Keywords

7.1 Introduction

The COVID-19 pandemic is basically under control, and people in many countries have transitioned to the new normal. However, its impact is likely to remain for a long time (Gössling et al., 2021; Tung, 2021; Uğur & Akbıyık, 2021). Travel is no exception. In 2021, the travel and tourism industry contributed 6.1% to the global gross domestic product (GDP), showing an increase compared to 2020 as this sector in 2020 only accounted for 5.3% to global GDP. However, travel and tourism GDP is still lower than the sector’s share of global GDP in 2019 (i.e., 10.3%). Likewise, the number of jobs in this sector has increased from 271 million in 2020 to 289 million jobs in 2021. That is, more than 18 million jobs have been restored during the new period. Even so, the current employment level has not yet returned to that in 2019 when 333 million jobs were created (WTTC, 2022).

Given the sector’s important role in the economy, many governments strive to recover the travel and tourism sector. Nevertheless, failure to grasp possible factors that influence tourism intention in the post pandemic may lead to undesirable outcome. Therefore, we investigate the determinants of attitude and intention to revisit a destination to explore the recent trends in the fields of tourism. The paper contributes to the existing research on tourism in at least two aspects. First, it explores how people’s travel intentions are affected in the post-COVID-19 period. By this way, the analysis adds to the picture of factors driving people’s travel intentions under the new normal. Second, the results of the study suggest factors that governments should focus on if they want to attract tourists. Due to limited resources, countries need to invest effectively in necessary items that have an impact on tourism (Chung et al., 2021; My & Tung, 2023; Wang et al., 2022). This can only be done if we understand the needs and tastes of potential tourists.

To achieve the research objective, we propose a model that includes the determinants of tourist attitudes and intentions. Previous studies have shown that past experiences of a destination can affect individuals’ attitudes and intentions to travel (Casali et al., 2021; Rasoolimanesh et al., 2021). In other words, the destination will benefit if visitors have a positive experience about the place and vice versa. Another factor that can influence tourist attitudes is the destination’s healthcare system (Donohoe et al., 2015; Moreno-González et al., 2020; Reisinger & Mavondo, 2005). The COVID-19 pandemic has caused not only the elderly but also the young to get sick and even die. Hence, the role of the healthcare system receives much attention in the post-pandemic period. Similarly, prior literature uncovers that crisis management can be associated with the attitude to revisit a destination (Avraham, 2015; Santana, 2004; Zheng et al., 2021). Proper crisis management may make potential tourists feel confident and secure, and therefore they can be more willing to revisit the destination.

After designing and testing a questionnaire on potential factors affecting tourism attitudes and intentions, we collected responses from 431 individuals. We then applied the Cronbach’s alpha test and estimated the composite reliability and the average variance extracted to check the validity and reliability of the scale. In the following steps, we calculated model fit metrics to ensure that the analytical model is appropriate. Since the scale satisfied valid and reliable requirements, we used the structural equation modeling to explore factors that could drive an individual’s attitude and intention to revisit. The results indicate that positive past travel experiences have a beneficial effect on attitude to revisit a destination. Similarly, healthcare systems and crisis management are associated with revisit attitudes. Positive tourist’s attitude in turn will boost the travel intention of potential tourists.

The rest of the paper is structured as follows: Sect. 7.2 summarizes findings from previous studies on factors that can influence travel decisions. Section 7.3 presents the methodology to test hypotheses, while Sect. 7.4 highlights empirical findings, discussion, and limitations. Section 7.5 is about conclusion.

7.2 Literature Review

7.2.1 Past Experience and Travel Decision

Experiences of past trips provide visitors with information about a destination. If visitors have a positive experience, they are more likely to revisit the destination. Conversely, if past trips create negative feelings, individuals may be more hesitant to return to that place. This implies that travel experience can influence a person’s travel decision through their positive/negative attitude about the destination. Here arises a question of what is tourist satisfaction based on? The expectation-disconfirmation model and the norm theory are potential candidates to answer this question.

The expectation-disconfirmation model is proposed by Oliver (1980). Accordingly, customers can compare their service expectations with the actual performance of the service. If the latter is worse than the former, they may feel dissatisfied and therefore consider other alternatives in future choices. By contrast, if the latter is better than the former, they would feel satisfied about the service. Regarding travel decision, Chon (1989) claims that individual satisfaction is based on the gap between their expectations of a destination and their perceived evaluations when experiencing the place. Meanwhile, the norm theory introduced by Latour and Peat (1979) suggests that norm can affect customers’ satisfaction. In the context of tourism, travelers can compare past and present experiences of destinations. These statements are supported by the study of Yoon (2005) who proposes that relevant managers should improve the level of tourist’s satisfaction to enhance the competitiveness of the destination. Similarly, Tsai (2012) suggests that past experience is associated with an individual’s future travel. The impact of past experience on travel decisions is also examined in other studies such as Casali et al. (2021) and Rasoolimanesh et al. (2021). Hence, we propose the following hypothesis:

  • H1. Positive past experience has a positive effect on attitude to revisit a destination.

7.2.2 Healthcare System and Travel Decision

Another factor that may be involved in the decision to travel is the healthcare system. The pandemic further underscores the need for the healthcare system (WHO, 2020). The outbreak of an illness often worries visitors and thus prevents them from returning to the attraction. Reducing health risks, for example, through building a strong and reliable healthcare system, can attract more tourists to the destination. In this regard, Reisinger and Mavondo (2005) investigate the factors affecting perception of travel risk and intention to travel. They find that the level of anxiety for safety is negatively related to travel decisions. This result is consistent with other studies (Donohoe et al., 2015; Moreno-González et al., 2020). For instance, Donohoe et al. (2015) discuss the relationship between Lyme disease and the tourism sector. They show that this disease can have an adverse effect on both tourism supply and demand. The authors thus propose that tourism managers and public health authorities should act to protect the health of tourists, such as by providing materials on how to protect themselves against the risk of the disease. Likewise, Castañeda-García et al. (2022) suppose that improvement in the public healthcare system could be a measure to sustain the tourism sector’s recovery. Based on findings from previous research, the following hypothesis is suggested:

  • H2. The healthcare system positively impacts attitude to revisit a destination.

7.2.3 Crisis Management and Travel Decision

Crisis can create concerns among potential tourists, preventing them from revisiting the destination. Santana (2004) argues that tourism is one of the most vulnerable industries when crises occur. The author claims that if the public sector does not respond appropriately, there may be other uncertainties for the future of the destination. In addition, given the frequency and complexity of crises, tourism destinations and travel companies should be prepared to cope with this phenomenon. Similarly, Avraham (2015) discusses the impact of the Arab Spring uprisings on the tourism sector as well as the strategies adopted by Middle Eastern countries to revive this sector. The author supposes that crisis management plays an important role in efforts to attract tourists back to this country. One of the major recent crises that have negatively influenced the travel and tourism industry is the COVID-19 pandemic. Zheng et al. (2021) examine the impact of this crisis and offer implications for tourism recovery in the post-crisis period. Specifically, they report that the pandemic may have triggered public fear, making travelers more cautious in travel decisions. Hence, in order to promote the recovery of the economy, it is essential to reduce potential tourists’ fears about the destination. Su et al. (2023) also emphasize the importance of crisis management to avoid adverse effects on the destination. Given suggestions from prior studies on crisis management, we suggest the following hypothesis:

  • H3. Crisis management positively impacts attitude to revisit a destination.

7.2.4 Attitude and Intention to Revisit a Destination

Attitude about revisiting a destination is a possible factor that can influence tourists’ intentions. If individuals have a negative attitude about a place, they are less likely to return to that place. Different authors have reported the relationship between attitude and intention to travel (Hasan et al., 2019; Huang & Hsu, 2009; Jalilvand et al., 2012; Wang et al., 2022). For example, Huang and Hsu (2009) analyze responses from 501 Chinese visitors and report that attitude is positively associated with revisit intention. Meanwhile, Jalilvand et al. (2012) investigate the relationship between tourists’ attitude and their travel intention. They discover that attitude about a destination is a potential indicator of travel decisions. They suggest that it is crucial to understand the lifestyles and attitudes of potential visitors. By this way, destination authorities and travel agencies can better meet the expectations and needs of their customers. Hasan et al. (2019) also explore the relationship between tourists’ attitude to revisit and their revisit intentions. The authors find evidence showing that there is a statistically significant positive relationship between attitude and intention to revisit the destination. Therefore, the following hypothesis is proposed:

  • H4. Positive attitude promotes tourists’ intention to revisit a destination (Fig. 7.1).

Fig. 7.1
A diagram of the proposed model. The past experience via H 1, health care system via H 2, and crisis management via H 3 point to positive attitude to revisit. It via H 4 points to intention to revisit.

Proposed research model

Full size image

7.3 Research Methodology

To investigate the factors that can influence revisit attitude and intention, we designed a questionnaire which included measurement items. All items in the questionnaire were measured using a five-point Likert scale, where 1 was “strongly disagree” and 5 was “strongly agree.” The questionnaire was consulted by experts to check whether the questionnaire was understandable, relevant, and consistent. Before the official survey, we conducted a pilot test to examine the implementation process, the wording, and the language of the questionnaire. Responses from the pilot test were not included in the analysis.

A total of 20 items were developed from previous studies to measure five constructs. Particularly, items for past experience, healthcare system, and crisis management were adapted from Rasoolimanesh et al. (2021). Items for revisit attitude and revisit intention were adopted from Huang and Hsu (2009) and Abbasi et al., (2021), respectively. The reason to examine the impact of these factors is that they have a significant influence on travel decisions in the related studies. Table 7.1 shows the questions used in the study.

Table 7.1 Constructs and items
Full size table

We then employed an online survey to gather data from domestic tourists in Vietnam. The online survey is a suitable tool in contexts such as the pandemic (Chung et al., 2021). We collected the data in October 2021 as the country entered the new normal. The COVID-19 pandemic has caused severe consequences to the global economy in general and the Vietnamese economy in particular. For example, travel and tourism GDP in 2020 decreased by USD 4855 billion or 50.4% compared to 2019. Similarly, millions of people lost their jobs in the same year. Vietnam is no exception. The General Statistics Office of Vietnam (GSO) estimates that the tourism and travel industry’s revenue in 2020 reached about VND 17.9 trillion, a decrease by 59.5% compared to 2019 (GSO, 2023). Therefore, when the country entered the post-COVID-19 period, the government has actively applied policies and programs to stimulate tourism demand. That was also the time when we collected data. Furthermore, we concentrate on domestic tourists. These subjects generate an internal force for maintaining sustainable tourism development in Vietnam, as described in Program No. 4698/BVHTTDL-TCDL of the Ministry of Culture, Sports and Tourism.

There was a total of 437 responses to the questionnaire, but after cleaning the data, only 431 responses were valid. We then checked the validity and reliability of the scale to ensure that the proposed model is appropriate for analysis. The model needs to satisfy the required conditions to be analyzed. Particularly, Cronbach’s alpha values of all items should be higher than 0.7, while composite reliability and average variance extracted should be higher than 0.7 and 0.6, respectively. We then estimated model fit indices to ensure that the proposed model was suitable for further analysis. Finally, the structural equation modeling (SEM) was employed to analyze the research hypotheses.

7.4 Results and Discussions

7.4.1 Sample Analysis

Table 7.2 presents the descriptive statistics of the sample. In terms of gender, 50.1% participants are female, and 49.9% participants are male. The majority of respondents (89.6%) are lower than 49 years old. The proportion of respondents who are studying in a high school or an intermediate school is 7.2%. Meanwhile, the proportion of respondents who are attending college, bachelor’s, and master’s degrees or above is 5.3%, 60.3%, and 27.1%, respectively. Among those who were surveyed, 56.4% of individuals report that on average they travel at least two times per year.

Table 7.2 Characteristics of the study sample
Full size table

7.4.2 Validity and Reliability Test

To test the model using SEM, the measurement model which includes five constructs, past experience, crisis management, healthcare system, revisit attitude, and revisit intention, need to satisfy the criteria of reliability and validity (Ali et al., 2021). We therefore start with an internal reliability check through calculating the Cronbach’s alpha values. As shown in Table 7.3, all these values are higher than 0.7, suggesting that we can proceed to the next step of analysis. In the EFA step, we find that all variables satisfy the required conditions and are extracted into five groups as suggested by the model.

Table 7.3 Results of confirmatory factor analysis
Full size table

We then employ CFA to check the reliability, the discriminant validity, and the convergent validity for all constructs. According to Hair et al. (2019), the composite reliability (CR) and average variance extracted (AVE) should be higher than 0.7 and 0.5, respectively. Results are exhibited in columns 3–4 of Table 7.3. Particularly, CR values are between 0.860 and 0.929, greater than the required level of 0.7, showing that the reliability of the scale is high. Similarly, AVE values report a convergent validity of the scale as they run from 0.605 to 0.767, greater than the suggested threshold of 0.5.

Finally, we calculate fit indices including Chi-square/df, goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), Tucker-Lewis index (TLI), comparative fit index (CFI), and root mean square error of approximation (RMSEA). Results, presented in Table 7.4, report that χ2/df, 1.995; p < 0.000; GFI = 0.930; AGFI = 0.910; TLI = 0.970; CFI = 0.975; and RMSEA = 0.048. As all indicators satisfy the required criteria, the proposed model is proper for further analysis.

Table 7.4 Results of the structural model
Full size table

7.4.3 Hypothesis Analysis

Results from analyzing the structural model are exhibited in Table 7.4. We find evidence showing that past experience is associated with tourists’ attitude to revisiting a destination. That is, if visitors have a pleasant experience, they are more prone to revisit the attraction. Therefore, hypothesis H1 is supported. This finding suggests that the government and tour operators should improve tourists’ experience to create positive attitudes about a destination. We also discovered that the healthcare system is a possible indicator of attitude to revisit a destination, and thus hypothesis H2 is confirmed. Another possible predictor of revisit attitude is crisis management. The results support hypothesis H3 on the positive relationship between crisis management and revisit attitude. Crises, including health crises, often cause anxiety in individuals. This is also an obstacle that prevents them from returning to a destination. Likewise, revisit attitude positively affects revisit intention or hypothesis H4 is confirmed. In other words, if a person has a positive attitude about returning to a destination, he/she is more likely to intend so.

7.4.4 Discussion and Limitation

The paper examines the recent trends in the field of tourism under the new normal by exploring the factors that influence the attitude and the intention to revisit a destination. We find that past experience can have a beneficial effect on tourists’ revisit attitude. The beneficial effect of positive experience on an individual’s attitude about a service has been reported in previous studies such as Oliver (1980) and Yoon (2005). A positive tourist attitude, in turn, can promote the intention to revisit a destination. The results imply that enhancing tourists’ experience with the destination can provide long-term benefits and motivate them to return. Local government and travel agencies at the destinations should therefore avoid short-term profit-making actions that ignore tourists’ feelings. Instead, they had better listen and absorb their customers’ opinions, which can be performed in person or through online review tools.

Tourists are also more concerned about the destination’s healthcare system in the post-pandemic context. Indeed, the study results reveal that healthcare is an important factor that individuals can consider when choosing a destination. This positive relationship is consistent with findings by Donohoe et al. (2015) and Castañeda-García et al. (2022). The COVID-19 pandemic has negative consequences for not only the elderly but also the young. This is probably one reason that makes individuals care more about the healthcare system. Hence, investing in the healthcare system can help potential tourists worry less and feel safer when deciding to revisit a destination.

Furthermore, the research results indicate that effective crisis management is beneficial for tourism recovery and development. The positive link between crisis management and revisit attitude is supported by prior literature (Avraham, 2015; Zheng et al., 2021). Crises, although stemming from different causes, often cause uncertainty and risk in the destination. This in turn can make potential visitors more anxious and more hesitant when choosing to revisit an attraction. The authorities therefore need to combine different methods to promptly control the crisis. More importantly, with the wide network of social networks, there can be conflicting information. In this context, governments and tour operators should invest in official communication channels to provide useful and transparent information to potential tourists.

This study reveals possible drivers of travel intentions in the post-pandemic period. The results complement to current literature on new trends in the tourism sector and provide suggestions for developing this industry. Nevertheless, it is not free from limitations. We focus our attention on the impact of past experiences, healthcare systems, and crisis management on individuals’ revisit attitudes and intentions. This is because related research has shown that they significantly influence travel decisions. In addition, as analyzed above, these factors also impact the intention to revisit destinations in Vietnam. However, other studies may be expanded to investigate different factors and explore whether and how such factors can affect tourism supply and demand. Moreover, we only consider the driving factors in the post-pandemic period. Further studies could examine whether factors influencing travel intentions and behavior differ between pre- and post-pandemic. Such studies will contribute to enriching the understanding of tourism trends over time.

7.5 Conclusion

The pandemic has been gradually brought under control, but its impact on individuals’ habits may persist for a long time. Travel decisions are no exception. In this study, we explore the factors that can influence the attitude and intention to revisit a destination in the post-pandemic. We accomplish this research objective by collecting 431 responses to travel decisions in Vietnam. After checking the validity and reliability of the scale, we applied SEM to test the hypothesis about the relationship between the factors. Research results indicate that a positive experience of an attraction will boost individuals’ positive feelings about that place. This in turn will have a beneficial impact on tourists’ intention to revisit the destination. Therefore, we suggest that destination authorities and travel agencies should diversify different ways to solicit feedback from tourists. Accordingly, they can grasp the needs and tastes of their customers to improve their services. Moreover, a good healthcare system is another factor that can help attract tourists. Tourists are probably more concerned about their health after the pandemic. We also suppose that to maintain and promote the development of the tourism industry, these factors should be combined with effective crisis management. One reason is because effective crisis management helps individuals feel more secure about their destination. Together with other related studies, our research adds to the analysis of factors that can influence attitudes and intentions to revisit a destination in the post-pandemic period.