Digital Commons Network^™

Course Syllabus: Ppol-G 741l Urban Housing Policy, Michael P. Johnson Jr.

Michael P. Johnson

This course will provide students with the ability to identify and analyze phenomena in cities and urbanized areas related to a socially fundamental need for adequate and affordable shelter that ensures individual well-being and social and community stability and sustainability. Students completing this course will understand the progress the United States, and other countries has made in ensuring decent and affordable housing for its population, as well as the considerable policy barriers that prevent many people enjoying the housing they desire and the individual and social benefits that arise from it.

Community-Engaged Decision Modeling For Local Economic Development, Michael P. Johnson Jr., Sandeep Jani

Michael P. Johnson

This presentation contains current results from a research project to identify success metrics and decision opportunities for Boston Main Streets organizations. It represents an application of qualitative decision analytic methods for values and objectives design

Data And Analytics For Neighborhood Development: Smart Shrinkage Decision Modeling In Baltimore, Maryland, Michael P. Johnson Jr., Justin Hollander, Eliza D. Whiteman

Michael P. Johnson

Many older cities in the United States confront the problem of long-term decline in population and economic activity resulting in blighted conditions that make conventional revitalization initiatives unlikely to succeed. Smart shrinkage, a planning approach that emphasizes alternative land uses while preserving quality of life, offers a way for cities to remain desirable places to live and work. However, there is little research on empirical methods to support planning decisions consistent with smart shrinkage. We present results from two studies with planners from the City of Baltimore that provide novel insights regarding ways in which planners can perform vacant property …

Data And Analytics For Neighborhood Development: Smart Shrinkage Decision Modeling In Baltimore, Maryland, Michael P. Johnson Jr., Justin Hollander, Eliza D. Whiteman

Michael P. Johnson

Researching What Matters With Community Members: Session Introduction, Michael P. Johnson Jr.

Michael P. Johnson

Data and technology can and do change people’s lives, but most often they are conceived as market-driven entities, where changes in people’s lives arise from consumption of goods and services they pay for. Of course, government is a big user of technology and data, but impacts are usually aggregate in nature, not usually targeted at specific communities. Yet, with inequality and structural barriers to economic and social progress quite high in the U.S., can there be a way to think of data and technology as a means to support individual and group opportunity, engagement, action for social justice? The purpose …

Community Impacts Of Decision Modeling For Foreclosed Redevelopment, Michael P. Johnson Jr., Alvine Sangang, Buki Usidame

Michael P. Johnson

Community development corporations purchase distressed housing to rehabilitate for renter or owner-occupancy. These mission-driven organizations, skilled in the business of housing development, often lack analytic expertise to determine which acquisitions to pursue that would maximize social impact. This paper presents results, using actual purchase data from a Boston-area CDC, to assess the potential social benefits associated with using a decision model as compared to conventional practices.

Data And Analytics For Neighborhood Development: Smart Shrinkage Decision Modeling In Baltimore, Maryland, Michael P. Johnson Jr., Justin Hollander, Eliza D. Whiteman

Michael P. Johnson

Many older cities in the United States confront the problem of long-term declines in population and economic activity in certain neighborhoods have resulted in blighted conditions that make conventional revitalization initiatives based on increased residential and commercial development unlikely to succeed. Planning scholars have developed a theory of smart shrinkage in which emphasis is placed on non-residential land uses that can maintain and improve quality of life while positioning some land for future growth-oriented activities (Hollander and Németh 2011). Smart shrinkage research and practice involves application of methods from information technology and decision science to identify vacant and abandoned parcels …

Strategy Design For Community Response To Distress And Decline Using Data Analytics, Michael P. Johnson Jr.

Michael P. Johnson

The foreclosure crisis in the U.S. has resulted in immense economic and social losses for individuals and neighborhoods. Some neighborhoods face long-term declines in population and economic activity that have been compounded by the foreclosure crisis. How can government and non-profit organizations design responses to neighborhood distress that reflect distinctive community characteristics and are consistent with long-term policy and planning goals? In this talk, I discuss alternative decision modeling strategies that support neighborhood health. Where foreclosure responses are likely to ensure that neighborhoods remain vital places for residential housing, productive strategies may include property acquisition and redevelopment. Other neighborhoods, however, …

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.

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.

Maintain, Demolish, Re‐Purpose: Policy Design For Vacant Land Management Using Decision Models, Michael P. Johnson Jr., Justin Hollander, Alma Hallulli

Michael P. Johnson

Neighborhoods, cities, regions and countries face sustained economic and population decline, due to lower population growth rates, deindustrialization and sustained disinvestment, and the housing foreclosure crisis. Planners increasingly see ‘decline’ as something to plan for: a place may lose population while ensuring a high quality of life and enhanced social value (Delken 2008, Hollander 2010). Growth-oriented planning continues to maintain its hegemony over local government decision-making. Can decision models help planners devise strategies that will maximize the social value of managed decline?