旅游熵:旅游住宿不可见的一面

Miguel Ángel Ruiz Reina
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引用次数: 2

摘要

. 随机情况的测量是计量经济学领域的一个相关事实。在计量经济学领域的通常实践中,对数据的统计分布进行假设。本文引入了物理学中的一个概念,具体地说,熵作为一种解释因素在旅游公寓住宿决策中的应用。“共享经济”概念的出现,推动了房地产市场的发展。假设与酒店等传统住宿直接竞争。为此,对2005年1月至2018年8月期间的熵时间序列进行了计算和定义,并使用最常用的预测模型对12个月的时间范围进行了预测和比较。为了进行预测比较,我们使用新的矩阵U1 Theil,它允许量化使用熵模型的增益。该研究应用的主要地点是西班牙、加泰罗尼亚和巴塞罗那。理论含义和经济后果是相关的利益相关者在决策。研究详细描述了旅游公寓住宿决策中的交换关系,详细描述了不确定情况下的交换关系,模型具有较高的解释能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Entropy of Tourism: the unseen side of tourism accommodation
. The measurement of random situations is a relevant fact within the field of Econometrics. In the usual practice of the field of Econometrics assumptions are made about the statistical distributions of the data. In this paper, a concept from Physics is introduced, specifically the use of Entropy as an explanatory factor in the decision-making of tourist accommodation in apartments. The emergence of a concept called Sharing Economy has made the housing market to evolve. Assuming a direct competition against traditional accommodation such as hotels. For this, the Entropy time series have been calculated and defined for the periods between January 2005 and August 2018, to forecast and compare them with a time horizon of 12 months with the most usual predictive models. To carry out the forecast comparisons, we work with the new Matrix U1 Theil which allows quantifying the gain of the use of the Entropy models. The main locations in which the study has been applied are Spain, Catalonia and Barcelona. The theoretical implications and economic consequences are relevant for stakeholders in decision-making. The study details the relations of exchange in the decision making of accommodations in tourist apartments and details the relationship of exchange in situations of uncertainty with a high explanatory capacity of the models.
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