Skip to main content
SpringerLink
Log in

Geographically Weighted Regression for the Post Carbon City and Real Estate Market Analysis: A Case Study

  • Conference paper
  • First Online:
New Metropolitan Perspectives (ISHT 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 100))

Included in the following conference series:

Abstract

Geographically Weighted Regression is a statistical technique for real estate market analysis, particularly adequate in order to identify homogeneous areas and to define the marginal contribution that the geographical location gives to the market value of the properties. In this paper a GWR has been applied, in order to verify the robustness of the real estate sample, this for the subsequent individuation of progressive real estate sub-samples in able to detect and to identify possible potential market premium in real estate exchange and rent markets for green buildings [21–28]. The model has been built on a large real estate dataset, related to the trades of residential real estate units in the city of Reggio Calabria (Calabria region, Southern Italy).

The authors contributed equally to the study.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Fotheringham, A.S.: Spatial structure and distance-decay parameters. Ann. Assoc. Am. Geogr. 71(3), 425–436 (1981)

    Google Scholar 

  2. Fotheringham, A.S.: Geographically weighted regression and multicollinearity: dispelling the myth. J. Geogr. Syst. 18(4), 303–329 (2016)

    Article  Google Scholar 

  3. Manganelli, B., Pontrandolfi, P., Azzato, A., Murgante, B.: Using geographically weighted regression for housing market segmentation. Int. J. Bus. Intell. Data Min. 9(2), 161–177 (2014)

    Article  Google Scholar 

  4. Del Giudice, V., De Paola, P.: Spatial analysis of residential real estate rental market. In: d’Amato, M., Kauko, T. (eds.) Advances in Automated Valuation Modeling. Studies in System, Decision and Control Series, vol. 86, pp. 9455–9459. Springer (2017)

    Google Scholar 

  5. Del Giudice, V., De Paola, P., Forte, F.: The appraisal of office towers in bilateral monopoly’s market: evidence from application of Newton’s physical laws to the Directional Centre of Naples. Int. J. Appl. Eng. Res. 11(18), 9455–9459 (2016)

    Google Scholar 

  6. Del Giudice, V., Manganelli, B., De Paola, P.: Depreciation methods for firm’s assets. In: ICCSA 2016, Part III. Lecture Notes in Computer Science, vol. 9788, pp. 214–227. Springer (2016)

    Google Scholar 

  7. Manganelli, B., Del Giudice, V., De Paola, P.: Linear programming in a multi-criteria model for real estate appraisal. In: ICCSA 2016, Part I. Lecture Notes in Computer Science, vol. 9786, pp. 182–192. Springer (2016)

    Chapter  Google Scholar 

  8. Del Giudice, V., De Paola, P., Manganelli, B.: Spline smoothing for estimating hedonic housing price models. In: ICCSA 2015, Part III. Lecture Notes in Computer Science, vol. 9157, pp. 210–219. Springer (2015)

    Google Scholar 

  9. Del Giudice, V., De Paola, P.: Geoadditive models for property market. Appl. Mech. Mater. Trans. Tech. Publ. 584–586, 2505–2509 (2014)

    Article  Google Scholar 

  10. Del Giudice, V., De Paola, P., Manganelli, B., Forte, F.: The monetary valuation of environmental externalities through the analysis of real estate prices. Sustainability 9(2), 229 (2017)

    Article  Google Scholar 

  11. Del Giudice, V., De Paola, P., Cantisani, G.B.: Rough Set Theory for real estate appraisals: an application to Directional District of Naples. Buildings 7(1), 12 (2017)

    Article  Google Scholar 

  12. Del Giudice, V., De Paola, P., Cantisani, G.B.: Valuation of real estate investments through Fuzzy Logic. Buildings 7(1), 26 (2017)

    Article  Google Scholar 

  13. Del Giudice, V., De Paola, P., Forte, F.: Using genetic algorithms for real estate appraisal. Buildings 7(2), 31 (2017)

    Article  Google Scholar 

  14. Del Giudice, V., Manganelli, B., De Paola, P.: Hedonic analysis of housing sales prices with semiparametric methods. Int. J. Agric. Env. Inf. Syst. 8(2), 65–77 (2017)

    Article  Google Scholar 

  15. Del Giudice, V., De Paola, P., Forte, F., Manganelli, B.: Real estate appraisals with bayesian approach and Markov Chain Hybrid Monte Carlo Method: an application to a central urban area of Naples. Sustainability 9, 2138 (2017)

    Article  Google Scholar 

  16. Morano, P., Locurcio, M., Tajani, F., Guarini, M.R.: Fuzzy logic and coherence control in multi-criteria evaluation of urban redevelopment projects. Int. J. Bus. Intell. Data Min. 10(1), 73–93 (2015)

    Article  Google Scholar 

  17. Guarini, M.R., D’Addabbo, N., Morano, P., Tajani, F.: Multi-criteria analysis in compound decision processes: the AHP and the architectural competition for the chamber of deputies in Rome (Italy). Buildings 7(2), 38 (2017)

    Article  Google Scholar 

  18. Antoniucci, V., Marella, G.: Immigrants and the city: the relevance of immigration on housing price gradient. Buildings 7, 91 (2017)

    Article  Google Scholar 

  19. Antoniucci, V., Marella, G.: Small town resilience: housing market crisis and urban density in Italy. Land Use Policy 59, 580–588 (2016)

    Article  Google Scholar 

  20. Saaty, T.L., De Paola, P.: Rethinking design and urban planning for the cities of the future. Buildings 7, 76 (2017)

    Article  Google Scholar 

  21. Del Giudice, V., Massimo, D.E., De Paola, P., Forte, F., Musolino, M., Malerba, A.: Post carbon city and real estate market: testing the dataset of Reggio Calabria market using spline smoothing semiparametric method. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds.) Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030. Springer, Berlin (2018). ISBN 978-3-319-92098-6

    Google Scholar 

  22. De Paola, P., Del Giudice, V., Massimo, D.E., Forte, F., Musolino, M., Malerba, A.: Isovalore maps for the spatial analysis of real estate market: a case study for a central urban area of Reggio Calabria, Italy. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds.) Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030. Springer, Berlin (2018). ISBN 978-3-319-92098-6

    Google Scholar 

  23. Massimo, D.E.: Green building: characteristics, energy implications and environmental impacts. Case study in Reggio Calabria, Italy. In: Coleman-Sanders, M. (ed.) Green Building and Phase Change Materials: Characteristics, Energy Implications and Environmental Impacts, pp. 71–101. Nova Science Publishers (2015)

    Google Scholar 

  24. Massimo, D.E.: Valuation of urban sustainability and building energy efficiency: a case study. Int. J. Sustain. Dev. 12(2–4), 223–247 (2009)

    Article  Google Scholar 

  25. Massimo, D.E.: Emerging Issues in Real Estate Appraisal: Market Premium for Building Sustainability. Aestimum, pp. 653–673 (2013). ISSN 1724-2118. http://www.fupress.net/index.php/ceset/article/view/13171. Accessed 21 Sept 2017

  26. Massimo, D.E., Musolino, M., Barbalace, A.: Stima degli effetti di localizzazioni universitarie sui prezzi immobiliari. In: Marone, E. (ed.) La valutazione degli investimenti pubblici per le politiche strutturali. Firenze University Press, Firenze (2011)

    Google Scholar 

  27. Massimo, D.E.: Stima del green premium per la sostenibilità architettonica mediante Market Comparison Approach, Valori e Valutazioni (2010)

    Google Scholar 

  28. Spampinato, G., Massimo, D.E., Musarella, C.M., De Paola, P., Malerba, A., Musolino, M.: Carbon sequestration by Cork Oak forests and raw material to built up post carbon city. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds.) Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030. Springer, Berlin (2018). ISBN 978-3-319-92098-6

    Google Scholar 

  29. Malerba, A., Massimo, D.E., Musolino, M., De Paola, P., Nicoletti, F.: Post Carbon City: building valuation and energy performance simulation programs. In: Calabrò, F., Della Spina, L., Bevilacqua, C.: Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030. Springer, Berlin (2018). ISBN 978-3-319-92098-6

    Google Scholar 

  30. ESRI 2011: ArcGIS Desktop: Release 10. Environmental Systems Research Institute, Redlands, CA (2011)

    Google Scholar 

  31. De Ruggiero, M., Forestiero, G., Manganelli, B., Salvo, F.: Buildings energy performance in a market comparison approach. Buildings 7, 16 (2017)

    Article  Google Scholar 

  32. Ciuna, M., Milazzo, L., Salvo, F.: A mass appraisal model based on market segment parameters. Buildings 7, 34 (2017)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Mediterranea University of Reggio Calabria, 89124, Reggio Calabria, Italy

    Domenico Enrico Massimo, Mariangela Musolino & Alessandro Malerba

  2. Federico II University of Naples, 80125, Naples, Italy

    Vincenzo Del Giudice & Pierfrancesco De Paola

  3. Luigi Vanvitelli University of Campania, 81031, Aversa, Italy

    Fabiana Forte

Authors
  1. Domenico Enrico Massimo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vincenzo Del Giudice
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pierfrancesco De Paola
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fabiana Forte
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mariangela Musolino
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Alessandro Malerba
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pierfrancesco De Paola .

Editor information

Editors and Affiliations

  1. Mediterranea University of Reggio Calabria, Reggio Calabria, Italy

    Francesco Calabrò

  2. Mediterranea University of Reggio Calabria, Reggio Calabria, Italy

    Lucia Della Spina

  3. University of Reggio Calabria, Reggio Calabria, Italy

    Carmelina Bevilacqua

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Massimo, D.E., Del Giudice, V., De Paola, P., Forte, F., Musolino, M., Malerba, A. (2019). Geographically Weighted Regression for the Post Carbon City and Real Estate Market Analysis: A Case Study. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds) New Metropolitan Perspectives. ISHT 2018. Smart Innovation, Systems and Technologies, vol 100. Springer, Cham. https://doi.org/10.1007/978-3-319-92099-3_17

Download citation

Publish with us

Policies and ethics

Search

Navigation