Measuring Conformity to Discourse Routines in Decision-Making Interactions

In an effort to develop measures of discourse level management strategies, this study examines a measure of the degree to which decisionmaking interactions consist of sequences of utterance functions that are linked in a decisionmaking routine. The measure is applied to 100 dyadic interactions elicited in both face-to-face and computer-mediated environments with systematic variation of task complexity and message-window size. Every utterance in the interactions is coded according to a system that identifies decision-makmg functions and other routine functions of utterances. Markov analyses of the coded utterances make it possible to measure the relative fi'equencies with which sequences of 2 and 3 utterances trace a path in a Markov model of the decision routine. These proportions suggest that interactions in all conditions adhere to the model, although we find greater conformity in the computer-mediated environments, which is probably due to increased processing and attmfional demands for greater efficiency, The results suggest that measures based on Markov analyses of coded interactions can provide useful measures for comparing discourse level properties, for correlating discourse features with other textual features, and for analyses of discourse management strategies.