"DECIDE" model

(noun)

The DECIDE model conceptualizes managerial decision making as a series of six steps. The decision process begins by precisely defining the problem or opportunity, along with the objectives and constraints. Next, the possible decision factors that make up the alternative courses of action (controllable factors) and uncertainties (uncontrollable factors) are enumerated. Then, relevant information on the alternatives and possible outcomes is collected. The next step is to identify and select the best alternative based on chosen criteria or measures of success. Then a detailed plan to develop and implement the alternative selected is developed and put into effect. Last, the outcome of the decision and the decision process itself are evaluated.

Related Terms

Examples of "DECIDE" model in the following topics:

  • Marketing Environment Research

    • The role of marketing research in managerial decision making is explained further using the framework of the "DECIDE" model: The DECIDE model conceptualizes managerial decision making as a series of six steps.
    • Break down marketing research to its two sets of categorical pairs and the DECIDE model

  • Economic Models

    • A model is simply a framework that is designed to show complex economic processes.
    • Economists use models in order to study and portray situations.
    • Models are based on theory and follow the rules of deductive logic.
    • However, creating a model does have two basic steps: 1) generate the model, and 2) checking the model for accuracy - also known as diagnostics.
    • Some economic models also use qualitative analysis.

  • Modeling Ecosystem Dynamics

    • Conceptual models describe ecosystem structure, while analytical and simulation models use algorithms to predict ecosystem dynamics.
    • Conceptual models are usually depicted graphically as flow charts.
    • These diagrams are sometimes called compartment models.
    • Like analytical models, simulation models use complex algorithms to predict ecosystem dynamics.
    • These kinds of models tend to be more widely used.

  • Introduction to Model selection

    • The best model is not always the most complicated.
    • In this section we discuss model selection strategies, which will help us eliminate from the model variables that are less important.
    • In this section, and in practice, the model that includes all available explanatory variables is often referred to as the full model.
    • Our goal is to assess whether the full model is the best model.
    • If it isn't, we want to identify a smaller model that is preferable.

  • Essential Functions for Mathematical Modeling

    • The process of developing a mathematical model is termed mathematical modeling.
    • Mathematical models can take many forms, including but not limited to dynamical systems, statistical models, differential equations, or game theoretic models.
    • These and other types of models can overlap, with a given model involving a variety of abstract structures.
    • In general, mathematical models may include logical models, as far as logic is taken as a part of mathematics.
    • For example, a simple model of population growth is the Malthusian growth model.

  • Two model selection strategies

    • If one of these smaller models has a higher adjusted R2 than our current model, we pick the smaller model with the largest adjusted R2.
    • That is, we fit the model including just the cond new predictor, then the model including just the stock photo variable, then a model with just duration, and a model with just wheels.
    • Each of the four models (yes, we fit four models!
    • We fit three new models:
    • If one of these models has a larger than the model with no variables, we use this new model.

  • Fama-French Three-Factor Model

    • The Fama–French three-factor model is a linear model designed by Eugene Fama and Kenneth French to describe stock returns.
    • The Fama–French three-factor model is a model designed by Eugene Fama and Kenneth French to describe stock returns .
    • Like CAPM and the Arbitrage Pricing Theory, the Fama-French three-factor model is a linear model that relates structural factors to the expected return of an asset.
    • Unlike those two models, however, the Fama-French model has three specific and defined factors.
    • Though it is more complex than CAPM, the Fama-French model has been shown to be a better at explaining the returns of a diversified portfolio: CAPM explains 70% of returns on average, while the Fama-French model explains 90% on average.

  • Comparing Nested Models

    • Multilevel models, or nested models, are statistical models of parameters that vary at more than one level.
    • These models can be seen as generalizations of linear models (in particular, linear regression); although, they can also extend to non-linear models.
    • Random intercepts model.
    • Random slopes model.
    • Random intercepts and slopes model.

  • Model selection exercises

    • Determine if any other variable(s) should be removed from the model.
    • Determine if any other variable(s) should be removed from the model.
    • Based on this table, which variable should be added to the model first?
    • Based on this table, which variable should be added to the model first?
    • We should consider removing this variable from the model.

  • Studying Ecosystem Dynamics

    • Many different models are used to study ecosystem dynamics, including holistic, experimental, conceptual, analytical, and simulation models.
    • A holistic ecosystem model attempts to quantify the composition, interaction, and dynamics of entire ecosystems.
    • A food web is an example of a holistic ecosystem model, which is the most representative of the ecosystem in its natural state.
    • Three basic types of ecosystem modeling are routinely used in research and ecosystem management: conceptual models, analytical models, and simulation models.
    • A simulation model is created using complex computer algorithms to holistically model ecosystems and to predict the effects of environmental disturbances on ecosystem structure and dynamics.