Digital Commons Network^™

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

Michael P. Johnson

Community Data Analytics: Localized Data Analysis And Decision Modeling In The Era Of ‘Big Data’ And ‘Smart Cities’, Michael P. Johnson Jr.

Michael P. Johnson

Success Measures For Local Economic Development: Project Final Report, Michael P. Johnson Jr., Sandeep Jani

Michael P. Johnson

No abstract provided.

Measuring Success: Community Analytics For Local Economic Development, Michael P. Johnson Jr., Sandeep Jani

Michael P. Johnson

An Agenda For Diversity And Inclusion-Related Research Within Or/Ms/Analytics, Michael P. Johnson Jr., George Chichirau

Michael P. Johnson

Estimating Strategic Impacts Of Foreclosed Housing Redevelopment Using Spatial Analysis, Michael P. Johnson Jr.

Michael P. Johnson

Decision Modeling For Housing And Community Development: #11;A Methodology For Evidence-Based Urban And Regional Planning, Michael P. Johnson Jr.

Michael P. Johnson

Measuring Success: Community Analytics For Local Economic Development, Michael P. Johnson Jr., Sandeep Jani

Michael P. Johnson

Community-Based Operations Research: Data Analytics And Decision Modeling For Community Development And Social Change, Michael P. Johnson Jr.

Michael P. Johnson

How Can Value Elicitation In Adult Basic Education Support Learners’ Success In Goal-Setting Policy?, Alma H. Biba, 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

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 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.

Practicum 2012 - 2013: Lift Boston Client Well Being Study, Lisa Kalimon, Buki Usidame, Ryan Kling, Ryan Mclane, Ryan Whalen, Ana M. Sanchez, Tanya Stepasiuk, Michael P. Johnson Jr.

Michael P. Johnson

A Boston based non-profit and a team of public policy PhD students engaged in several months of collaborative problem identification and goal setting focused on the effectiveness of the organization’s unique service delivery model. The nonprofit uses volunteer advocates and a goal-oriented process with no eligibility criteria to assist clients in distress. We collected administrative data, administered a survey, and conducted interviews to explore client well-being.

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.

Uplifting: Improvements In Boston Area Client Well-Being, Ryan Kling, Lisa Kalimon, Tanya Stepasiuk, Bukola Usidame, Ryan Mclane, Ryan Whalen, Ana Maria Sanchez, Michael P. Johnson Jr.

Michael P. Johnson

LIFT-Boston, a local non-profit organization, entered into a collaborative partnership in September 2012 with McCormack Graduate School Public Policy Ph.D. students and faculty to develop and execute a research project. The goals of this endeavor were to assist LIFT-Boston in understanding the outcomes associated with its services and enable the organization to further pursue service goals. The primary research questions respond to the organization’s most fundamental questions. These include how the organization’s unique service model impacts clients across several objective and subjective dimensions of well-being. Secondary questions focus on how these impacts may translate into increases or decreases in student …

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.