By Arie Y. Lewin and Melvin F. Shakun (Auth.)
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Extra resources for Policy Sciences. Methodologies and Cases
Example text
The strategic level involves the incorporation of information processing strategies into the design of new methods for improving efficiency, which is the basis of the situational normativism methodology developed in this book. Actual decision-making models can be used to identify participants, goals, and standard rules in the existing situation. Then, for normative purposes, a mathematical model based on this information is designed. The model should generate satisfactory solutions that are better than the existing one using a search process in which goals and constraints are modified.
In the traditional problem, the values of bj and the functions f and gj are given. Traditionally, optimizing (associated with normative theory) takes place 45 46 Policy Sciences: Methodologies and Cases within given constraints, whereas under satisficing (associated with behavioral theory) the evolution and definition of constraints occur simultaneously with the search for solutions. However, under the situational normativism viewpoint, mathematical optimizing algorithms (or heuristic solution techniques or simulation)* may be used in searching for solutions within the search for goals (constraints).
34 Policy Sciences: Methodologies and Cases Information Governmental Unit's Policy ^^ ii Specified Outcome ■ ^^ } Fig. 5a. Information Processing Framework [ Begin j Collect Neighbors' Salaries Compute the Average C Is Our Salary < the Average? > Yes No Increase Grant the Average f Halt j Fig. 5b. Example of a Discrimination Net f Situational Normativism-Descriptive Models 35 Thus, information is processed along a path through the net until ultimately a choice is reached. It should be readily apparent from Fig.