Decision Science for Housing and Community Development: by Michael P. Johnson, Jeffrey M. Keisler, Senay Solak, David

By Michael P. Johnson, Jeffrey M. Keisler, Senay Solak, David A. Turcotte, Armagan Bayram, Rachel Bogardus Drew

A multidisciplinary method of problem-solving in community-based corporations utilizing determination types and operations examine applications

A complete therapy of public-sector operations learn and administration technology, Decision technological know-how for Housing and group improvement: Localized and Evidence-Based Responses to troubled Housing and Blighted groups addresses serious difficulties in city housing and group improvement via a various set of selection types and functions. The publication represents a bridge among thought and perform and is a resource of collaboration among choice and information scientists and planners, advocates, and group practitioners.

The publication is influenced via the wishes of community-based companies to answer local fiscal and social misery, represented via foreclosed, deserted, and blighted housing, via neighborhood organizing, carrier provision, and native improvement. The ebook emphasizes analytic methods that elevate the facility of neighborhood practitioners to behave speedy, thoughtfully, and successfully. via doing so, practitioners can layout and enforce responses that mirror stakeholder values linked to fit and sustainable groups; that take advantage of elevated organizational capability for evidence-based responses; and that bring about suggestions that symbolize advancements over the established order in accordance with a number of social end result measures. that includes quantitative and qualitative analytic tools in addition to prescriptive and exploratory selection modeling, the publication additionally includes:

  • Discussions of the foundations of choice conception and descriptive research to explain how you can determine and quantify values and pursuits for group development
  • Mathematical programming purposes for real-world challenge fixing in foreclosed housing acquisition and redevelopment
  • Applications of case experiences and community-engaged study ideas to analytics and selection modeling

Decision technological know-how for Housing and neighborhood improvement: Localized and Evidence-Based Responses to troubled Housing and Blighted groups is a terrific textbook for upper-undergraduate and graduate-level classes in determination types and functions; humanitarian logistics; nonprofit operations administration; city operations examine; public economics; functionality administration; city stories; public coverage; city and neighborhood making plans; and platforms layout and optimization. The publication can also be a good reference for teachers, researchers, and practitioners in operations learn, administration technological know-how, operations administration, platforms engineering, coverage research, urban making plans, and information analytics.

 

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Extra info for Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities

Example text

The outcome of this step is a qualitative statement of a problem to be solved, even if it appears to exceed the scope of traditional OR/MS. The next step of CBOR, problem solution, recognizes that there may be multiple solutions to a defined problem; they may be derived from quantitative analytic methods such as optimization or simulation or mixed-methods 17 COMMUNITY-BASED OPERATIONS RESEARCH approaches such as problem structuring and collaborative learning. These solutions can be derived through research frameworks such as mathematical modeling (Winston and Venkataramanan, 2003; Winston, 2004), case studies (Yin, 2013), and action research (Burns, 2007).

Mathematical modeling solution methods, applied in the context of CBOR, should account for a community or an organization’s available expertise, technology, and resources and may yield optimal algorithms, heuristics, or perhaps an entirely qualitative presentation of decision problems and solutions that may provide substantial insight for CBOs. Case studies use multiple sources of evidence and rely on theoretical propositions to guide inquiry rather than explicit hypotheses (Yin, 2013). They are an important way to provide crucial social and organizational context to primarily quantitative analytic decision models.

However, purely technical approaches are insufficient. Innovative decision-modeling approaches must be based on best and most current social science evidence; recognize the centrality of lived experiences and social, racial, and class barriers to opportunity; and critically examine previous efforts in community development. , 2009). We describe now the ways in which CBOR can meet these goals. CBOR is conceived as a collection of four analytical steps. The first, problem identification, recognizes that determining the nature of a problem to be solved is an opportunity for application of problem structuring and values clarification methods such as value-focused thinking (Keeney, 1992), soft systems methodology (Checkland, 1981), and facilitated modeling (Franco and Montibeller, 2010).

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