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Social and Behavioral Sciences

Michael P. Johnson

Community data analytics

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Articles 1 - 4 of 4

Full-Text Articles in Engineering

Community Data Analytics: Localized Data Analysis And Decision Modeling In The Era Of ‘Big Data’ And ‘Smart Cities’, Michael P. Johnson Jr. Jan 2017

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

Community-based organizations use data for program design, services provision and strategic planning. However, CBOs often have limited ability to identify, access and apply these data. Thus, CBOs may make decisions on the basis of inadequate data, or limited understanding of the local environment, or limited ability to generate mission-aligned solutions.Community data analytics (CDA) uses local know-how and clearly-articulated values in order to transform data into action. CDA is rooted in principles of operations research and management science for public benefi#12;t. These principles include: active participation by local stakeholders to identify problems of interest; a critical perspective on issues of problem …

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Community-Engaged Decision Modeling For Local Economic Development, Michael P. Johnson Jr., Sandeep Jani Nov 2015

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

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Decision Science For Housing And Community Development: Localized And Evidence‐Based Responses To Distressed Housing And Blighted Communities: Wiley Interview, Michael P. Johnson Jr., Jeffrey Keisler, Senay Solak, David A. Turcotte, Armagan Bayram, Rachel B. Drew Oct 2015

Decision Science For Housing And Community Development: Localized And Evidence‐Based Responses To Distressed Housing And Blighted Communities: Wiley Interview, Michael P. Johnson Jr., Jeffrey Keisler, Senay Solak, David A. Turcotte, Armagan Bayram, Rachel B. Drew

Michael P. Johnson

This is an interview with staff at John Wiley & Sons regarding my book "Decision Science for Housing and Community Development: Localized and Evidence‐Based Responses to Distressed Housing and Blighted Communities" that was published by Wiley in 2015. It describes the motivation for the book, essential knowledge my co-authors and I would like each reader to take away from the book, and our assessment of the book's contribution to research and practice.

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Data And Analytics For Neighborhood Development: Smart Shrinkage Decision Modeling In Baltimore, Maryland, Michael P. Johnson Jr., Justin Hollander, Eliza D. Whiteman Jul 2015

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 …

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