Major Tourist Cities Research Articles

How air pollution affects tourism revenue: evidence from China

ABSTRACT It is acknowledged that air pollution has a detrimental impact on tourism revenue, but the mechanisms behind this impact remain unknown. Previous studies have merely assumed that air pollution affects tourism revenue through the number of tourists. Based on the inbound tourism data of 47 major tourist cities in China from 2005 to 2017, this study reveals that in addition to lowering the number of tourists, air pollution also reduces tourist expenditure per capita by shortening their length of stay, ultimately leading to a decrease in tourism revenue. The finding is robust even when the endogeneity of air pollution is considered. Moreover, the results also show that the impact of air pollution on tourism revenue, tourist flow, tourist expenditure per capita, and length of stay is nonlinear. The findings of this paper contribute to an accurate assessment of the economic consequences of air pollution on tourism.

A constraint programming approach for multi-objective tourist trip design problem with mandatory visits: A case study for İzmir Turkey

The Orienteering Problem (OP) is an optimization problem that finds the locations and routes that will return the highest profit/benefit, starting from the initial location of the traveler/vehicle, visiting these locations, and ending with the starting location of the tour within a given time or distance limit. There is no obligation to visit all locations in the problem structure. OP has many real-life applications, such as staff routing and disaster relief routing. In this study, OP with Time Windows (OPTW), an extension of OP, is discussed with hotel selection and mandatory visits. Although the main objective of OPTW is profit maximization, it is also essential to minimize the total travel time to complete the tour efficiently. For this reason, we consider the OPTW as a multi-objective problem. In the problem considered here, it is assumed that the profit/benefit, travel time between locations, service period, and time interval that each location can be visited are determined to be known. Within the scope of the study, first, a Mixed Integer Programming (MIP) model is prepared for the problem. Since the proposed mathematical model does not provide solutions in a reasonable time for large networks, the problem is solved by a Constraint Programming (CP) approach. Attractive tourist points of interest for Izmir, one of Turkey's major tourist cities, are determined, and the proposed method is applied to the real-life problem. The problem is modeled as Multi-Objective OPTW with MIP and CP and solved. Also, sensitivity analysis is performed by considering two different scenarios.

City Marathon Events and Tourism Industry: A Quasi-Natural Experiment

Building the relationship between marathon events and tourism is a significant strategy for the local governments. However, there has been little agreement on the effect of city marathon events on local tourism performance. Therefore, this research gap is addressed by providing empirical evidence for the effect of city marathon events on local tourism performance. First, the paper analyzes the theoretical mechanism of the effect of city marathon events on tourism from three aspects: the preliminary effect before marathon events, the agglomeration effect during marathon events, and the legacy effect after marathon events. Second, taking the city marathon events in China as a quasi-natural experiment, the paper uses the Difference-in-Difference model to identify the effect of the marathon events on tourism based on the panel data of 50 major tourist cities from 2010 to 2017. The results indicate that city marathon events significantly boost local tourism performance. These research findings are further confirmed by performing various robustness checks.

Spatiotemporal Evolution of Tourism Eco-Efficiency in Major Tourist Cities in China

Tourism development consumes ecological resources to varying extents while bringing economic benefits; tourism eco-efficiency (TEE) assessment has thus become an area of major focus in destination sustainability research. This paper intends to examine the spatiotemporal characteristics and driving factors of eco-efficiency changes in 36 tourist cities on the Chinese mainland from 2010 to 2019, using a super-slacks-based measure (SBM) model, the data envelopment analysis (DEA)–Malmquist index, spatial correlation, and regression analysis. In contrast to the previous work, this work explores TEE among major tourist cities in China by considering the undesirable outputs of carbon emissions and sewage. The results show that (1) the TEE of most cities during the study period was low but increasing; there were significant spatial differences among different cities, and the eco-efficiency of the same city fluctuated over time. (2) The TEE was globally uncorrelated, but low-eco-efficiency areas were adjacent to each other and formed agglomerates, enhancing the negative spillover effect. (3) Despite fluctuations, the Malmquist indices exhibited positive trends, which resulted from the technical progress index rather than the technical efficiency index. (4) Socioeconomic development significantly promoted TEE. This research reveals the evolutionary law of TEE on the urban scale and explores the impact of social and economic development on TEE, which can provide a reference for policymaking and enrich research on destination sustainability.

Vulnerability of Tourist Cities’ Economic Systems Amid the COVID-19 Pandemic: System Characteristics and Formation Mechanisms—A Case Study of 46 Major Tourist Cities in China

Research on the vulnerability of tourist cities’ economic systems during COVID-19 can offer insightful implications for tourism recovery and resilience. We built a vulnerability index of tourist cities’ economic systems based on sensitivity and responsiveness amid COVID-19. Taking 46 major tourist cities in China as a case, the vulnerability indices and main vulnerability-induced factors were analyzed using a comprehensive assessment model and a factor identification model. The results revealed several trends. First, after the pandemic emerged, the vulnerability of the economic systems of major tourist cities remained mostly moderate. Vulnerability could be further divided into four types across four city characteristics and four system characteristics. Second, sensitivity had a more pronounced effect on system vulnerability; crisis pressure and inbound tourism reliance exerted key influences on the vulnerability of tourist cities’ economic systems. Cities with high and relatively high vulnerability were subject to tourism reliance sensitivity factors and urban guarantee responsiveness factors. Third, the pandemic’s influence on tourist cities’ economic system vulnerability was mainly reflected in exogenous environmental stress vulnerability (i.e., due to external environmental stress), but was essentially endogenous structural imbalance vulnerability (i.e., due to imbalanced internal structures). Fourth, system vulnerability can be alleviated by reducing system sensitivity, improving system responsiveness, and enhancing the system’s engineering resilience and ecological resilience. This study not only offers an overview of the vulnerability characteristics of tourist cities’ economic systems amid the COVID-19 pandemic, but also highlights the formation mechanisms of vulnerability.

Spatiotemporal Difference Characteristics and Influencing Factors of Tourism Urbanization in China's Major Tourist Cities.

Tourism is crucial for promoting industrial development and is an important driver of China’s new type of urbanization. A tourism urbanization index system was constructed in three dimensions: the tourism industry, urbanization, and the ecological environment. The spatial–temporal differentiation characteristics and influencing factors of tourism urbanization in 35 major tourist cities in China from 2009 to 2018 were analyzed using the state space method, standard deviation ellipse, and spatial autocorrelation analysis. The results show the following. (1) Over time, the tourism industry index displays an upward trend, the urbanization index exhibits a more obvious upward trend, and the ecological environment index fluctuates strongly. Under the influence of all three factors, the tourism urbanization index shows a fluctuating rising trend. (2) Regarding the spatial distribution pattern, the development center of tourism urbanization shifts to the southeast, and the distribution direction is northeast-southwest. There is a significant agglomeration in global spatial autocorrelation. The local spatial correlation pattern is dominated by correlation characteristics and supplemented by different characteristics. (3) In terms of influencing factors, policy and regional development strategy, tourism resource endowment, economic development level, and traffic conditions are listed in descending order of influencing degree. Finally, we put forward some suggestions.

Yeast complexes of urbanozems of some southern cities of Russia (Krasnodar, Maykop, Simferopol, Sochi)

Yeasts number and diversity in urban soils of Krasnodar, Maykop, Simferopol, and Sochi was investigated. The soils of botanical gardens and suburbans were studied as a control. Maximum number was found in the topsoil 0-20 cm in the urban soils of Sochi and Simferopol, where it was 5.7 ± 0.2 and 5.4 ± 0.01 lg(CFU/g), respectively. The minimum number, 2.0 ± 0.1 lg(CFU/g), was characteristic of a 60-80-cm layer in the suburban soils in all cities. The number of yeasts was shown to depend primarily on the depth and type of soil and to a lesser extent on location. A total of 20 yeast species were isolated. In the soils of the major tourist cities of Sochi and Simferopol, a high relative abundance of Candida sake and Meyerozyma guilliermondii was found, which fundamentally distinguished the studied soils from the ones of Krasnodar and Maykop. The cities of Sochi and Simferopol are characterized by a higher anthropogenic load compared to Krasnodar and Maykop, which is associated not only with their high population, but also with a significant tourist load. Detection in urban soils of C. sake and M. guilliermondii which are clinically significant species, was therefore consequential.

Spatiotemporal Evolution and Trend Prediction of Tourism Economic Vulnerability in China’s Major Tourist Cities

The evaluation and trend prediction of tourism economic vulnerability (TEV) in major tourist cities are necessary for formulating tourism economic strategies scientifically and promoting the sustainable development of regional tourism. In this study, 58 major tourist cities in China were taken as the research object, and an evaluation index system of TEV was constructed from two aspects of sensitivity and adaptive capacity. On the basis of the entropy weight method, TOPSIS model, obstacle diagnosis model, and BP neural network model, this study analyzed the spatiotemporal patterns, obstacle factors, and future trends of TEV in major tourist cities in China from 2004 to 2019. The results show three key findings: (1) In terms of spatiotemporal patterns, the TEV index of most of China’s tourist cities has been on the rise from 2004 to 2019. Cities throughout the coast of China’s Yangtze River Delta and the Pearl River Delta urban agglomeration show high vulnerability, whereas low vulnerability has a scattered distribution in China’s northeast, central, and western regions. (2) The proportion of international tourists out of total tourists, tourism output density, urban industrial sulfur dioxide emissions per unit area, urban industrial smoke and dust emission per unit area, and discharge of urban industrial wastewater per unit area are the five major obstacles affecting the vulnerability degree of the tourism economy. (3) According to the prediction results of TEV from 2021 to 2030, although the TEV of many tourist cities in China is increasing year by year, cities with low TEV levels occupy the dominant position. Research results can provide reference for tourist cities to prevent tourism crises from occurring and to reasonably improve the resilience of the tourism economic system.

Coupling Relationship and Interactive Response between Intensive Land Use and Tourism Industry Development in China’s Major Tourist Cities

(1) Background: Exploring the interactive relationship between intensive land use (ILU) and tourism industry development (TID) is of vital significance to promote the high-quality and sustainable development of tourism and the urban economy. (2) Methods: This paper constructs an evaluation index system of ILU and TID, and comprehensively measures the coupling and interaction between ILU and TID in China’s 58 major tourist cities from 2004 to 2018 by using the entropy weight method, coupling coordination degree model, and panel vector autoregressive model. (3) Results: In terms of the coupling relationship, the coupling coordination degree of ILU and TID in China’s major tourist cities were optimized year by year, and the coupling coordination degree from 2004 to 2008 was less than 0.2, which is part of the serious imbalance recession stage. From 2009 to 2018, the coupling coordination degree was between 0.2 and 0.4, which is part of the moderate maladjustment recession stage. In terms of interactive response, ILU and TID formed a long-term interactive relationship, and the intensity effect of ILU on TID is significantly higher than that of TID on ILU. (4) Conclusions: There is a significant correlation and bidirectional process between ILU and TID, and they have an essential impact on the high-quality development of tourist cities.

Do hotel industry operations deteriorate air quality?

This study proposes and tests two hypotheses concerning the effects of hotel industry operations on air quality based on data of 26 major tourist cities in China from 2002 to 2017. The empirical analyses take two steps. In the first step, panel regression test results reveal that hotel industry operations (measured by hotel sales revenue) significantly raise the value of particulate matter (PM)2.5 (the key indicator of air quality), supporting the first hypothesis that hotel industry operations deteriorate air quality and providing empirical evidence of the adverse impact of the hotel industry on air quality. In the second step, subsample analyses support the second hypothesis that the impact of hotel sales revenue on air quality diminishes over time. The results from the rolling regression tests validate the existence of a diminishing effect of hotel industry operations on air quality.

Spatiotemporal Differentiation of Coupling and Coordination Relationship of Tourism–Urbanization–Ecological Environment System in China’s Major Tourist Cities

Determining the coupling development mode and evolution process of the tourism–urbanization–ecological environment system is of great significance in promoting high-quality and sustainable development of tourism and the urban economy. In this study, an evaluation index system of the tourism–urbanization–ecological environment system was established, and the spatiotemporal differentiation of the coupling and coordination relationship of the tourism–urbanization–ecological environment system was analyzed for 35 major tourist cities in China from 2009 to 2018. The results show that the comprehensive development indices of the tourism industry subsystem and urbanization subsystem of China’s major tourist cities have steadily increased. The comprehensive development indices of large-sized and medium-sized cities in the east are relatively high. From 2009 to 2018, the coordination degree and coupling degree of the tourism–urbanization–ecological environment’ system of 35 tourist cities showed an upward trend. The growth rate of the coupling coordination degree lags behind the growth rate of the coupling degree, and the overall system coordination level is still low. There are significant differences in the coupling degree and coupling coordination degree among the eastern, central, and western cities. This study offers both theoretical and practical implications for further equalizing the development level between the cities, as well as improving the overall coordination between the tourism industry, urbanization, and the ecological environment in China.

Air quality effect on the hotel industry

This article makes an original contribution to the hospitality research literature. It proposes a curvilinear impact of air quality (AQ) on hotel sales (HS) and then empirically tests this nonlinear effect using data from 26 major tourist cities in China from 2002 to 2016. The results of dynamic panel regression test based on estimations of the system generalized method of moments reveal an inverse U-shaped impact of AQ (measured by concentrations of the fine particulate matter, i.e. PM2.5) on HS and thus validate the proposal. Empirical findings offer valuable policy implications for hotel business owners and tourism authorities and policymakers.

Efficiency and Driving Factors of Green Development of Tourist Cities Based on Ecological Footprint

For tourist cities, the ecological footprint not only affects tourism competitiveness but also affects green development. This paper adopted an improved ecological footprint accounting model, used a series of relevant indicators of ecological footprint to compare the green development efficiency, and explored the main driving factors of the per capita ecological footprint and city classification of 16 major tourist cities in China from 2000 to 2017. The results show that the green development efficiency of the studied tourist cities still needs to be improved. Secondly, the panel data analysis shows that the proportion of the primary industry in GDP, the proportion of the secondary industry in GDP, the per capita investment in fixed assets, and the length of highways per 10,000 people can increase the per capita ecological footprint. Then, the cluster analysis divides the selected tourist cities into four categories, and different types of cities need to be managed differently. Finally, this paper puts forward corresponding suggestions to improve the quality of the green development of selected tourist cities. The in-depth study of the ecological footprint in this paper will provide a scientific basis for tourist cities to promote green economic growth that considers ecological footprint and GDP and achieve sustainable development of tourism.

Yeast Complexes in Urban Soils of Some Southern Cities of Russia (Krasnodar, Maykop, Simferopol, and Sochi)

Yeast number and species diversity in urban soils characterized by various intensities of anthropogenic impact in the southern cities of Russia (Krasnodar, Maykop, Simferopol, and Sochi) was investigated. The soils of botanical gardens and the reference soils in the vicinities of cities were used for comparison to reveal the degree of anthropogenic impact. The maximum yeast number was found in a layer of 0–20 cm in the urban soils of Sochi and Simferopol, where it was 5.7 ± 0.2 and 5.4 ± 0.01 log (CFU/g), respectively. The minimum number of yeasts, 2.0 ± 0.1 log (CFU/g), was characteristic of a 60–80-cm layer in the soils in the vicinities of all cities. The number of yeasts was shown to depend primarily on the depth and type of soil and to a lesser extent on location. A total of 20 yeast species were isolated from the studied soils: 10 ascomycetes and 10 basidiomycetes. All basidiomycete yeasts isolated from urban soils and control soils were typical representatives of pedobiont and epiphytic yeast complexes. In the soils of the major tourist cities of Sochi and Simferopol, a high relative abundance of ascomycete species Candida sake and Meyerozyma guilliermondii was found, which fundamentally distinguished the studied soils from the ones of Krasnodar and Maykop. The cities of Sochi and Simferopol are characterized by a higher anthropogenic load compared to Krasnodar and Maykop, which is associated not only with their high population, but also with a significant tourist load. Detection in urban soils of C. sake and M. guilliermondii which, according to some data, are clinically significant, was therefore consequential.

Nordic home-sharing utopia: a critical analysis of Airbnb in Helsinki

ABSTRACT The proliferation of Airbnb listings has been studied in major tourist cities, but much less is known about the phenomenon in Nordic cities. In this paper we have examined the situation in Helsinki, the capital of Finland, which has been largely unexplored in the research literature. Using our situated knowledge as an entry point, this study is based on geostatistical analysis, qualitative analysis of Airbnb listings, thematic conversations with experts and analysis of public discourses through media, to illustrate how Airbnb listings are distributed within the city and what perceptions and responses this phenomenon is generating. In the study, we challenge the public narrative that portrays short-term renting of homes in Helsinki as a form of sharing economy, as opposed to more destructive developments in major European tourist cities.

Do hotel business benefit from increased tourist accessibility? Evidence from China’s high-speed railway program

The operation of high-speed railway (HSR) always plays a key role in promoting tourism development of city by improving transportation accessibility and facilitating tourists’ travel. Based on the panel data of 50 major tourist cities in China from 2010 to 2017, this article uses a Tobit model to explore the impact of HSR service on hotel performance that is embodied in occupancy rate. The results show that with other factors unchanged, the cities with a high-frequency HSR service system or hub HSR station tend to have higher hotel occupancy rate. Moreover, the hotel occupancy rate of cities with a suburb HSR station is lower than that of other HSR-served cities. After classifying hotels into luxury and budget groups, this article finds that HSR train frequency and station grade still show positive effects on both luxury and budget hotels. However, in cities with suburb HSR stations, budget hotels tend to have lower occupancy rates, while occupancy rate for luxury hotels shows no significant difference.

Nonlinear Impact of Air Quality on Tourist Arrivals: New Proposal and Evidence

This study makes a novel contribution to the tourism literature by proposing an inverted U–shaped impact of air quality on tourist arrivals and examining this relationship using 58 major tourist cities in China from 2004 to 2015. The estimation of linear and nonlinear dynamic panel regression tests is based on the system generalized method of moments. The linear test results show that air quality measured by the concentration of fine particulate matter (PM2.5) has a significantly negative impact on both inbound and domestic tourist arrivals. The nonlinear test results validate an inverted U–shaped link between air quality and both inbound and domestic tourist arrivals.

One visitor too many: assessing the degree of overtourism in established European urban destinations

Purpose The purpose of this study is to provide a series of indicators to determine the limits to urban tourism growth, tourism gentrification and overtourism. The study addresses overtourism within the frame of urban liveability through a proxy analysis of tourism-relevant indicators for major European tourist cities. Design/methodology/approach Based on the various indicators, a composite overtourism indicator is derived. The following dimensions are considered for the composite indicator: total number of overnight stays per relevant tourist area in km2; number of museum visitors per population; average annual change in total nights between 2009 and 2017; and foreign nights per population. Findings Based on the results, Venice is the city with the highest degree of overtourism, followed by Florence, Seville and Lisbon. The remaining cities have a lower than average overtourism potential as indicated by the negative z-score. Research limitations/implications This study and the composite overtourism indicators are only a starting point that can lead to further research in the field. Recommendations for further studies include the assessment of visitor flow and overtourism at different times of the year and to expand the study to other European urban destinations. Practical implications The paper suggests that policymakers should use these indicators when managing urban tourism development and monitoring visitor growth. Furthermore, they can be a starting point from which to assess the impact of tourism on the quality of life of local residents. Social implications This study provides a starting point from which to assess the causes for social unrest tied to overtourism. If the city under study is found to have a lower than average overtourism potential, this indicates that there may be other social or psychological issues at play apart from sheer overcrowding. Originality/value To date, there has been no composite indicator that considered the different numerical aspects of overtourism altogether. This study provides a set of key indicators and a composite overtourism indicator to provide a preliminary appraisal of overtourism as a demand-side phenomenon with evidence from a range of established European urban destinations.

Airbnb, sun-and-beach tourism and residential rental prices. The case of the coast of Andalusia (Spain)

ABSTRACTAccording to studies carried out to date, the arrival of the sharing economy in the field of tourist accommodation is giving rise to an increase in residential rental prices, also called long-term rental, in major tourist cities. In this paper, we analyse the effect on the residential rental price of Airbnb accommodation offered for sun-and-beach tourism on the coast of Andalusia (Spain). We use an econometric specification that includes average disposable income, the number of second homes, the offer of accommodation in exclusively tourist hotels and apartments, the temporary hiring of immigrant workers, and permanent immigration. The main result to emerge from the work is that sun-and-beach Airbnb listings explains 13.69% of the price of residential rental prices in the coastal area of Andalusia.

Effect of climate change over landfalling hurricanes at the Yucatan Peninsula

Tropical cyclones generated in the North Atlantic and the Eastern Pacific are a constant hazard for Mexico. Along with a possible increased hazard of tropical cyclones due to global warming, there is an inescapable increase in vulnerability and disaster risk towards tropical cyclones due to population growth and coastal infrastructure developments. In Mexico, the Yucatan Peninsula has the highest landfall rates of major category hurricanes in addition to the highest rate of population growth in major tourist cities. Therefore, the assessment of landfalling tropical cyclones is of paramount importance for emergency management and planning. This paper provides an assessment of the future climate for landfalling tropical cyclones in the Yucatan Peninsula, based on synthetic tropical cyclones driven by atmospheric models (reanalysis and six different general circulation models (GCMs)) and under the Representative Concentration Pathway 8.5 climate change scenario. The results using the ensemble mean from the GCMs show that the Yucatan Peninsula will be more susceptible to more frequent intense hurricanes and more regular events undergoing rapid intensification. We conclude that even under the uncertainty imposed by the results, it is more likely than not that the future climate will bring more extreme events to this area. Therefore, it becomes imperative to implement strategic planning based on the characterization of tropical cyclone hazards framed within the assessment of global warming effects.