Regarding environmental sustainability and market pricing, the energy class is an increasingly more decisive characteristic in the real estate sector. For this reason, a great deal of attention is now devoted to exploring new technologies, energy consumption forecasting tools, intelligent platforms, site management devices, optimised procedures, software, and guidelines. New investments and smart possibilities are currently the object of different research in energy efficiency in building stocks to reach widespread ZEB standards as soon as possible. In this light, this work focuses on analysing 13 cities in Northern Italy to understand the impact of energy class on market values. An extensive data-mining process collects information about 13,093 properties in Lombardia, Piemonte, Emilia Romagna, Friuli Venezia-Giulia, Veneto, and Trentino alto Adige. Then, a feature importance analysis and a machine learning forecasting tool help understand the influence of energy class on market prices today.
What Is the Impact of the Energy Class on Market Value Assessments of Residential Buildings? An Analysis throughout Northern Italy Based on Extensive Data Mining and Artificial Intelligence
Gabrielli, Laura;Scarpa, Massimiliano;Marella, Giuliano
2023-01-01
Abstract
Regarding environmental sustainability and market pricing, the energy class is an increasingly more decisive characteristic in the real estate sector. For this reason, a great deal of attention is now devoted to exploring new technologies, energy consumption forecasting tools, intelligent platforms, site management devices, optimised procedures, software, and guidelines. New investments and smart possibilities are currently the object of different research in energy efficiency in building stocks to reach widespread ZEB standards as soon as possible. In this light, this work focuses on analysing 13 cities in Northern Italy to understand the impact of energy class on market values. An extensive data-mining process collects information about 13,093 properties in Lombardia, Piemonte, Emilia Romagna, Friuli Venezia-Giulia, Veneto, and Trentino alto Adige. Then, a feature importance analysis and a machine learning forecasting tool help understand the influence of energy class on market prices today.File | Dimensione | Formato | |
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