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The purpose of this study is to provide up-to-date evidence on the net effect of COVID-19 pandemic on international arrivals and occupancy rates in Greece. Analysis and forecasting point out the demand for 2020, and thus yielding more concrete evidence on the pure effect of the pandemic on the tourism industry.

Monthly observations from January 2000 to December 2020 were extracted from the Tourist Enterprises Association (SETE) for Athens, Thessaloniki, Kalamata, Rhodes, Mytilene, Santorini, Zante, Kefalonia and Crete. To model and forecast the volatility and the time trend effect of tourist arrivals individually, the study applies the autoregressive integrated moving average (ARIMA) (p,d,q) and the error, trend, seasonality (ETS) model.

Empirical results suggested that Athens, Thessaloniki and Crete were three destinations with the worst losses in international tourist arrivals. Specifically, Athens was expecting to have (without the existence of COVID-19) more than 330,000 tourist arrivals in December 2020 while instead only 73,000 international tourists visited Athens that period. Similarly, Thessaloniki and the island of Crete lost more than 150,000 international visitors during December 2020.

The author’s study adds to a growing number of studies regarding the impact of COVID-19 by incorporating monthly international arrival data and occupancy rate data for the whole 2020 reflecting differences in transportation or vacation choices. Also, the authors operationalized multiple time-series forecasting models (ETS and ARIMA) for reaching more concrete forecasts and estimates on the effect of COVID-19 on the Greek tourism sector.

Tourism development is critical for economic transformation, particularly in emerging economies. However, the growing spate of terrorism dissuades international tourists, reduces tourism receipts and ultimately hampers the tourism sector's performance. Thus, the government intervenes by altering its military spending to curtail terrorism. Against this backdrop, this study examines the moderating role of military spending in the terrorism–tourism nexus in Nigeria.

The study employs the dynamic ordinary least squares (DOLS) to investigate the moderating role of military spending in the terrorism–tourism nexus in Nigeria. The authors employ the data that cover the period 1995Q1–2019Q4.

The results reveal that terrorism has a catastrophic effect on tourism arrivals in Nigeria while military spending has a positive impact on tourism arrivals. The results further show the moderating role of military spending in the terrorism–tourism nexus is positive and statistically significant. However, the findings are subject to the measures of military spending, terrorism and tourism.

The practical implication of the findings is the need for deliberate and strategic budgeting for the Ministry of Defence to combat terrorism, which should not only focus on the procurement of arms and ammunition but also cover the welfare of the military personnel. Nigeria also needs to formulate and implement necessary tourism policies aimed at countering terrorism in a bid to create and maintain a positive image on the global tourist map.

Many studies, particularly in developing countries like Nigeria, had examined the effect of terrorism on tourism but none has examined the moderating role of military spending in the terrorism–tourism nexus. Hence, this study examines the moderating role of military spending in the relationship between terrorism and tourism in Nigeria, a terrorism-prone country with several tourist sites.

The purpose of this study is to empirically examine the determinants of foreign and domestic tourist arrivals and revenue receipts from tourism using state-level panel data in 25 Indian states for the period 1995 to 2011.

The study uses IV-2SLS method to examine the determinants of foreign and domestic tourist arrivals in Indian states. Economic development (proxied by per capita income, PCI) is an endogenous variable. We have used the state-wise “liable to flood prone area” as an instrument for PCI to control for endogeneity. An inverse relationship exists between state-wise “liable to flood prone area” and real PCI, in a sense that states with greater proportion of area marked as liable to flood experience lower economic development. For robust analysis, the study has also used IV-Tobit model to examine the effects of economic development and crime on revenue receipts from tourism.

The empirical results based on IV-2SLS method suggest that, in addition to economic development, other factors such as the presence of world-class monuments, natural landscapes and cultural heritage also encourage both international and domestic visitors in Indian states. While crime activities adversely affect the inflow of foreign and domestic tourist arrivals, terror activities do not significantly impact tourist arrivals and tourism receipts. Finally, the estimates of IV-Tobit model show that economic development and government expenditure on tourism sector leads to a significant increase in tourism receipts.

To the best of our knowledge, this is the first study done in Indian context in which state-level panel data have been used to examine the impact of economic, social and cultural factors on tourist arrivals and revenue earnings from tourism. Hence, the present study not only contributes to existing tourism literature, but also makes an important contribution to structuring suitable tourism management policies for the Indian states.

This study analyzes the impact of exchange rate volatility (ERV) on inbound tourist arrivals from four ASEAN countries namely Indonesia, the Philippines, Singapore, and Thailand during 1970–2017. Volatility in the exchange rates between the tourist currency and ringgit Malaysia is measured using the Generalized Autoregressive Conditional Heteroskedasticity model. The results from Autoregressive Distributed Lagged models indicate that ERV has no significant impact on tourist arrivals from ASEAN to Malaysia. This implies that tourists from these countries may not be sensitive to ERV when choosing Malaysia as their travel destination. There are two possible explanations for the results. First, Malaysian ringgit has been depreciating against major currencies and regional currencies in recent years, which makes ringgit relatively cheaper than other ASEAN currencies. Second, the empirical results of the study support the argument that ERV has a more serious impact on tourist spending compared to tourist arrivals.

This study explores the pioneering approach of utilising machine learning (ML) models and integrating social media data for predicting tourist arrivals in Sri Lanka.

Two sets of experiments are performed in this research. First, the predictive accuracy of three ML models, support vector regression (SVR), random forest (RF) and artificial neural network (ANN), is compared against the seasonal autoregressive integrated moving average (SARIMA) model using historical tourist arrivals as features. Subsequently, the impact of incorporating social media data from TripAdvisor and Google Trends as additional features is investigated.

The findings reveal that the ML models generally outperform the SARIMA model, particularly from 2019 to 2021, when several unexpected events occurred in Sri Lanka. When integrating social media data, the RF model performs significantly better during most years, whereas the SVR model does not exhibit significant improvement. Although adding social media data to the ANN model does not yield superior forecasts, it exhibits proficiency in capturing data trends.

The findings offer substantial implications for the industry's growth and resilience, allowing stakeholders to make accurate data-driven decisions to navigate the unpredictable dynamics of Sri Lanka's tourism sector.

This study presents the first exploration of ML models and the integration of social media data for forecasting Sri Lankan tourist arrivals, contributing to the advancement of research in this domain.

This paper aims to understand the character of the relationship between tourism growth and residents’ social trust.

The study uses large-scale data to model the effect of tourism on generalized trust attitudes Among advantages to analyzing data from large-scale social surveys, extensive content and representative coverage of the population are probably the most appealing. The broad coverage of the population of the large-scale social surveys allows for a broader generalization of the study results as well as comparison of areas with very different tourist activity.

This study offers two key findings. First, the effect of tourist arrivals (as per capita) on social trust attitudes is stronger in poorer regions than in wealthier regions. Second, only domestic tourism positively affects trust.

This study delivered a straightforward analysis of large data to be able to generalize findings and make a significant theoretical contribution to tourism discipline. This goal was pursued at the expense of complex or in-depth explanation of the observed phenomenon.

Findings from this study indicate that there are at least two crucial criteria for tourism to be able to strengthen residents’ social trust. First, domestic tourism should be encouraged in destination regions in their early development stages and in more homogeneous regions. Perhaps, focus on domestic tourists before internationalization of a tourism product is the most effective way to promote tourism development that is supported by local residents. Second, tourism is likely to have stronger positive effect on social trust in poorer regions. Thus, tourism policy makers should take into consideration the actual economic need for tourism. Residents in wealthier regions may show less support for tourism simply because they don’t need it and they have no economic incentives to be involved. In fact, tourism in wealthier regions is likely to diminish residents’ social trust, and thus it disrupts local social and political processes that rely on high social trust.

Social trust is considered an important measure of social cohesion and it enables modern societies to thrive. Social trust has not been problematized in the context of contemporary tourism growth. This is the first study that uses large data social survey to model the effect of tourism on social trust in European destination regions.

This study aims to determine the effects of lodging infrastructure development (LID) on Cordillera Administrative Region’s (CAR) environmental quality and natural resource management and its implication to globally responsible leadership. Specifically, this study sought to determine the contribution of LID to environmental deterioration and natural resource degradation in the CAR. As a result, a mathematical model is developed, which supports sustainability practices to maintain the environmental quality and natural resource management in CAR, Philippines.

This study used a descriptive research design using a mixed-methods approach. Self-structured interview and survey were used to gather the data. The population of this study involved three groups. There were 6.28% (34) experts in the field for the qualitative data, 70.24% (380) respondents for the quantitative data and 23.47% (127) from the lodging establishments. 120 respondents from the Department of Tourism – CAR (DOT-CAR) accredited hotels. Nonparametric and nonlinear regression analysis was used to process the data.

The effects of LID on the environmental quality and natural resource management in CAR as measured through carbon emission from liquefied petroleum gas (LPG), electricity and water consumption in the occupied guest rooms revealed a direct correlation between the LID. Findings conclude that the increase in tourist arrival is a trigger factor in the increase in LID in the CAR. The increase in LID implies a rise in carbon emission in the lodging infrastructure. Any increase in tourist arrivals increases lodging room occupancy; the increased lodging room occupancy contributes to carbon emissions. Thus, tourism trends contribute to the deterioration of the environmental quality and degradation of the natural resources in the CAR. A log-log model shows the percentage change in the average growth of tourist arrival and the percentage increase in carbon emissions. Establishments should observe standard room capacity to maintain the carbon emission of occupied lodging rooms at a minimum. Responsible leadership is a factor in the implementation of policy on standard room capacity.

The result of the study has some implications for the lodging businesses, the local government unit (LGU), the Department of Tourism (DOT) and the Department of Environment and Natural Resources (DENR) in the CAR. The study highlights the contribution of the lodging establishments to CO₂ emission, which can degrade the quality of the environment, and the implication of responsible leadership in managing natural resources in the CAR. The direct inverse relationship between energy use and CO₂ emission in hotels indicates that increased energy consumption leads to environmental degradation (Ahmad et al., 2018). Therefore, responsible leadership among policymakers in the lodging and government sectors – LGU, DOT and DENR – should abound in the CAR. Benchmarking on the model embarked from this study can help in designing and/or enhancing the policy on room capacity standardization, considering the total area with its maximum capacity to keep the carbon emission at a lower rate. Furthermore, as a responsible leader in the community, one should create programs that regulate the number of tourists visiting the place to decrease the number of overnight stays. Besides, having the political will to implement reduced room occupancy throughout the lodging establishments in CAR can help reduce the carbon emissions from the lodging businesses. After all, one of the aims of the International Environment Protection Organization is to reduce CO₂ emissions in the tourism industry. Hence, responsible leadership in environmental quality preservation and sustainable natural resource management must help prevent and avoid greenhouse gas (GHG) emissions.

Most studies about carbon emission in the environment tackle about carbon dioxide emitted by transportation and factories. This study adds to the insights on the existing information about the carbon emission in the environment from the lodging establishments through the use of LPG, electricity and water consumption in the occupied guest rooms. The findings of the study open an avenue for globally responsible leadership in sustaining environmental quality and preservation of natural resources by revisiting and amending the policies on the number of room occupancy, guidelines and standardization, considering the total lodging area with its maximum capacity to keep the carbon emission at a minimum, thus contributing to the lowering of GHG emissions from the lodging industry.

This paper aims to analyse the current state of tourism in Sri Lanka and make practical suggestions for a shared vision.

The paper is written in the context of a strategic question: “how might post-war Sri Lanka develop inbound tourism?” An analytical approach is taken to discuss the practicality of the tourist arrival target of 2.5 million tourists to Sri Lanka by 2016.

Achieving the 2.5 million tourist arrival target in 2016 is not realistic and should be revised to a more manageable two million target. Macro level changes since the end of the war in 2009 should be taken into consideration in preparing a new master plan. Assuming that continuous peace will be there for a long time, is simply not sufficient. Rebuilding the social economic foundation of the society has to be faster and must be the top agenda point for Sri Lanka. This is an essential ingredient for long lasting peace and a healthy and sustainably developed tourism industry in the future.

Addressing six key challenges and incorporating six key strategies identified in this paper should be helpful in developing a new master plan. Debating with and getting inputs from all major stakeholders of the tourism industry is recommended to ensure sustainable tourism development.

This paper provides thought-provoking practical tips from three well-experienced leaders of tourism industry, hotel industry and hospitality education.

This study investigated the micro–macro link in the hospitality and tourism (H&T) sector, specifically considering whether the gender diversity, independence and board attendance rates of H&T firms' boards, alongside the moderation effect of board policies, played a significant role in tourism sector performance.

The 2011–2018 data were retrieved from the World Bank and the Thomson Reuters Eikon databases, and fixed effects panel regression was conducted.

While female directors were a significant driver of tourism sector performance in terms of tourist arrivals and tourism receipts, independent directors were effective in improving tourist arrivals only. Furthermore, moderation analyses demonstrated the inefficacy of board policies in enhancing these directors' contributions to the sector's development. Moreover, the findings revealed the inefficiency of board meetings.

Concerning the efficacy of board policies, the results suggest that firms' boards should review and revise their policies. Surprisingly, while board-diversity policies made no difference to female directors' role in the sector's development (although females were influential), board-independence policies produced unexpected results. In the absence of a board-independence policy, independent directors are influential, but if a policy exists, they are not.

Although prior firm-level studies tested whether board characteristics enhanced firms' performance in the H&T sector, they did not investigate whether board characteristics promoted tourism sector performance. Moreover, the moderating effect of board policies on boards' structures and tourism sector performance has not yet been examined.

Although extensive studies have examined the link between tourism and carbon emissions, the impact of tourism on carbon emissions remains controversial. In contrast to prior studies, this study aims to investigate the effects of tourism on carbon emissions at the city level and the underlying moderating mechanism.

This study designs an econometric model drawing on panel data for 313 city-level regions in China from 2001 to 2019. This study also performs rigorous robustness tests to support the regression results. In addition, the temporal and spatial heterogeneity is analyzed based on which this study discusses the moderators of the effects of tourism on carbon emissions.

The results show that both tourist arrivals and tourism revenue significantly impact carbon emissions. Also, there exists a significant temporal and spatial heterogeneity of these effects. Economic development significantly enhances while green technology and tertiary industry development suppress the positive relationship between tourism and carbon emissions. Moreover, regarding the impact on carbon emissions, an explicit substitution exists between tourism and tertiary industry development.

For the first time, this study quantitatively estimates the moderators of tourism’s impact on carbon emissions and concludes the moderating effects of economic growth, technological progress and industrial structure, thus furthering the theoretical understanding of the heterogeneity of tourism’s association with carbon emissions. The study also fills a technical gap in previous studies by demonstrating the reliability of the findings through various robustness tests. This is also the first empirical study to systematically examine the relationship between tourism and carbon emissions in China.

尽管已经有大量的研究考察了旅游和碳排放之间的联系, 但旅游对碳排放的影响仍有争议。与之前的研究相比, 本研究旨在研究城市层面上旅游业对碳排放的影响以及潜在的调节机制。

本研究基于2001-2019年中国313个城市层面的面板数据, 设计了一个计量经济学模型。本研究还进行了各种严格的稳健性检验以支持基准回归结果。本研究还分析了时空异质性, 并在此基础上讨论了旅游对碳排放影响的调节因素。

研究结果显示, 旅游者人次和旅游收入都对碳排放有明显影响。同时, 这些影响存在明显的时间和空间异质性。经济发展明显增强但是绿色技术和第三产业发展抑制了旅游业与碳排放之间的正向关系。此外, 旅游业和第三产业发展在对碳排放的影响方面存在显著的替代关系。

本研究首次定量估计了旅游业对碳排放影响的调节因素, 并总结出经济增长、技术进步和产业结构的调节作用, 从而进一步推动了对旅游业与碳排放关联的异质性的理论认识。文章还填补了以往研究的技术空白, 通过各种稳健性检验证明了研究结果的可靠性。本研究还是第一个系统地研究中国旅游业与碳排放关系的实证研究。

Este estudio diseña un modelo econométrico basado en datos de panel para 313 regiones a nivel de ciudad en China desde 2001 hasta 2019. Este estudio también aplica rigurosas pruebas de robustez para apoyar los resultados de la regresión. Además, se analiza la heterogeneidad temporal y espacial en base a la cual este estudio discute los moderadores efectos del turismo en las emisiones de carbono.

Aunque numerosos estudios han examinado la relación entre el turismo y las emisiones de carbono, su impacto sigue siendo controvertido. A diferencia de los estudios anteriores, este estudio pretende investigar los efectos del turismo en las emisiones de carbono a nivel de ciudad y el mecanismo moderador subyacente.

Los resultados muestran que tanto las llegadas de turistas como los ingresos por turismo influyen significativamente en las emisiones de carbono. Además, existe una importante heterogeneidad temporal y espacial de estos efectos. El desarrollo económico aumenta significativamente, mientras que la tecnología verde y el desarrollo de la industria terciaria suprimen la relación positiva entre el turismo y las emisiones de carbono. Además, en lo que respecta al impacto sobre las emisiones de carbono, existe una sustitución explícita entre el turismo y el desarrollo de la industria terciaria.

Por primera vez, este estudio estima cuantitativamente los moderadores del impacto del turismo en las emisiones de carbono y concluye los efectos moderadores del crecimiento económico, el progreso tecnológico y la estructura industrial, lo que permite avanzar en la comprensión teórica de la heterogeneidad de la asociación del turismo con las emisiones de carbono. El artículo también resuelve una carencia técnica de los estudios anteriores al demostrar la fiabilidad de las conclusiones mediante diversas pruebas de solidez. Este es también el primer estudio empírico que examina sistemáticamente la relación entre el turismo y las emisiones de carbono en China.