Australian Tourist Flow: A Gravity Model Approach

Abstract

The primary aim of this study is to analyze the determinants of international tourist arrivals in Australia using a gravity model approach. Even though the gravity model is widely applied in tourism research, this method has not been used to analyze international tourist flow to Australia. Given the substantial economic impact of tourism globally, a deeper understanding of determining factors is essential for effective strategic planning and policy formulation within this sector. This research adopted a gravity model to evaluate various influencing elements, including GDP, distance, population size, migration stocks, and cultural similarities. This model facilitates the assessment of how these variables correlate with the influx of tourists to Australia. This study unveiled that factor such as GDP, migration ties, and cultural similarities significantly influence tourist arrivals. In contrast, distance and cost of living appeared to have a lesser impact, indicating that other elements may compensate for these deterrents. The findings suggest that economic prosperity and cultural ties are paramount in attracting international tourists to Australia. These results underscore the importance of targeted marketing strategies that leverage Australia’s cultural assets and economic strengths. Additionally, this study highlights the need for further research on how emergent factors, such as digital marketing and environmental sustainability, affect tourism. The broader implications of this research could inform future policy and marketing strategies in the tourism industry, enhancing its economic contributions while advancement of sustainable growth.

1. Introduction

The tourism industry is one of the fastest growing economic sectors in the world that have played a significant role in driving global economic growth. The contribution of tourism industry accounted for 9.1% of the global GDP [1]. The tourism industry’s inherent structure exhibits a multiplier effect on the economy that creates jobs, increases production, generates foreign revenue earnings and facilitates regional development. Over the years, Australia has attracted many visitors from all over the world because of its varied topography, biodiversity, and extensive cultural history. Before the COVID-19 pandemic, the travel and tourism sector employed 1.82 million people in Australia and contributed USD 154 billion to the national economy [1]. However, due to the pandemic and subsequent travel restrictions, the tourism sector in Australia was severely affected. Since 2023, the sector has gradually recovered, but its current status is still below the pre-pandemic level. Therefore, policymakers and industry stakeholders in Australia must understand the factors that determine the flow of tourists into the nation for the further development of the tourism sector.

In tourism research, the gravity model has been used extensively to analyze the variables that influence visitor flows between nations. This model conceptualizes visitor flows as being impacted by the economic scale of nations and the distance between such countries. It derives its inspiration from Newton’s law of gravity. It is an effective method of data analysis that helps in identifying the primary factors of bilateral tourist flow. The extended gravity model can also incorporate intricate intra-industry linkages and interactions of socio-economic factors essential for tourism flow.

A number of papers have applied the gravity model to study the factors that determine international tourism flows. In fact, quite a few papers have worked with Australian data, as well. However, to our knowledge, no study has incorporated exogenous global shocks like COVID-19 in a gravity model to analyze Australia’s tourist flow. More research is needed to focus primarily on Australian visitor flow in order to design focused marketing strategies that will help the tourism sector fully recover from the setback caused by COVID-19. This study aims to fill in this vacuum in the existing research by using a gravity model. First, this paper will provide insights into the fundamental elements that influence the flow of tourists to Australia. This will provide a fresh viewpoint on a location with distinct natural and cultural attractions. Secondly, the paper will shed light on the impact of global disasters like COVID-19 on tourism flow. The results will assist policymakers and industry players design precautionary policies to mitigate the impact of such economic and natural disasters in the future.

The remaining portions of this document are structured as follows: Section 2 represents brief overview of the Australian tourism industry. Section 3 provides literature review. The methodology and data collection procedures are discussed in Section 4. The empirical results are presented in Section 5. Section 6 provides conclusion that conclude with a summary of the most important results, a discussion of the consequences of those findings, and suggestions for further research.

2. A Brief Overview of the Australian Tourism Sector

Australia, also known as the “Land Down Under”, is a huge, diverse southern hemisphere nation. It is the world’s sixth-largest nation by land area, with 7.7 million square kilometers, and is bounded by the Indian and Pacific Oceans. Australia is known for its breathtaking natural vistas, including the renowned Sydney Opera House and the Great Barrier Reef, as well as the wide desert and ancient rainforests. Australia also has a diverse cultural legacy developed by Indigenous Aboriginals, British colonizers, and international immigrants. The Australian economy is highly developed and one of the wealthiest in the world. Mining, agriculture, manufacturing, and services are all critical industries. The flourishing Australian tourist industry is a crucial contribution to the economy.

The Australian tourist industry is an integral part of the country’s economy, providing employment, cash, and opportunities for cultural interaction. According to the World Tourist and Travel Council, Australia ranked 11th in the list of most popular tourist destinations in the world in year 2019. Before the pandemic, the tourism industry employed 748,200 people directly and twice as many in secondary industries and host communities through intra-industry linkages. In addition, tourism plays a vital role in the adoption of sustainable eco-tourism practices and infrastructural development in remote areas of Australia.

2.1. The Australian Tourism Industry and Air Traffic Flow

Air traffic flow is an essential indicator of the tourism industry’s performance since it reflects the movement of both international and domestic travelers to and from Australia.

The development of foreign airlines’ routes to Australia and the rising desire from Australian citizens to go overseas have aided the rise of air traffic flow throughout the years. Prior to the COVID-19 outbreak, Australia’s aviation passenger movements exhibited a constant rising trend, according to statistics from the Australian Bureau of Infrastructure, Transport and Regional Economics (BITRE). Total passenger movements reached a record 164 million in 2019, with foreign travelers accounting for a significant portion of this figure [2]. This consistent development reflected Australia’s appeal as a preferred destination for worldwide travelers.

The leading international airports in Australia, such as Sydney, Melbourne, Brisbane, and Perth, served as vital entry points for foreign travelers. Millions of passengers arrive and depart from these airports each year, promoting economic activity and cultural contact between Australia and the rest of the globe.

2.2. The Impacts of COVID-19 on Australian Tourism

The emergence of the COVID-19 pandemic in early 2020 had an unprecedented and devastating effect on the worldwide tourist sector, with Australia being one of the most severely impacted nations. Numerous travel restrictions, border closures, and quarantine procedures were put in place to stop the spread of the virus. The effects of the pandemic were felt across the travel sector, from airlines and hotels to tour operators, restaurants, and retail enterprises. Many businesses had financial difficulties, resulting in job losses and temporary closures. Domestic tourism suffered as state and territory borders were blocked on a regular basis in response to localized outbreaks.

As a consequence, aviation traffic into and out of Australia fell precipitously. International travel came to a halt as several nations locked their borders to prevent sick people from entering. According to the International Air Transport Association (IATA), international air travel demand fell by 98.1% in 2020 compared to the previous year [3]. The Australian government reacted quickly to safeguard public health by instituting severe border restrictions and travel prohibitions. As a result, passenger movements at the country’s main international airports decreased significantly, affecting airlines, airport operators, and various other tourism-related businesses. The closing of international borders resulted in a significant loss of incoming tourist earnings, which had a knock-on impact on the Australian economy. According to Tourism Research Australia, the predicted loss in foreign tourist expenditure during the epidemic was billions of euros [2].

Figure 1 demonstrates the Australian tourist flow among various locations before and after the COVID-19 pandemic. The countries include Brunei, Canada, Chile, China, Fiji, Hong Kong (SAR), India, Indonesia, Japan, Korea, Malaysia, Mauritius, New Zealand, the Philippines, Qatar, Singapore, the Solomon Islands, South Africa, Sri Lanka, Taiwan, Thailand, Tonga, the UK, the United Arab Emirates, the USA, and Vietnam.

The Australian government launched several economic stimulus programs, financial aid, and targeted assistance measures to help the suffering tourist industry. These measures attempted to assist firms in remaining solvent, retaining employment, and preparing for the future reopening of international borders when it was safe. Despite the difficulties, Australia’s tourist industry displayed tenacity and adaptation. Many tour companies turned their attention to domestic travelers, emphasizing local travel experiences and distinctive sites inside the nation. As the globe steadily recovers from the epidemic, Australia’s rich natural and cultural attractions are also prepared to capture travelers once again and contribute to the country’s tourist sector’s rebirth.

3. Literature Review

The existing research on the tourist flow is quite extensive. By synchronizing the recent literature based on the determinants of tourist flow, positive impacts of tourism, economic benefits, and cultural implications, this paper incorporates a comprehensive analysis to explore the determinants of tourist flow. The literature review is organized into the following two sections: The first segment discusses studies that have attempted to identify the determinants of tourist inflow. The second segment reviews papers that analyzed the impact of various exogenous shocks, including COVID-19, on the tourism industry.

3.1. Determinants of Tourist Inflow

The income level of people from both the destination and origin country plays a significant role in tourism inflow, as people travel more and engage in leisurely activities during prosperous times [4]. Gross domestic product (GDP) is widely used in this regard to assess the economic condition of a country or region. In addition, different studies described that personal income can influence international tourism expressively. The authors found that there has been a positive association between personal income and tourism behavior. In addition, another study on GCC countries highlighted that income level escalation influences residents engaging in international travel [5,6].

A negative relationship between distance and inbound tourism demand is quite evident in the existing literature. A greater geographical distance between nations tends to deter tourism flows due to higher traveling costs and time. This highlights the role of space as a barrier to travel and suggests that proximity plays a significant role in tourism demand [7]. Likewise, another study on Turkey reveals a negative association between distance and tourism demand. Countries closer to Turkey tend to generate higher tourist flows, indicating the influence of proximity on travel decisions [8]. Additionally, islands and geographically isolated destinations experience lower tourist arrivals than mainland destinations [9].

International migration to a country can also influence its tourist inflow and vice versa, indicating that these two phenomena are interrelated and mutually reinforcing. A migrant community from a particular country in a destination country was correlated with increased tourist arrivals from that country [10,11]. Moreover, focusing on EU28 countries, a study found that migrants can act as a bond between their home countries and their host countries, attracting visitors from their home countries to visit them. Furthermore, another study on EU member states highlighted that the contribution of human migration, specifically VFR travel (visits made by individuals to their friends and relatives residing in another location), positively impacts destination economies [12]. Also, it promotes cultural tourism and attracts visitors interested in experiencing different cultures [13].

Moreover, common cultural factors, such as colonial origin, language, and religion positively impact bilateral international tourist flows [14]. Countries sharing the same official language exhibited higher tourism flows due to improved communication and reduced language barriers [15]. Another study also confirmed that shared languages can enhance communication, cultural exchange, and familiarity, which positively influence tourism flows [16]. Similarly, another study on GCC countries implies that cultural similarities between GCC countries and potential destinations positively influence outbound tourism. Nevertheless, cultural differences also shape tourism patterns, suggesting that cultural factors still influence tourists’ destination choices [17].

Moreover, it has also been emphasized that tourist arrivals or expenditures are a better indicator for predicting and understanding tourism demand [18]. Nevertheless, currency fluctuations and exchange rates can affect tourism demand [19]. Another study also investigated the influence of exchange rates on tourism demand, as exchange rate fluctuations can affect travel costs [20]. However, a favorable exchange rate and a solid economic performance positively affect international tourist arrivals [21,22,23].

The tourism industry is particularly susceptible to seasonal effects. A study revealed that both temperature and precipitation had a considerable impact on the number of tourist arrivals. For instance, temperature strongly impacted tourist arrivals during summer, while rainfall played a more prominent role in the shoulder seasons [24]. Another study highlighted the concentration of tourist arrivals during specific months and the challenge of attracting visitors during off-peak periods. The research identified several factors, including climatic conditions, cultural events and festivals, school holidays, and marketing efforts, contributing to tourism seasonality [25].

3.2. Impact of COVID-19 on the Tourism Industry

Several studies investigated the negative impacts of exogenous shocks on international tourist arrivals. In a recent survey, it was posited that extreme weather conditions (excessively hot or cold temperatures, heavy precipitation) had a more pronounced impact on tourism demand than moderate variations. Likewise, various types of natural disasters, such as hurricanes, earthquakes, floods, and volcanic eruptions, lead to a decline in tourist arrivals in affected destinations [26]. Moreover, air pollution can act as a deterrent to international tourists. Another paper found that higher levels of air pollution, represented by PM2.5 concentration, are associated with reduced tourist arrivals to China [27].

Quite a few papers have analyzed the effects of the COVID-19 pandemic and the unprecedented challenges it posed. A qualitative study analyzed the impact of COVID-19 on the Australian economy by summarizing government policies and socio-economic responses [28]. Using a computable general equilibrium (CGE) model, a paper has analyzed the short-term impact of COVID-19 on inbound tourism in Australia and estimated an abrupt increase of between AUD 39 and AUD 42 billion in GDP [29]. Another paper has analyzed the asymmetric impact of COVID-19 tourist inflow between China and Australia using a non-linear auto-regressive lag distribution model. The results suggest that the impact of positive change in policy uncertainty is more prominent than negative uncertainty [30]. However, no paper has applied the gravity model to assess the impact of COVID-19 in Australia.

Nonetheless, the gravity model has been used extensively in country-specific and regional studies to assess the impact of COVID-19. A paper analyzed the impact of COVID-19 on tourism using panel data from selected Asia-Pacific countries and found that on average, tourism inflow decreased by 0.689% compared to pre-pandemic periods [31]. Another study analyzed data from Indonesia using the gravity model and found that COVID-19 had a negative and significant effect on Indonesia’s tourist demand [32]. In order to assess China’s domestic tourist demand before and after the COVID-19 pandemic, another group of researchers also applied an extended gravity model [33].

In addition to providing insights into the magnitude and duration of the impact on tourism demand, a recent study highlights the necessity of implementing effective crisis management strategies. The paper emphasized the importance of enhancing health-related infrastructure and communication and developing targeted recovery plans to rebuild tourism demand [7]. Likewise, a paper also investigated the global nature of the pandemic and the broader implications it has had on tourism. Their analysis found the pandemic’s effects on international tourist arrivals [34].

The COVID-19 pandemic was associated with economic uncertainty due to restriction measures such as containment, lockdown, and job cuts. A study finds that higher levels of economic uncertainty are associated with decreased tourism demand, as individuals and households become more cautious about their travel expenditures during uncertain times. Similarly, uncertainties related to travel arrangements, destination characteristics, unfamiliar cultural environments, personal safety, health concerns, financial risks, and socio-political stability also affect tourists’ decision-making [35,36,37].

In addition, higher levels of political risk, including political instability, corruption, and social unrest, hurt tourism development [38]. In addition to armed conflict, military expenditure also affects tourism arrivals negatively. A study indicates that countries experiencing armed conflicts tend to attract fewer tourists due to safety concerns, perceived risks, and disruptions to tourism infrastructure and services [39]. Moreover, terrorism incidents have a negative impact on tourism demand. Both international and domestic tourist arrivals in Kenya are significantly affected by acts of terrorism. Tourists exhibit heightened sensitivity to security concerns and are likelier to avoid destinations with a history of terrorist incidents [40].

Apart from distance, spatial spillover due to shared borders can also positively impact tourism flow. The presence of spatial spillover effects influenced China’s outbound tourist flow to the Silk Road destinations [41]. Another study confirmed that visitor flows to one attraction can positively influence the popularity and demand for neighboring attractions. The control variables, such as attraction characteristics (e.g., size, uniqueness), accessibility measures (e.g., transportation infrastructure, travel time), and socio-economic factors (e.g., population, income levels) interacting with visitor flows, further shape the spillover effects [42]. Likewise, socio-demographic factors, destination image, and marketing, infrastructure and accessibility, and push and pull factors are some important determinants that also influence international tourist flows [43,44,45]. In addition, factors such as travel costs, income levels, transportation networks, accommodation, food, population, size, and destination attractiveness exhibit varying degrees of influence on tourist flows [46,47].

Moreover, the “multilateral resistance to tourism” concept highlighted that destination attractiveness is crucial to tourists’ travel decisions. This analysis reveals that tourists are more likely to choose beautiful destinations and exhibit a “pull factor”, thereby influencing the overall tourism flows [48,49]. Furthermore, another paper emphasized the importance of these factors contributing to tourism competitiveness and their impact on the overall performance of the tourism sector [50]. Also, another study in Australia found that tourism expenditure, employment, value-added, resource efficiency, visitor satisfaction, and community well-being enhance tourism productivity [51].

In addition, happiness can also be an essential indicator of tourism growth; another paper found that happiness influences tourism decisions. It explained that higher happiness levels were associated with increased tourism demand, suggesting that individuals with higher subjective well-being are more likely to engage in travel and tourism activities [52].

In addition, some determinants of inbound tourism, such as economic factors, geographic factors, travel restrictions, exchange rates, air connectivity, and cultural similarities, are key drivers of tourism demand [7,53]. Similarly, another study on small island developing state (SIDS) countries described those factors, including GDP per capita, population size, air connectivity, distance from source markets, and political stability, significantly affecting tourist arrivals [54]. In addition, some more determinants include economic growth, inflation, oil prices, transportation costs, and political stability, which also affect the arrival of international tourists [55,56]. In addition, some trust elements, including perceived safety, perceived attractiveness, destination image, prior experience, and familiarity with the destination, also play a significant role in shaping tourists’ trust toward goals [57].

Moreover, cultural heritage sites create a unique appeal for tourists. Their global recognition, historical significance, and cultural appeal significantly stimulate visitor numbers [58]. Likewise, focusing on Italy, a study indicates that certain regions in a particular country can be more attractive to tourists based on natural landscapes, cultural heritage, infrastructure, and services [59,60]. Additionally, it has been reported that having more memorable experiences is more likely to exhibit positive behavioral intentions among tourists, including revisiting the destination, recommending it to others, and engaging in positive word-of-mouth [61].

In addition, flight availability can be another important determinant for international tourism. In a study, it has been highlighted that increases in seat capacity are associated with higher numbers of tourist arrivals, indicating a positive relationship between flight availability and international tourism flows [62]. Additionally, the availability of low-cost flights increases accessibility and affordability, attracting more tourists to the destination. Hence, low-cost carriers significantly stimulate visitor arrivals and expand the tourism market [63]. Nevertheless, another paper claimed that market characteristics, economic conditions, infrastructure availability, and regulatory frameworks could be challenging for air freight transportation [64].

In addition, several journals have studied the impact of ICT and infrastructure development in the tourism sector. Another group strongly believes that there is a positive association between ICT development and tourism growth in Africa. Improved access to ICT, including internet connectivity and mobile phone usage, contributes to enhanced information dissemination, marketing, and communication within the tourism sector, attracting more tourists. Likewise, improvements in tourism-related infrastructure, such as the expansion of hotel capacity and the enhancement of transportation facilities and recreational amenities, contribute to increased tourism demand and attract more international visitors to urban destinations [65,66].

Hence, these dynamics bring the substantial direct and indirect economic benefits that tourism generates. Some immediate economic benefits generated by tourism include employment creation, income generation, foreign exchange earnings, and tax revenue. Similarly, some indirect economic advantages for related industries are generated, such as agriculture, manufacturing, and services, and the potential for stimulating entrepreneurship and investment [67]. Moreover, these features impact knowledge exchange and collaboration among tourism stakeholders by creating favorable tourism features [68]. In addition, an interesting study found that panda diplomacy initiatives, such as the loaning of pandas to other countries, are associated with increased interest and visitation from Chinese tourists. The presence of pandas in host countries serves as a symbolic attraction and motivates Chinese tourists to visit [69].

Overall, adding to the current literature, this paper gives new insights about Australian tourism from a novel viewpoint. In addition, using a gravity model, we aim to fill the research gap by examining the variables influencing the number of tourists that visit Australia. Additionally, this study not only contributes to the refinement of gravity models in the context of Australian tourism but also sheds light on the intricate interplay between various determinants of tourist flow. Moreover, going beyond conventional models, this study commences a nuanced examination of the impact of the COVID-19 period, allowing for a dynamic understanding of the tourism landscape.

4. Empirical Methodology

4.1. Model

The gravity model was applied widely to describe a variety of macroeconomic variables, including tourist revenues and cross-border migration, among other things [4].

Our empirical model of tourist flow that was constructed using the gravity framework and was based on the method suggested the fundamental paradigm for tourist flow to Australia from partner countries, denoted by “i” (home country) and “j” (partner country), is as follows:

$${TouristFlow}_{ijt}=\frac{{{\beta }_{0}GDP}_{it}^{{\beta }_1}{GDP}_{jt}^{{\beta }_2}}{{Distance}_{ij}^{{\beta }_3}}{\epsilon }_{ijt}$$

(1)

The model assumes that tourist flow is directly proportional to home and partner countries’ GDP and inversely proportional to distance. Taking natural log on both sides, Equation (1) can be rewritten as

$$\begin{array}{c}ln{TouristFlow}_{ijt}\\ ={\beta }_0+{\beta }_1\ln {GDP}_{it}+{\beta }_2{lnGDP}_{jt}+{\beta }_3\ln {Distance}_{ij}\\ +{\epsilon }_{ijt}\end{array}$$

(2)

Here, ${TouristFlow}_{ijt}$ = tourist flow to home country i from country j at time t, ${GDP}_{it}$ = GDP of country i (home country at time t, ${GDP}_j$ = GDP of country j (partner country) at time t ${Distance}_{ij}$ = distance between country i and j, and ${\epsilon }_{ijt}$ is the random error term.

Since the paper deals with tourist flow to Australia (home country) from its partner countries, we can incorporate “i = 1, 2 … 36” into the equation. The model can be further extended using a set of suitable control variables $X_{ijt}$.

$$\begin{array}{c}ln{TouristFlow}_{ijt}\\ ={\beta }_0+{\beta }_1\ln {GDP}_{it}+{\beta }_2{lnGDP}_{jt}+{\beta }_3\ln {Distance}_{ij}\\ +\phi X_{ijt}+{\epsilon }_{ijt}\end{array}$$

(3)

To extend the gravity model of tourist flow, first, we take a standard set of gravity control variables like population, contiguity, common language, and shared colonial history from the Dynamic Gravity dataset (Gravity Portal: Dynamic Gravity Dataset (n.d.)). Since determining the effect that COVID-19 has on the tourist flow is our primary aim, the first thing that we do is include a COVID-19 dummy into the gravity model. The COVID-19 dummy variable is assumed to have a value of 0 for periods that occur before the COVID-19 breakout, and it is assumed to have a value of 1 for periods that occur after the COVID-19 breakout. In addition to this, we also performed estimations using the following explanatory variables: number of confirmed COVID-19 cases, number of COVID-19 deaths, and the rollout of vaccinations in both the origin and destination countries. The extended linear models can be written as follows:

$$\begin{array}{c}ln{TouristFlow}_{ijt}\\ ={\beta }_0+{\beta }_1\ln {GDP}_{it}+{\beta }_2{lnGDP}_{jt}\\ +{\beta }_3\ln {Distance}_{ij}+{{\beta }_{4}lnMigS}_{ijt}+{\beta }_{5}Covidt\\ +{{\beta }_{6}CovidCases}_{it}+{{\beta }_{7}CovidCases}_{jt}+\phi X_{ijt}\\ +{\mathsf{\eta }}_{ijt}\end{array}$$

(4)

$$\begin{array}{c}ln{TouristFlow}_{ijt}\\ ={\beta }_0+{\beta }_1\ln {GDP}_{it}+{\beta }_2{lnGDP}_{jt}\\ +{\beta }_3\ln {Distance}_{ij}+{{\beta }_{4}lnMigS}_{ijt}+{\beta }_{5}Covidt\\ +{{\beta }_{6}CovidMortality}_{it}+{{\beta }_{7}CovidMortality}_{jt}\\ +\phi X_{ijt}+{\mathsf{\eta }}_{ijt}\end{array}$$

(5)

$$\begin{array}{c}ln{TouristFlow}_{ijt}\\ ={\beta }_0+{\beta }_1\ln {GDP}_{it}+{\beta }_2{lnGDP}_{jt}\\ +{\beta }_3\ln {Distance}_{ij}+{{\beta }_{4}lnMigS}_{ijt}+{\beta }_{5}Covidt\\ +{{\beta }_{6}Vaccination}_{it}+{{\beta }_{7}CovidVaccination}_{jt}\\ +\phi X_{ijt}{+\mathsf{\eta }}_{ijt}\end{array}$$

(6)

$$\begin{array}{c}ln{TouristFlow}_{ijt}\\ ={\beta }_0+{\beta }_1\ln {GDP}_{it}+{\beta }_2{lnGDP}_{jt}\\ +{\beta }_3\ln {Distance}_{ij}+{{\beta }_{4}lnMigS}_{ijt}+{\beta }_{5}Covidt\\ +{{\beta }_{6}Vaccination}_{it}+{{\beta }_{7}CovidRestrictions}_{jt}\\ +\phi X_{ijt}{+\mathsf{\eta }}_{ijt}\end{array}$$

(7)

4.2. Data and Variables

We use air traffic flow to figure out the monthly statistics on tourist flow to Australia from its partner countries (January 2018 to May 2022). Monthly Industrial Production Index (IPI) statistics are used as an alternative to monthly GDP data as a proxy for GDP. This is because monthly GDP data is not available. The International Monetary Fund (IMF) gathered monthly IPI data from International Financial Statistics. IOM is where migration statistics are collected. The Dynamic Gravity datasets created by the United States International Trade Commission are used to determine distance and standard gravity control factors like population, contiguity, common language, common colonial origin, etc. According to the data [70] on cases, deaths, and vaccinations for COVID-19 are gathered from the Our World in Data website. To identify the COVID-19 pandemic phases, a COVID-19 dummy is created. Pre-COVID-19 periods (January 2018–January 2020) are indicated by the reference dummy 0. Periods of the COVID-19 pandemic (February 2020 to May 2022) are denoted by 1.

5. Result and Discussions

5.1. Interpretation of PPML Estimation

The results of Poisson pseudo-maximum likelihood (PPML) estimations are presented in Table S1. LN_GDPD represents the natural logarithm of the destination country’s gross domestic product (GDP). The coefficient values (2.767, 2.909, 3.103, 0.917) indicate that an increase in the destination country’s GDP is associated with an increase in Australian tourist flow. The coefficients are statistically significant at a 1% significance level, suggesting a strong relationship between GDP and tourist flow. As the economic condition improves, more foreign tourists can afford to travel to Australia. The LN_GDPP variable represents the natural logarithm of the GDP per capita of Australia. The negative and statistically significant coefficient values (−0.0586, −0.0583, −0.0592, −0.0519) suggest that a higher GDP per capita is associated with a decrease in Australian tourist flow. The tourism policy of the Australian government is one of the reasons behind this negative relationship. When the Australian economy is doing well, fewer foreign tourists are allowed in the country for sustainability purposes. However, during economically tough times, the Australian government provides various incentives and tour packages to attract foreign tourists to boost the national economy.

However, contrary to some studies, our findings suggest that distance does not have a statistically significant impact on tourist inflow in Australia. This occurrence can be attributed to the unique geographical location and attributes of the Australian tourism market. Geographically, Australia is separated from the rest of the world by the Great Pacific Ocean. Its exotic biodiversity, natural beauty, and unique attractions may offset concerns about distance and traveling costs. Australia is a classic example of a tourist destination that shows how unique attractions and destination branding can mitigate the negative impacts of geographical distance.

LN_Mig_D represents the natural logarithm of the migration stock of the destination country from Australia. The positive and statistically significant coefficient values (0.00944, 0.00932, 0.00827, and 0.00699) suggest that as more Australian people migrate to other countries, Australian tourist flow increases. It seems logical because being of Australian origin, it is easier for them to visit Australia. Interestingly, we observe a negative coefficient (−0.00921, −0.00875, −0.00699, −0.00961) between migration to Australia and tourist inflow. The coefficients are statistically significant. Since Australia has strict visa policies for foreigners, friends and family members of immigrants cannot visit Australia as easily. Most of the time, it is the immigrants who visit their home countries, resulting in a negative correlation.

LN_T_POP_D represents the natural logarithm of the population of the destination country. The coefficient values (−2.054, −1.268, −0.553, −0.00495) suggest that a larger population in the destination country is associated with a decrease in Australian tourist flow. However, the coefficients are not statistically significant, indicating that the population may not substantially impact tourist flow. LN_TPOP_P is the natural logarithm of the people of the origin country. The positive coefficient values (0.0246, 0.0262, 0.0260, 0.0276) suggest that a larger population in the origin country is associated with increased Australian tourist flow. The coefficients are statistically significant, indicating a positive relationship between people and tourist flow.

COL variable represents the cost of living in the destination country. The coefficient values (0.0222, 0.0264, 0.0272, and 0.0208) suggest that a higher cost of living in the destination country is associated with increased Australian tourist flow. However, the coefficients are not statistically significant, indicating that the cost of living may have little impact on tourist flow.

Common language plays a significant impact on tourism flow. It shows that Australia experiences lesser tourist inflow (−0.00125, −0.00120, −0.00136, −0.00114) from countries that do not share a common language with Australia than countries that have a shared common language.

Most importantly, the COVID-19 dummy is negative and statistically significant in all four versions of the model we have run. This implies that the extended gravity model successfully captured the negative impact of COVID-19 on Australian tourist inflow. The results imply tourist inflow in Australia decreased by (−0.276%, −0.288%, −0.296%, and −0.0276%) during the COVID-19 pandemic period.

The additional COVID-19 measures that we have used generated mixed results. We must understand that the COVID-19 cases and COVID-19 mortality variable will not have a direct impact on tourist inflow, as Australia was one of the countries that imposed the maximum border restriction, containment, and isolation measures, regardless of the COVID-19 situation in the country. Therefore, among the four measures, a strong lockdown and restriction policy taken by the government (COV_STR) seemed to have the most severe impact. Vaccination rollout in partner countries had a positive impact on tourism inflow. Our estimations show that as vaccine rollout in destination countries increased by 1%, tourist inflow increased by 1.99 × 10⁻⁹. This implies that the mandatory vaccination policy played a significant role in the tourism sector’s recovery.

5.2. Robustness Check

In addition, we conducted an OLS estimation to check for robustness, and the results are presented in Table S2. Since the tourism industry has a strong seasonality component, we ran another regression with a fixed effect and month dummy. The results are presented in Table S3. As expected, the time dummy is statistically significant, which implies the presence of a seasonal effect on tourism inflow.

Both the methodology-generated results are consistent with the estimations derived using the PPML methodology. The results provide robust support for the relevance of GDP, migration ties, and cultural similarities as significant determinants of international tourist arrivals in Australia. In addition, the COVID-19 dummy once again reiterates the negative impact of COVID-19 on the tourism sector in Australia. The estimations of COVID-19 vaccination and COVID-19 restrictions are also consistent with the PPML estimations.

6. Conclusions and Policy Recommendations

Using a gravity model as our method, the purpose of this research was to analyze the factors determining the number of tourists visiting Australia. We tried to understand the primary forces responsible for the flow of tourists to Australia by researching a wide variety of economic, demographic, and sociocultural issues. The results contribute to academic research and practical implications for policymakers and industry stakeholders. Both sets of audiences may benefit from these contributions. The assessment of the gravity model yielded some notable findings on the factors that determine the flow of tourists to Australia. A destination country’s GDP was shown to influence the number of tourists that visited that country favorably. This indicates that as the economic size and wealth of the destination country increase, more visitors are drawn to Australia. Secondly, the migration rate has a positive impact on both the country of origin and the country of destination. Thirdly, the diaspora population is another driving force behind improved tourism between nations. Nevertheless, distance did not turn out to be a statistically significant factor in tourism in Australia. Hence, physical proximity might play a minor role in visiting Australia.

However, determinants like accessibility and transportation infrastructure might lessen the effect of physical distance. In addition, it was shown that the cultural similarities between countries had a statistically significant impact on the flow of tourists. These finding also suggests that shared cultural characteristics and interests affect travel choices.

The results of this research have significant repercussions for the decision-makers and industry stakeholders engaged in the marketing and administration of Australian tourism. The following is a list of policy proposals that have been presented based on the identified determinants:

(a)

Economic Policies: Governments should prioritize programs that seek to improve the economic well-being of the country to which they export their goods. This involves activities such as promoting economic development, improving infrastructure, and developing a favorable business climate to attract more visitors. In addition, there should be efforts made to enhance the accessibility of tourist-related services and goods, as well as their capacity to compete in the market.

(b)

Engaging the Diaspora: Because migration stocks have a beneficial impact on tourism flows, officials should seriously consider developing focused marketing tactics that involve and use diaspora groups. The marketing of Australia as a preferred destination among these groups may be facilitated through collaborative efforts such as cultural festivals, exchange programs, and community-based tourism projects. These kinds of projects can be found in Australia.

(c)

Marketing and Branding: The findings show the need to present Australia’s distinctive cultural history and natural attractions to prospective visitors. This is especially important because Australia has many natural attractions. Marketing initiatives have to center on presenting the varied landscapes, native cultures, and culinary traditions of the nation, as well as the abundant animals. Increased exposure and the ability to appeal to a wider variety of travelers may be achieved via partnerships with foreign travel agents, airlines, and internet platforms.

(d)

Connection and Infrastructure: Since distance was not identified as a critical factor, officials could focus on enhancing relationships and transportation infrastructure to make it simpler for people to visit Australia. Increasing visitor arrivals may be helped by improving air connections and airline routes and streamlining the visa application and approval procedure.

(e)

Collaborative Partnerships: To build comprehensive tourist policies, governments and other players in the sector should work together to foster partnerships. In this context, “collaboration” refers to working with the commercial sector, tourist boards, travel agencies, and local communities to guarantee sustainable tourism practices, destination management, and the preservation of natural and cultural assets.

(f)

Research and Monitoring: To effectively modify policies and plans, the continuous monitoring of tourist trends, market dynamics, and developing consumer preferences is vital. It is essential to invest in research and data collecting to obtain insights about developing tourist habits and preferences, making it easier to make decisions based on facts.

Even though this research contributes to our understanding of the factors that determine the number of tourists that visit Australia, it is essential to note that it has significant limitations. To begin, the gravity model method considers just a fraction of the potential variables that influence the flow of tourists. Other unobserved factors may play a part in the phenomenon. In a further study, it could be worthwhile to investigate the possibility of including other factors, such as currency exchange rates, levels of political stability, the image of the destination, and the amount spent on marketing.

The second primary emphasis of the research was on the arrival of tourists to Australia. The study of outbound tourism from Australia would give a complete knowledge of the tourist flows between countries and the reciprocal impacts between nations.

In conclusion, for policymakers and other industry stakeholders to establish successful strategies for supporting sustainable tourism development, they need to have a solid grasp of the factors that determine the flow of tourists to Australia. This research gives unique insights into the elements that determine visitor flows to Australia. These findings also have practical implications for policy formation, marketing, and the administration of tourist destinations. Australia can position itself as an appealing and competitive tourist destination in the global market if it follows the recommendations about the policies to be implemented and continuously monitors tourism trends.