Digital Commons Network^™

Community-Engaged Operations Research: Trends, New Frontiers And Current Applications, Michael P. Johnson Jr.

Michael P. Johnson

Course Syllabus: Ppol-G 742 Community-Based Operations Research, Michael P. Johnson Jr.

Michael P. Johnson

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

Community Development Analytics: From Data To Decisions For Boston Main Streets, Michael P. Johnson Jr., Sandeep Jani

Michael P. Johnson

A successful Main Street organization should be able to identify community strengths and deficits, to formulate a range of potentially effective local initiatives for economic and neighborhood development, to implement select initiatives using the best mix of volunteer and paid resources, to share data and best practices among all Boston Main Street districts, and to communicate project progress and outcome measures with the Office of Business Development. This project seeks to help Boston Main Street DIstricts operate more effectively by articulating values, identifying performance metrics and choosing decision opportunities. We present preliminary study results from a survey of Boston Main …

Data, Analytics And Community-Based Organizations: Transforming Data To Decisions For Community Development, Michael P. Johnson Jr.

Michael P. Johnson

The past ten years have seen a revolution in two disciplines related to operations and strategy design. “Big Data” has transformed the theory and practice of producing and selling goods and services through methods associated with computer science and information technology. “Analytics” has popularized primarily quantitative models and methods by which organizations and systems can measure multiple aspects of performance. As these fields rely on information technology to collect, store, process and share data, we refer to the collection of knowledge and applications associated with Big Data and analytics as “data analytics and information technology.” The impacts of data analytics …

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, …

Data, Analytics And Community-Based Organizations: #11;Transforming Data To Decisions For Community Development, Michael P. Johnson Jr.

Michael P. Johnson

Big data and analytics for community-focused nonprofits can improve analytic capabilities and increase impact. However, Community-based organization needs do not match well with conventional notions of data and analytics. Decentralized model for data-driven research may be preferred, but centralized model is dominant. CBOs can articulate data needs, but are often not yet able to access relevant data easily and use data effectively. Finally, certain values maximize impact of big data and analytics

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.

Decision Modeling For Local Housing Development: ‘Strategic Value’ And Other Social Impact Measures, Michael P. Johnson Jr.

Michael P. Johnson

Acquisition and redevelopment of foreclosed properties by community organizations helps to mitigate the social impacts of foreclosures on neighborhoods and residents. Social impacts can be measured in a variety of ways: (a) Strategic value of foreclosed property locations (b) Averted lost value to proximate properties Models can estimate magnitudes of such effects to identify potential acquisition candidates and social impacts of alternative development strategies. Application of models to a local case study demonstrates how these measures can be used in practice.

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?

Decison Models For Housing And Community Development, Michael P. Johnson Jr.

Michael P. Johnson

Values, Objectives, And Decisions: Using Community-Based Operations Research For Neighborhood Redevelopment, Michael P. Johnson Jr., Rachel B. Drew, Jeffrey Keisler, David Turcotte

Michael P. Johnson

In this presentation we describe an application of value-focused thinking and decision analysis to the design and evaluation of strategies for housing development especially in urban communities affected by the ongoing foreclosure crisis. This is part of a multi-campus, multi-disciplinary effort to study decision processes of community development corporations (CDCs) acquiring and redeveloping foreclosed properties for neighborhood stabilization.

Michael Johnson Research Profile, Michael P. Johnson Jr.

Michael P. Johnson

This document summarizes my disciplinary training and my research products.

Community-Engaged Decision Support For Foreclosed Housing Acquisition And Redevelopment In Boston, Michael P. Johnson Jr.

Michael P. Johnson

This project develops decision tools and analytical methods to help non‐profit community development corporations (CDCs) acquire and redevelop foreclosed housing for neighborhood stabilization and revitalization. Interviews and direct observations at partner CDCs have helped us identify current practices, data and requirements for our decision models. Problem‐structuring methods through CDC focus groups have generated core operational and organizational objectives. Spreadsheet‐ and optimization based decision models generate policy and operational alternatives that address multiple resident and community outcomes. Our research will support efficient responses to the recent foreclosure crisis, especially in distressed neighborhoods, and suggest policy implications at local and national levels.

Decision Models For Foreclosed Housing Acquisition And Redevelopment: A University Of Massachusetts Multi-Campus Collaborative Project - Processes And Findings To Date, Michael P. Johnson Jr., Jeffrey Keisler, Senay Solak, David Turcotte, Rachel B. Drew, Armagan Bayram, Emily Vidrine

Michael P. Johnson

The recent housing foreclosure crisis has had devastating impacts on individuals, communities, organizations and government. In response, several community development corporations (CDCs) have sought new ways to assist neighborhoods suffering from the myriad effects of high foreclosures, including neighborhood instability, increased vandalism and crime, lower property values, and economic disinvestment. This research project focuses on activities of community-based organizations that acquire and redevelop foreclosed properties to support neighborhood stabilization and revitalization. However, the costs of pursuing this strategy far exceed the resources available to typical CDCs. Thus, our project seeks to solve the following decision problem: What subset of a …

Senior Center Network Redesign Under Demand Uncertainty, Osman Ozaltin, Michael P. Johnson Jr., Andrew Schaefer

Michael P. Johnson

Senior centers off#11;er a variety of services to facilitate independent living of older adults. In the U.S., increasing suburbanization and aging of suburban residents necessitate reconfiguring senior services. We propose a two-echelon network of senior centers across large study areas and formulate a stochastic facility location/allocation model with mixed-integer recourse. We apply our model to Allegheny County, Pennsylvania, which has one of the oldest population in the U.S. Our model shows that a two-echelon network design is appropriate for increasing the occupancy of senior centers as community focal points while maintaining customized and accessible programming in small neighborhood areas.