In describing cause and effect relationships, difficulties may arise when two or more factors act as causes of a particular outcome. The complication results from the possibility that any one or more of the factors modify the extent to which others provide an effect. Such complex multi-factor interactions imply that multiple causal chains have at least some part in common; thus the evaluation of the synergistic effect of two or more causes is pertinent to the study of the causal mechanisms involved. The aim of this paper is to propose a new approach to systematically analyse combinations of interacting causal factors that might lead to good outcomes. Our approach was demonstrated on data from a highly complex field; a large dataset about Information Technology impact on business value collected by the Australian Department of Communication, IT and Art. Experimental evaluation confirms that this approach is able to statistically estimate the magnitude of higher-order interactions from multiple causal factors. Hence, synergistic interactions can be hypothesised and tested between any number of factors.
McGrane, Martin and Poon, Simon K., "A Method to Estimate High-Dimensional Synergistic Interactions: A Case Study on Information Technology Business Value" (2011). ACIS 2011 Proceedings. 28.