In and around destinations, shock and stress are felt during a crisis regardless of the event's type, probability, or magnitude. Studies have shown how the crisis affects the destination, awareness, feedback and adaptations to the crisis, and spending patterns (41–43). Tourism crisis research has primarily focused on monetary and health issues. The financial crisis has gotten more academic attention for the first time because it is linked to socioeconomic issues such as unemployment (44, 45). As a result, job insecurity and the resulting decrease in available spending power heavily influence people's travel decisions. The tourism industry has been the focus of previous studies on SARS. SARS or the avian flu may threaten people's health, safety, and wellbeing, but it also poses difficulties for the travel industry, particularly inbound travelers. In this sense, it is comparable to a financial meltdown.

Tourists' travel plans and activities are influenced by a crisis in numerous ways, from before, during, and after the crisis. According to Wang and Wang (20), tourists prefer to stay in low-cost hotels and rooms during economic uncertainty. When it comes to tourist demand in a recession, income and personal economic situation have little or no effect, according to Robaina-Alves et al. (46). They also noted that the European financial crisis did not deter Europeans from taking vacations. Middle-aged and experienced travelers, according to Zhang and Zhang (47), are less sensitive to a crisis than younger and less experienced travelers. No current evidence explains why tourists react differently when confronted with a crisis. However, the impact of a crisis on tourism varies depending on the type of visitor and their goals. According to Ming Cheng et al. (48), health crises (such as food security) are more important to first-time visitors than repeat visitors' financial risks, indicating a motivational divide between the two groups. According to Wieczorek-Kosmala (49), women are more concerned about their health and nutrition than men are. It has become more common for people to spend their vacations at home rather than going out to eat more often, buy more private labels, and entertain at home more often. According to Luo and Deng and Ramukumba (42, 44). From a broader perspective, the current state of the economy restricts tourists' ability to travel further.

These previous tourism crisis studies, on the other hand, neglected to take into account how crises evolve. In most studies, only the time of the crisis is examined, ignoring changes before, after, and during the disaster. Instead, they concentrate with respect to just one instance and how it affects the number of tourists. Crisis type, tourist profile, purpose, and pattern all play a role in how it affects tourist behavior. So, more research is needed to look at the impact of health crises and changes from a tourist's point of view.

In contrast to disaster, which is the result of action outside of the body that may have an immediate effect, “crisis” refers to incidents that are more closely tied to the company's environment (41). The tourism crisis is deeply rooted in economics, sociology, the environment, and politics. Both crises and disasters significantly impact the tourism industry regarding reduced tourist flow, travel plans by tourists, unemployment, and investment by businesses. Luo and Deng (42) also points out that a crisis occurs as a result of a failure to respond to a disaster. There has been a lot of attention paid to disasters and crises in tourism studies, but few studies have focused on the economic crisis. For example, a theoretical model that examines the connections between health crises (41), tourism competitiveness, and green financial development was developed recently (43, 50). It has been shown that tourism competitiveness is influenced by the health crisis when an economic crisis occurs in Spain (51, 52). No one knows much about the impact of disaster and crisis on tourism, particularly the evolutionary differences in tourist behavior caused by different crises, despite findings published by Korstanje and Tarlow (53).

Because of the uncertainty, disruption, and risk accompanying health crises (54), health crises alter behavior and normal tourism trends. With the recent Arab uprisings, tourism in the Middle East and North Africa was put at risk and negatively impacted tourism development. Arab uprising effects vary even among Mediterranean countries, as revealed by Atan and Arslanturk (55) in their study Puri et al. (56). There has been a significant reduction in tourism to the Middle East and North Africa as a result of the ongoing Syrian conflict (57). The crisis has a greater impact on inbound tourism than outbound tourism (58). For example, incoming tourism to the Middle East is still at risk due to the high probability of terrorist attacks. A crisis can significantly impact declining tourist numbers, the use of facilities at tourist destinations, and an imbalance between supply and demand.

For example, according to a study conducted in Turkey by Chen et al. (59), the growth of financial markets has a significant impact on tourism development and expansion. According to their empirical analysis, foreign direct investment and trade play a mediating role in the underlying connection between the tourism industry and economic growth, spanning 1960 to 2015. Also, in Malaysia, Lei et al. (60) found that tourism demand increased as a result of improvements in financial development while taking into account the country's structural data breaks. Çaglayan et al. (11) report mixed effects of China's economic development on the country's tourism growth in a study looking at how it affects both the sector's positive and negative outcomes. They found that financial development causes tourism growth. In contrast, Abdullah et al. (61) green tourism is directly linked to financial development and vice versa, based on data collected from 2000 to 2016.

A lack of research has examined how regional tourism demand has been affected by financial development, which includes several countries beyond the country level. For example, according to Feng et al. and Lv et al. (62, 95), the long-term demand for tourism to Japan, South Korea, and Singapore will be increased by green economic literacy, especially in the short term. Nabeeh et al. (63) Research has found a causal connection only in high-income countries in the United States but not Europe or Asia. The link is established between international tourism to financial services.

Finally, Punzi (64) observed the link between tourism specialization and economic expansion in one of the few reported studies that performed a panel analysis for a larger number of nations (129) over the timeframe 1995–2011. Their research examines whether this relationship is linked to a host country's financial development. As it turns out, green financial development lessens the link between tourism dependence and public health crises. Still, the benefits are diminishing in those countries with high levels of financial development, and a heavy reliance on tourism tends to suffer economic setbacks.

To the best of our knowledge, no studies have empirically examined the impact of financial inclusion on tourism development despite the body of literature on the topic expanding rapidly. As we mentioned in the introduction (65, 66), are the sole notable exception. Due to its similarity to our work, this paper deserves further discussion. At least two distinct dimensions must be considered when assessing financial sector development: financial sector depth and financial inclusion. A plethora of literature has already established this point. The former typically refers to a country's overall development in banking, equity, and bond markets. In contrast, the latter refers to the provision of access to and use of financial services. The failure of a Debrah et al. and Wang et al. (67, 68) to distinguish between these two dimensions implies that their results cannot differentiate between the effects of financial inclusion and the impact of the depth and efficiency of the green financial market.

This ambiguity necessitates establishing a link between economic growth and tourism demand can be seen. Academic studies have discovered a substantial change in macroeconomic and development outcomes between financial inclusion and depth or efficiency. This is important in light of these findings (69). Since there is still a significant gap in the literature on whether financial inclusion's unique effects influence tourism demand, it is important to address this issue in tourism development.

For this purpose, the following instrumental variable econometric model is used to analyze the health crisis's effect on tourism. The system GMM model is used to estimate our model. Unobserved nation impact, the endogeneity of control variables, the correlation between independent variables and past or possible current error realizations, and heteroskedasticity and autocorrelation within individuals are addressed by this assessor (70).

Estimates for international tourism receipts are made using the following model specification:

The dependent variable yit is a measure of the revenue received from tourists from outside the country; the lagged variable y (it-1) represents the lagged dependent variable; the vector zit contains control variables; the vector xit contains explanatory variables; and the error term, u it, includes the variables I and _it; random disturbance term _it; unobserved country-specific effects or fixed effects where is correlated with y (it-1). A first difference transformation of Equation (1) by Tolkach (71) eliminated the unobserved effects:

Taking the first Difference in Equation 2 involves:

The first operator of Difference is. There is a new bias that the differenced error term can be correlated with the lagged dependent variable after the first differencing. The system GMM estimator was proposed by Danish & Wang (72) and Phoochinda (73). In this system, A lagged first difference is used to instrument the explanatory variables and a level of one in between each of those variables, using two equations, one first-differenced and one in groups. For the system estimator to work, variables in levels and differences are both instrumented with the lags of their levels and vice versa. Level moment conditions in System GMM supplement the first differenced moment conditions of Difference GMM, as noted by Arzhang and Hamidi (74), for improved estimation efficiency. The System GMM estimation has two diagnostic tests to ensure its accuracy. There are two ways to test the validity of the instrument set: the Sargan test for over-identification and the Arellano–Bond (AR2) autocorrelation, both of which were proposed by Korstanje and Tarlow (53). Stata 16's System GMM estimation can be performed with the xtabond2 command Santana-Talavera and Fernandez-Betancort (75).

The empirical analysis is based on a cross-sectional dataset containing data from 97 developed and developing countries. The availability of data dictates the countries that are considered. This study incorporates data from a variety of sources, including the World Development Indicators (WDI), the World Travel and Tourism Council (WTTC) (WTTC, 2020), and the F.M. Global and Associates (F.M. Global and Associates, 2019) (2020).

Tourism: A country's tourism industry can be gauged using five different metrics: the amount of money spent on leisure travel, the amount spent on business travel, the amount of money spent on travel and tourism that goes directly into GDP, and the number of tourists who cross the country's borders (in millions). For the purpose of capturing the tourism variable, we use the international tourism receipts in US dollars expressed in current prices. based on the World Development Indicators published by the World Bank (WDI). Health crises measures: In this study, the outbreak of COVID-19 and previous non-COVID health crises are used to define health crises in a tourist destination country. WDI indicators are also used. This is in addition to OECD (2011) using COVID-based and non-COVID-based diseases to define a country's health crisis. Green financial development: Green financial development is also linked with better health conditions in any country. Green financial development means the inflow of investment to reduce the CO₂ emission in the environment. Financial wellbeing is necessary for businesses and health institutions to combat the COVID and non-COVID health crises for good health conditions. The number of COVID-19 deaths and cases that have been confirmed reveals the severity of the health crisis. Financial inclusion: It is possible to construct the financial inclusion (FI) index using information about the depth, accessibility, and efficiency of financial institutions and financial markets. In addition, the study takes into consideration three other important determinants of tourism development, including GDP; trade openness, which is measured using information on total trade in goods and services, and trading partners' diversity (exports and imports).

The System GMM estimation results of developing and developed countries are presented in Tables 2, 3. Each panel of developing and developed countries is subjected to six regression analyses, separately using the health feature variables. We also examine the impact of international tourism revenue on the rising quality of health in developed countries. Lagged variable for international tourism is positive and significant. International tourism have an important impact on achieving more international tourism. The findings of the study are in line with Su (76). Strongly positive and significant are the results of the variable. This implies that international tourism could rise as a consequence of a rising average lifespan or that an increase in life expectancy is correlated with an increase in revenue from international tourism. For developing countries, the findings shows that an increase in COVID_confirm_cases of 1 % will result in an decrease of 0.427 % in international tourism, while for developed countries, 0.406 % decrease in international tourist receipts. According to Pulicherla et al. (77), for medium and low-income countries, a country's average lifespan is an essential element of its safety.

This study found that a 1% decrease in COVID_deaths results in a 0.271% decrease in international tourism, while, the association among COVID_deaths and tourism is negative and statistically significant, a 1% increase in COVID_deaths, results in a 0.257% decrease in tourism in the developing countries. It shows the average lifespan is a significant and strong negative. International tourism revenue could be advanced in countries with a low mortality rate if they focus their hard work on reducing the death rate.

International tourism receipts are positively affected by the non-COVID variable. The risk of maternal death negatively impacts global tourism receipts over the course of one's life. Development countries' international tourism revenue will drop by 0.427%. Domestic government health expenditures have tourism revenues in emerging regions have a positive but not statistically significant influence. The government's spending on health care in developed countries has a considerable impact on the amount of money from international tourism. As a result, developed countries' high public health expenditures and high tourism revenues go hand in hand. Cui et al. (78) support this conclusion. For developing countries, the emission of CO₂ is a highly negative and significant variable. In other words, as the prevalence of malnutrition rises, international tourism revenue may fall. To attract more tourists and raise their income, developing countries must reduce the number of people living in poverty.

As a result, the health quality variable in developing countries is marginally negative but significant. In other words, a high death toll from tuberculosis hurts the country's ability to attract tourists from around the world. If the death toll from tuberculosis rises by 1%, international tourism revenues will fall by 0.0295%. The death toll from tuberculosis has a downbeat blow on international tourism revenue, but this is not statistically significant when comparing developed and developing nations. Negative and significant health quality components are the most important. This suggests that a decrease in international tourism receipts is linked to the decline in the quality of health in both developed and developing countries. Moreover, GDP, financial inclusion and financial development in most developed and developing countries have positive and significant on tourism. According to numerous studies, real GDP per capita has a positive impact on international tourism receipts (79).

Revenues from travel and tourism abroad in developing countries are positively impacted by trade openness, although in a small but meaningful way. International tourism receipts are expected to rise as a result of more significant free trade. Trade openness has a small but positive impact on international tourism receipts in developed countries, but it is still statistically significant. However, this is consistent with the findings of Feng et al., Ohajionu et al., and Rowan and Galanakis (62, 80, 81).

The relationship between worldwide trade and tourism revenues is weak but not important, as has been constantly observed by many previous studies. Lv et al. (96) and Sarangi (82) have found similar results. As a result of the perceived effect of exchange rates on tourism industry revenues, we expect to increase international tourism revenue. The supply chain of the “tourist destination” region is enhanced by a reduction in trade terms. Wage growth has a small but noticeable effect on foreign tourism revenue in developed and emerging economies. It's safe to say that the financial risk factor is both present and significant. As a result, developing and developed countries will see an increase in their revenue from international tourism when financial risk is lower. Because of this, reduced financial exposure should be a priority for all countries, developing and developed alike. Incorporating the 2008–2009 global economic crises as a model variable resulted in interesting empirical findings. The financial crisis dummy variable negatively impacts tourism receipts. So, it's safe to say that the recent global financial crisis has had an effect on travel to emerging markets. Research by Cui et al. and Wang and Zhi (78, 83) supports this.

Additionally, as a robustness check, we also examine the effect of additional control variables on our results. Our re-estimation of the main model takes into account the proportion of the population over 65, the log of population density, and the log of the urban population as a % age of the total population. The total number of confirmed deaths and cases was used instead of the fatality rate as an additional explanatory variable. Table 4 summarizes the findings from this experiment. The key explanatory variables show no significant shifts in their signs or significance. With the proportion of people over 65 and confirmed deaths, tourism has a positive and significant correlation (84).

It's also possible to make the case that a relative rather than an absolute indicator of the health of the tourism industry is preferable to look at. We double-checked using the ratio of tourists visiting a country i to the total number of tourists visiting all of our sample countries or the ratio of visitors to the country i to total tourists visiting by region for all the countries included in the sample robustness of our estimates. Logically, a country's tourism sector is more significant if the value of these ratios is > 0. Table 4 displays the exercise's outcomes. When it comes to signs and magnitudes, consistent with initial estimates, the variables of interest's limits are generally estimated in the same way.

Among the immediate concerns is the effect of COVID-19 on the geographic distance of travel. More than 70% of those polled said they wanted to travel more within the United States. Only a sliver of those surveyed said they wanted to travel more internationally. According to the research, 23.1% of people are increasingly interested in traveling alone, with women showing a slightly higher interest (25.0%) than men (20.8%). At the same time, most respondents (68.7 %) will use tourist intermediaries as before. Only 19.8 % and 11.5 % plan to decrease or increase their use in planning their trip.

Of those polled, 47% stated that they would continue to contract the same type of insurance before COVID-19, but 34.4 % stated their insurance needs had increased rather than decreased, while just 17% stated the opposite. It's also worth noting that women (38.0 %) have a higher proclivity than men (35.0 %) to obtain additional insurance (31.6 % ).

While most respondents (71.4 %) expect their vacations to be the same length as last year, a sizable minority (27.0 %) intend to cut back on their time away. As a result, 38.3% of respondents plan to alter their usual travel schedules. According to the gender of the respondents, there were significant differences in the results. 42.5 % of women would change their dates, compared to 33.0 % of men, in this situation. According to these findings, those willing to change their travel dates are remarkably similar in age and sex (2 = 11.904; p = 0.018) (see Table 2).

Pandemics have a negative impact on tourist arrivals in 97 countries. Only low-income countries are affected by this effect. Traveler arrivals are expected to fall by 2.1% for every 10% increase in the discussion about the pandemics index. When the pandemic is active, the index value rises dramatically, and countries that experience a drop in visitor numbers suffer economically. In addition, the impact of pandemics on fast and slow-growing tourism destinations will be different.

Because the world has never seen a pandemic of this magnitude, it is difficult to predict how COVID-19 will affect it. The governments are implementing travel restrictions and border closures. As a result, our findings from previous pandemics will only have limited utility in predicting the potential effects of COVID-19 on tourism. Using data from a single country or a group of countries on a quarterly/yearly basis, Tourist arrivals can be studied in future studies using the autoregressive distributed lag model to examine the short and long-term effects of pandemic outbreaks (85).

A statistically significant and positive effect on tourism arrivals is found, indicating that inbound tourism is persistent at a high level. In columns 7–9, the estimates are based on various income levels. The negative impact of pandemics on tourist arrivals disappears for emerging and advanced economies, and it remains only for low-income economies. There may be fewer tourists visiting low-income countries because of the lack of openness and inadequate health care facilities. The previous pandemics in recent history were confined to a small geographic area and caused far fewer deaths and illnesses than the coronavirus. As a result, the health systems of advanced and emerging economies could handle the pandemics. Travel bans and curfew restrictions were not widely implemented. On the other hand, Viruses have become more global in scope as a result of increased globalization. COVID-19-related deaths and infections are rising, and countries worldwide are enacting travel restrictions, quarantines, and curfews to stem the tide. A flattening of the COVID-19 curve is needed because the health care systems in nearly every country are on their way to failure. Because of this, Kleih et al. (86) argue that the impact of COVID-19 will be unique, making it difficult to extrapolate from previous experiences.

Tourist arrivals are positively correlated with GDP per capita in all estimations. Tourist arrivals increase as GDP per capita rises. Tourist arrivals increase when the exchange rate is favorable. The findings are consistent with previous research (85). Trade openness positively impacts tourist arrivals, implying that countries that integrate with the rest of the world are more likely to attract tourists. It is shown in Table 3 that pandemics have a long-term impact on tourism. For all estimates, there is no evidence of a lag effect. There were no long-term effects of the previous pandemics on tourist arrivals because they were short-lived.