Knowledge that Transforms

T he causal relationships in a two variable system are examined, using a simultaneous linear differential equation model. Emphasis is placed on the necessity for considering mutual interaction instead of looking for unidirectional causality. To demonstrate the usefulness of this approach an example is taken from the management science literature concerning the relationship between labour turnover and overtime. It is shown that, on certain assumptions, the data disconfirm a hypothesis previously thought to be confirmed. Certain informal observations made in the original paper were shown to receive confirmation from the data.

O rganization structure is determined by the interaction of several variables. Woodward's work suggested that technology is one of the most important and this study attempts to extend her findings from the industrial to the non‐manufacturing sphere. The results show that structure does relate to task within the non‐manufacturing group — but that taken as a whole the structures of the non‐manufacturing group differ from all those Woodward found in manufacture. Some of these differences are seen to derive from the relative simplicity of the non‐manufacturing technology. Others can be traced to the operation of intervening variables.