Seasonality In Tourism Demand Research Articles

Tourism demand with subtle seasonality: Recognition and forecasting

Existing studies on tourism seasonality have been mainly identified at annual or monthly level and the seasonality in tourism demand forecasting has always been addressed by modeling season patterns. However, annual or monthly seasonality is coarse-grained and can’t capture the subtle changes emerging both in tourism theory and practice. This study recognizes tourism seasonality based on intra-day patterns and inter-day similarity and suggests a novel approach to addressing seasonality in tourism demand forecasting. The proposed three-step method contains tourism seasonality recognition, tourism seasonality matching, and tourism demand forecasting. The empirical findings, based on two attractions in China, demonstrate that the proposed method based on dynamic time warping and density-peak clustering can precisely capture tourism seasonality at the daily level. The method can also detect special tourism periods or subtle changes in seasonality, such as staggered peak travel phenomenon. Superior forecasting performance with seasonality matching is also revealed. This study sheds new light on tourism seasonality recognition and contributes to forecasting methodology.

Examining Seasonality in Tourism with Special Reference to the Recent Effects of Covid-19 – The Case of the Sopron-Fertő Tourism Destination (Hungary)

Abstract Seasonality, meaning that the vast majority of tourist locations do not distribute arrivals evenly throughout the year, in tourism, it is widely regarded as one of the most crucial problems for the majority of the world’s destinations, particularly in terms of sustainability. Nevertheless, despite its importance and that this unbalanced nature has become one of tourism’s most distinguishing characteristics, we can say that no globally comparable international measurement of seasonality is currently available. Based on the abovementioned phenomena, the main objective of the present study and research is to detect and analyse the tourism seasonality of a case study area, the Sopron-Fertő destination (Hungary), using multiple methodologies such as the Gini index, a representative consumer questionnaire and expert interviews. The analysis demonstrates seasonality in tourism demand between 2008–2021, based on which implications on product development and new directions and challenges, influenced by the most recent impacts of the COVID-19 pandemic, are revealed and suggested.

Seasonality of tourism demand in Turkey: a multi-methodical analysis

ABSTRACT Analyzing seasonality in the modern tourism industry is essential for successful organization and destination management. The purpose of this paper is therefore to provide an in-depth analysis of seasonality in the main destinations in Turkey. The methods used include the seasonal index of the time series model, the seasonality indicator, the Gini coefficient, the Theil index, the Lorenz Curve, and the coefficient of variation. The results suggest that domestic tourism was moderately seasonal, whereas inbound tourism was highly seasonal during 2017–2020. Moreover, capacity utilization on average was approximately half of the relative capacity, which indicates a substantial discrepancy. One of the salient findings of this study is that the novel coronavirus disease has aggravated the seasonal fluctuations in the country’s tourism demand. In addition, the paper provides an adjustment to an interpretation of the Gini coefficient.

The Seasonal Labor Hoarding in Tourist Enterprises—Choice or Necessity?

The seasonality of tourism demand is a natural condition for the functioning of tourist enterprises and affects the choice of employment practice. The aim of the research is to identify the practices of employing workers in tourism industry enterprises and try to understand the determinants of these decisions. The main research questions were what employment practices are used in tourist enterprises and how does the opinion on the condition of the local labor market influence this choice? It was assumed that, in the tourism industry, seasonal fluctuations can be treated the same way cyclical fluctuations are treated in the analysis of dynamic labor demand. The basis for the conclusions was the results of a survey conducted in the tourism industry enterprises in the seaside region of Poland. In the tourist region of the Polish Baltic Sea, 75.6% of tourist enterprises use the practice of total or partial labor hoarding, and 24.4% of enterprises do not use the practice of labor hoarding. They immediately adjust employment to seasonal changes in demand.

New seasonal measurement with stability and clustering seasonal patterns: A case study in Japan from 2011 to 2019.

Seasonality of tourism demand witnesses fluctuations over multiple years. The fluctuations and seasonality often cause seasonal pattern changes. This study presents a new seasonal measurement that considers the stability of seasonal patterns. The measurement is based on a seasonal index and expressed interval-valued data, which are a kind of symbolic data. As a case study, the new measurements are calculated from Japanese overnight data from 2011 to 2019 and the results classify the seasonal patterns of 47 prefectures using a hierarchical clustering method for interval-valued data based on Ward's method. The analysis results indicate that there are differences in not only seasonal patterns but also their stability between domestic overnight demand and inbound overnight demand. The analysis procedure suggested in this study could be helpful in organizing numerous other unstable seasonal patterns.

Measuring Seasonality of Tourism Demand in Petra, Jordan (2006-2017)

Petra is a mature tourism destination in the south of Jordan with a degree of seasonality over the last 10 years. Despite the recognized importance of Petra for the tourism industry in Jordan, there has been a lack of studies that discuss seasonal demand variations and its impacts on other related industries in the region. Yet, this study aims at analyzing patterns and effects of seasonality of tourism demand in Petra for the period 2006-2017. The required data was obtained from Ministry of Tourism and Antiquities (MoTA). Four methods were used to measure tourism seasonality in Petra. These are: Seasonality indicator; Seasonality ratio; Gini coefficient; and Seasonality index. The results of the study showed a modest level of tourism seasonality in the study area. Among methods, Seasonality index appeared to be the appropriate and simple way to calculate seasonality patterns at tourism destinations. The results showed that there are two peaks of seasonality in tourism demand of Petra. The first and the highest one was in April and the second took place in the months of October and November. In addition, seven months represented the low season of tourism demand in Petra. These are December, January and February as well as June, July, August and September. The tourism seasonality in Petra based on that is mainly due to the weather in these months which represent the coldest and warmest months in the year respectively.

REVITALIZING DEPRESSED AREAS OF THE RUSSIAN NORTH (THE CASE OF VELIKY USTYUG)

The study discusses the experience of «Veliky Ustyug – Ded Moroz Homeland» - one of the most successful Russian projects of regional tourism development in scarcely populated and depressed areas of the Russian North.Founded in 1147, Veliky Ustyug is among the oldest towns of the Russian North with a ‘historic city’ and ‘open-air museum’ status. However, in the 1980-1990s it was a typical small town with depressive socio-economic structure based on forestry, small enterprises, folk crafts and distinctive social challenges such as migration, high unemployment, et al. The project «Veliky Ustyug – Ded Moroz Homeland» comparable to Santa Claus Village in Rovaniemi, Finland has increased greatly the tourist flow to the town and improved considerably its socio-economic situation.The research is based on extensive field studies, theoretical observations and includes statistics analysis as well as the results of in-depth interviews with experts and regional stakeholders taken in 2011-2016, review of official legislation. Study reveals that the main idea of the project is to revitalize the depressed community with a wide range of social, educational, economic, infrastructural, cultural, leisure and tourism activities to promote its future sustainable development. The project life cycle is discussed within the birth, growth and maturity periods; each of them is provided with quantitative characterization. Key problems of the project and their possible solutions are identified. The main constraints to the project connected with poor transport accessibility of the destination and high seasonality of tourism demand are considered.

Measuring tourism seasonality across European countries

This paper will propose a general approach for the analysis and measurement of seasonality in tourism, based on an analysis of the pattern of seasonal swing, as a preliminary step for the assessment of seasonal amplitude. The seasonality of tourism demand across European countries will be analyzed and clusters of countries identified, which are based on a similarity of their seasonal pattern. After discussing the limitations of the most frequently used indices employed in the tourism literature, a new index for measuring seasonality in tourism will be suggested in order to measure seasonal amplitude. The latter takes into account the ordinal and cyclical structures of seasonal variations. The results demonstrate a strong connection between seasonal patterns and the spatial distribution throughout European countries, which may orient future policy actions for dealing with seasonality on a European level.

Potential Impact of Climate Change on Beach Tourism in MENA Countries: A Survey Based Study

Climate is a principal resource for tourism, as it codetermines the suitability of locations for a wide range of tourist activities, is a principal driver of global seasonality in tourism demand in MENA Countries, and has an important influence on operating costs, such as heating-cooling, snowmaking, irrigation, food and water supply, and insurance costs. Thus, changes in the length and quality of climate- dependent tourism seasons (e.g., sun-and-sea or winter sports holidays) could have considerable implications for competitive relationships between destinations and therefore the profitability of tourism enterprises. A Quantitative Approach-Questionnaire was designed with the aim of travellers to the MENA Countries. It was structured to focus on the role of climate in general as a destination attribute specifically issues of the relationship between weather beach tourism and climate change impacts Results showed that Adapting to climate change requires anticipating change. Some sectors will be better able to plan than others depending on their capacity to adapt. Enhancing this capacity can reduce risks of adverse future impacts. That is why it would be strategic to increase adaptive capacity in tourism sector. To prevent the impact of climate change on coastal tourism and vice versa, a joint organization for MENA tourism should exist and should meet the need of the States, the tourist destinations, the private sector and NGOs to group together and form joint ventures.

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.

Effects of Tourism Seasonality at Local Level

Abstract The paper underlines the importance of identifying seasonality effects over tourism development. The study applies a simple test for examining the presence of seasonality in tourism demand in the line of exploring its concentration and strength at local level. The investigation is covered by calculating some commonly applied indicators for measuring tourism seasonality, like Gini coefficient, Seasonality Indicator and Coefficient of Variation. The data set addresses the total tourist arrivals between 2000-2013 and elaborates the case of Ohrid, as the most famous tourist destination in Macedonia. The research results point to high level of tourism seasonality with significant flow distribution to tourism development. Finally, the study may serve as a base for identifying measures and activities necessary for creating comprehensive local and regional tourism policy.

A note on seasonal breaks in tourism demand time series

In this paper, a structural break test procedure proposed in literature is employed in a tourism demand analysis context. This article is the first to apply a graphical approach using seasonal surface and seasonal contour maps, which can be important tools for seasonal pattern evolution analyses. For the purpose of empirical study, total lodging figures were selected to analyze British tourism demand in the Algarve. The seasonality of tourism demand has several effects on economic activity. Identifying seasonal breaks in tourism time series allowed us to obtain evidence of efforts to lessen seasonality and that can hopefully benefit long-run policy evaluation and planning.

Empirical analysis of seasonality patter ns in tourism

The paper makes an attempt empirically to investigate the presence of seasonality patterns in tourism. For that purpose, the case of Macedonia is elaborated by introducing data referring tourist arrivals for the period 1992-2012. The analysis is based upon employment of the Gini coefficient, as one of the most commonly applied indicators for measuring and expressing inequalities caused by temporary disorders. The computed data reject the research hypothesis and highlights new facts regarding seasonality in tourism demand in Macedonia. Namely, the outcomes point to conclusion of absence of seasonality i.e. tourism flow concentration is not significant to tourism development. Hence, this study underlines that the up-to-date modest tourism results must not be addressed to seasonality as strong and limiting factor for tourism development in Macedonia, since there is no such.

Spectral analysis of seasonality in tourism demand

This paper aims to analyse the seasonality in New Zealand tourism demand from Australia and the USA using spectral analysis. Tourism demand is divided into four different categories depending on the tourists’ visiting purposes as registered in the customs cards upon their arrivals in New Zealand. Spectral analysis based on the sample from January 1980 to December 2007 revealed that different travel purposes share similar cyclical components but their contributions to the total variation in tourism demand differ between travel purposes and markets. More importantly, the results show that analysing aggregated data is often not sufficient to reveal the underlying seasonal patterns of tourist arrivals and policy makers would benefit greatly by analysing disaggregated data rather than relying on the analysis of aggregated data alone.

Analysing Seasonal Changes in New Zealand's Largest Inbound Market

The purpose of the paper is to analyse seasonal changes in tourism demand by New Zealand's major tourist source market, Australia, for the period 1979–2005. A time series regression model is used to test the significance of monthly seasonality. By examining sub-periods that are based on major exogenous events which have had significant impacts on international travel demand to New Zealand, seasonal distributions and intra-year seasonal variations over the 27-year period are subsequently estimated using normalized seasonal indices, coefficient of variation, seasonal ratio and the Gini coefficient. Compared with the findings of previous studies for other countries, the empirical evidence suggests that, while the tourism flow distribution or concentration is not significant for New Zealand, the seasonality in tourism demand by New Zealand's largest inbound market has changed over time.

Patterns of seasonality in employment in tourism in the UK

Tourism employment has grown rapidly (a fact which has been of interest to policymakers concerned with job generation) but it has a marked seasonal character. Several attempts have been made by the industry to lessen seasonality in tourism demand (and hence in tourism employment) by fillng troughs. This paper uses recent advances in econometric work to investigate whether seasonality has lessened as a result of these policies, and if so, the nature of the changes in seasonality. A quarterly UK data series from 1982:1 to 1996:4 is examined. The distinction between stochastic and deterministic trend is made, and it is found that seasonality has in fact lessened and is best modelled as a break in deterministic seasonality. There has been approximately a 30% fall in the summer (second quarter) effect and approximately a 24% fall in the winter (fourth quarter) effect: thus the seasonal smoothing comes from lower hiring at the start of the peak season and lower firing at the end of the season.