The term seasonality, by its semantic meaning, is rooted from seasonal, which means something that is happening or needed only at a particular time of year. That is, seasonality refers to the rise and fall in prices or in demand according to the various times of year. For example, the price of heating oil rising in winter is an effect of seasonality. Seasonality occurs in a wide range of industrial and agricultural sectors. It can be defined as a cyclical pattern that more or less repeats itself each year, and usually refers to a temporal imbalance in the demand. Seasonality also has a market characteristic in which a product or service becomes very popular for a period of a few months each year and then drops off significantly. Examples of seasonality would be Valentine’s Day candy, swimming suits, winter ski chalets, or Halloween costumes.
Seasonality makes demand fluctuation occur not only yearly, but also daily, weekly, and monthly. The causes of seasonality incorporate two basic elements: natural and institutional. The first relates to regular temporal variations in natural phenomena, particularly those associated with climate (temperature, rainfall, snowfall, sunlight, and the like) and the period of the year. The second cause depends on social factors and policies concerning specific customs and legislated holidays. They include school schedules, industrial and public holidays, festivals (religious and cultural), and other events. Richard Butler added three more causes of seasonality: social pressure or fashion (e.g., taking waters at spas or hunting on country estates among the privileged elites), sporting season (e.g., snow skiing or surfing), and inertia or tradition (referring to the tendency of business operators to accept the status quo). For example, some family business owners might actually prefer to close for part of the year.
Put simply, climate or weather are generally held responsible for seasonal fluctuations in demand, but social customs, and especially holiday periods, exacerbate the tendency for summertime peaks in the Northern Hemisphere and wintertime peaks in tropical destinations. In addition to these two main factors, seasonality can also be influenced by business customs and calendar effects such as special events. The supply side is also a potential cause, such as where constraints in labor availability and the alternative uses of facilities lead to closures or altered target markets.
Much of the literature on seasonality focuses on the examination of destination-specific demand patterns and the consequent problems. Among various types of businesses, such as automotive, construction, food stores, hotels and motels, restaurants, department stores, retail stores, rental properties, and utilities, it is argued that hotels and motels, restaurants, food stores, department stores, and retail stores are most affected by seasonality. For instance, demand variability exists at a more micro level in terms of differences between midweek and weekend occupancy in business operations and between breakfast and lunch service in many hotels. Such variation has social as well as practical consequences and historically has been the justification of split shifts within the sector, itself an alleged contributory cause of alcoholism among hospitality employees. The sector also caters for extremes in demand in areas such as banqueting where demand may be occasional or erratic and where the management response is generally to employ an army of casual or agency staff as and when demand dictates.
Advantages And Disadvantages
Seasonality is often perceived negatively. Possible disadvantages include declining returns on investment and problems caused by recruiting and employing full and part-time staff, the temporal effects related to the efficiency and the capacity of the facilities and to the management of public goods and services such as infrastructures, public safety, public health, and natural resources. Furthermore, a reduction in the quality of the services may occur because of congestion, overbooking, or saturation with subsequent reduced satisfaction level, when the demand exceeds the capacities of supply.
In addition to negative perception, seasonality can be viewed positively. For example, ecological impacts are occurring because of the concentration of visitors during the peak season at a destination. The negative effects include congested roads, disturbance of wildlife, physical erosion of footpaths, and litter problems. The off-season period provides such benefits as time for environmental reclamation and resident recovery. Moreover, some researchers argue that maintenance work on buildings or attractions is typically scheduled for the off-peak periods and supports construction jobs and specialist trades.
Seasonality of demand is typically caused by institutional and/or natural factors with the pattern usually remaining stable over many years. This predictability of seasonality makes it possible for businesses, lenders, and investors to anticipate many of its impacts as well as react to them. The literature suggests that employment, cost, and facilities are the three areas in which operations can adjust to counter seasonality. Facilities can be closed during off-peak seasons, staff can be laid off, and costs therefore can be reduced.
To lessen the impact of seasonality, some strategies are also suggested, such as (1) extending the season or introducing additional season(s) by holding some events and festivals; (2) identifying new market segments, which helps to increase demand outside the peak season; and (3) introducing a flexible pricing policy. In general, promotional pricing is effective in increasing demand over low or off-peak seasons.
- Bar-On, “Seasonality in Tourism: A Guide to the Analysis of Seasonality and Trends for Policy Making,” The Economist Intelligence Unit, Technical Series (1975);
- Tom Baum and Svend Lundtorp, eds., Seasonality in Tourism (Pergamon, 2001);
- Butler, “Seasonality in Tourism: Issues and Problems,” in Tourism: The State of the Art, A. V. Seaton, ed. (Wiley, 1994);
- Miquel Clar, JuanCarlos Duque, and Rosina Moreno, “Forecasting Business and Consumer Surveys Indicators: A Time-series Models Competition,” Applied Economics (v.36/20, 2007);
- Oscar Claveria, Ernest Pons, and Raul Ramos, “Business and Consumer Expectations and Macroeconomic Forecasts,” International Journal of Forecasting (v.23/1, 2007);
- Karl H. van Donselaar, Rob J. Hyndman, Ton G. de Kok, and Pim Ouwehand, A State Space Model for Exponential Smoothing With Group Seasonality (Monash University, Department of Econometrics and Business Statistics, 2007);
- Phillip G. Gould et al., Forecasting Time-Series With Correlated Seasonality (Monash University, Department of Econometrics and Business Statistics, 2004);
- SooCheong (Shawn) C. Jang, “Mitigating Tourism Seasonality: A Quantitative Approach,” Annals of Tourism Research (v.31/4, 2004);
- Javier Capó Parrilla, Antoni Riera Font, and Jaume Rosselló Nadal, “Accommodation Determinants of Seasonal Patterns,” Annals of Tourism Research (v.34/2, 2007);
- Robert P. Roney, Bounded Chaos in Equity Markets: Seasonality, Information Effects and the SEC Filings (Soenen, 2003).
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