A Comparative Study on Modelling and Forecasting Tourism Revenues: The Case of Turkey

Abstract

Tourism revenues have important implications for tourism countries in terms of management of tourism-related policies. In order to accurately direct production planning, pricing, promotion and strategic marketing programs, labor and capital resources, accurate and reliable forecasts are needed. Forecasting the developments in tourism with scientific basis methods is an important guide for central and local public administration programs and tourism operators. When reviewing the literature, comparative studies on modeling and forecasting tourism revenues using Artificial Neural Networks (ANNs) are limited and this paper aims to fill this gap. Based on the gap seen in the literature, the purpose of this study is to develop the optimal forecasting model that yields the highest accuracy when comparing the performances of three different methods namely Exponential Smoothing, Box-Jenkins and ANNs for forecasting Turkey's tourism revenues. Forecasting performances of the models were measured by MAPE statistics. As a result of the analyses performed, it was found that ANN Model with [4:5:1] architecture was the best one among the all models applied in this study.

The Effect of Perceptions on Tourism: An Econometric Analysis of the Impacts and Opportunities for Economic and Financial Development in Albania and Kosovo

“…The contribution of tourism to GDP in Kosovo in 2019 was 9.3% [14]. Overall [9], the number of foreign tourists fell by 29%, a much larger decrease than the previous global decrease of 3.99% which occurred in 2009. Kosovo is emerging as a tourist destination, and it is ideal for a relaxing long weekend or an excursion as a part of a longer tour including the neighboring countries of Albania, North Macedonia, and Montenegro.…”

“…Most tourists in Kosovo, almost 79%, visit these countries as well. Another view relating the number of tourists and their contribution to the economy according can be found in [9], who studied countries such as Germany and Austria, where tourism is not a major pillar of the economy. They estimated that tourism contributed USD 3780.55 billion to Germany's GDP and USD 446.31 billion to Austria's GDP.…”

“…According to the UNWTO, the tourism industry has been one of the sectors most stricken by the COVID-19 pandemic, resulting in a loss of up to USD 50 billion in spending and a decline in international tourist arrivals by up to 3% worldwide [8]. The tourism industry is considered the major contributor to GDP for several countries, and as of 2020 over 100 million direct tourism jobs were at risk [9]. The tourism and leisure industry plays an essential role in the economic activities of both studied countries, and customer satisfaction has an important impact on the industry [10].…”

Assessment of Tourism-Led Growth Risks in Resource-Rich Countries: Evidence from Azerbaijan

“…Thus, the the result of the research shows strong evidence of a link between tourism and economic growth (1% increase in tourism receipts leads to economic growth by 0.314%). Also, Işık Maden et al (2019), Cuhadar (2020), Yenişehirlioğlu et al (2020), andOzer (2021) describe the tourism sector as a contributor to Turkey's economic growth. Tang & Tan (2013) try to find an answer question of "How stable is the tourism-led growth hypothesis in Malaysia?"…”

Forecasting the Tourist Arrival Volumes and Tourism Income with Combined ANN Architecture in the Post COVID-19 Period: The Case of Turkey

“…Hassani et al [41] analyze the results of singular spectrum analysis (SSA), ARIMA, exponential smoothing (ETS), and neural networks (NN), and the performance comparison shows the higher performance of SSA among other models. With the aim of obtaining a better performance, Cuhadar [42] compares exponential smoothing, Box-Jenkins, and an ANN model for Turkey's tourism revenues forecasting and concludes that the ANN model outperforms the other models.…”