Mental Models
Mental models are descriptive representations of decision-making situations that people form in their head and think about.
Their thought process work through scenarios to consider the utility of and risks involved in each potential alternative.
Typically, mental models are used when there are mostly qualitative factors in the decision-marking problem.
Mental models help frame the decision –making situation, a topic of cognition theory.
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Mathematical (Quantitative Models)
The complexity of relationships in many organizational system cannot be represented by icons or analogically because such representation would soon become cumbersome and using them would be time-consuming.
Therefore, more abstract models are described mathematically.
Most DSS analyses are performed numerically with mathematical or other quantitative models.
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The Benefits of Models
Manipulating a model (changing decision variables or the environment) is much easier than manipulating a real system. Experimentation is easier and does not interfere with the organization’s daily operations.
Models enable the compression of time. Years of operations can be simulated in minutes or seconds of computer time.
The cost of modeling analysis is much lower than the cost of a similar experiment conducted on a real system.
The cost of making mistakes during a trial-error experiment is much lower when models are used than with real system.
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The Benefits of Models
The business environment involves considerable uncertainty. With modeling, a manager can estimate the risks resulting from specific actions.
Mathematical models enable the analysis of very large, sometimes infinite, number of possible solutions. Even in simple problems, managers often have a large number of alternatives from which to choose.
Models enhance and reinforce learning and training.
Models and solution methods are readily available on the Web.
Many Java applets (and other Web programs) are available to readily solve models.
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The Benefits of Models
The existence of a problem can be determined by monitoring and analyzing the organization’s productivity level
The measurement of productivity and the construction of a model are based on real data
The collection of data and the estimation of future data are among the most difficult steps in the analysis
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2.4 Phases of Decision Making Process