Document Type : Research Paper
Authors
PhD student in Tourism, Allameh Tabataba'i University, Tehran, Iran
Abstract
Tourism is one of the largest economic activities worldwide, with a significant share in employment and countries’ GDP, attracting policymakers’ attention in recent decades. According to global reports, in 2019, this industry directly and indirectly supported over 10 percent of global jobs. Iran, with its climatic diversity and rich cultural-historical heritage, has high potential to benefit from tourism. However, the development of inbound tourism is influenced by various factors whose identification can assist effective policymaking. This study, using the gravity model and panel data, examines the economic and non-economic factors affecting foreign
tourist attraction to Iran from 2000 to 2020. Key variables include per capita GDP, population density, geographical distance, relative pollution, exchange rate, and linguistic and religious commonalities. Results show that per capita GDP, population density, exchange rate, and shared religion have a significant positive impact on tourist attraction with 99% confidence, and common language with 90% confidence. Geographical distance has a significant negative effect with 99% confidence, indicating that as distance increases, tourists’ willingness to travel decreases. These findings are consistent with the gravity theory of tourism. Therefore, focusing on neighboring countries with greater cultural and religious similarities and shorter distances, along with developing pilgrimage tourism, can be an effective strategy. Overall, a combination of economic and non-economic factors shapes the pattern of inbound tourism demand to Iran, and based on this, policy recommendations for sustainable development are proposed.
Introduction
After the COVID-19 pandemic, the tourism industry has witnessed remarkable growth and plays a vital role in the global GDP. Besides its economic importance, tourism significantly contributes to promoting peace, cultural exchange, and sustainable development. Despite Iran’s rich cultural, historical, and natural diversity, the country has not fully utilized its potential in attracting international tourists. Data from 2024 show an increase in inbound tourists, mainly from neighboring countries. This study aims to investigate the factors influencing inbound tourism development in Iran using the gravity model.
According to this model, factors such as GDP per capita, population density, geographical distance, air pollution levels, exchange rates, shared language, and shared religion are key determinants in attracting tourists. These variables impact tourism flows through economic, cultural, and geographical dimensions. Analyzing these factors can help policymakers design more effective strategies to boost tourism development and improve Iran’s position in the international tourism market.
Methods and Material
This study aims to identify and analyze factors affecting inbound tourism development in Iran using a panel gravity model. The sample includes 19 countries: Afghanistan, Armenia, Azerbaijan, Bahrain, China, Germany, Georgia, India, Italy, Iraq, Kuwait, Lebanon, Oman, Pakistan, Russia, Saudi Arabia, Turkey, and Uzbekistan, considering Iran as the destination country. Based on previous research, the explanatory variables are GDP per capita, population density, geographical distance, relative pollution (CO₂ emissions), exchange rate, common language, and shared religion, with inbound tourist arrivals as the dependent variable. Data from 2000 to 2020 are used. The study employs a panel data approach, combining cross-sectional and time-series data, which offers advantages like higher variability, more degrees of freedom, and efficiency.
Gravity models are widely used in trade economics to assess bilateral flows, which is applicable here given tourism’s service-trade nature. The econometric modeling involves testing fixed effects and random effects through the F-test and the Hausman test. The gravity model equation is log-linearized, using GDP per capita and population size instead of GDP levels.
Geographical distance reflects transport costs between countries. The final model structure is based on Anderson (2011) and other studies, considering economic mass and distance as key determinants. This methodological framework allows a dynamic analysis of tourism inflow factors and offers robust insights into policy-making for enhancing Iran’s tourism sector.
Results and Discussion
The study analyzed the factors affecting the development of inbound tourism in Iran using a panel gravity model. Descriptive statistics for the variables under study were presented in Table 1. According to Table 2, the average number of foreign tourist arrivals in Iran was 1,874,896, with a minimum of 28,000 and a maximum of 2,635,488. The average per capita GDP for the available data was $10,982, with a minimum of $0 and a maximum of $55,494.
The average population density was 215.11 people per square kilometer, with a minimum of 7.32 and a maximum of 2,181.51 people per square kilometer. The average geographic distance from Iran was 2,298.39 km, ranging from 0 km (for the reference country, Iran) to 6,410 km.
Regarding shared language, countries like Afghanistan, Pakistan, and Uzbekistan share a language with Iran, while 16 other countries have minimal language overlap. Countries such as Afghanistan, Azerbaijan, Bahrain, Iraq, Kuwait, Lebanon, Oman, Pakistan, and Uzbekistan share religious beliefs with Iran. The Chow test confirmed that the data follow a panel structure, with a significant F-statistic of 261.97, supporting the rejection of pooled effects (OLS) and accepting fixed effects.
The Hausman test further supported random effects. Tests for heteroscedasticity and autocorrelation showed that variance homogeneity and lack of serial correlation were valid assumptions. The VIF results indicated no multicollinearity between explanatory variables.
The final estimation results, based on random effects, showed that variables such as GDP per capita, population density, exchange rates, and shared religion had a significant positive impact on inbound tourism, while geographic distance negatively affected tourism. Specifically, a 1% increase in GDP per capita could increase tourist arrivals by 125.52%, a 1% increase in population density could increase arrivals by 0.369%, and a 1% decrease in geographic distance could lead to an 82.96% increase in tourism. On the other hand, air pollution (CO2 emissions) was not significant. Overall, the findings suggest that improving economic factors (e.g., GDP per capita), population density, favorable exchange rates, and religious and language similarities can increase tourism, while greater geographic distance poses a barrier.
Conclusion
This study examines the factors influencing inbound tourism development in Iran using the gravity panel approach. Key variables such as GDP per capita, population density, geographic distance, relative pollution, exchange rates, common language, and common religion from 2000 to 2020 for 19 countries were considered.
The results revealed that GDP per capita, population density, exchange rates, and common religion positively impact foreign tourist attraction to Iran. Geographic distance had a negative effect on tourism, confirming the gravity model in the tourism industry. Iran, with its rich history and civilization, has the potential to attract tourists. Major obstacles to tourism development in Iran include economic instability, lack of tourism infrastructure, and inadequate facilities. The study suggests focusing on neighboring countries and organizing religious and tourism events to boost tourist inflows.
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