ON EMPLOYING EXTENDED
CHARACTERISTIC SURFACE MODEL
FOR TOURISM DEMAND FORECASTING

Janusz OpiłaORCID logo

AGH University of Science and Technology
Cracow, Poland



INDECS 20(5), 621-639, 2022
DOI 10.7906/indecs.20.5.8
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Received: 6th September 2021.
Accepted: 5th June 2022.
Regular article

ABSTRACT

Extended Characteristic Surface Model is a theoretical tool of general application designed for computing coefficients in Monte Carlo stochastic simulations in particular in multi equation stochastic econometric models. Econometric models are most often used for economic analysis of large enterprises as well as national economies but rarely for analysis of small entities. The reason is that the costs of building and testing such large-scale models are very high. However, the hereby presented Extended Characteristic Surface Model delivers a not-so-expensive, rather intuitive, and flexible method eligible for consumer sentiment analysis and forecasting as well as for "what-if" inferring suitable for entities of all sizes. In particular, it allows for analysis of demand variation resulting from messages concerning competing merchandise. The article is focused on the application of the Extended Characteristic Surface Model for the evaluation of sentiment and forecast of demand in tourism. In the work extended characteristic surface method is explained in thorough detail, furthermore, the influence of factors such as demographic structure, prices, or market size on financial outcomes is analysed on the example of a small touristic entity.

KEY WORDS
forecasting, sentiment, tourism, visualization, machine learning

CLASSIFICATION
JEL:C01, C53, D81, D91, Z32


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