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Despite the role of wealth in modeling the propensity to consume luxurious goods and services, the literature has so far neglected the role of wealth as inferred from the stock market in modeling tourism inflow. Using 43 European countries over the period 1994???2019, we demonstrate that demand-side wealth effect as inferred from the Morgan Stanley Capital International (MSCI) indexes is an important determinant of inbound tourism. We find that a good financial mood extrapolated from the bullish wealth effect positively influences the inflow of tourists to Europe. The effect of the relationship between external wealth effect and inbound tourism is higher for non-EU member countries and countries in Eastern Europe. Lastly, we find that the wealth effect in the US was an important factor in predicting inbound tourism during the global financial crisis. [ABSTRACT FROM AUTHOR]

This study examines the impact of economic stimulus policies on tourism-related firms' stock prices, after movement restriction announcements, and differences in the relationships between economic policy responses and stock prices for large firms vis-à-vis small firms. Using a cross-section data of 888 firms from 56 countries listed on several stock exchanges, we find a positive and significant association between the COVID-19 economic stimulus index and 1- and 2-week average changes in tourism firms' stock prices after movement restriction announcements. Tourism firms' stock prices responded favorably to the introduction of macrofinancial packages and monetary policies. This study complements the literature on stock market reactions during the pandemic and contributes to the growing body of literature examining its overall effect. [ABSTRACT FROM AUTHOR]

Tourism development is often used as a strategy to fight poverty, but in the tourism literature it remains controversial as a tool for poverty alleviation in a poor region. This study adopts a multidimensional framework to measure regional poverty. Specifically, we examine four dimensions, including economics, education, social security, and medical service, to reflect poverty alleviation for a region. Then we establish econometric models to explore the link between tourism and poverty alleviation. The result shows that tourism development has a positive influence on multidimensional poverty alleviation in 73 counties in Guizhou province, a typically poor region in China. The consideration of the multidimensional nature of poverty in this study is more convictive to conclude that tourism can reduce poverty. This study further demonstrates that political pressure, indicated by the time period near the end of the fight-against-poverty campaign and by whether a county has red-culture heritages, affects tourism-led poverty alleviation in China. [ABSTRACT FROM AUTHOR]

In this article the self-organizing map algorithm is used for studying whether and which tourism flows in Sicily are synchronized (i.e., which flows show similar patterns in time and space), if any. Synchrony hunting was performed for domestic and international tourists both on a yearly and monthly basis. Local tourism, meaning the holidays spent in Sicily by residents on the island, is also considered but on a yearly basis only. The analysis makes use of time series representing the number of overnight stays in Sicily over the period 2013‐2019. Results provide evidence for a domestic market overall more synchronized than the international one, both in time and space. Spatiotemporal patterns for local tourism seem strongly influenced by the landscape. Some policy implications are drawn. [ABSTRACT FROM AUTHOR]

In response to the unprecedented circumstances resulting from the COVID-19 pandemic, various national government policies were implemented to reduce the serious economic damage caused by the pandemic and attempts to control it. These policies generally aimed to kick-start domestic-led recoveries in many sectors. This study examines how different types of fiscal measures adopted by governments in response to this pandemic are associated with the growth of expenditure on domestic travel in 2020. Utilizing data from 76 countries and applying OLS estimator and 2SLS regression (which mitigates the potential endogeneity problem), the study shows that governments' additional spending and tax reductions (especially in non-health sectors) positively contributed to rising expenditure in domestic travel destinations. Similar results are found for countries that are very reliant on tourism. Our findings lend empirical support for Keynesian theory's prediction concerning the effect of government spending and tax reduction on household consumption behavior in the short run, particularly during periods of economic stress and uncertainty. [ABSTRACT FROM AUTHOR]

From a political???economic perspective, this research examines the nexus between Chinese foreign aid and tourism demand in 138 recipient countries. Specifically, it investigates two mechanisms and their interplay: (1) an economic channel that entices an influx of international tourists through infrastructure development; and (2) a political channel that attracts Chinese tourists by diminishing political distance. A cross-country panel dataset on Chinese aid projects is analyzed. The results suggest that Chinese aid has a significant impact on Chinese tourists after a 1-year lag through the political channel, while the economic channel's effect on Chinese/other international tourists is not salient within 5 years. Significant long-run equilibrium relationships are found between aid and both tourist segments. The economic effect emerges in the long term, while the political effect fades out. This study provides a novel political???economic perspective for tourism research and presents new insights into China???s soft power in global tourism. [ABSTRACT FROM AUTHOR]

This research analyzed the behavior of receptive tourism in Ecuador and its relationship with the economy of the US. An index was developed to measure instability and crisis levels as well as the vector autoregressive (VAR) models, cointegration, as well as hypothesis tests through vectors. The findings indicate that Ecuador endured a crisis 12 out of 19 years; on the other hand, while the US entered a crisis, the figures of Ecuadorian tourism improved. Likewise, the GDP's inverse growth movement influenced the reduction in the number of tourists. Therefore, expenditure capacity decided the touristic destination, not so Ecuador's internal cost index. Finally, it was proven that the average expenditure of a foreign tourist was reduced across time. [ABSTRACT FROM AUTHOR]

Online communication (Web 2.0) is an important tool that can assist consumers in choosing a service and/or buying a product and, if used effectively, can help businesses to improve organizational performance. This is a study of the websites of a sample of 4,080 Italian agritourism farms, which focuses on the construction, utility, and relative maturity of these businesses. The study entails an exploration of how and where the organization of websites is effective for the promotion of the features of agritourism farms and is therefore essential for providing recommendations for decisionmakers in the Italian agritourism sector. To test the study hypotheses, an extended model of internet commerce adoption (eMICA) is used, which is adapted to include the information reported on each agritourism farm website. Chi-square automatic interaction detection (CHAID) helps to analyze the differences in website design and vacation types on offer at the provincial level. The eMICA highlights the utility of using interactivity to measure the relative maturity of agritourism farm websites. In contrast, the CHAID decision tree shows how the diversification of vacation types is an important strategy for selling local agrifood products, especially to farm accommodation guests. [ABSTRACT FROM AUTHOR]

Tourists travel because they are pushed by their internal motivations and attracted or pulled by certain elements and features of destinations. However, a growing number of destinations have similar tourist attractions and need to differentiate themselves. The aim of this study is to unveil the power of high-level culinary tourism, focusing on Michelin-starred restaurants, as a pull factor and generator of tourism flows, as well as to create a model to quantify the level of importance of these highquality restaurants as nuclei of a destination. The gastronomic and culinary industry is one of the most traditional sectors in most economies and is now becoming a fundamental element in attracting tourism and promotion. In this study, we argue that certain types of business, such as high-quality restaurants, can generate tourism flows in their own right within a context where the role of tourists and enterprises has shifted from a passive to an active one, in which companies actively seek to become destination pull factors. A quantitative survey questionnaire with structured questions was applied to customers of high-quality Spanish restaurants, specifically Michelin starred, with 432 valid responses. The results show distinctive motivations of customers who travel mainly for the restaurant and those who do so for the destination. They also show the importance of the nucleus (restaurant) as a factor of attraction to the destination, but also the importance of the destination/ surroundings to the nucleus. These findings provide valuable information and insights for culinary tourism in the future, both for culinary companies and for destination managers, who can then adjust their marketing and management strategies, emphasizing the need for mutual collaboration. The findings may also be helpful to institutions and to communication managers of the destinations to improve their promotion and communication strategies, to diversify supply in mature destinations, and to deseasonalized demand. [ABSTRACT FROM AUTHOR]

The aim of this study is to analyze the operational efficiency of tourism firms using weights-restricted data envelopment analysis (DEA) in a mathematical optimization framework. The use of weight restrictions has been applied in several studies on efficiency and performance evaluation, in order to account for the decision maker's information. In this study, a nonstandard approach to operational efficiency evaluation is applied in an attempt to overcome certain limitations in tourism analysis— namely, the fact that the analyst may choose to consider only a few rather than all of the input variables. One of the main findings of this study is that total weight flexibility can lead to nonrational weights due to the fact that certain inputs are effectively ignored. Furthermore, total weight flexibility can result in too many units being assessed as efficient, reducing the discriminatory power of the model. This problem can be solved by applying weight restrictions. A first practical implication is that the weighted DEA model yields better efficiency estimations. Moreover, since a high number of efficient units could be considered an unrealistic result, the findings of this study demonstrate that the choice of weighted or restricted DEA model produces more accurate efficiency results. [ABSTRACT FROM AUTHOR]

This study examines the nexus between foreign direct investment (FDI) inflow and tourism development. Using annual data for 44 countries in Africa from 1995 to 2014, and three different specifications of panel autoregressive distributed lag model, the study investigates short-run and long-run dynamics between FDI and tourism development. The study finds a significant positive relationship and a bidirectional long-run causality between FDI inflows and tourism development. In addition, the results show a negative short-run relationship between exchange rate and tourism development. Furthermore, there is evidence that economic growth and political stability are important determinants of tourism development. A major policy implication for African countries is that creating a politically stable environment and sustaining a growing economy help attract FDI inflows to boost tourism development. [ABSTRACT FROM AUTHOR]

Due to the spectacular growth of traveler-generated content (TGC), researchers are using TGC as a source of data to analyze the image of destinations as perceived by tourists. In order to analyze a destination's projected image, researchers typically look to websites from destination marketing or management organizations (DMOs). The objective of this study is to calculate the gap between the projected and perceived images of Barcelona, Catalonia, in 2017, using Gartner's classification and applying compositional analysis. The official online press dossier is used as an induced source, the Lonely Planet guidebook as an autonomous source, and a collection of more than 70,000 online travel reviews hosted on TripAdvisor as an organic source. In addition to quantitative content analysis, this study undertakes two thematic analyses: the masterworks of architect Gaudi recognized as UNESCO WHS as part of the cognitive image component and feeling-related keywords as part of the affective image component. The results reveal strong differences between the induced and organic sources, but much smaller differences between the autonomous and organic sources. These results can be useful for DMOs to optimize promotion and supply. [ABSTRACT FROM AUTHOR]

The ambidexterity concept is largely used in the strategic management field. However, little is known about its use in travel, tourism, hospitality, leisure, and event research. This study offers not only the first comprehensive analysis of the use of this concept but also a rationale for why it should be more widely used in travel, tourism, hospitality, leisure, and event research. The results show that (1) ambidexterity is scarcely used by researchers, (2) most papers are based on empirical data, and (3) all empirical studies were done either in Europe or in Asia. Moreover, scholars have focused on three main outcomes: sustainability, human resources performance, and market performance. This review allowed us to advance suggestions for practice and future research. [ABSTRACT FROM AUTHOR]

This study compares the contents of different online tourism information sources. In addition to developing a quantitative linguistic framework for comparing heterogeneous tourism information sources, a case study of the city of Barcelona in Chinese sources is presented. To understand the structural characteristics of textual communication, efficiency, and information gaps, this research examines texts not only from the websites of the Barcelona Tourism Office (local DMO) and a set of Mainland Chinese travel agencies, but also from Chinese online travel guidebooks and Chinese travel blogs. The findings reveal that the local DMO website texts are, overall, lower in lexical density and keyword density while higher in entropy. Chinese travel agency texts have lower entropy values while keyword and lexical densities are higher. Travel blogs are the most diverse and richest sources. The results explain the easiness of comprehension as well as the concentration, distribution, and repetition of information among the different sources. The findings also identify descriptive– subjective and procedural–propositional knowledge as the main semantic dimensions that affect the information gaps. Lastly, theoretical and practical contributions are discussed. [ABSTRACT FROM AUTHOR]

By 2014 Indonesia registered 11.6 million inbound foreign tourists, 135% higher than the year 2000. Since then, government policies to promote tourism flourished. This article investigates the determinants of inbound tourism from the top nine mayor tourist origin countries into Indonesia covering the period of 2000 to 2014. This research employs a dynamic panel dataset to estimate the impact of per capita real income, relative prices, accommodation capacity, distance, and public infrastructure investment on international tourism demand in Indonesia, capturing demand- and supply-side effects. The results show that per capita income of tourists, relative price, and available rooms have a positive effect on tourism expenditure in Indonesia, while distance has a negative effect. Dummy variables capture large negative shocks in tourism arising from two terrorist attacks in 2002 and 2005, as well as from the global financial crisis in 2008. Income plays a positive but low impact on tourism demand compared to other nations. The positive effect of prices suggests an advantage of Indonesia in competitive tourism prices. Nevertheless, low prices also denote low value in tourism services. The substantial impact of accommodation may indicate that significant effects of tourism are allocated in lodging, minimizing the impact on other sectors. [ABSTRACT FROM AUTHOR]

This study explores the differences in tourism demand between French Polynesia and Singapore by applying the panel data technique. Although the tourism industry in these small states tends to be the main economic activity, they have a different economic structure: French Polynesia is highly dependent on the tourism industry, whereas Singapore has several service industries. This article applies the tourism demand model to panel data from 2008 to 2013. Different elasticities are observed in the model estimation between the two islands, such as income elasticity and transportation accessibility. Additionally, this article compares time dummies to estimate the impact of global bankruptcy in 2008. The results show that French Polynesia has slightly declined, while Singapore has gradually increased since 2008. An implication of this study is that the demand in a destination highly dependent on the tourism industry tends to result in a relatively high-income market, but the economy is affected by global phenomena. A destination that owns diversified industries is likely to have good accessibility, and the global economic impact is lower in the tourism market. [ABSTRACT FROM AUTHOR]

Visitors' movement patterns can provide important information on popular sites visited and the timing of visits. Such information can be used for transportation planning, appropriate use and management of tourism resources/facilities, and market segmentation. Traditional market segmentation methods typically use one or more nonspatial variables, which cannot reflect the spatial consumption of a destination if the spatial movement patterns are not considered. While studies on visitors' spatial movements in an urban area have recently gained popularity, few, if any, have investigated visitors' spatial movements in relation to urban forests (i. e., parks, gardens, and green spaces in an urban area). In view of this, this study segments visitor markets in Washington, DC based on dominant movement patterns of 1,090 visitors. General log-linear models are used to identify dominant movement patterns and poLCA in R Studio is used for segmentation analysis. Ten significant movement patterns are identified, including seven two-ward patterns and three three-ward patterns, with the National Mall as the most visited area in the city. Findings of this study are useful for the maintenance of urban forests, the design of visitor itineraries, and the effective marketing and management of attractions and facilities in the city. [ABSTRACT FROM AUTHOR]

Compositional data analysis (CoDa) is the standard statistical methodology when data contain information about the relative importance of parts of a whole. Many research questions in tourism are either related to distribution of a whole (e.g., distribution, share, allocation, etc.) or relative importance (e.g., dominance, concentration, profile, etc.). Example research questions might be: How does time allocated to different types of activities relate to tourist satisfaction? or Which origins and destinations concentrate the most tourist flows per tourist segment? The first aim of this article is to present the manner in which CoDa solves statistical problems that arise when treating compositional data with classical statistical methods (e.g., spurious correlations, meaningless distances, assumption violation). The second aim is to review all CoDa applications in tourism and hospitality to date. The third is to present CoDa applications in related fields (e.g., finance, sociology, geography, economics, management, ecology, education), which can be translated into future research in tourism. In order to show how to apply the most common CoDa tools (exploratory analysis of compositions, and use of compositions as variables in a model) an example of restaurant menu styles is used. [ABSTRACT FROM AUTHOR]