Year: 2024 | Month: December | Volume: 11 | Issue: 12 | Pages: 141-150
DOI: https://doi.org/10.52403/ijrr.20241217
Artificial Intelligence Modelling of Package Tour Revenues in Türkiye
Dr. Cagatay Tuncsiper
Ege University, Cesme Faculty of Tourism, Department of Tour Guidance, Izmir, Türkiye.
ABSTRACT
Package tours in Türkiye offer a convenient way for tourists to explore the country’s rich history, diverse landscapes, and cultural sites without the hassle of planning each detail. They often provide cost savings by bundling accommodations, transportation, and guided tours, making popular attractions like Istanbul, Cappadocia, and Ephesus more accessible. Additionally, package tours help boost local economies by promoting regional tourism, supporting local businesses, and creating jobs. Package tours significantly contribute to Türkiye’s economy by driving revenue through tourism-related services such as hotels, transportation, and local attractions. They also generate employment opportunities across various sectors, from hospitality to guiding services, supporting both urban and rural communities. The revenues of package tours in Türkiye are modelled in this work. The quarterly package tour revenues between 2012Q1 to 2024Q3 are taken from official sources and plotted to observe the seasonality of these revenues. Then, a deep learning model for modelling these revenues are developed in Python programming language. The developed deep learning model has three hidden layers each of which include fifteen neurons. The lagged values of the package tour revenue data are fed as inputs to the developed deep learning model efficiently making the model to be an autoregressive model. The 70% of the available data are chosen as the training data whereas the remaining 30% of the data are used as the test data. The actual package tour revenue data and the model results are plotted on the same axis pair implying the accuracy of the developed deep learning model. Furthermore, the accuracy metrics such as the coefficient of determination, mean absolute error, mean absolute percentage error and root mean square error are also computed verifying the precision of the developed model.
Keywords: package tours, tourism revenue, artificial intelligence, modelling.
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