In contrast to a process model, a causal or variance model studies the covariance of
the success dimensions to determine if there exists a causal relationship among them.
For example, higher system quality is expected to lead to higher user satisfaction and
use, leading to positive impacts on individual productivity, resulting in organizational
productivity improvements. The purpose of combining the success taxonomy with
the success model was to aid in the understanding of the possible causal interrelationships
among the dimensions of success and to provide a more parsimonious exposition
of the relationships. Unhappily, for some critics this combination has proved
troublesome, leading them to suggest a number of reformulations. These will be discussed
later in this paper.