Analysis and development of a tourism demand forecast system at the canary islands

  1. Elisa María Jorge González
Supervised by:
  1. Enrique Francisco González Dávila Director

Defence university: Universidad de La Laguna

Year of defence: 2019

  1. Jesús Juan Ruiz Chair
  2. María Mercedes Suárez Rancel Secretary
  3. Josep Ginebra Committee member
  1. Matemáticas, Estadística e Investigación Operativa

Type: Thesis

Teseo: 605593 DIALNET lock_openRIULL editor


Over the last thirty years, the phenomenal growth of both the world-wide tourism sector and academic interest in tourism has created great curiosity in tourism demand modelling and forecasting from both business and research sectors. Tourism is one of the main sectors which has a direct impact on the economic and financial development of a vast variety of countries around the world. World Tourism Organization (2019) reported that Spain is the top second destination by international tourist arrivals and in turn, Canary Islands is one of the top three destinations choose in Spain. Time series modelling and forecasting have a positive and effective impact on the elaboration and planification of all engagements of the tourism industry besides defining the relationship with other factors contributing to tourism demand. There are a vast variety of methods to understand and analyse the relationship between tourism and its determining factors, besides in recent times it has been applied several quantitative time series models and forecasting techniques to forecasting tourist arrivals. This thesis studies time series analysis including Autoregressive Integrated Moving Average Models and Structural Time Series Models and its application. The techniques that are developed in this thesis aimed at practical application to real problems in applied time series analysis. This thesis arose from the need expressed by Instituto Canario de Estadística, which based on international recommendations has been developing in recent years a research strategy to offer information on tourism with the best possible quality at a regional level, to respond to administrations as well a companies and business associations that ask them to know the future tourists demand. To this end, a research project arose in which I was lucky to participate, whose goal was to forecast the number of tourist entries by destination island and visitor nationality in the following twelve months from the last available data.