Binary decision analysis: An empirical approach to predicting and understanding organizational decisions

Binary decision analysis is an alternative approach to the analysis of organizational decisions that lends itself well to mathematic analysis. The purpose of this paper is to present and test the application of the binary approach to decision analysis and its subsequent mathematical testing using logit regression. Binary decision analysis focuses on each decision as a single choice between two distinct alternatives or a step in a sequence of such binary choices in more complex organizational decisions. Logit regression is a type of regression especially developed to deal with binary dependent variables in the context of inferential statistical testing. By successfully combining these two approaches, and adhering to the theoretical and statistical assumptions upon which they are based, a potentially useful tool of organizational decision analysis results. An applied example of this approach tests its utility. Appropriate conclusions about the method are made based on that test.