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Predictive analytics can facilitate proactive property vacancy policies for cities

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  • Appel, Sheila U.
  • Botti, Derek
  • Jamison, James
  • Plant, Leslie
  • Shyr, Jing Y.
  • Varshney, Lav R.

Abstract

Is it possible for a city to understand, analyze, predict, and therefore prevent vacant properties? In this paper, we demonstrate the feasibility of using techniques from machine learning and data mining to determine the future vacancy risks for individual properties and for neighborhoods using a variety of structural, demographic, socioeconomic, and city activity features with high accuracy. Within a larger systems-of-systems framework that we develop, these predictive analytics will allow a city to move from decision-making based on ‘educated anecdotes’ and reactive strategies aimed at the most urgent need, to policy development based on informed, holistic insight and proactive interventions that prevent and reverse decline. A demonstration of the use of predictive analytics within the sociotechnical system is provided using data from Syracuse, New York.

Suggested Citation

  • Appel, Sheila U. & Botti, Derek & Jamison, James & Plant, Leslie & Shyr, Jing Y. & Varshney, Lav R., 2014. "Predictive analytics can facilitate proactive property vacancy policies for cities," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 161-173.
    • Handle: RePEc:eee:tefoso:v:89:y:2014:i:c:p:161-173
    DOI: 10.1016/j.techfore.2013.08.028
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    References listed on IDEAS

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    2. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    3. Luis Bettencourt & Geoffrey West, 2010. "A unified theory of urban living," Nature, Nature, vol. 467(7318), pages 912-913, October.
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    Cited by:

    1. Ha Thi Khanh Van & Tran Vinh Ha & Takumi Asada & Mikiharu Arimura, 2022. "Vacancy Dwellings Spatial Distribution—The Determinants and Policy Implications in the City of Sapporo, Japan," Sustainability, MDPI, vol. 14(19), pages 1-26, September.
    2. Minako Hara & Tomomi Nagao & Shinsuke Hannoe & Jiro Nakamura, 2016. "New Key Performance Indicators for a Smart Sustainable City," Sustainability, MDPI, vol. 8(3), pages 1-19, March.

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