception has a significant partial intermediary effect between the place image depicted in anti-epidemic music videos and potential tourists’ place attachment (β = 0.140, p < 0.001), and tourism risk perception in anti-epidemic music videos has a significant partial intermediary effect between the potential tourists’ place image and travel intention (β = 0.175, p < 0.001). The conclusion of this study reversely echoes the conclusion of Court and Lupton (1997) [56] that the negative image of tourist destinations improves tourists’ risk perception and reduces their travel intention. The research conclusion analyzes the intermediary transmission effect of tourism risk perception, verifies the importance of tourism risk perception in tourists’ decision theory in severe epidemics, and provides theoretical support for tourism destination risk management.
Third, in severe epidemics, potential tourists without previous visiting history (β = 0.391, p < 0.001) and with visiting history (β = 0.611, p < 0.001) function as a regulatory for tourism risk perception and place attachment. Specifically, the tourism risk perception of the group without visiting history had less influence on place attachment, and vice versa. Potential tourists without visiting history (β = 0.498, p < 0.001) and with visiting history (β = 0.680, p < 0.001) serve as an intermediary between tourism risk perception and travel intention. Specifically, tourism risk perception of the group without visiting history had less influence on travel intention, and vice versa. The conclusion of the study is consistent with the results of Lew (1987) [49] and Xin-hui et al. (2016) [33]. This result confirms that visiting history balances the impact of tourism risk perception on place attachment and travel intention, that is, potential tourists who have visiting history can pay more attention to emergencies at the site and make a more comprehensive evaluation of the risk, thereby reducing the impact of the epidemic on place attachments, reducing the impact of the crisis on the willingness to travel, and providing the theoretical support of classified marketing and classified risk management for tourist destinations in severe epidemics.
In sum, this study analyzes the relationship between the place image depicted in anti-epidemic music videos, tourism risk perception, place attachment, and travel intention, and discusses the mechanism of tourism risk perception in severe epidemics, which enriches the theoretical content of perceived risk, and expands the theoretical source of tourism decision making, and promotes the application of music videos in tourism research. In short, this study explores the mechanism of potential tourists’ risk perception under the epidemic situation from the perspective of the “person–place” relationship, enriching the interdisciplinary research of geography, management, and tourism.

5.2. Research Inspiration

This novel coronavirus pneumonia epidemic has a huge impact on the world’s tourism industry, along with new challenges to tourism development. Because risk factors have characteristics such as suddenness, cognitive bias, and difficulty in recovering [57], the study of the mechanism of tourism risk perception provides an explanatory basis for understanding the attitudes and behaviors of tourists in response to risks, and provides a theoretical basis for formulating and perfecting the management strategies of tourism risks [10] Combining theoretical findings, this study proposes the following risk management countermeasures for destinations.
First, in severe epidemics, comprehensive management and control of the destination’s tourism risks should be strengthened to reduce the potential tourists’ risk perception of destinations. On the one hand, destinations should carry out tourism risk management from the perspective of risk factors, risk levels, possible impact areas, starting time, and precautionary measures to comprehensively reduce the potential tourists’ destination risk perception and to create a safe and reliable tourism environment after the epidemics and to promote the tourists’ travel intention in the future. On the other hand, destinations should ensure the tourists with safety and security by reducing the potential tourists’ risk perception of physical, functional, social, psychological risks, and so on, thereby enhancing the safety perception effectiveness of potential tourists and providing a security guarantee for the sustainable development of tourism after an epidemic.
Second, in severe epidemics, destinations should make full use of the cultural media and actively implant and spread place images to reduce tourism risk perception and enhance place attachment and the travel intention of the destinations. Destination managers can create cultural products such as music themes, micro-films, literary works, and other cultural products that mainly display place image. Various communication channels such as news portals, social media, video sites, and public welfare platforms should be established to stimulate through repeated cycles for multiple senses of potential tourists such as hearing and vision, and continue to conduct in-depth “idea exchange” with potential tourists through “music video scenes” to enhance the potential tourists’ sensory experience of place images, resonate and associate, and form a unique place impression to help the recovery and development of the destination after the epidemic outbreak. In addition, when facing severe epidemics, destinations should focus on demonstrating high-quality tourism resources, improving tourism facilities and services, and presenting potential tourists with a fully functional destination environment. Appealing cultural works allow potential tourists to understand themselves through destination travel after the epidemic and strengthen the emotional connection with the destination, thereby enhancing the potential tourists’ emotional attachment to the destination and promoting travel intention.
Third, in severe epidemics, destinations should classify tourists based on potential tourists’ visiting history, especially paying more attention to tourists with visiting history. Through large activities such as exhibitions, festivals, and sports events, destinations should display regional characteristics and a cultural scenery of destinations in a comprehensive, multi-view and multi-sensory manner, thus enabling more potential tourists to visit Wuhan and actively promoting place images. At the same time, the destinations should pay attention to the effective role of tourists’ visiting history on tourism risk perception. In the destination marketing process, tourists should be classified into different groups based on the visiting history of tourists, carry out classified marketing and tender marketing from the perspective of the emotional connection of “person–place” interaction. Particularly, in the face of potential revisitors who can objectively regard the epidemic at the destination, it is necessary to strengthen tourists’ place attachment by enhancing the symbolic meaning of signs, tourism marketing copywriting, and service experience interface, thereby reducing tourism risk perception to promote travel intention and achieve the precise marketing of tourist destinations in the context of the epidemic crisis.

5.3. Deficiency and Forward

Taking the novel coronavirus pneumonia epidemic as the background and building upon the perceptual risk theory, this study explores the mechanism of potential tourists’ risk perception in severe epidemics from the perspective of “person–place” relationship. However, there are certain limitations. First of all, this research adopts a network questionnaire for data collection, which should be further verified by in-field research in future practice. Secondly, due to the close connection between risk and uncertainty, risk perception is subjective and complex [10], and tourism risk perception is susceptible to differences in many factors, such as individuals, time, and places, so it may change at any time and has a certain dynamic; the practical application of the research results still requires more empirical testing, and its application in other crisis situations still needs further verification. In future research, we should further expand the scope of research, explore diversified media or cultural products to reduce tourism risk perception, and provide corresponding theoretical support for the refined classification of multiple tourism marketing; at the same time, we should also study the difference in the decision-making of risk perceptions to place attachment and travel intention with tourist groups with different attributes, and help to formulate more refined tourism risk management and marketing strategies.

Author Contributions

Conceptualization, B.W., F.W.; formal analysis, F.W., T.X. and T.W.; writing—original draft, F.W., T.X. and T.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by general project of National Social Science Fund (18BGL155).

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 12 05454 g001 550
Figure 1. Conceptual model.
Figure 1. Conceptual model.
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Figure 2. Intermediary effect testing of the tourism risk perception. Note: *** means p < 0.001.
Figure 2. Intermediary effect testing of the tourism risk perception. Note: *** means p < 0.001.
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Figure 3. Overall model testing. Note: *** means p < 0.001.
Figure 3. Overall model testing. Note: *** means p < 0.001.
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Table
Table 1. Sample demographic characteristics.
Table 1. Sample demographic characteristics.
DimensionFrequencyPercentage% DimensionFrequencyPercentage%
AgeUnder 18 years old444.66GenderMale45047.62
18–25 years old24626.03Female49552.38
26–30 years old30932.70Average income monthlyLess than 200021322.54
31–40 years old22323.602000–500024125.50
41–50 years old10511.115000–10,00029831.53
51–60 years old161.6910,000–20,00015115.98
>60 years old20.21More than 20,000424.44
EducationHigh school and below717.51Visiting history of WuhanNo49752.59
College24025.401–3 times29130.79
Undergraduate37639.794 or more tours697.30
Master degree and above25827.30Used to be a long-term resident889.31
Table
Table 2. Descriptive statistics and confirmatory factor analysis.
Table 2. Descriptive statistics and confirmatory factor analysis.
DimensionMeasurement ItemMeanReliabilityValidity
Cronbach’s αCombined Reliability(CR)Factor LoadingAverage Variation Extraction (AVE)
Place image depicted in anti-epidemic music videosStreet scene5.720.9140.86310.6540.5594
Urban landscape5.790.689
Full of love5.670.794
Full of strength5.710.805
Overall impression is good5.710.785
Tourism risk perceptionPersonal safety is guaranteed4.830.9180.88160.7830.6510
The event environment is very safe4.790.861
Without any safety concerns4.230.815
Others consider it is safe4.090.765
Place attachmentMore desirable tourist destination3.540.9460.90850.8020.6239
Travel scenery is more intoxicating3.350.842
Better travel experience3.360.817
Self-understanding3.630.757
Sense of belonging3.590.788
Emotional connection3.640.728
Travel intentionWant to travel4.070.9080.88250.8090.7147
Recommend to others3.610.858
Prior choice3.500.868
Table
Table 3. Correlation and discriminant validity analysis of the main variables.
Table 3. Correlation and discriminant validity analysis of the main variables.
Latent VariablePlace Image Depicted in Anti-Epidemic Music VideosTourism Risk PerceptionPlace AttachmentTravel Intention
Place image depicted in anti-epidemic music videos0.748
Tourism risk perception0.268 **0.807
Place attachment0.296 **0.434 **0.790
Travel intention0.262 **0.487 **0.781 **0.845
Note: The bold numbers on the diagonal are the square root of the AVE; ** means p < 0.01, * means p < 0.05.
Table
Table 4. Direct effect verification results.
Table 4. Direct effect verification results.
Model 1Model 2Model 3Hypothesis Testing
Independent VariableDependent Variable: Tourism Risk PerceptionDependent Variable: Place AttachmentDependent Variable: Travel Intention
βSETβSETβSET
Constant4.954 ***0.27018.3525.089 ***0.29617.2224.408 ***0.31813.878/
Gender−0.285 **0.093−3.066−0.299 **0.102−2.936−0.216 *0.109−1.971/
Age−0.0330.051−0.6500.0020.0560.035−0.0690.060−1.148/
Education0.0110.0610.182−0.334 ***0.067−4.966−0.0770.072−1.060/
income0.0230.0450.518−0.0040.049−0.0790.0510.0530.959/
Place image−0.359 ***0.039−9.1560.400 ***0.0439.3410.393 ***0.0468.480H1
Tourism risk perception———−0.479 ***0.032−14.907−0.571 ***0.034−16.989H2/H3
Place attachment——————0.845 ***0.02239.021/
R2 = 0.011, p= 0.000R2 = 0.035, p = 0.000R2 = 0.006, p = 0.000/
Note: * means p < 0.05, ** means p < 0.01, *** means p < 0.001.
Table
Table 5. The bootstrapping analysis results with tourism risk perception as the mediator.
Table 5. The bootstrapping analysis results with tourism risk perception as the mediator.
EffectHypothetical DirectionCoefficientSETP95% BootCI
LLCI (Lower limit of confidence interval)ULCI (Upper limit of confidence interval)
Total effectX on Y10.4050.0459.0960.0000.3180.493
Direct effectX on Y10.2650.0455.9390.0000.1780.353
Indirect effectH4: X→M→Y10.1400.022//0.0990.187
Total effectX on Y20.3790.0477.9940.0000.2860.472
Direct effectX on Y20.2030.0474.3390.0000.1120.297
Indirect effectH5: X→M→Y20.1750.027//0.1210.228
Note: N = 945. β is the regression coefficient. X is place image depicted in anti-epidemic music videos, M is tourism risk perception, Y1 is place attachment, Y2 is travel intention.
Table
Table 6. Moderating effects of visiting history on tourism risk perception and place attachment.
Table 6. Moderating effects of visiting history on tourism risk perception and place attachment.
VariableWithout Visiting History (N = 497)With Visiting History (N = 448)
Dependent Variable: Place AttachmentDependent Variable: Place Attachment
Model 4Model 5Model 6Model 7
Constant4.746 *** (0.357)2.812 *** (0.387)5.941 *** (0.576)2.888 *** (0.548)
Gender−0.023 (0.127)0.075 (0.119)−0.622 *** (0.167)−0.424 ** (0.142)
Age0.037 (0.074)0.047 (0.068)−0.057 (0.087)−0.030 (0.073)
Education−0.445 *** (0.081)−0.435 *** (0.075)−0.287 * (0.133)−0.318 ** (0.112)
Income0.007 (0.066)−0.009 (0.061)−0.062 (0.076)−0.061 (0.064)
Tourism risk perception 0.391 ***(0.040) 0.611 *** (0.051)
R20.0540.1840.0580.336
Adjusted R20.0470.1770.0470.326
F-statistic8.422 ***26.612 ***5.236 ***34.552 ***
Prob (F-statistic)0.0000.0000.0000.000
Note: * means p < 0.05, ** means p < 0.01, *** means p < 0.001. The numbers in brackets are the standard error values.
Table
Table 7. Moderating effects of visiting history on tourism risk perception and travel intention.
Table 7. Moderating effects of visiting history on tourism risk perception and travel intention.
VariableWithout Visiting History (N = 497)With Visiting History (N = 448)
Dependent Variable: Travel IntentionDependent Variable: Travel Intention
Model 8Model 9Model 10Model 11
Constant4.123 *** (0.390)1.660 *** (0.411)5.591 *** (0.609)2.192 *** (0.565)
Gender−0.024 (0.139)0.101 (0.126)−0.430 * (0.177)−0.210 (0.146)
Age−0.117 (0.080)−0.104 (0.073)−0.032 (0.092)−0.002 (0.076)
Education−0.130 (0.088)−0.117 (0.079)−0.196 (0.141)−0.231 * (0.116)
Income0.126 (0.072)0.106 (0.065)−0.088 (0.080)−0.087 (0.066)
Tourism risk perception 0.498 *** (0.043) 0.680 *** (0.053)
R20.0500.1940.0300.348
Adjusted R20.0020.1870.0190.338
F-statistic1.326 ***28.449 ***2.645 **36.438 ***
Prob (F-statistic)0.0000.0000.0000.000
Note: * means p < 0.05, ** means p < 0.01, *** means p < 0.001. The numbers in brackets are the standard error values.

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Wang, F.; Xue, T.; Wang, T.; Wu, B. The Mechanism of Tourism Risk Perception in Severe Epidemic—The Antecedent Effect of Place Image Depicted in Anti-Epidemic Music Videos and the Moderating Effect of Visiting History. Sustainability 2020, 12, 5454. https://0-doi-org.brum.beds.ac.uk/10.3390/su12135454

AMA Style

Wang F, Xue T, Wang T, Wu B. The Mechanism of Tourism Risk Perception in Severe Epidemic—The Antecedent Effect of Place Image Depicted in Anti-Epidemic Music Videos and the Moderating Effect of Visiting History. Sustainability. 2020; 12(13):5454. https://0-doi-org.brum.beds.ac.uk/10.3390/su12135454

Chicago/Turabian Style

Wang, Fang, Tao Xue, Ting Wang, and Bihu Wu. 2020. "The Mechanism of Tourism Risk Perception in Severe Epidemic—The Antecedent Effect of Place Image Depicted in Anti-Epidemic Music Videos and the Moderating Effect of Visiting History" Sustainability 12, no. 13: 5454. https://0-doi-org.brum.beds.ac.uk/10.3390/su12135454

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