2.2 Problem structuring
2.2.1 Problem structuring methods, soft OR and value-focused thinking
The field of operations research and management science (OR/MS; ‘‘OR’’
henceforth) typically consists of formal quantitative analysis on individual and
organizational decision-making and problem solving, with varying levels of
connections to real-world problems through practical methods. In the past two
decades or so, particular classes of qualitative methods to engage real-world
stakeholders and solve challenging problems have received growing attention under
the labels of problem structuring methods (PSM) and ‘‘soft OR’’. In the discussion
which follows we provide details on the range of quantitative analysis that motivates
and frames the present analysis, and argue that the qualitative methods that are the
focus of this paper are properly viewed through the lens of PSM and soft OR.
Decision modeling for housing and community development encompasses both
mathematical programming approaches and decision-analytic approaches (Johnson
2011b). In the former, the choice set can be very large, and prior knowledge of
decision maker preferences is less important than the solution of models comprised
of objective functions and constraints to generate decision policies (see e.g., Bayram
et al. 2014; Johnson et al. 2010a). In the latter approach, however, the primary focus
is modeling uncertainty, structuring preferences, objectives and attributes to help
individual decision makers choose among alternatives (Dyer and Keisler 2012);
examples of relevant applications include Armacost et al. (1994) and Johnson
(2005). While recent published work on decision modeling for housing has focused
on elaboration of specific social objectives arising from engagement with
community partners (Johnson et al. 2012, 2013), there has been less attention paid
to the way in which certain objectives are chosen to incorporate into prescriptive
models, nor to the relationship these objectives may have with underlying
organizational values. It is this approach in which we position our present inquiry.
Decision analysis (DA), a subfield of operations research, is typically used to (1)
identify alternatives, uncertainties, and objectives, (2) elicit subjective probabilities
and preferences over associated outcomes that are inputs to models for quantitative
analysis, and (3) derive from these models a recommended course of action. DA is
also used for a variety of other ways, such as sensitivity analysis.
2.2 Problem structuring2.2.1 Problem structuring methods, soft OR and value-focused thinkingThe field of operations research and management science (OR/MS; ‘‘OR’’henceforth) typically consists of formal quantitative analysis on individual andorganizational decision-making and problem solving, with varying levels ofconnections to real-world problems through practical methods. In the past twodecades or so, particular classes of qualitative methods to engage real-worldstakeholders and solve challenging problems have received growing attention underthe labels of problem structuring methods (PSM) and ‘‘soft OR’’. In the discussionwhich follows we provide details on the range of quantitative analysis that motivatesand frames the present analysis, and argue that the qualitative methods that are thefocus of this paper are properly viewed through the lens of PSM and soft OR.Decision modeling for housing and community development encompasses bothmathematical programming approaches and decision-analytic approaches (Johnson2011b). In the former, the choice set can be very large, and prior knowledge ofdecision maker preferences is less important than the solution of models comprisedof objective functions and constraints to generate decision policies (see e.g., Bayramet al. 2014; Johnson et al. 2010a). In the latter approach, however, the primary focusis modeling uncertainty, structuring preferences, objectives and attributes to helpindividual decision makers choose among alternatives (Dyer and Keisler 2012);examples of relevant applications include Armacost et al. (1994) and Johnson(2005). While recent published work on decision modeling for housing has focusedon elaboration of specific social objectives arising from engagement withcommunity partners (Johnson et al. 2012, 2013), there has been less attention paidto the way in which certain objectives are chosen to incorporate into prescriptivemodels, nor to the relationship these objectives may have with underlyingorganizational values. It is this approach in which we position our present inquiry.Decision analysis (DA), a subfield of operations research, is typically used to (1)identify alternatives, uncertainties, and objectives, (2) elicit subjective probabilitiesand preferences over associated outcomes that are inputs to models for quantitativeanalysis, and (3) derive from these models a recommended course of action. DA isalso used for a variety of other ways, such as sensitivity analysis.
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2.2 Problem structuring
2.2.1 Problem structuring methods, soft OR and value-focused thinking
The field of operations research and management science (OR/MS; ‘‘OR’’
henceforth) typically consists of formal quantitative analysis on individual and
organizational decision-making and problem solving, with varying levels of
connections to real-world problems through practical methods. In the past two
decades or so, particular classes of qualitative methods to engage real-world
stakeholders and solve challenging problems have received growing attention under
the labels of problem structuring methods (PSM) and ‘‘soft OR’’. In the discussion
which follows we provide details on the range of quantitative analysis that motivates
and frames the present analysis, and argue that the qualitative methods that are the
focus of this paper are properly viewed through the lens of PSM and soft OR.
Decision modeling for housing and community development encompasses both
mathematical programming approaches and decision-analytic approaches (Johnson
2011b). In the former, the choice set can be very large, and prior knowledge of
decision maker preferences is less important than the solution of models comprised
of objective functions and constraints to generate decision policies (see e.g., Bayram
et al. 2014; Johnson et al. 2010a). In the latter approach, however, the primary focus
is modeling uncertainty, structuring preferences, objectives and attributes to help
individual decision makers choose among alternatives (Dyer and Keisler 2012);
examples of relevant applications include Armacost et al. (1994) and Johnson
(2005). While recent published work on decision modeling for housing has focused
on elaboration of specific social objectives arising from engagement with
community partners (Johnson et al. 2012, 2013), there has been less attention paid
to the way in which certain objectives are chosen to incorporate into prescriptive
models, nor to the relationship these objectives may have with underlying
organizational values. It is this approach in which we position our present inquiry.
Decision analysis (DA), a subfield of operations research, is typically used to (1)
identify alternatives, uncertainties, and objectives, (2) elicit subjective probabilities
and preferences over associated outcomes that are inputs to models for quantitative
analysis, and (3) derive from these models a recommended course of action. DA is
also used for a variety of other ways, such as sensitivity analysis.
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