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Visual Description of the Indoor Space of Real Estate in Crowd-Sourcing Environments

Author

Listed:
  • Haghbayan Sara

    (Faculty of Geodesy and Geomatics Engineering, University of K.N.Toosi in Tehran)

  • Malek Mohammad Reza

    (Faculty of Geodesy and Geomatics Engineering, University of K.N.Toosi in Tehran)

  • Tashayo Behnam

    (Faculty of Civil Engineering and Transportation, University of Isfahan)

Abstract

Emerging the power of collective intelligence through crowdsourcing could create a clear path for visualizing real estate as well. One of the Crowdsourcing applications is describing the indoor space of a real estate. This paper aims to describe real estate in the context of spatial crowdsourcing. Qualitative and quantitative criteria were used in this study to describe the real estate space, topological relationships, directional relations, color, location, dimensions, and height as qualitative criteria. Quantitative criteria were selected as the dimensions and height. The proposed model was evaluated by two groups: those who had never seen the real estate and others that had already seen the same real estate. We implemented a website called SAMA1 to evaluate the proposed model with crowdsourcing data using online collaborative tools. SAMA is using tools, such as a sketch plan, photo, text, virtual tour, and visual descriptions. To evaluate SAMA, we compared it with four representative commercial websites, and the impact of the tools was precisely examined. The obtained results demonstrate that the proposed model can be utilized to visually describe the indoor space of real estate in crowd-sourcing environments.

Suggested Citation

  • Haghbayan Sara & Malek Mohammad Reza & Tashayo Behnam, 2020. "Visual Description of the Indoor Space of Real Estate in Crowd-Sourcing Environments," Real Estate Management and Valuation, Sciendo, vol. 28(3), pages 91-103, September.
    • Handle: RePEc:vrs:remava:v:28:y:2020:i:3:p:91-103:n:8
    DOI: 10.1515/remav-2020-0026
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    References listed on IDEAS

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    1. Ho, Hui-Ping & Chang, Ching-Ter & Ku, Cheng-Yuan, 2015. "House selection via the internet by considering homebuyers’ risk attitudes with S-shaped utility functions," European Journal of Operational Research, Elsevier, vol. 241(1), pages 188-201.
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    3. Marcus T. Allen & Anjelita Cadena & Jessica Rutherford & Ronald C. Rutherford, 2015. "Effects of Real Estate Brokers' Marketing Strategies: Public Open Houses, Broker Open Houses, MLS Virtual Tours, and MLS Photographs," Journal of Real Estate Research, American Real Estate Society, vol. 37(3), pages 343-370.
    4. Michael J. Seiler & Poornima Madhavan & Molly Liechty, 2012. "Toward an Understanding of Real Estate Homebuyer Internet Search Behavior: An Application of Ocular Tracking Technology," Journal of Real Estate Research, American Real Estate Society, vol. 34(2), pages 211-242.
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    More about this item

    Keywords

    crowdsourcing; indoor space; visual describing; real estate; sketch plan;
    All these keywords.

    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services
    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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