Search

Mass tourism puts enormous pressure on wastewater treatment plants due to its expansive growth during the summer months. To adapt to the fluctuations, the Ravda wastewater treatment plant (WWTP) uses innovative methods and technologies, allowing for "shrinking" and "expanding" of the facilities according to the season. This has been built in stages over the years, with two separate biological treatment lines adapting to different numbers of tourists and to the quantity of influent wastewater. The aim of this study is to make a comparative assessment of the work of WWTP Ravda in the summer and winter seasons and its effectiveness, as well as to compare them. In addition, it examines the years of the COVID-19 pandemic, when a much higher consumption of water per person was noted. Data were analyzed for the period of 2018–2022 inclusive, comparing influent and effluent BOD5 and COD in the summer and winter. Nitrogen and phosphorus removal efficiencies were also tracked. The study shows that municipal wastewater treatment is effective, but much higher values, close to the maximum permissible discharge values, are observed during the tourist season. With the continued growth of the tourism sector, the Ravda wastewater treatment plant would not be able to cope with the discharge standards set by the Ministry of Environment and Water, so measures need to be taken promptly. [ABSTRACT FROM AUTHOR]

Copyright of Tourism Tribune / Lvyou Xuekan is the property of Tourism Institute of Beijing Union University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tourism currently contributes significantly to the national economy. When investing in the accommodation facility on the real-estate market, the tourism sector also represents a certain risk due to a high level of seasonality. This paper investigates the risks related to prices, income and occupancy of accommodation facilities for selected regions in Slovakia. The value of accommodation facilities is estimated using discounted cash flow, probabilistic distribution of rental prices and occupancy of accommodation facilities in selected Slovak regions. The results provide information for potential and profitable investments in exposed regions in tourism. The information can be used in the field of risk management to avoid or reduce the risk of risk investments. Although the resulting values were calculated only for some selected regions, the proposed procedure can be used for any region and compared with the current values. [ABSTRACT FROM AUTHOR]

Copyright of Intercathedra is the property of Poznan University of Life Sciences Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Multivariate forecasting methods are intuitively appealing since they are able to capture the interseries dependencies, and therefore may forecast more accurately. This study proposes a multiseries structural time series method based on a novel data restacking technique as an alternative approach to seasonal tourism demand forecasting. The proposed approach is analogous to the multivariate method but only requires one variable. In this study, a quarterly tourism demand series is split into four component series, each component representing the demand in a particular quarter of each year; the component series are then restacked to build a multiseries structural time series model. Empirical evidence from Hong Kong inbound tourism demand forecasting shows that the newly proposed approach improves the forecast accuracy, compared with traditional univariate models. [ABSTRACT FROM AUTHOR]

A new model that links climate and seasonal tourism demand is developed to study the effects of home climate, destination climate, and climate difference between destinations and source markets on seasonal tourism demand. Using the dynamic panel data technique, the study focuses on the demand of tourists from Hong Kong for 19 of the major tourism cities in Mainland China. The results show that the home climate, destination climate, and the difference in climate between home and destination cities all have significant influence on tourism demand. Furthermore, demand for Mainland Chinese tourism among Hong Kong residents is found to be driven by the climate at the place of origin, while the effects of destination climate and climate difference are weaker. [ABSTRACT FROM AUTHOR]

Since coastal tourism is one of the fastest growing sectors of tourism industry, coastal areas have become increasingly vulnerable in the case of flooding. While in recent years a number of different methods have been put forward to map coastal flood risks, the implications of tourism dynamics for the assessment of human casualties has remained largely overlooked in these models. This chapter examines to what extent the ignorance of (residential) coastal tourism may bias the calculations of human casualties. To this end, a case study has been conducted on the Belgian coast. Both the dynamic nature of coastal tourism and the behaviour of residential tourists in storm surge scenarios are considered. The results of this study show that including tourism dynamics in flood risk management is justified and appropriate, depending on the tourist attractiveness of the flood-prone area and its temporal fluctuations. [ABSTRACT FROM AUTHOR]

Abstract: This study investigates the motivations, concerns and obstacles regarding the use of weather derivatives in the winter tourism industry. The findings from the interviews with 61 ski lift operators in Austria indicate that while the majority of operators are aware of weather risks and report substantial weather exposure, using weather derivatives as a means of offsetting potential loss is rarely considered. This is primarily due to a lack of awareness and knowledge, but on becoming aware of the availability of such instruments ski lift operators express interest in their possible use. The task is thus to increase awareness, knowledge and support for the ski lift operators with reference to the use of weather derivatives. [ABSTRACT FROM AUTHOR]

This paper aims to determine suitable SARIMA models to forecast the monthly outbound tourism departures of three major destinations from Taiwan to Hong Kong, Japan and the USA, respectively. The HEGY test is used to identify the deterministic seasonality in the data. The mean absolute per cent error (MAPE) is used to measure forecast accuracy. A low MAPE demonstrates the adequacy of the fitted SARIMA models. The results indicate that all series with first non-seasonal difference are needed to obtain the deterministic trend in outbound tourism series in Taiwan. [ABSTRACT FROM AUTHOR]

Croatia and Tunisia, located on the northern and the southern coast of the Mediterranean Sea, respectively, have hot and dry summers and rainy winters and, for these reasons, they are both referred to as coastal tourism destinations for European countries. A comparison of the monthly incoming tourism of these two countries during 2002 reveals that Croatia and Tunisia present two different models of coastal tourism. The Tunisian model presents continuity and stability in the amount of incoming tourists throughout the whole year, while the Croatian model is a seasonal one, with a very high peak during the summer and a minimum influx of tourists during the winter. The main reason for this difference is the Croatian colder winter; the result is high seasonal instability in the Croatian tourism industry. [ABSTRACT FROM AUTHOR]

This paper deals with the analysis of the number of tourists travelling to the Canary Islands by means of using different seasonal statistical models. Deterministic and stochastic seasonality is considered. For the latter case, we employ seasonal unit roots and seasonally fractionally integrated models. As a final approach, we also employ a model with possibly different orders of integration at zero and the seasonal frequencies. All these models are compared in terms of their forecasting ability in an out-of-sample experiment. The results in the paper show that a simple deterministic model with seasonal dummy variables and AR(1) disturbances produce better results than other approaches based on seasonal fractional and integer differentiation over short horizons. However, increasing the time horizon, the results cannot distinguish between the model based on seasonal dummies and another using fractional integration at zero and the seasonal frequencies. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Tourism has become a major sector in Turkey. The key to continued attraction of visitors to the country in significant numbers is a careful coordination of marketing and planning of tourism supply resources. These supply resources of tourism certainly include favourable climate and climatic elements. The nature of spatial distribution of resources does affect the dispersion of demand in the country. This current study attempts to classify cities based on their supply indicators and establish the connection between supply resources and selected demand measures. It is hoped that the results of this study will have planning, marketing and resource allocation implications for Turkish tourism. [ABSTRACT FROM AUTHOR]

Each summer millions of northern Europeans have historically escaped the unfavorable weather conditions in their countries in search of the traditional "sun, sand, and sea" vacation in the Mediterranean region. Climate change may alter this longstanding tourism flow, however. Based on combination of a series of scientific climate change scenarios with the Tourism Climatic Index (TCI), a method of evaluating a location's climate for general tourism activity, this article examines projected changes in climatic suitability for tourism in northwestern Europe. Under all the scenarios considered, peak season conditions throughout northwestern Europe are projected to improve over the course of the coming century. In addition, the length of the peak season is also projected to increase in many regions, encompassing not only summer, but extending also into spring and autumn. Our findings suggest that projected climate change could considerably enhance northwestern Europe's competitive advantage relative to the Mediterranean in the summer season. Such shifts in climatic suitability could potentially have substantial impacts on the volumes, spatial distributions, and timing of travel within and to Europe. Together, these alterations to tourism activity have profound implications for the operation of the European tourism industry, from the planning, location, and development of new accommodations, transportation routes, and attractions, to the staffing and operation of existing enterprises. As discussed further in the article, the ability of tourism businesses to successfully adapt to these new conditions is likely to depend heavily on their recognition of climate change as an issue (i.e., the adoption of a proactive rather than reactive stance); to their organizational flexibility; and to the mobility of their capital investments. [ABSTRACT FROM AUTHOR]

The study analysed the seasonality of foreign tourists’ space consumption in Estonia using mobile positioning dataset with anonymous roaming data. The method which uses mobile phone positioning coordinates in space–time movement studies in Estonia is called the social positioning method. The dataset allowed analysis of the distribution of foreigners’ country of origin in Estonia with the precision of network cells of mobile operators. Privacy of mobile phone holders was guaranteed according to EU regulation. It was concluded that seasonality produces very different and sometimes even opposite tourists’ space consumption patterns in Estonia. Coastal areas are popular for summer tourism and not so popular in winter; continental inland areas were used more for winter tourism. The popular summer tourism areas along the Baltic Sea beaches are dominated by one nationality: the Finnish in western Estonia, and the Russians in eastern Estonia. Latvians made up a higher percentage in Saaremaa and Pärnu during summer and in Otepää and Lake Peipsi in winter. The mobile positioning data have great potential for tourism studies and monitoring, but is a sensitive issue due to the fear of surveillance. [Copyright &y& Elsevier]

In recent research it has been shown that a large share of the tourism work force in the Swedish mountain municipalities have their permanent place of residence outside of daily commuting distance from the municipality where they work. In this study, tourism labour mobility and migration to two Swedish mountain municipalities, Åre and Malung, is examined. The principal question addressed is whether temporal tourism labour migration leads to permanent migration of tourism workers or not. The research is based on a longitudinal database material including individual observations between the years 1991–2001. It is shown that the case municipalities have a higher propensity than the rest to employ in‐migrants in tourism. Results also show that relatively few people involved in temporary labour migration to tourism employment in the case municipalities later will permanently migrate to the mountain municipalities but that tourism sector employment is important for the in‐migration of long distance commuters to the case municipalities. The reason for this it is argued is that the motive to seasonally migrate to tourism employment is lifestyle‐related and not meant to be permanent. The seasonality of tourism employment has implications for the local and regional development through tourism. [ABSTRACT FROM AUTHOR]

The study of migrations and mobility has historically been severely limited by the absence of reliable data or the temporal sparsity of available data. Using geospatial digital trace data, the study of population movements can be much more precisely and dynamically measured. Our research seeks to develop a near real-time (one-day lag) Twitter census that gives a more temporally granular picture of local and non-local population at the county level. Internal validation reveals over 80% accuracy when compared with users' self-reported home location. External validation results suggest these stocks correlate with available statistics of residents/non-residents at the county level and can accurately reflect regular (seasonal tourism) and non-regular events such as the Great American Solar Eclipse of 2017. The findings demonstrate that Twitter holds the potential to introduce the dynamic component often lacking in population estimates. This study could potentially benefit various fields such as demography, tourism, emergency management, and public health and create new opportunities for large-scale mobility analyses. [ABSTRACT FROM AUTHOR]

The article considers the best time to visit Washington, D.C. The city's peak seasons generally coincide with two activities, which are the sessions of Congress and springtime. Mid-March through June traditionally is the most busy season, when families and school groups descend upon the city to see the cherry blossoms and enjoy Washington's spring. In July and August, the weather in the city is very hot and humid.