Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Urban Studies and Planning
Parcel-Level Redevelopment Strategies For Distressed Neighborhoods, Michael P. Johnson Jr., Justin Hollander
Parcel-Level Redevelopment Strategies For Distressed Neighborhoods, Michael P. Johnson Jr., Justin Hollander
Michael P. Johnson
Certain distressed neighborhoods cannot support traditional residential-focused development. For these communities, we develop decision models for acquisition and redevelopment of chronically vacant lands and structures for primarily non-residential and greening uses. We address social benefits and costs of redevelopment strategies, parcel clustering to exploit economies of scale, and conflicting values among stakeholders. We illustrate our models using data from Baltimore, MD.
Community-Based Analytics: Big Data And Decision Making For Community-Based Organizations, Michael P. Johnson Jr.
Community-Based Analytics: Big Data And Decision Making For Community-Based Organizations, Michael P. Johnson Jr.
Michael P. Johnson
Community-based organizations face significant challenges in identifying data needs, and assembling data resources for service provision, strategy design and advocacy. We develop principles by which CBOs can develop and share large datasets in order to formulate and solve decision problems that improve the well-being of localized, often marginalized or distressed communities. We illustrate these ideas using field research from Boston, MA.
Property Value Impacts Of Foreclosed Housing Acquisitions Under Uncertainty, Michael P. Johnson Jr., Senay Solak, Rachel B. Drew, Jeffrey Keisler
Property Value Impacts Of Foreclosed Housing Acquisitions Under Uncertainty, Michael P. Johnson Jr., Senay Solak, Rachel B. Drew, Jeffrey Keisler
Michael P. Johnson
Community development corporations seek to stabilize neighborhoods affected by the recent foreclosure crisis through acquisition and redevelopment of distressed properties. One rationale for this work is the alleviation or avoidance of negative foreclosure impacts. We estimate the lost value to proximate properties associated with a single foreclosure through a Markov chain representing probabilistic transitions between foreclosure stages. We apply our model to a case study of foreclosure properties in Chelsea, MA. A rank ordering by estimated property value impacts indicates significant potential gains in social value as compared to current community development practice. We extend our basic model to address …