Entropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand

A new methodology is presented for measuring, classifying and predicting the cycles of uncertainty that occur in temporary decision-making in the tourist accommodation market (apartments and hotels). Special attention is paid to the role of entropy and cycles in the process under the Adaptive Market...

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Autor principal:	Miguel Ángel Ruiz Reina
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	information theory Shannon entropy forecasting decision-making randomness cycle Science Q Astrophysics QB460-466 Physics QC1-999
Acceso en línea:	https://doaj.org/article/f0f00f843a9d41ffb3ae2395d2b94f75
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spelling	oai:doaj.org-article:f0f00f843a9d41ffb3ae2395d2b94f752021-11-25T17:29:05ZEntropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand10.3390/e231113701099-4300https://doaj.org/article/f0f00f843a9d41ffb3ae2395d2b94f752021-10-01T00:00:00Zhttps://www.mdpi.com/1099-4300/23/11/1370https://doaj.org/toc/1099-4300A new methodology is presented for measuring, classifying and predicting the cycles of uncertainty that occur in temporary decision-making in the tourist accommodation market (apartments and hotels). Special attention is paid to the role of entropy and cycles in the process under the Adaptive Markets Hypothesis. The work scheme analyses random cycles from time to time, and in the frequency domain, the linear and nonlinear causality relationships between variables are studied. The period analysed is from January 2005 to December 2018; the following empirical results stand out: (1) On longer scales, the periodicity of the uncertainty of decision-making is between 6 and 12 months, respectively, for all the nationalities described. (2) The elasticity of demand for tourist apartments is approximately 1% due to changes in demand for tourist hotels. (3) The elasticity of the uncertainty factor is highly correlated with the country of origin of tourists visiting Spain. For example, it has been empirically shown that increases of 1% in uncertainty cause increases in the demand for apartments of 2.12% (worldwide), 3.05% (UK), 1.91% (Germany), 1.78% (France), 7.21% (Ireland), 3.61% (The Netherlands) respectively. This modelling has an explanatory capacity of 99% in all the models analysed.Miguel Ángel Ruiz ReinaMDPI AGarticleinformation theoryShannon entropyforecastingdecision-makingrandomnesscycleScienceQAstrophysicsQB460-466PhysicsQC1-999ENEntropy, Vol 23, Iss 1370, p 1370 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	information theory Shannon entropy forecasting decision-making randomness cycle Science Q Astrophysics QB460-466 Physics QC1-999
spellingShingle	information theory Shannon entropy forecasting decision-making randomness cycle Science Q Astrophysics QB460-466 Physics QC1-999 Miguel Ángel Ruiz Reina Entropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand
description	A new methodology is presented for measuring, classifying and predicting the cycles of uncertainty that occur in temporary decision-making in the tourist accommodation market (apartments and hotels). Special attention is paid to the role of entropy and cycles in the process under the Adaptive Markets Hypothesis. The work scheme analyses random cycles from time to time, and in the frequency domain, the linear and nonlinear causality relationships between variables are studied. The period analysed is from January 2005 to December 2018; the following empirical results stand out: (1) On longer scales, the periodicity of the uncertainty of decision-making is between 6 and 12 months, respectively, for all the nationalities described. (2) The elasticity of demand for tourist apartments is approximately 1% due to changes in demand for tourist hotels. (3) The elasticity of the uncertainty factor is highly correlated with the country of origin of tourists visiting Spain. For example, it has been empirically shown that increases of 1% in uncertainty cause increases in the demand for apartments of 2.12% (worldwide), 3.05% (UK), 1.91% (Germany), 1.78% (France), 7.21% (Ireland), 3.61% (The Netherlands) respectively. This modelling has an explanatory capacity of 99% in all the models analysed.
format	article
author	Miguel Ángel Ruiz Reina
author_facet	Miguel Ángel Ruiz Reina
author_sort	Miguel Ángel Ruiz Reina
title	Entropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand
title_short	Entropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand
title_full	Entropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand
title_fullStr	Entropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand
title_full_unstemmed	Entropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand
title_sort	entropy method for decision-making: uncertainty cycles in tourism demand
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/f0f00f843a9d41ffb3ae2395d2b94f75
work_keys_str_mv	AT miguelangelruizreina entropymethodfordecisionmakinguncertaintycyclesintourismdemand
_version_	1718412321596899328

Entropy Method for Decision-Making: Uncertainty Cycles in Tourism Demand

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