Evaluating predictors for brownfield redevelopment

Evaluating predictors for brownfield redevelopment This paper quantitatively examines what drives brownfield redevelopment and what factors predict a completed brownfield redevelopment. This research investigated 200 brownfield properties that were listed with the United States Environmental Protection Agency (EPA) and redeveloped between the years 2000 and 2015. Three significant correlations were found in this study: socio-economic factor (income level), green development, and tax incentives significantly correlated with brownfield redevelopment. The combination of six predictor variables was analyzed using multiple regression. Socio-economic (income level) [β = 0.27, t = 3.96, p < 0.001] and sustainable building practice (green development) [β = −0.17, t = −2.56, p = 0.01] significantly predicted brownfield redevelopment. Type of contamination (β = 0.07, t = 0.98, p > 0.05), political climate (β = −0.04, t = −0.52, p > 0.05) and stakeholder involvement (β = 0.04, t = 0.62, p > 0.05) did not significantly predict brownfield redevelopment. Hypothesis two and four assessed predictors of brownfield redevelopment. The findings indicated a significant relationship between brownfield redevelopment and two variables (a) socio-economic factor (income levels) significantly predicted brownfield redevelopment, and (b) green development significantly predicted brownfield redevelopment. The higher value of socio-economic factor, the higher value of brownfield redevelopment. The projects with sustainable development had high brownfield redevelopment value than projects without green development. Recommendations for practice include (a) developers and other stakeholders incorporate sustainable building practices in brownfield redevelopments, (b) government agencies involved in the building process such as building and planning departments provide narratives of best practices in sustainable building to help guide brownfield redevelopments and implement policies to mitigate the displacement of low income residents (c) creation of a centralized database of brownfields that have been redeveloped detailing the project attributes. Recommendations for future research may include (a) quantitative study of demographic factors such as age, gender, race, and education as possible predictors of successful brownfield redevelopment and (b) a study on the types of contamination that have been successfully remediated resulting in a successful brownfield redevelopment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Land Use Policy Elsevier

Evaluating predictors for brownfield redevelopment

Loading next page...
 
/lp/elsevier/evaluating-predictors-for-brownfield-redevelopment-JsIg0ZZTKD
Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Ltd
ISSN
0264-8377
D.O.I.
10.1016/j.landusepol.2018.01.008
Publisher site
See Article on Publisher Site

Abstract

This paper quantitatively examines what drives brownfield redevelopment and what factors predict a completed brownfield redevelopment. This research investigated 200 brownfield properties that were listed with the United States Environmental Protection Agency (EPA) and redeveloped between the years 2000 and 2015. Three significant correlations were found in this study: socio-economic factor (income level), green development, and tax incentives significantly correlated with brownfield redevelopment. The combination of six predictor variables was analyzed using multiple regression. Socio-economic (income level) [β = 0.27, t = 3.96, p < 0.001] and sustainable building practice (green development) [β = −0.17, t = −2.56, p = 0.01] significantly predicted brownfield redevelopment. Type of contamination (β = 0.07, t = 0.98, p > 0.05), political climate (β = −0.04, t = −0.52, p > 0.05) and stakeholder involvement (β = 0.04, t = 0.62, p > 0.05) did not significantly predict brownfield redevelopment. Hypothesis two and four assessed predictors of brownfield redevelopment. The findings indicated a significant relationship between brownfield redevelopment and two variables (a) socio-economic factor (income levels) significantly predicted brownfield redevelopment, and (b) green development significantly predicted brownfield redevelopment. The higher value of socio-economic factor, the higher value of brownfield redevelopment. The projects with sustainable development had high brownfield redevelopment value than projects without green development. Recommendations for practice include (a) developers and other stakeholders incorporate sustainable building practices in brownfield redevelopments, (b) government agencies involved in the building process such as building and planning departments provide narratives of best practices in sustainable building to help guide brownfield redevelopments and implement policies to mitigate the displacement of low income residents (c) creation of a centralized database of brownfields that have been redeveloped detailing the project attributes. Recommendations for future research may include (a) quantitative study of demographic factors such as age, gender, race, and education as possible predictors of successful brownfield redevelopment and (b) a study on the types of contamination that have been successfully remediated resulting in a successful brownfield redevelopment.

Journal

Land Use PolicyElsevier

Published: Apr 1, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off