Decision Models for Housing and Community Development

Decision sciences, also referred to as operations research/management science (OR/MS), is dedicated to modeling and analysis to improve operations management and policy design. OR/MS topics are not ordinarily a part of the training that housing and community development professionals receive. However, housing and community development problems are often multifaceted and technically demanding and require action in the face of limited information and/or resources. They address operational concerns such as location, tenure type, size, development cost, timing and financing and policy concerns such as programmatic focus, service type, social impacts, strategy design, perceptions of fairness, and social, environmental, and economic sustainability. Problem solutions must address the needs and preferences of multiple stakeholders, uncertainty regarding problem data and decision alternatives, multiple analytic methods, and varying units of analysis. These problems, in the words of Saul Gass, are “wicked.” In these cases, decision models may provide insights that are unavailable using conventional analytic methods.

In particular, decision models allow analysts to quantify diverse impacts and constraints related to housing and community development, to develop deeper understandings regarding trade-offs associated with multiple goals or objectives, and to identify alternative policies and specific courses of action. Decision models may incorporate qualitative methods, such as value-focused thinking and problem-structuring methods; quantitative methods, such as mathematical programming and stochastic modeling; and mixed-method approaches that incorporate aspects of community planning.

The literature on decision models and methods related to housing and community development is long-lived, multidisciplinary, and broadly conceived, from very stylized models of real-world systems mostly relevant to scholars to computer-based applications intended to assist practitioners. This literature may be divided into three areas: descriptive models that provide theory, abstracted representations, and data regarding policies, systems, and phenomena; prescriptive models that generate specific recommendations for actions that are best, or optimal; and decision support systems that automate the process of generating data, solving models, and displaying results.