With reference to the current topic of the energy efficiency of residential properties, the aim of this research is to analyze the contribution of the energy performance component on the housing prices. The study has been carried out on a sample of two hundred residential properties recently sold and located in the city of Bari (Italy). In addition to the characteristics of energy performance, the main influencing factors considered by buyers and sellers in the transactions have been detected. For this purpose, a data-driven technique has been implemented, that employs a genetic algorithm to identify the best functional expressions. The outputs obtained highlight an appreciable influence of the energy factors on the housing prices. The results could be a useful support for both the private and public actors operating in the field of residential property management.
An analysis of the energy efficiency impacts on the residential property prices in the city of Bari (Italy) / Morano, Pierluigi; Rosato, Paolo; Tajani, Francesco; Di Liddo, Felicia (GREEN ENERGY AND TECHNOLOGY). - In: Values and Functions for Future Cities / [a cura di] Giulio Mondini; Alessandra Oppio; Stefano Stanghellini; Marta Bottero; Francesca Abastante. - STAMPA. - Cham, CH : Springer, 2020. - ISBN 978-3-030-23784-4. - pp. 73-88 [10.1007/978-3-030-23786-8_5]
An analysis of the energy efficiency impacts on the residential property prices in the city of Bari (Italy)
Pierluigi Morano;Francesco Tajani;Felicia Di Liddo
2020-01-01
Abstract
With reference to the current topic of the energy efficiency of residential properties, the aim of this research is to analyze the contribution of the energy performance component on the housing prices. The study has been carried out on a sample of two hundred residential properties recently sold and located in the city of Bari (Italy). In addition to the characteristics of energy performance, the main influencing factors considered by buyers and sellers in the transactions have been detected. For this purpose, a data-driven technique has been implemented, that employs a genetic algorithm to identify the best functional expressions. The outputs obtained highlight an appreciable influence of the energy factors on the housing prices. The results could be a useful support for both the private and public actors operating in the field of residential property management.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
