Constructive and Operational Definitions

Before a concept or construct can be measured, it must be defined. Researchers develop two kinds of definitions:

  1. Theoretical Definitions
  2. Operational Definitions

Theoretical Definitions: Theoretical definitions are basic dictionary definitions. They are frequently called constitutive or conceptual definitions. A theoretical definition gives meaning to the concept or construct under investigation. It should distinguish it from all other concepts or constructs. A theoretical definition assumes both knowledge and acceptance of the theories it depends upon. For example, a theoretical definition for the concept "customer satisfaction" is often defined as the degree to which a customer's experience with a product or service conforms to his or her expectations and the ideal experience.

Operational Definitions: Operational definitions define an object, event, variable, concept, or construct in terms of the specific processes, tests, and measurements used to determine its presence or quantity. Operational definitions transform theoretical definitions into observable events. This is because an operational definition states which characteristics will be measured in the assignment of a value to the concept or construct under study. Operational definitions form the basis for the research questions, hypotheses, and the theories associated with the research. If a researcher is concerned about levels of brand satisfaction, the researcher could ask customers to rate their experiences with this brand and competitive brands on a five-point scale: Very Satisfied, Satisfied, Neutral, Dissatisfied, and Very Dissatisfied.

Independent and Dependent Variables: With the exception of descriptive studies, all research must have at least two variables: An independent or predictor variable on one hand and a dependent or response variable on the other.

Independent Variable: An independent variable is the input into a process that influences the dependent variable.

Dependent Variable: The dependent variable is the output associated with the independent variable. It is called the dependent variable because it "depends" on or "responds" to other variables. The dependent variable is the result you want to achieve. In marketing, for example, the desired result might be sales revenue.

Let's say we are studying the impact of advertising spending on the sales revenue of 20 product categories. In our study, advertising spending is the independent variable that predicts sales revenue, the dependent or response variable.

In any study there must be at least one independent variable. Typically there is more than one independent variable. Independent variables are associated with changes in the dependent variable. In the example where sales revenue is the dependent variable, the independent variables could include each of the marketing mix strategies (including advertising spending) in addition to competitive brand activity and the state of the economy.

Discreet and Continuous Variables: We can classify a variable as either discreet or continuous. A discrete variable takes one of a series of finite values. A continuous variable can take an infinite number of values on a scale.

A discreet scale is used to classify variables. Here are some examples of a discreet scale.

Are you a full-time student? Yes or No.

Do you agree with the president's policy on immigration? Yes, No, or No Opinion.

A continuous scale measures intensity of a concept. Value can be assigned using an infinite number of values anywhere along a scale. Your weight is a continuous variable. While you might say that you weight 135 pounds. But, your weight fluctuates throughout the day. There are an infinite number of measures between 134 and 136 pounds as you can divide the difference between 134 and 136 pounds into infinititely smaller units.

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