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热力学熵和信息熵在改进房地产估值方法中的作用。

The Role of Thermodynamic and Informational Entropy in Improving Real Estate Valuation Methods.

作者信息

Özdilek Ünsal

机构信息

Business School, Department of Strategy, Social and Environmental Responsibility, University of Quebec, Montreal, QC H3C 3P8, Canada.

出版信息

Entropy (Basel). 2023 Jun 7;25(6):907. doi: 10.3390/e25060907.

Abstract

Price, Cost and Income (PCI) are distinct economic indicators intrinsically linked to the values they denote. These observables take center stage in the multi-criteria decision-making process that enables economic agents to convey subjective utilities of market-exchanged commodities objectively. The valuation of these commodities heavily relies on PCI-based empirical observables and their supported methodologies. This valuation measure's accuracy is critical, as it influences subsequent decisions within the market chain. However, measurement errors often arise due to inherent uncertainties in the value state, impacting economic agents' wealth, particularly when trading significant commodities such as real estate properties. This paper addresses this issue by incorporating entropy measurements into real estate valuation. This mathematical technique adjusts and integrates triadic PCI estimates, improving the final stage of appraisal systems where definitive value decisions are crucial. Employing entropy within the appraisal system can also aid market agents in devising informed production/trading strategies for optimal returns. The results from our practical demonstration indicate promising implications. The entropy's integration with PCI estimates significantly improved the value measurement's precision and reduced economic decision-making errors.

摘要

价格、成本与收益(PCI)是与它们所代表的价值内在相关的不同经济指标。这些可观测指标在多标准决策过程中占据核心地位,该过程使经济主体能够客观地传达市场交易商品的主观效用。这些商品的估值严重依赖基于PCI的实证可观测指标及其支持的方法。这种估值方法的准确性至关重要,因为它会影响市场链中的后续决策。然而,由于价值状态中固有的不确定性,测量误差经常出现,影响经济主体的财富,尤其是在交易重大商品(如房地产)时。本文通过将熵测量纳入房地产估值来解决这个问题。这种数学技术调整并整合三元PCI估计值,改进了评估系统的最后阶段,在这个阶段确定价值决策至关重要。在评估系统中采用熵还可以帮助市场主体制定明智的生产/交易策略以实现最优回报。我们实际演示的结果显示出有前景的影响。熵与PCI估计值的整合显著提高了价值测量的精度并减少了经济决策误差。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e9e/10297045/71b724f05500/entropy-25-00907-g001.jpg

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