Predictive analytics can facilitate proactive property vacancy policies for cities
Sheila U. Appel,
Derek Botti,
James Jamison,
Leslie Plant,
Jing Y. Shyr and
Lav R. Varshney
Technological Forecasting and Social Change, 2014, vol. 89, issue C, 161-173
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.
Keywords: Property vacancy; Systems of systems; Predictive analytics; Urban planning (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162513002138
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:89:y:2014:i:c:p:161-173
DOI: 10.1016/j.techfore.2013.08.028
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().