On Using Discrete Random Models within Decision Support Systems

Article Abstract:

Discrete random system modeling is analyzed in light of its usefulness to practical decision making. Organizational requirements are highly dispositive of the type of model to be used. Practical examples of Markov chain models and decision models, as well as cohort models are used to demonstrate the organizational requirements link. Technical and social applications are both used. Models can range from the descriptive to optimization type. Models can be applied using either straight forward numerical analysis or interactive modeling methods for management evaluation. Numerical methods are shown to the model's structure in addition to application considerations. Model selection has a high impact on computational possibilities. A vehicle insurance company is the focus of various modeling applications. Graphs of premium status overtime are featured. Tables of jumping intensities between data sets are included, as are manpower planning data tables.

Models, Automobile insurance, Numbers, Random, Random numbers

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A fuzzy logic-based decision model to satisfy goals for successful product/service introduction

Article Abstract:

A model is developed, based on fuzzy logic, for satisfying goals for a successful product or service launch.

Multiple criteria decision making, Management, New products, Product introduction

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Intervention methodology for complex problems: the FAcT-Mirror method

Article Abstract:

A new intervention method for solving complex and/or recurring situations is described.

Problem solving

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