Chapter 5: Results

• 5 Results
• 5.1 Validity
• 5.2 Reliability
• 5.3 Regression Analysis

5.1 Validity

A research is valid if its measures actually measure what they claim to, and if there are no errors in drawing conclusions from the survey data. There are many labels for different types of validity, but they all have to do with threats and biases which would undermine the meaningfulness of research.

Construct validity has to do with the logic of items which comprise measures of social concepts. A good construct has a theoretical basis which is translated through clear definitions involving measurable indicators. A poor construct may be characterized by lack of theoretical agreement on its content, or by flawed operationalization such that its indicators may be construed as measuring one thing by one researcher and another thing by another researcher.

Construct validity can be broken down into two sub-categories: convergent validity and discriminate validity. Convergent validity is the actual general agreement among ratings, gathered independently of one another, where measures should be theoretically related. Discriminate validity is the lack of a relationship among measures which theoretically should not be related.

A correlation matrix was run to test the convergent and discriminant validity of the constructs in the research model (Hair et al., 1998). All items within their constructs are highly validated (convergent and discriminate) with a significance level of at least <0,05 (most of the times even <0,01). Except for construct “Receiver's Purchase Intentions” where one item was only validated against one other item. However, I kept this item within the construct because it did not have any major effects on the results. The correlation matrix is not shown here because of the size (i.e., 28 items).