背景(考古学)
范围(计算机科学)
价值(数学)
差异(会计)
建筑设计
业务
建筑模式
对象(语法)
建筑工程
营销
计算机科学
建筑
工程类
人工智能
古生物学
艺术
会计
软件
机器学习
软件开发
软件设计
视觉艺术
生物
程序设计语言
作者
Tomas Skripkiūnas,Valentinas Navickas
标识
DOI:10.2478/remav-2023-0003
摘要
ABSTRACT A housing price, not considering its change over time, is widely determined by hedonic properties. This is common in literature; however, there is a significant part of a price, the so-called unexplained variance, that is not captured by hedonic models. The scientific problem of this research is how to classify and visualize architectural factors that might have an influence on the market value of a dwelling. The object of the research are architectural factors in a housing market value analysis and the aim of research is to describe the theoretical framework that defines the structure and scope of architectural variables influencing a housing market value. Not all architectural factors described in the literature review are equal in terms of scale, measurability, public or private context, aesthetic or functional priority. A systematic approach would be to classify architectural factors as a matrix of built environment properties. Two orthogonal dimensions can be identified: architectural factors spanning from non-design (functional, utilitarian) to design (abstract, unexplained) and factors spanning from architectural design (private) to urban design (public). A multidimensional and complex system of architectural variables influencing a housing market value exists. Understanding this system is crucial for a housing development to succeed.
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