Seasonality of tourism demand in Turkey: a multi-methodical analysis
Orhan Yabancı
Abstract
Orhan Yabancı
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.
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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.
Key concepts: Tourism, Seasonality, Regional science, Business, Economic geography, Economics, Geography, Statistics