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An Automatic Tool for the Determination of Housing Rental Prices: An Analysis of the Italian Context

Author

Listed:
  • Francesco Tajani

    (Department of Architecture and Design, Sapienza University of Rome, Via Flaminia 359, 00196 Rome, Italy)

  • Felicia Di Liddo

    (Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy)

  • Rossana Ranieri

    (Department of Architecture and Design, Sapienza University of Rome, Via Flaminia 359, 00196 Rome, Italy)

  • Debora Anelli

    (Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy)

Abstract

In the last decades, some global events such as the economic crisis of 2008 and the COVID-19 emergency of 2020, have generated more attention towards the housing rental market and its capacity to meet several social needs. In order to study the existent demand for houses, then define the interventions on the residential assets to make them more affordable for the most fragile population groups, adequate evaluation tools are required. With reference to the residential property segment of five metropolitan cities located in the Italian territory, the present research is aimed at analyzing the contribution of the most influencing factors on rental prices. In particular, this research refers to the rented properties of the second half of 2019, with a set of variables that represent the intrinsic and extrinsic factors of the local market. The implementation of an automated valuation model allows the determination of the most significant factors and the functional relationships that they have with housing rental fees. The outputs obtained could support the improvement of equitable public housing policies or could guide private investment decisions, such as refurbishment interventions of certain significant factors that could increase the market rental value. This study is the first step in wider research that is currently in progress, which aims to investigate the effects of the existing COVID-19 pandemic on the residential rental market.

Suggested Citation

  • Francesco Tajani & Felicia Di Liddo & Rossana Ranieri & Debora Anelli, 2021. "An Automatic Tool for the Determination of Housing Rental Prices: An Analysis of the Italian Context," Sustainability, MDPI, vol. 14(1), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2021:i:1:p:309-:d:713074
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    Cited by:

    1. Min-feng Lee & Guey-shya Chen & Shao-pin Lin & Wei-jie Wang, 2022. "A Data Mining Study on House Price in Central Regions of Taiwan Using Education Categorical Data, Environmental Indicators, and House Features Data," Sustainability, MDPI, vol. 14(11), pages 1-15, May.

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