The effect of tourism activity on housing affordability

Although researchers have confirmed the impact of tourism on housing prices in many destinations affected with overtourism, they do not consider housing affordability in relation to the population's income levels. This study explores the relationship between tourism activity and housing affordability, using a sample of Croatian municipalities. Specifically, the study investigates how tourist accommodation, concentration, seasonality and overall vulnerability to tourism influence housing affordability in this emerging tourism-driven European country. The results obtained reveal tourism intensification's deteriorating effect on local residents' abilities to afford housing. The findings indicate a particularly strong tourism seasonality impact, suggesting the presence of common negative externalities, such as employment fluctuations, difficulties in maintaining economic status, and revenue instabilities, in localities prone to seasonal tourism fluctuations.     

Tourism,seasonality and social change

This paper examines various aspects of seasonality in recreational travel and tourism. There is an institutionalized and a natural seasonality which both affect tourism. Since tourist seasonality is subject to change and the appraisal of climatic resources for recreation varies from culture to culture, a historical and cross-cultural perspective is necessary. In advanced western societies a swift change of place and season is possible, so that travel agencies are able to offer particular seasonal environments, which could also be understood on a global scale as ‘space-time packages’. Seasonality is usually a problem for a regional tourist service system. An economically-oriented policy stresses a more evenly-spread tourist seasonality. This may also be beneficial for the social environment and ecological base of a tourist region.     

Yearly,monthly and weekly seasonality of tourism demand: A decomposition analysis

Annual seasonal variations in tourism demand have been a central theme in literature. However, annual seasonality is not the only time-based inequality in tourism flows that has important implications on policy-making decisions at destinations. Within the context of tourism, this study aims to make an in-depth analysis of intra-monthly and intra-weekly tourism demand using the entropy and relative redundancy measures as alternative seasonality indicators to the Gini coefficient in order to provide new tools to manage tourism and propose new action policies at these frequencies. In comparison with the Gini coefficient, the entropy measure is simpler to compute and it is easily decomposable. Using the case study of air arrivals and departures to and from the Balearic Islands, results show the appropriateness of entropy and relative redundancy as seasonal indicators but also as a new information tools for tourism seasonality analysis.     

Seasonality in tourist flows: Decomposing and testing changes in seasonal concentration

This paper shows that changes in timing and magnitude of seasonality in tourist flows can be measured by decomposing the change in the Gini index, a widely used index of seasonal concentration, into two components. One of them tracks the change in the pattern of seasonal fluctuations and the second captures the change in their magnitude. To assess whether changes in the seasonal pattern and magnitude are significant, a technique for testing hypotheses concerning the two components is developed. We examine changes in the seasonal concentration of tourist arrivals in six tourist destinations in the Veneto Region, one of the most tourism-oriented regions in Europe, from 2006 to 2016. The magnitude of seasonality significantly decreased in some destinations with a diversified tourism product, such as Euganean Spas and Lake Garda. The seasonal pattern remained substantially stable for all destinations except Venice, where a non-negligible shift in the seasonal pattern occurred.     

The measurement of spatial variations in tourist activity

This paper looks at the problems of using physical accommodation capacity figures to identify spatial variations in the level of tourist activity and considers the implications for the interpretation of Defert's tourist function index. An analysis of accomodation use patterns in New Brunswick, Canada, shows considerable differences in the intensity of use among the various forms of accommodation. A closer look at hotel and motel occupancy characteristics also reveals large spatial variations, but their combined effect on the relationship between physical accommdation capacity and yearly tourist use shows little variation over space. It is concluded that Defert's index is a most useful tool for examining tourist activity in areas where most accommodation is in the form of hotels and motels, but should be interpreted with caution where there are large spatial variations in the types of accommodation available.     

主题公园黄金周游客流季节性研究——以深圳华侨城主题公园为例

旅游季节性是旅游活动的普遍特征,是主题公园经营需要面临的一个难题.文章以深圳华侨城主题公园(深圳欢乐谷、世界之窗和锦绣中华)为例,选取了2002年春节黄金周到2008年春节黄金周之间的数据,对主题公园旺季游客流季节性及其影响因素进行分析.研究表明,主题公园游客流的时间集中性较低,近程市场和重游市场比重增加的主题公园的黄金周游客流集中性逐年降低；不同类型主题公园具有不同的市场结构和气候要求,其黄金周游客流波动存在明显差异；主题公园黄金周的峰值日出现在假期的前半段,且游客流高峰持续时间短.在此基础上,结合以往研究,文章归纳出黄金周内峰值日的一般规律.     

Determinants of revenue per available room: Influential roles of average daily rate,demand, seasonality and yearly trend

Determining price per room to be charged to customers is an important decision to be taken by hotel management. Hotels frequently change their room rates based on the demand of room, occupancy rate, seasonal pattern, and strategies undertaken by other hotels on pricing. We formulated four models to analyse how various influencing variables, such as hotel price, demand, yearly trend and monthly seasonality influence hotel revenue per available room (RevPar). To analyse a case, we used monthly accommodation statistics for Sweden taken for Swedish Agency for Economic and Regional Growth and Statistics from January 2008 to July 2017. We carried out data analysis using both multiple regression and Multivariate Adaptive Regression Splines (MARS) model and found that application of MARS can help establishing a nonlinear relationship of RevPar with other determining variables in a superior way. We also proposed the possibility of developing a better forecasting model using MARS.     

Destination performance: Introducing the utility function in the mean-variance space

Economic characteristics of home countries can cause considerable variations in the tourism demand. For example, the average level of expenditure per tourist varies from one origin to another and these variations may alter overtime. Thus different tourist nationalities are associated with different level of expenditures and risks. Therefore strategies aimed at minimizing the variations may become an important issue for the policy makers. In this paper, we aim to use the productivity measurement theory in a mean-variance space to a French region (Nord Pas-de-Calais) by introducing the utility function in a mean-variance framework. With this method, we can calculate the optimal portfolio share for each origin and give some useful political advices to the policy decision makers to improve the performance of the tourist sector.     

Regional development policies: an assessment of their evolution and effects on the Spanish tourist model

This paper assesses the incidence of regional development policy on the evolution of the Spanish tourist model. Spain's tourist boom took place within the framework of an authoritarian, centralist regime in which no true regional policy existed. Macroeconomic interests prevailed and planning was relaxed in front of the limited economic resources available and the urgent need to earn foreign currency and give coastal areas economic dynamism, all within a favourable context of international demand growth. The country's democratisation process entailed a politico-administrative decentralisation that was more suitable for the development of an effective regional policy.Spain's entry into the European Community increased the economic resources available and largely improved regional policy principles and instruments. While the centralist policy is associated with the sun-and-beach tourist model concentrated on the coast, the new regional policy represents an essential, though sometimes unnoticed, element in the current process of diversification and spatial spread of the Spanish tourist supply.     

The contributions of economics to tourism

Both the logical and empirical dimensions of economic analysis have contributed to the quality of decisionmaking in the tourism industry. In particular, the recognition of the potential contribution of economic rent derived from tourist attractions and the complex role of public goods have aided the understanding of the functioning of tourism. On more practical levels, market segmentation has a part to play in maximizing revenues by reducing the adverse effects of seasonality, and empirical research on tourism demand has provided basic underpinnings for national development programs and project research. Finally, cost-benefit analysis allows the industry to judge its contributions more correctly in the light of other applications of scarce resources.     

Seasonality in New Zealand Winery Visitation

Summary

Seasonality is a major issue in tourism management; however, the implications of seasonality for wine tourism have only received limited attention. Arguably, because of the interaction between seasonal patterns of consumer demand with the inherent seasonality of vineyard work and wine supply means that seasonality issues may be even more problematic for wine tourism than other forms of tourism. The article provides the results of a national study on wine tourism in New Zealand. The article highlights the seasonal nature of visitation and suggests a number of marketing strategies by which some of the effects of seasonality may be overcome in terms of both target markets and the improved management of human resources.     

Tourism demand forecasting with online news data mining

This study empirically tests the role of news discourse in forecasting tourist arrivals by examining Hong Kong. It employs structural topic modeling to identify key topics and their meanings related to tourism demand. The impact of the extracted news topics on tourist arrivals is then examined to forecast tourism demand using the seasonal autoregressive integrated moving average with the selected news topic variables method. This study confirms that including news data significantly improves forecasting performance. Our forecasting model using news topics also outperformed the others when the destination was experiencing social unrest at the local level. These findings contribute to tourism demand forecasting research by incorporating discourse analysis and can help tourism destinations address various externalities related to news media.     

A latent class approach to tourists’ length of stay

In this paper, a conditional demand function is estimated for the length of stay at a tourist destination. The microeconomic model specifies the demand for the length of stay conditional on the remaining holiday characteristics that the tourist has chosen (the destination, type of accommodation etc.). The empirical model uses a latent class truncated Poisson regression, which acknowledges the existence of groups or segments of demand with different preferences. In the case under study, a distinction is made between two segments with a preference for either a longer or shorter holiday. The statistical model also resolves a problem of multimodality, acknowledged in previous analyses to be one of the main characteristics of this variable.     

Self-catering accommodation in Switzerland

This article examines the situation of self-catering accommodation in the light of tourist experience in Switzerland. Swiss tourism is currently declining, and so are traditional forms of accommodation such as hotels. At the same time there is evidence that the demand for self-catering holiday properties is increasing. Yet very little is known about this sector in Switzerland. The present paper attempts to identify the number of Swiss self-catering properties and presents the results of interviews and an on-line survey, which shed light on this industry and allows the situation in Switzerland to be compared with that in other countries. The number of holiday homes in Switzerland has increased steadily since the 1980s, and could provide a valuable source of rented property and local income. The Swiss self-catering industry is highly seasonal, although rental properties are mostly available all year round. Swiss accommodation is relatively small and expensive, partly because the rent usually includes laundry and other services, not offered in other countries. Owners often rent to offset the cost of upkeep, rather than to make a profit, and this attitude is reflected in the fragmented and rather unprofessional nature of marketing, representation and communications in the sector. A number of recommendations are made for developing the industry, based on the findings.     

Temporary population estimates of mass tourism destinations: The case of Benidorm

Benidorm (Spain) is a large-scale tourism destination on the Mediterranean coast, and its temporary population can be divided into users of regulated tourist accommodation and unregistered visitors, as occurs in other destinations. The number of these different types of unregistered temporary inhabitants should be estimated separately to gauge more accurate population figures in tourist destinations which are subject to seasonality. Indicators such as drinking water consumption or solid waste generation are used to estimate the number of unregistered visitors. The results reveal that the average total population of Benidorm at least doubles the registered resident population. Additionally, a population density index has been calculated to assess urban sustainability. The methodology adopted can be applied to other case studies in order to estimate total populations, which is vital for the adequate provision of public services.     

Effects of location on Airbnb apartment pricing in Málaga

The relatively recent social movement known as the “sharing economy” is becoming increasingly visible in online peer-to-peer platforms. One such platform is Airbnb; an accommodation marketplace which provides access to tourist accommodation. These platforms are having an important social and economic impact on tourist destinations such as Málaga, Spain. This paper presents a spatial econometric hedonic model that explains the pricing strategy of Airbnb tourist apartments in Málaga using factors such as host, guest, structural characteristics, and location. In relation to locational factors, the model in this study confirms the impact of spatial spillover effects, accessibility to certain amenities, traffic noise, walkability, and the ethnicity of residents in the neighborhood where the listing is located.     

Senior tourists’ accommodation choices

The current trend towards short-term travelling and reduced spending on accommodation has had a significant impact on the hotel sector. However, the hotel industry is becoming increasingly interested in the senior tourist segment, a population group that prefers hotel-type accommodation to other more inexpensive alternatives, even in periods of economic uncertainty. This paper aims to identify the variables that determine senior tourists’ accommodation choices in Spain. In so doing, it identifies the following variables: length of stay, self-perceived health, self-perceived economic status, self-perceived available time, security/safety at the destination, medical coverage, climate, events and festivals, places of historical/artistic interest, and attractions and natural landscapes. These results have important implications for both the hotel industry and the development of tourist destinations.     

The impacts of climate change on tourist mobility in mountain areas

This study investigates the effects of climate change on tourist mobility in mountain areas, distinguishing between infrastructure, transport operation and travel demand. We examine change in tourist travel demand by proposing a two-step approach to forecast its future development. A multi-origin, multi-destination model for tourism demand quantifies the variation in overnight stays within a given region, and a linear, deterministic model determines the traffic-related implications. The method, tested on the Autonomous Province of South Tyrol (Italy), exhibits expected variations in winter and summer travel demand up to 2080 under different scenarios. Results reveal that average summer traffic can be more than twice as intense as average winter traffic, contributing to significantly increasing the peak days of congestion along the Provincial road network. Despite this evidence, all stakeholders seem to be at an early stage in incorporating this information into their strategic planning. The need for adequate transport policies and measures is considered essential to obtain the optimal balance of transport modes that will be required in the near future.     

Modelling Australian domestic and international inbound travel: a spatial–temporal approach

In this paper Australian domestic and international inbound travel are modelled by an anisotropic dynamic spatial lag panel Origin-Destination (OD) travel flow model. Spatial OD travel flow models have traditionally been applied in a single cross-sectional context, where the spatial structure is assumed to have reached its long run equilibrium and temporal dynamics are not explicitly considered. On the other hand, spatial effects are rarely accounted for in traditional tourism demand modelling. We attempt to address this dichotomy between spatial modelling and time series modelling in tourism research by using a spatial-temporal model. In particular, tourism behaviour is modelled as travel flows between regions. Temporal dependencies are accounted for via the inclusion of autoregressive components, while spatial autocorrelations are explicitly accounted for at both the origin and the destination. We allow the strength of spatial autocorrelation to exhibit seasonal variations, and we allow for the possibility of asymmetry between capital-city neighbours and non-capital-city neighbours. Significant temporal and spatial dynamics have been uncovered for both domestic and international tourism demand. For example we find strong seasonal temporal autocorrelations, significant trends and significant spatial autocorrelations at both the origin and the destination. Moreover, the spatial patterns are found to be most significant during peak holiday seasons. Understanding these patterns in tourist behaviour has important implications for tourism operators.     

Tourism seasonality in cultural destinations: Empirical evidence from Sicily

Seasonality is one of the main phenomena affecting tourism. It depends on the characteristics of both tourism demand and tourism destinations in terms of location and services supplied. This paper focuses on a particular aspect of tourism supply: the cultural attractiveness of tourism destinations, and aims to evaluate the role of cultural tourism in tourism seasonality. We analyze the seasonality of tourist presence in different destinations in Sicily, selected according to their different degree of cultural attractiveness. The methodology adopted to measure seasonality is based on a regression analysis approach, using the Census-X12-Arima procedure. Results are discussed and some policy implications are derived.