The tourist demand of the hotel chain. Time series for a forecast model

Abstract

In an increasingly uncertain world where world dynamics accelerates the way of managing processes in any sector, the forecast of tourist demand becomes very important. In this sense, the present research aims to forecast the tourist demand of the Cuban Hotel Chain of Pinar del Río, Cuba, until December 2019, through the use of time series techniques, which facilitate planning and decision-making. in this sector and in this way work towards the achievement of an integration in the productive chains, considering that tourism is one of the socioeconomic activities that activates many other sectors of production and services, as well as predicting the behavior of tourism. For this, the quantitative research method was used as the guiding method, based on the Box - Jenkins methodology and the Holt - Winters exponential smoothing method. It is also possible to characterize tourism management taking into consideration two indicators: cost per weight and average income per tourist, referring to efficiency and effectiveness respectively. In addition, a multivariate analysis of time series was carried out that made it possible to characterize the tourist activity in four fundamental stages in the hotel chain taken as the object of study.