The Use of Configurational Analysis in the Evaluation of Real Estate Dynamics

  • Enrico G. Caldarola
  • Valerio Di PintoEmail author
  • Antonio M. RinaldiEmail author
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 217)


The shape of urban space together with the choices that lead to its configuration have been the base of long and multidisciplinary debates taking into account several and heterogeneous factors. In this context, the goal of decision makers is to create and improve the value of a given area and manufactures. In this paper we propose a quantitative approach based on configurational analysis in the domain of real estate. The use of geographic information systems to integrate and analyze data form different data sources shows similarities among social-economics models and spatial approaches which consider completely different parameters.


  1. 1.
    Muth, R.: Cities and Housing. University of Chicago Press (1969)Google Scholar
  2. 2.
    Hillier, B., Hanson, J.: The Social Logic of Space. Cambridge University Press, UK (1984)CrossRefGoogle Scholar
  3. 3.
    Hillier, B.: Space is the Machine. Cambridge University Press, UK (1996)Google Scholar
  4. 4.
    Cataldo, A., Pinto, V.D., Rinaldi, A.M.: Representing and sharing spatial knowledge using configurational ontology. Int. J. Bus. Intell. Data Min 10(2), 123–151 (2015)CrossRefGoogle Scholar
  5. 5.
    Wingo, L.: Transportation and Urban Land. Resources for the Future (1961)Google Scholar
  6. 6.
    Alonso, W.: Location and Land Use. Harvard University Press (1964)Google Scholar
  7. 7.
    Chiaradia, A., Hillier, B., Barnes, Y., Schwander, C.: Residential property value patterns. In: Proceedings of the 7th International Space Syntax Symposium, pp. 015:1–015:12. Stockholm, SVE (2009). KTHGoogle Scholar
  8. 8.
    Matthews, J., Turnbull, G.: Neighborhood street layout and property value: the interaction of accessibility and land use mix. J. Real Estate Financ. Econ. 35, 111–141 (2007)CrossRefGoogle Scholar
  9. 9.
    Cataldo, A., Cutini, V., Pinto, V.D., Rinaldi, A.M.: Subjectivity and objectivity in urban knowledge representation. In: Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (KDIR-2014), pp. 411–417. Scitepress (2014)Google Scholar
  10. 10.
    Turner, A.: Angular analysis. In: Proceedings of the 3rd International Space Syntax Symposium, pp. 015:1–015:12 (2001)Google Scholar
  11. 11.
    B. Hillier. Centrality as a process. Accounting for attraction inequalities in deformed grids. In: Proceedings of the 2nd International Space Syntax Symposium, pp. 06.1–06.20 (1999)Google Scholar
  12. 12.
    Hillier, B., Penn, A., Hanson, J., Grajewski, T., Xu, J.: Natural movement: configuration and attraction in urban pedestrian movement. Environ. Plan. B: Plan. Des. 20, 29–66 (1993)CrossRefGoogle Scholar
  13. 13.
    Hillier, B.: The hidden geometry of deformed grids: or, why space syntax works, when it looks as though it shouldn’t. Environ. Plan. B: Plan. Des. 26, 169–191 (1999)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Electrical Engineering and Information Technology (DIETI)University of Naples Federico IINaplesItaly
  2. 2.Institute of Industrial Technologies and AutomationNational Research CouncilBariItaly
  3. 3.Department of Civil, Architectural and Environmental Engineering (DICEA)University of Naples Federico IINaplesItaly
  4. 4.IKNOS-LAB Intelligent and Knowledge Systems (LUPT)University of Naples Federico IINaplesItaly

Personalised recommendations