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Evaluating the Urban Quality Through a Hybrid Approach: Application in the Milan (Italy) City Area

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

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Abstract

Urban planning can support the optimal exploitation of the resources available in an urban system with specific reference to the accessibility of goods and services by an increase of the quality of the public space. In this perspective, knowing the economic effects generated by urban planning choices can be fundamental to guide decision-making processes. For this purpose, a research work which proposes a method for defining a synthetic index through the Multi-Attribute Value Theory to describe urban quality is presented. The synthetic index proposed in this study reflects the public open spaces, accessibility and provision of services qualities of the urban context. Besides, this study estimates these advantages through the hedonic prices method, analyzing the residential market. The combined methodology has been applied in detail to three districts located in the Municipality of Milan (Italy). The simultaneous reading of the indices used to spatialise the urban quality levels allows identifying the extrinsic characteristics of the three neighbourhoods analyzed. Considering the changes induced on house prices, the results of the hedonic models show that the economic impacts generated by low levels of urban quality are significant. Accordingly, the policies that aim to transform the existing urban fabric become fundamental for the creation of economic and social value.

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Change history

  • 12 November 2020

    In the version of this paper that was originally published the names and surnames of the authors have been inverted.These are now corrected as following:

    Alessandra Oppio

    Marta Bottero

    Federico Dell’Anna

    Marta Dell’Ovo

    Laura Gabrielli

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Author information

Authors and Affiliations

  1. Department of Architecture and Urban Studies, Politecnico Di Milano, Via Bonardi 3, 20133, Milan, Italy

    Alessandra Oppio

  2. Department of Regional and Urban Studies and Planning, Politecnico di Torino, Corso Mattioli 39, 10125, Turin, Italy

    Marta Bottero & Federico Dell’Anna

  3. Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, via Bonardi 9, 20133, Milan, Italy

    Marta Dell’Ovo

  4. Department of Architecture and Arts, IUAV University of Venice, Dorsoduro 2206, 30123, Venice, Italy

    Laura Gabrielli

Authors
  1. Alessandra Oppio
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  2. Marta Bottero
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  3. Federico Dell’Anna
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  4. Marta Dell’Ovo
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  5. Laura Gabrielli
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Corresponding author

Correspondence to Alessandra Oppio .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

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Oppio, A., Bottero, M., Dell’Anna, F., Dell’Ovo, M., Gabrielli, L. (2020). Evaluating the Urban Quality Through a Hybrid Approach: Application in the Milan (Italy) City Area. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12253. Springer, Cham. https://doi.org/10.1007/978-3-030-58814-4_21

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  • DOI: https://doi.org/10.1007/978-3-030-58814-4_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58813-7

  • Online ISBN: 978-3-030-58814-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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