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Tourism may have important positive and negative economic, socio-cultural and environmental impacts. However, cultural and natural resources are also the base to the development of competitive destinations and changes in these resources can have an important impact on tourism development. Despite the considerable literature regarding the impacts of tourism, a limited number of studies examine the impact of the environment on tourism, specifically the impact of air quality (AQ). Therefore, this paper aims to review what is known about the impact of AQ on tourism demand, analysing the different methods and approaches used, as well as the results obtained.

A systematic literature review method was used to examine the state of the art in this topic and identify research gaps and new research directions. Only 26 papers were identified that examine the impact of AQ on tourism demand.

The majority of the studies were carried out in China and investigate the impact of AQ on tourism from the perspective of tourism demand. Both global (tourism demand) and individual (tourist perceptions) approaches have been used to investigate the impact of AQ on tourism.

This is the first systematic literature review on the impact of outdoor AQ on tourism demand. Moreover, this paper analyses the methods and approaches that have been used in the literature to examine the impact of outdoor AQ on tourism demand. The paper ends with a discussion on the identified research gaps concerning the influence of AQ on tourism development.

This paper aims to investigate how information and communication technology (ICT) services and digital finance affect the development of international tourism.

The two-way fixed effect panel regression model, spatial econometric model, panel threshold regression model and panel quantile regression model are used. Data on tourism, economic and social development in 198 Chinese cities from 2011 to 2020 are analyzed.

This study finds that digital economy including ICT services and digital finance has significantly promoted the development of international tourism industry, while there is a negative spatial spillover effect. The promotion effect of international tourism increases significantly after digital innovation reaches the threshold value. International tourism is benefiting more from digital economy with the development of international tourism industry.

The development quality of international tourism industry has not been analyzed due to data limitations, and the mechanism has not been tested.

This study creatively reveals the development of international tourism industry in the digital economy era from ICT services and digital finance perspectives. This study also shows the spatial, nonlinear and asymmetric relationship between digital economy and international tourism.

This study aims to critically evaluate hospitality and tourism demand research and introduce a behavioral economics approach to solve the problems faced by researchers.

Current issues in hospitality and tourism demand analysis are identified through critical reflection, and a behavioral economics approach is adopted to develop a new conceptual framework.

Four issues in hospitality and tourism studies are identified from the microeconomic theory and econometric modeling perspectives. The study’s demand framework provides both a theoretical underpinning and quantitative models to resolve the identified issues. With a focus on consumers’ cost–benefit assessments in light of individual differences and environmental factors, the authors’ conceptual framework represents a new effort to quantify hospitality and tourism demand at the disaggregate level with interactive multiple demand curve estimations.

The study’s analytical framework for hospitality and tourism demand analysis is unique, and it fills the research gap. However, this research is still in the conceptual stage, and the authors leave it to future studies to empirically test the framework.

The proposed demand framework at the disaggregate level will benefit both private and public sectors involved in hospitality and tourism businesses in terms of pricing, marketing and policymaking.

The authors offer a new conceptual model that bridges the gap between aggregate and disaggregate hospitality and tourism demand analyses. Specifically, the authors identify research directions for future hospitality and tourism demand research involving individual tourists/consumers at the disaggregate level.

The present study aims to investigate the dynamic relationship between international tourist receipts, economic growth, energy use and carbon dioxide (CO₂) emissions in Pakistan over the period 1980-2016. Many researchers have investigated the link between tourism and CO₂ emissions, but there is no clear picture as the results are contradictory. This study is an attempt to compliment the literature related to tourism and environmental quality.

The study adopted the autoregressive distributed lagged (ARDL) model to investigate the short- and long-run estimates simultaneously. The study further applied Granger causality to find out the direction of causalities. To arrive at long-run robust estimates, the study used dynamic ordinary least squares (DOLS) model.

The results found that tourist receipts have no significant impact on environmental quality, while growth and energy consumption are the main determinants of CO₂ emissions in Pakistan. The Granger causality test confirmed unidirectional causalities from GDP and energy consumption toward CO₂ emissions, while tourist receipts do not affect environmental quality. DOLS technique confirmed the long-run estimates of ARDL model.

The result of the study complements the literature by adding new evidence regarding the nexus of tourism and environment. Findings of the study are important for policymakers and regulatory bodies to place their focus on the development of tourism sector (services sector) rather than energy-intensive manufacturing activities to sustain the growth of the country in higher quartiles, as tourism receipts have no significant negative externalities toward environment, while energy use is one of the key determinants of environmental degradation.

This study used time series data over the period 1980-2016 for Pakistan to inspect the dynamic relationship between tourist receipts, economic growth, energy consumption and CO₂ emissions.

The purpose of this study is to investigate the causal linkages between tourism and economic growth in the USA and determine how they respond to shocks in the system.

The study uses a variety of time series procedures, including the bounds test, Granger causality test, impulse response functions and generalized variance decomposition to analyze the relationship between monthly tourist arrivals (TA) to the USA, real gross domestic product (GDP) and real effective exchange rates.

Results suggest that GDP Granger causes TA in the USA in the long run, indicating the economy-driven tourism growth hypothesis. Additionally, a shock to GDP generates a positive and significant effect on TA that persists in the long-run, while exchange rate shocks only have a significant effect in the first six months.

Different tourism sectors may exert different degrees of influence on the economy. The use of aggregate data on TA in the analysis assumes homogeneity in the industry, thus, only represents the average relationship between tourism and GDP.

This study provides insight that shapes the investment, marketing, sustainability decisions of the public and private sectors aim at increasing tourist flows to drive economic development at the national, state and local levels.

Though several studies have examined the factors influencing the international tourist demand of the USA, this is the first to investigate the causal relationships between tourism, GDP and exchange rates for the USA. It is also the first in the US tourism literature to account for the nature of interactions between the three variables because of innovations in the system.

A convenient payment system is increasingly recognized as an asset of tourism destinations. By using data on payments with cards issued in foreign countries, together with other monthly tourism flow variables, the authors assess the importance of card payments to identify seasonality in inbound tourism in Portugal.

The authors compute seasonality measures using Portuguese data on card payments from 2003 to 2019, together with data on nights spent and the Balance of Payments travel credit. The authors also assess seasonal behaviour in the timespan of the different tourism strategic plans in place during this period.

Card payments grew at a faster pace than the other inbound tourism variables and show a seasonal pattern similar to the other variables. Seasonality decreases when variables measured in quantities are considered (nights spent and number of card transactions). However, when the authors use value variables (Balance of Payments travel credit and value of card transactions), seasonality in 2019 is higher than in 2003.

The widespread use of digital payments makes card payment information an even better proxy of tourism activity and since it is available in a short time-span it has informational potential for tourism stakeholders and for researchers in this field.

The authors study the seasonal behaviour of foreign card payments along with other international tourism flow variables. The authors’ results highlight the informational potential of card payment data and the importance of electronic payment infrastructure for tourist activity.

This study aims to propose and estimate the urban tourism performance index (UTPI), an index that can measure and track the month-by-month tourism performance on main tourism cities since the initial outbreak of the COVID-19 pandemic. The UTPI is estimated for the following urban destinations: Bangkok, Paris, London, Dubai, Singapore, Kuala Lumpur, New York, Istanbul, Tokyo, Seoul, Osaka, Phuket, Milan, Barcelona, Bali and Hong Kong.

Monthly based data measuring the tourism industry’s performance for these urban destinations has been collected. This data includes airlines’ and hotels’ performance, as well as potential tourists’ online searches. The obtained data has been combined using a principal component analysis, generating the UTPI.

The UTPI shows that all urban areas analyzed in this study experienced a devastating negative impact because of the COVID-19 pandemic outbreak. However, the tourism recovery evolution follows heterogeneous patterns.

The proposed index can be estimated using additional variables. Moreover, the index is only estimated for 16 tourism cities. Future studies can reproduce the methodology by incorporating further variables and amplifying the geographical coverage.

The UTPI might be useful for researchers and policymakers interested in using a measure of tourism performance during the COVID-19 pandemic in some of the most important urban destinations. Likewise, the UTPI index may serve as a suitable aggregated measure of tourism performance in a post-COVID-19 era or to monitor tourism during future crises.

This study analyzes the tourism performance during the COVID-19 pandemic from an urban perspective.

The purpose of this paper is to examine, through a microeconomic analysis, the extent to which trip characteristics influence tourism expenditure in 14 emerging urban-cultural cities in Andalusia (Spain).

This analysis was carried out using an ordinary least squares method, which measures influence on tourism expenditure based on the trip characteristics of tourists visiting emerging urban-cultural cities. For this, the authors used 3,030 surveys conducted on tourists who, in 2013, visited 14 emerging urban-cultural cities in Andalusia (Spain).

It was confirmed that certain trip characteristics – type of accommodation, length of stay, trip planning and internet use – determine tourism expenditure in these destinations. The findings provide stakeholders in these destinations with information for the implementation of policies aiming to increase revenue in destinations where tourism development levels are still in their infancy and where, therefore, there are many unexploited opportunities.

First, this study identifies those trip characteristics which influence tourist expenditure in emerging urban tourist destinations. These destinations, to date, had not been previously analysed in expenditure segmentation studies. Second, aside from the factors traditionally analysed in scientific literature, other trip-specific variables were considered; these relate to the means by which tourists familiarise themselves with their destination and the way in which they plan their trip (use of the internet), as the rise of new technologies has radically changed tourism.

This paper aims to examine the impact of the existing information and communication technology (ICT) infrastructure and the development of the destination’s ICT on the tourism demand of international tourists in an emerging economy, Vietnam.

Using time-series data from 1995 to 2019, this study applies vector error correction model to analyse the impact of ICT infrastructure in the short- and long term.

The results of analysis show that although ICT infrastructure does not affect the number of international tourists in the short term, it positively contributes to tourism development in the long term. In addition, the results also show that in the short term, consumer prices have a negative impact on tourist arrivals while having a positive effect in the long run.

This study only considers the impact of ICT infrastructure on the whole without going into each factor reflecting different aspects of the ICT infrastructure. Moreover, this research only stops at the pre-pandemic period, so it has not shown the role of ICT infrastructure in travel and tourism demand during severe pandemic periods.

The research results are an essential basis to support the Vietnamese Government’s strategy to pursue an accelerated investment policy in ICT infrastructure, especially investment in the tourism and hotel industries. On the other hand, the research results also create more motivation and confidence for managers and operators of destinations in Vietnam to invest in ICT infrastructure and apply ICT in management.

This study adds to the literature on tourism–ICT linkages in an emerging tourism market directly between ICT infrastructure and international arrivals with a dynamic time series–based approach that considers the dynamics in the tourist demand identification model. In addition, this study used consumer price index to assess the impact of price on tourist demand instead of using the exchange rate or using the relative prices between the origin and destination countries.

本文探讨了现有 ICT 基础设施和目的地 ICT 发展对新兴经济体越南国际游客旅游需求的影响。

该研究使用 1995 年至 2019 年的时间序列数据, 应用矢量纠错模型 (VECM) 来分析 ICT 基础设施的短期和长期影响。

分析结果表明, 虽然ICT基础设施在短期内不会影响国际游客数量, 但从长远来看对旅游业发展有积极贡献。此外, 研究结果还表明, 在短期内, 消费价格对游客人数产生了负面影响, 而从长期来看, 则产生了积极影响。

研究结果是支持越南政府加快信息通信技术基础设施投资政策战略的重要基础, 特别是对旅游业和酒店业的投资。另一方面, 研究成果也为越南旅游目的地的管理者和经营者投资ICT基础设施和在管理中应用ICT创造了更多动力和信心。

本研究通过考虑旅游需求识别模型中的动态的基于动态时间序列的方法, 增加了有关新兴旅游市场中旅游与 ICT 联系的文献, 该联系直接在 ICT 基础设施和国际入境者之间进行。此外, 该研究使用 CPI 来评估价格对游客需求的影响, 而不是使用汇率或使用来源国和目的地国之间的相对价格。