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Article

Emotional State, Psychological Resilience, and Travel Intention to National Forest Park during COVID-19

by
Lisheng Weng
1,
Yawen Wu
1,
Guang Han
1,
Huifang Liu
2 and
Feng Cui
1,*
1
College of Humanities & Social Development, Nanjing Agricultural University, Nanjing 210095, China
2
College of Business Administration, Xinjiang University of Science & Technology, Korla 841000, China
*
Author to whom correspondence should be addressed.
Forests 2022, 13(5), 750; https://doi.org/10.3390/f13050750
Submission received: 15 April 2022 / Revised: 11 May 2022 / Accepted: 11 May 2022 / Published: 12 May 2022
(This article belongs to the Special Issue Nature-Based Tourism and Nature Conservation Activation by Tourism)
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Abstract

:
The outbreak of the COVID-19 pandemic has impacted the tourism industry worldwide. This study examines the relationships among potential tourists’ emotional states, psychological resilience, and their travel intention to a national forest park in the context of COVID-19. It also investigates the moderating effect of gender. Kanas National Forest Park on the northwestern border of China was chosen as the research case. The survey questionnaires were administered both online and offline to collect data. A total of 492 valid questionnaires were collected (263 from online and 229 from offline) and analyzed in this study. Results demonstrate that visitors’ positive emotions have significant positive effects on their psychological resilience and travel intention. Yet, visitors’ negative emotions have significant negative effects on psychological resilience and travel intention. Moreover, psychological resilience partially mediates the relationship between emotional state and travel intention, indicating that visitors’ positive emotion and negative emotion can not only directly affect travel intention, but also indirectly affect travel intention through psychological resilience. The results of moderating effect analysis indicate that men and women are found to have differences in the experience of emotion, and women are more advised to foster positive emotions and psychological resilience. Visitors are advised to advocate more mutual encouragement, and tourism practitioners are recommended to provide tailored services to reduce travel anxiety. Findings provide implications on emotional regulation for tourists and crisis management strategies for nature-based tourism destinations.

1. Introduction

The global COVID-19 outbreak in 2020 jeopardized the entire tourism industry, with a significant volume of tourists reducing or even canceling their travel plans [1]. Under the constraints of the global pandemic at home, people may experience different emotions. According to the cognitive evaluation theory, emotion is the response of individuals to an environment that they perceive as harmful or beneficial [2]. The cognitive evaluation theory is a psychology theory that attempts to explain how intrinsic emotion and motivation is affected by extrinsic environment [3]. Based on this theory, potential tourists may develop positive emotion and motivation, and are more likely to participate in travel activity if they perceive a safe environment [4]. Generally, emotions can be split into positive emotions and negative emotions [5]. In the face of the pandemic, people with positive emotions may feel they can work from home in accordance with a more flexible schedule and have more time to take care of their families. In contrast, those with negative emotions might be anxious about the risks of being infected by the virus and struck by its complications. Such negative emotions can easily cause mental health issues such as anxiety, stress, fear, sadness, and depression [6,7]. These issues can be addressed by enhancing individuals’ psychological resilience.
Psychological resilience is defined as a person’s ability to adjust, bounce back, and even thrive in the face of change or adversity [8]. Previous tourism studies have shown that in-depth examinations of emotional processes of visitors’ experiences of adversity are crucial for comprehensively understanding the development mechanism of psychological resilience [9,10,11]. Moreover, the stimulus-organism-response (SOR) theory proposed by Mehrabian and Russell (1974) provides an interpretive perspective for understanding how external stimuli affect people’s psychological processing, responses, and behaviors [12]. Stimulus refers to the external factors that cause changes in individuals’ internal state [13]. Organism delineates the internal experiences of individuals’ information processing and emotional state [13,14]. Response is a behavioral result that represents people’s final actions in response to a certain stimulus [13,14]. The SOR theory has been widely employed to investigate the relationship between inputs (stimulus), processes (organism), and outputs (response) [14,15]. Regarding tourism, however, existing studies primarily focus on the influence of the COVID-19 pandemic (stimulus) on the tourism industry from a macro level [16,17,18], and investigations into the influences of potential tourists’ emotional states on their psychological resilience (organism) and travel intention (response) from the micro-level remain scarce.
In addition, it is worth noting that gender may be a salient factor differentiating emotional experience [19,20]. A large number of studies have found that women are more likely than men to experience stronger negative emotions in the face of adversity [21,22]. To that end, the level of psychological resilience and travel intentions between male and female tourists may also have certain differences. However, the intricate relationships among potential tourists’ emotional state, gender, psychological resilience, and travel intention have not been fully understood.
The goal of this study is to fill in the research gaps. Specifically, the objectives of this study are as follows: (1) Exploring the relationships among potential tourists’ emotional states, psychological resilience, and their travel intention in the context of COVID-19; and (2) examining the moderating effect of gender in the above-mentioned influence relationship. During the pandemic, tourists tend to go to natural places with lower population density. Nature-based tourism destinations (e.g., National Forest Park) have become one of the best choices for tourists’ leisure travel and outdoor recreation [13]. Thus, a national forest park was chosen as the research case for this study. Findings of the present study can provide theoretical implications to tourism literature on tourists’ emotion, psychology, and behavior, and offer guidance for nature-based tourism destinations to effectively manage crises and promote more sustainable tourism development.

2. Literature Review and Hypotheses Development

2.1. The Need for Nature-Based Tourism during COVID-19

Nature-based tourism is composed of various geographical environments and generally involves excursions to national forest parks and wilderness areas [23,24,25,26,27,28]. In recent years, as the global demand for nature-based tourism has been increasing, nature-based tourism has shown a trend of prosperity. Especially, the COVID-19 outbreak in 2020 further boosted the demand for nature-based tourism and people developed a stronger desire to be close to nature [29]. According to mobile tracking data from Oslo, the capital of Norway, outdoor recreation increased by 291% during the COVID-19 lockdown [30]. Meanwhile, Swedish national parks experienced a sharp increase in visitor numbers in 2020 even before the peak season, some of which were as high as 75% [31].
The experience of nature-based tourism plays an irreplaceable role in maintaining people’s physical and mental health [21,22,23]. By traveling in a natural environment, people can improve their physical state, reduce stress, and relieve mental fatigue. Wilson (1984) argues that people have an innate need to connect with nature, and meeting that need would improve people’s happiness and bring certain positive effects [32]. Ulrich et al. (1991) suggest that people’s exposure to nature could reduce physical and psychological stress and thus improve well-being [33]. As tourism in natural environments becomes increasingly popular during COVID-19, the relationships among people’s emotional states, psychological resilience, and their travel intention to natural destination (e.g., national forest park) require further attention.

2.2. The Relationship among Emotional States, Psychological Resilience and Travel Intention

Emotion is a general term for a series of subjective cognitive experiences. According to the cognitive-evaluation theory, emotion is the response of individuals to an environment that they perceive as harmful or beneficial [2]. Thus, individuals may experience different emotional states. Generally, emotion can be divided into positive emotion and negative emotion [5]. Positive emotion is a temporary reaction of pleasure brought by something of personal significance [34]. It has positive psychological characteristics such as happiness, enthusiasm, and friendliness [34]. When the external environment is meaningful to the individual, the individual usually produces the subjective experience of pleasure accordingly. Conversely, negative emotion refers to the sentiments that are unpleasant and destructive in response to external or internal influences [35]. Negative emotion usually leads to human behaviors that are not conducive to continued work or normal thinking [35]. It has negative psychological characteristics such as sadness, frustration, anxiety, and fear [35].
Under the constraints of the pandemic at home, the interruption of travel plans, a sense of crisis, and other factors can easily cause mental health problems such as anxiety, stress, and depression [6,7]. Psychological resilience is critical for people to adjust their mental state, recover from stress and depression, and even thrive during this challenging time [8,36]. Troy and Mauss (2011) propose that emotion regulation, as a protective factor, is beneficial for individuals to acquire psychological resilience, especially in stressful situations [37]. Positive emotions may improve the ability to cope with stress and adversity by expanding and building the individual’s psychological, social, and physiological resources [38]. Positive emotion is a significant feature of individuals with physiological mental resilience [39,40,41]. Fredrickson et al. (2008) also support this point of view and assert that positive emotions can help individuals gain psychological resilience after stress [38].
If a person cannot effectively detract attention from the negatives of themselves or the environment, the resulting negative emotions become stronger and more persistent, and psychological resilience becomes more difficult to achieve. People may have different emotions in the face of COVID-19, which in turn tend to have different effects on psychological resilience. Thus, the first two hypotheses are proposed below:
Hypothesis 1 (H1).
Visitors’ positive emotion has a significant positive effect on psychological resilience.
Hypothesis 2 (H2).
Visitors’ negative emotion has a significant negative effect on psychological resilience.
In this study, travel intention refers to the willingness of the visitor to travel to a national forest park in the future [42,43]. The willingness of visitors to support a destination is increasingly becoming the key to the destination’s success in its COVID-19 recovery strategy [44]. Emotion provides motivation for decision-making, which enables visitors to make behavioral choices consistent with their emotional attributes. Emotional experiences have been identified as important drivers and determinants of visitor travel intentions in tourism literature [45]. Positive emotion is an important factor affecting visitors’ travel intention. Visitors who have positive emotions are more likely to have the intention to travel and recommend the destination [46]. This argument is also supported by the research of Jang et al. (2009) [47]. They argue that positive affect has a significant impact on future travel intention [47]. Meanwhile, negative emotions may also have a significant impact on visitors’ decision-making, which can organize and stimulate tourist decision-making. If a visitor awakens negative emotions such as COVID-19 fear and travel anxiety, it may have negative influences on travel intention [48]. For example, Luo and Lam (2020) support this point with the view that fear of COVID-19, travel anxiety, and risk attitude negatively influence visitors’ travel intention [48].
The level of psychological resilience determines the subject’s dynamic regulation and adaptability to the external environment [49]. Rutter (2000) argues that an individual who has a stronger ability to control the external environment can cope with difficulties more effectively [50]. Strong psychological resilience can help people accept, process, and adapt to the changes that individuals need to experience throughout their lives, so as to achieve social adaptation and make positive behavioral choices [51]. Thus, visitors’ emotional state has significant effects on psychological resilience, and psychological resilience can further affect visitors’ travel intention. Based on the above discussion, the third to sixth hypotheses are proposed as follows:
Hypothesis 3 (H3).
Visitors’ positive emotion has a significant positive effect on travel intention.
Hypothesis 4 (H4).
Visitors’ negative emotion has a significant negative effect on travel intention.
Hypothesis 5 (H5).
Visitors’ psychological resilience has a significant positive effect on travel intention.
Hypothesis 6 (H6a).
Visitors’ psychological resilience mediates the relationship between positive emotion and travel intention.
Hypothesis 6 (H6b).
Visitors’ psychological resilience mediates the relationship between negative emotion and travel intention.

2.3. The Moderating Effect of Gender

Studies of the relationship between gender and emotion have found that men and women differ in the experience and expression of emotion. Women generally experience emotions more frequently and intensely than men [52,53]. In addition, women are more likely than men to report negative emotions such as fear, anxiety, and sadness [54]. In the face of COVID-19, men and women may react differently and have different emotions. As discussed earlier, positive emotion may improve the ability to cope with external pressure and tends to have positive influences on psychological resilience and travel intention. Gender may moderate the relationship between positive emotion and psychological resilience and travel intention. Therefore, using the above evidence, it is logical to propose the last two hypotheses:
Hypothesis 7 (H7a).
Gender has a moderating effect on the relationship between positive emotion and psychological resilience.
Hypothesis 7 (H7b).
Gender has a moderating effect on the relationship between positive emotion and travel intention.
The conceptual framework with seven hypotheses of this study is presented in Figure 1 as follows:

3. Materials and Methods

3.1. Description of the Research Case

Kanas National Forest Park (hereinafter referred to as Kanas) was chosen as the research case because it is well known for its natural landscape sceneries, and it attracts a large number of national and international visitors each year. The area is vast and sparsely populated, and most tourism activities are outdoors, which can bring a certain sense of safety in the context of COVID-19. Kanas is located on the northwesternmost border of China (see Figure 2). It covers a total area of 10,030 km2. Affected by the Quaternary glaciers and the climate of the Arctic Ocean, forests, grasslands, and meadows are vertically distributed in Kanas, resulting in special natural landscapes and vegetation types. In 2018, Kanas received nearly 6.8 million tourists, with a total tourism income of $0.63 billion. Even affected by the COVID-19, Kanas’ tourism industry recovered quickly due to good control by the Chinese government.

3.2. Survey Instrument Development

A survey questionnaire was developed to collect tourists’ data. The questionnaire includes two parts. The first part focused on participants’ socio-demographics, including gender, age, educational background, and income. The second part is related to the measurements of the four key constructs, namely positive emotion, negative emotion, psychological resilience, and travel intention.
The Positive and Negative Affect Schedule (PANAS) was employed to assess respondents’ positive emotions and negative emotions. It consists of 20 items, with 10 items measuring each construct. The PANAS was first developed by Watson et al. in 1988 and has been widely utilized since in academia and industry [55]. The Connor-Davidson Resilience Scale (CD-RISC) was designed to measure respondents’ psychological resilience [56]. It is a 25-item scale that is supposed to capture resilient attributes and behaviors in people who adapt well in the face of adversity. The original five-dimensional CD-RISC was then revised to include three dimensions to better adapt to the Chinese cultural context [57]. The three dimensions are tenacity (13 items; e.g., “Even when things look hopeless, I don’t give up”), strength (8 items; e.g., “Past successes give me confidence in dealing with new challenges and difficulties”), and optimism (4 items; e.g., “I can deal with whatever comes”). The assessment of travel intention was adopted from the study of Jalilvand, et al. (2012) [58], Jang, et al. (2009) [47], and Weng et al. (2021) [25], such as “If everything goes as I wish, I plan to visit this place in the future”.
A five-point Likert scale was employed to assess the measurement items. Items originally developed in English were translated into Chinese for respondents. A round of back-translation was used to ensure translation quality [59,60,61]. Furthermore, a pilot study was conducted among 50 respondents to make sure all respondents could understand the questionnaire without any vagueness. The participants in the pilot study were asked to fill out the testing questionnaire and to provide comments and feedback regarding the measurement scales and wording. According to the feedback, some ambiguous items were modified to improve clarity with regard to the research context.

3.3. Data Collection and Analysis

The formal data were collected both online and offline from May to June 2020. The online questionnaires were administered on the Sojump platform (www.sojump.com, accessed on 1 May 2020). The offline investigation was conducted in an open park in Nanjing and four well-trained research assistants were hired to collect data.
Two criteria were applied to select qualified respondents in the online and offline surveys. First, the respondents in this study should never have visited Kanas. Thus, the confounding influence of prior tourism experiences could be filtered out [60]. In addition, the respondents should be over 18 years old. Considering that Kanas is far away from the population center, the time and economic costs for respondents are relatively high. Only respondents over the age of 18 are fully capable of civil conduct [25].
After the screening questions, the qualified respondents were instructed to indicate the extent to which they agreed with the statements in the questionnaire as it applied to their current situations [61]. Each respondent received a small gift (offline survey) or cash reward (online survey) as compensation for their time upon completing the questionnaire. Overall, 526 questionnaires were collected in this study, with 286 from online survey and 240 from offline. Due to missing values, 34 of these questionnaires were eliminated from the final analysis, leaving a total sample size of 492 (263 from online and 229 from offline).
This study used SPSS 20.0 and Amos 21.0 for data analysis. Data analysis consists of three steps. First, reliability and validity tests and confirmation factor analysis (CFA) were performed to examine the rationality of the scales. Second, the measurement model was examined via hypotheses test and mediating analysis. Finally, moderating effect analysis was performed to test the research hypotheses.
The questionnaire design, data collection, and analysis procedure are presented in Figure 3.

4. Results

4.1. Sample Profile

The sample profiles are presented in Table 1. Among 492 respondents, males made up 51.2% (n = 252), while females made up 48.8% (n = 240). Most of the respondents (72.8%) had an associate degree or higher. Over 70% of the respondents reported their profession as enterprise employee, self-employment or owner, or student. The majority of the respondents (91.7%) had a monthly personal income of more than 3000 RMB ($470).

4.2. Measurement Model Testing

4.2.1. Reliability Test

The reliability test aims to evaluate the measurement scale’s internal consistency. Generally, a Cronbach’s α coefficient above 0.7 indicates that the scale has good reliability [61]. The analysis indicates that the Cronbach’s α coefficient value of the scale is 0.865. In addition, the Cronbach’s α coefficient values of positive emotion, negative emotion, psychological resilience, and travel intention are 0.906, 0.921, 0.928, and 0.811, respectively (Table 2), which indicates that the measurement of this study has great reliability.

4.2.2. Validity Test

The validity test is mainly evaluated by convergent validity and discriminant validity. Convergent validity refers to the correlation between different items of the same variable [62]. Based on the criteria proposed by Hair et al. (2006) [63], all the factor loads in the present study are bigger than 0.5, and the p values are significant. Moreover, as shown in Table 2, the average variance extracted (AVE) is larger than 0.5, and the composite reliability (CR) is greater than 0.6. [64]. This indicates that the latent variables have good convergence validity.
Discriminant validity refers to the discrimination between different variables [65]. According to Hu and Bentler (1999) [66], the discriminant validity is good when the square root of AVE is bigger than its correlation coefficient with other variables. As shown in Table 3, the correlation coefficient of each variable is between −0.434 and 0.407. Each variable’s square root of AVE is bigger than its correlation coefficient with other variables, indicating that the variables have good discriminant validity.

4.2.3. Confirmatory Factor Analysis

The measurement model was also evaluated using confirmatory factor analysis (CFA). Table 2 (More detailed information can be found in Appendix A) shows the model fit indices that meet the cutoff points (χ2/df = 1.155, NFI = 0.910, CFI = 0.987, GFI = 0.910, AGFI = 0.901, RMSEA = 0.018, SRMR = 0.031) [55,59,67], which confirm that the measurement model fits well with the data.

4.3. Structural Model and Hypotheses Testing

4.3.1. Structural Model Goodness-of-Fit Test

The data was checked for skewness and kurtosis to ensure that it was normal. The skewness ranged from −1.360 to 0.692, and the kurtosis ranged from −0.715 to 2.610, indicating that the data was distributed normally [63].
The goodness-of-fit test was also performed on the structural model between latent variables. Results indicated that the structural model also shows a good fit of the data (χ2/df = 1.353, NFI = 0.937, CFI = 0.983, GFI = 0.944, AGFI = 0.933, RMSEA = 0.027, SRMR = 0.031) [63,66,68]).

4.3.2. Hypotheses Test and the Mediating Effect Analysis

Structural equation model was used to test the research hypothesis proposed above, and the results are shown in Table 4. The standardization path coefficient of H1 is 0.153 (t = 2.464, p = 0.014 < 0.05), indicating that visitor’s positive emotion has a significant positive impact on psychological resilience. Hence, H1 was supported. The standardization path coefficient of H2 is −0.32 (t = −4.793, p = 0.000 < 0.001), indicating that visitor’s negative emotion has a significant positive effect on psychological resilience. Thus, H2 was also supported. Result of the standardization path coefficient of H3 is 0.237 (t = 4.87, p = 0.000 < 0.001), which shows that visitor’s positive emotion has a significant positive effect on travel intention. Therefore, H3 was supported. The standardization path coefficient of H4 is −0.275 (t = −5.241, p = 0.000 < 0.001), indicating that visitor’s negative emotion has a significant positive effect on travel intention. Thus, H4 was also supported. The standardization path coefficient of H5 is 0.286 (t = 4.215, p = 0.000 < 0.001), indicating that visitor’s psychological resilience has a significant positive effect on travel intention. Therefore, H5 was supported.
The present study uses psychological resilience as the mediating variable. For the test of the mediating effect, this study applied the Bootstrap method via conducting 2000 sampling tests and calculating the total effect, indirect effect, and direct effect, respectively (Table 5). Results revealed that the Bias-Corrected 95% confidence interval for the total effect of positive emotion on travel intention is 0.195–0.469, and the Percentile 95% confidence interval is 0.187–0.455, indicating that the total effect is significant and the strength of the effect is 0.319. The Bias-Corrected 95% confidence interval of the indirect effect (mediating effect) is 0.011–0.114, and the Percentile 95% confidence interval is 0.008–0.107, demonstrating that the mediating effect of psychological resilience exists. The Bias-Corrected 95% confidence interval of the direct effect is 0.141–0.418, and the Percentile 95% confidence interval is 0.133–0.407, neither of which includes 0, demonstrating that the direct effect also exists.
Similarly, the Bias-Corrected 95% confidence interval for the total effect of negative emotion on travel intention is −0.636 to −0.280, and the Percentile 95% confidence interval is −0.636 to −0.280, demonstrating that the total effect is significant. The Bias-Corrected 95% confidence interval of the indirect effect (mediating effect) is −0.224 to −0.051, and the Percentile 95% confidence interval is −0.212 to −0.045, demonstrating that the mediating effect of psychological resilience exists. The Bias-Corrected 95% confidence interval of the direct effect is −0.520 to −0.176, and the Percentile 95% confidence interval is −0.512 to −0.172, indicating that the direct effect also exists.
Thus, the mediating effect of psychological resilience is partially mediated. In other words, visitor’s positive emotion and negative emotion can both directly and indirectly influence travel intention. Thus, H6a and H6b were both supported.

4.4. Moderating Effect of Gender

The moderating effect of gender was examined by setting up a multi-group sample in a structural equation model. As shown in Table 6, for the male sample, the influence coefficient of positive emotion on psychological resilience is 0.240 (t = 2.786, p = 0.005 < 0.01), which is significant at the level of 0.01, while the influence coefficient of positive emotion on psychological resilience for the female sample is 0.072 (t = 0.802, p = 0.412 > 0.05), which does not reach the range of significance. Similarly, the influence coefficient of positive emotion on travel intention for the male sample is 0.467 (t = 6.831, p < 0.001), which is significant at the level of 0.001, while the influence coefficient of positive emotion on travel intention for the female sample is 0.104 (t = 1.478, p = 0.140 > 0.05), which is not significant.
In addition, it can be found from Table 6 that the influence coefficients of negative emotion on psychological resilience and travel intention both in the male and female sample are all negative (t = −2.689, p = 0.007; t = −3.531, p < 0.001; t = −4.522, p < 0.001; t = −3.114, p = 0.002). Furthermore, the influence coefficient of psychological resilience on travel intention for the female sample is generally larger than that for the male sample (t = 2.380, p = 0.017; t = 2.993, p = 0.003), indicating that the female group obtains a higher level of psychological resilience and that their travel intention will also be stronger compared with the male group.
Overall, the results demonstrate that gender had significant moderating effects between positive emotions and psychological resilience and travel intention, and the moderating effect of males was better than that of females. However, the moderating effect of gender was not significant if the respondents reported negative emotions. Therefore, H7a and H7b were both supported.

5. Discussion

5.1. Theoretical Implications

The current study makes several significant contributions to the existing literature. It represents one of the first efforts to empirically explore and examine the relationships among visitors’ emotional state, psychological resilience, and their travel intention to national forest park in the context of COVID-19. Existing studies mostly focus on the impacts of the COVID-19 pandemic on the tourism industry from a macro level [16,17,18]. For example, Škare, Soriano, and Porada-Rochoń (2021) use data from 185 countries to evaluate the global impact of the pandemic crisis on the tourism industry, and discover that recovery will take longer than the average [16]. Such research is undoubtedly meaningful, but the micro-level emotional state and psychological resilience of potential tourists remain scarce in tourism literature. The present study fills this research gap and the findings indicate that positive emotions determine potential tourists’ psychological resilience and their behavioral intentions while negative emotions such as fear and anxiety may diminish potential tourists’ psychological resilience and their travel intentions. This result supports the argument that eliciting positive emotion is extremely crucial for tourism recovery after the current pandemic ends [69,70,71]. The micro-level examination of visitors’ emotional state, psychological resilience, and their travel intention is a subsystem of the macro-level research on tourism industry. Only when individuals have positive emotions and a high level of psychological resilience can they stimulate the willingness to travel, thereby promoting the recovery and sustainable development of the entire tourism industry.
Second, the present study contributes to tourism psychology research by applying and examining the mediating effect of psychological resilience on the influence of visitors’ emotional state on their travel intention. An abundance of extant literature (e.g., SOR theory) emphasizes the psychological changes and development process of individuals experiencing catastrophic events, and proves that psychological resilience is a dynamic process for individuals to achieve good adaptation or successful response in the face of adversity, threats, or other major pressures [12,72]. The results of this study are consistent with this statement and the SOR theory. The findings demonstrate that emotional state cannot only directly affect visitors’ willingness to travel, but also indirectly affect their travel intention through psychological resilience. This suggests that psychological resilience can be developed and managed [73]. Individuals must develop resilience by accumulating psychological resources when confronted with stressful experiences, and these psychological resources can then be used to encourage travel behavior in the future.
Third, the present study recognizes the moderating role of gender in the relationship between visitors’ emotional state, psychological resilience, and their travel intention. Studies on gender and emotion have found that men and women differ in the experience and expression of emotion, and that women are more likely than men to report negative emotions [53,54,74]. For example, Heffner et al. (2021) found that women who were anxious and absorbed high amounts of COVID-19 media from their social networks were the most vulnerable to suffering emotional distress [75]. Similar results were also found in this study. The results of moderating effect analysis show that gender has significant moderating effects between positive emotions and psychological resilience and travel intention. The moderating effect of males is stronger than that of females, indicating that men are more likely than women to report positive emotions. It is hoped that it will serve as a foundation for future research in this field and stimulate even more significant research.

5.2. Practical Implications

The findings of this study offer guidance for potential tourists in terms of regulating emotions and psychology, and provide important implications on crisis management to nature-based tourism destinations in the context of COVID-19. Hypotheses testing results indicate that positive emotions have a significant effect on visitors’ psychological resilience and their travel intention, and psychological resilience also has a significant effect on travel intention, indicating that the positive emotions of visitors are the inducing motivation for their behavioral intention. In addition, psychological resilience is considered to be an important psychological quality related to a person’s health and happy life, which can be enhanced and improved through effective training [76]. Potential tourists should focus on regulating their emotions, try to increase positive emotions, and make themselves optimistic. They should stay away from negative information, communicate more with family and friends, and advocate more mutual encouragement [48]. To lessen travel anxiety, tourism practitioners can also share more information about the destinations’ risk level on their official websites or self-media platforms, such that visitors can perceive risks as manageable and under control [48].
Furthermore, men and women are found to have differences in the experience and expression of emotions. Women are more advised to foster positive emotions and psychological resilience. The results of the present research reveal that women are more likely than men to report negative emotions in the face of COVID-19. However, the moderating effect results further show that the effect size of psychological resilience on travel intention for females is larger than that for males in general. This suggests that women are even more willing to travel than men when both men and women have psychological resilience. Thus, based on the findings, one suggestion could be made to nature-based tourism destinations, which is that, to gradually restore the tourism market, an emphasis should be placed on improving potential female visitors’ psychological resilience during the COVID-19 crisis.
In addition, suggestions are also provided for nature-based tourism destinations such as world natural heritage sites and national forest parks as to how to conduct crisis management and recovery strategies. The tourism industry is extremely vulnerable to the ongoing COVID-19 pandemic. Therefore, destination management organizations should guide potential tourists to stimulate positive emotions and psychological resilience, especially female tourists, which can better increase their willingness to travel. In addition, nature-based tourism destinations should concentrate on lowering visitors’ anxiety levels and work on increasing visitors’ interest in the destination. Particularly, to make visitors feel at ease while traveling, restaurants, hotels, and transportation firms should provide tailored services and follow strict safety procedures [48]. Nature-based tourism destinations are recommended to take public health and social measures, and provide tourists with a healthy and safe recreational space. Moreover, nature-based tourism destinations should also consider continuously updating their products, so as to better attract tourist arrivals and promote more sustainable tourism development after the pandemic has subsided [31].

6. Conclusions

The COVID-19 pandemic has impacted the lives of hundreds of millions of individuals around the world, as well as the tourism industry. The present research applied structural equation modeling to examine the relationships among potential tourists’ emotional states, psychological resilience, and their travel intention to a national forest park in the context of COVID-19, and also to investigate the moderating effect of gender in the above-mentioned influence relationship.
The results demonstrate that visitors’ positive emotion has significant positive effects on their psychological resilience and travel intention. In addition, visitors’ psychological resilience has a significant positive effect on travel intention. However, visitors’ negative emotion has a significant negative effect on psychological resilience and travel intention. Moreover, the mediating effect of psychological resilience and the moderating effect of gender were also examined in this study. The results indicate that psychological resilience partially mediates the relationship between emotional state and travel intention, indicating that visitor’s positive emotion and negative emotion can not only directly affect travel intention, but also indirectly affect travel intention through psychological resilience. The moderating effect of gender is recognized and verified, and the results show that gender has significant moderating effects between positive emotions and psychological resilience and travel intention, and that the moderating effect of males is stronger than that of females. However, the moderating effect of gender was not significant if the respondents reported negative emotions. The present study has laid a solid foundation for future research on the relationship between emotion state, psychological resilience, and travel intention. Further studies are encouraged to examine and verify the results presented in this study.

Author Contributions

Conceptualization, L.W. and F.C.; methodology, L.W. and G.H.; software, L.W.; validation, L.W. and F.C.; formal analysis, L.W.; investigation, Y.W. and H.L.; resources, F.C.; data curation, L.W.; writing—original draft preparation, L.W., Y.W. and H.L.; writing—review and editing, L.W. and G.H.; visualization, L.W.; supervision, F.C.; project administration, F.C.; funding acquisition, L.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Social Science Fund of China under Grant [21CH197]; Jiangsu University Philosophy and Social Science Fund Project [2020SJA0052]; 2020 Central University Basic Scientific Research Business Fee Humanities and Social Sciences Fund under Grant [SKYC2020017, SKYZ2020022].

Data Availability Statement

Data available on request.

Acknowledgments

The authors would like to acknowledge the helpful support received from the respondents in the field data collection.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. CFA Results.
Table A1. CFA Results.
Dependent VariablesMean
(SD)		Factor
Loading		CRAVECronbach’s α
Positive emotion 0.9120.5090.906
Interested3.94 (0.87)0.734
Excited3.91 (0.86)0.703
Strong3.98 (0.88)0.682
Enthusiastic3.95 (0.90)0.711
Proud3.85 (0.91)0.644
 Alert3.95 (0.88)0.694
 Inspired3.92 (0.87)0.695
 Determined3.93 (0.88)0.692
 Attentive3.90 (0.90)0.733
 Active3.93 (0.87)0.830
Negative emotion 0.9220.5410.921
 Distressed2.11 (0.82)0.731
 Upset2.14 (0.90)0.785
 Guilty2.18 (0.87)0.746
 Scared2.17 (0.87)0.714
 Hostile2.16 (0.85)0.741
 Irritable2.18 (0.84)0.703
 Shy2.10 (0.89)0.737
 Tense2.15 (0.85)0.746
Antsy2.14 (0.87)0.738
 Fearful2.18 (0.85)0.708
Tenacity 0.9400.5470.940
 Work to attain goals3.32 (0.85)0.723
 Even when things look hopeless, I don’t give up3.30 (0.89)0.728
 Know where to turn for help3.33 (0.83)0.721
 Under pressure, focus and think clearly3.33 (0.85)0.748
 Prefer to take the lead in problem-solving3.34 (0.85)0.706
 Not easily discouraged by failure3.30 (0.84)0.723
 Think of self as strong person3.33 (0.90)0.734
 Make unpopular or difficult decisions3.34 (0.90)0.769
 Can handle unpleasant feelings3.33 (0.90)0.756
 Have to act on a hunch3.29 (0.85)0.720
 Strong sense of purpose3.25 (0.86)0.740
 In control of life3.28 (0.87)0.741
 Like challenges3.32 (0.88)0.807
Strength 0.9110.5620.911
 Adapt to change3.98 (0.78)0.764
 Past successes give me confidence in dealing with new challenges and difficulties4.00 (0.80)0.776
 Coping with stress strengthens3.96 (0.80)0.731
 Tend to bounce back after illness or hardship3.96 (0.80)0.759
 Things happen for a reason3.98 (0.81)0.731
 Best effort no matter what3.96 (0.82)0.772
 Can achieve goals3.95 (0.80)0.719
 Pride in achievements3.97 (0.78)0.745
Optimism 0.8170.5280.816
 Close and secure relationships3.70 (0.83)0.683
 Sometimes fate or god can help3.76 (0.78)0.774
 Can deal with whatever comes3.74 (0.82)0.718
 See humorous side of things3.68 (0.80)0.728
Travel intention 0.8180.6940.811
 I want to travel to Kanas in Xinjiang
 If everything goes as I wish, I plan to visit this place in the future		4.24 (0.83)
4.16 (0.79)		0.906
0.754

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Forests 13 00750 g001 550
Figure 1. The conceptual framework of this study.
Figure 1. The conceptual framework of this study.
Forests 13 00750 g001
Forests 13 00750 g002 550
Figure 2. Kanas Lake and cabins of Kanas National Forest Park in Xinjiang province, China. (Photographed by the first author).
Figure 2. Kanas Lake and cabins of Kanas National Forest Park in Xinjiang province, China. (Photographed by the first author).
Forests 13 00750 g002
Forests 13 00750 g003 550
Figure 3. Questionnaire design, data collection, and analysis procedure.
Figure 3. Questionnaire design, data collection, and analysis procedure.
Forests 13 00750 g003
Table
Table 1. Sample profile.
Table 1. Sample profile.
Frequency (n = 492)Percentage (%)
GenderMale25251.2
Female24048.8
Age18 to 22 years7916.1
23 to 35 years16834.1
36 to 45 years13327.0
46 to 55 years5010.2
56 to 65 years408.1
Over 65 years224.5
EducationHigh school or below13427.2
Associate degree15331.1
Bachelor’s degree17836.2
Master’s degree or above275.5
OccupationEnterprise employee12926.2
Self-employment or owner6413.0
Student16333.1
Government officials5411.0
Professionals, teacher or technical306.1
Other5210.5
Personal monthly Income (RMB)Less than 3000418.3
3001–600013727.9
6001–10,00016533.5
10,001–15,0007916.1
More than 15,0007014.2
Table
Table 2. Reliability and validity analysis.
Table 2. Reliability and validity analysis.
VariablesCRAVECronbach’s α
Positive emotion0.9120.5090.906
Negative emotion0.9220.5410.921
Psychological resilience 0.928
 Tenacity0.9400.5470.940
 Strength0.9110.5620.911
 Optimism0.8170.5280.816
Travel intention0.8180.6940.811
Note: Model fit indices: χ2/df = 1.155, NFI = 0.910, CFI = 0.987, GFI = 0.910, AGFI = 0.901, RMSEA = 0.018, SRMR = 0.031.
Table
Table 3. Discriminant validity and the correlations of variables.
Table 3. Discriminant validity and the correlations of variables.
VariablesPositive EmotionNegative EmotionTenacityStrengthOptimismTravel Intention
Positive emotion0.713 *
Negative emotion−0.2370.735 *
Tenacity0.125−0.1960.739 *
Strength0.113−0.2420.4070.749 *
Optimism0.193−0.2070.3540.3440.726 *
Travel intention0.367−0.4340.2070.2760.340.833 *
Note: * indicates that the data is the square root of each variable AVE, and the rest of the data are the correlation coefficients between the variables.
Table
Table 4. Standardization path coefficient and hypothesis testing results.
Table 4. Standardization path coefficient and hypothesis testing results.
Hypothesis PathsEstimateS.E.tpResults
H1: Positive emotion → Psychological resilience0.1530.0362.4640.014 *Support
H2: Negative emotion → Psychological resilience−0.3200.043−4.793***Support
H3: Positive emotion → Travel intention0.2370.0564.870***Support
H4: Negative emotion → Travel intention−0.2750.066−5.241***Support
H5: Psychological resilience → Travel intention0.2860.1334.215***Support
Note: * < 0.05, *** < 0.001.
Table
Table 5. Results of mediation effect analysis.
Table 5. Results of mediation effect analysis.
Hypothesis PathsPath EffectsEffect SizeBias-Corrected 95% CIPercentile 95% CI
LowerUpperLowerUpper
Positive emotion → Travel intentionTotal0.3190.1950.4690.1870.455
Indirect0.0500.0110.1140.0080.107
Direct0.2690.1410.4180.1330.407
Negative emotion → Travel intentionTotal−0.460−0.636−0.280−0.636−0.280
Indirect−0.115−0.224−0.051−0.212−0.045
Direct−0.345−0.520−0.176−0.512−0.172
Table
Table 6. The moderating effect of gender.
Table 6. The moderating effect of gender.
Hypothesis PathsMale GroupFemale Group
EstimatetpEstimatetp
H1: Positive emotion → Psychological resilience0.2402.7860.005 **0.0720.8020.412
H2: Negative emotion → Psychological resilience−0.220−2.6890.007 **−0.381−3.531***
H3: Positive emotion → Travel intention0.4676.831***0.1041.4780.140
H4: Negative emotion → Travel intention−0.276−4.522***−0.267−3.1140.002 **
H5: Psychological resilience → Travel intention0.1702.3800.017 *0.3302.9930.003 **
Note: * < 0.05, ** < 0.01, *** < 0.001.
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Weng, L.; Wu, Y.; Han, G.; Liu, H.; Cui, F. Emotional State, Psychological Resilience, and Travel Intention to National Forest Park during COVID-19. Forests 2022, 13, 750. https://doi.org/10.3390/f13050750

AMA Style

Weng L, Wu Y, Han G, Liu H, Cui F. Emotional State, Psychological Resilience, and Travel Intention to National Forest Park during COVID-19. Forests. 2022; 13(5):750. https://doi.org/10.3390/f13050750

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Weng, Lisheng, Yawen Wu, Guang Han, Huifang Liu, and Feng Cui. 2022. "Emotional State, Psychological Resilience, and Travel Intention to National Forest Park during COVID-19" Forests 13, no. 5: 750. https://doi.org/10.3390/f13050750

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