Fuzzy Logic Patterns Communication and Team Performance

Abstract

Analyzing the complex maze of content and flow in communication between team members could help unlock researchers’ understanding of team performance. This research analyzes the communication patterns of two teams, based on their team performance, in order to test and expand a developing team mapping technique to assess content and flow between team members. A two-pronged methodology was executed: (1) communication data processing by (a) classifying utterances into content topics and flow, (b) indexing the speech acts, and (c) validation, and (2) analyzing the communication patterns using augmented fuzzy cognitive maps (FCMs). The strengths of the relationships among key communication concepts were estimated and compared between the two, low and high, performance teams’ FCMs. The results indicated that FCMs could apply to larger teams and in an alternate domain. The FCM communication patterns recognized that the “providing information” concept was significantly different between the high and low team performances. This research demonstrates that, using fuzzy logic, different patterns can assist in understanding team performance while providing insights into complex team communication dynamics.