Date of Award
2022
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Industrial and Systems Engineering
Department
Mechanical, Industrial and Systems Engineering
First Advisor
Gretchen Macht
Abstract
In recent decades, tasks, jobs, and systems have become increasingly complex, with no changing anytime soon. Therefore, the need to understand team dynamics to form and train better teams, and maximize their performance has become a focus of research in the organizational behavior, industrial & organizational psychology, and human factors & ergonomics disciplines. There has been a rise in the number of works focused on understanding different team dynamics through a variety of methods, such as psychometrics and physiological measures. Of these methods, one that has been used the longest and is among the least invasive is the use of speech or communication to qualify or quantify team dynamics. Team communication has long been accepted as a suitable method for analyzing team coordination dynamics. Teams must communicate in one form or another (verbal or nonverbal) to keep track of the task at hand and the progress. As such, it is recognized that team communication is, in fact, team cognition and coordination. Thus, one method of understanding team coordination dynamics is by analyzing of team communication patterns.
The study of team communication patterns has often been done regarding the quantity of communication. However, content of communication is just as important, and debated, maybe even more so. This work focuses on the expansion of quantitative methods for the analysis of team communication content in order to discover patterns that aid the understanding of team cognition and coordination. Different methods for analyzing naturalistic team communication will be presented, and the results obtained from these methods will be discussed in-depth to advance the quantitative study of team communication content in naturalistic environments. At its core, this dissertation is concerned with how team communication content can be quantified and analyzed to provide insight on team communication flow, team coordination, and team cognition.
The first chapter of this dissertation serves as a guide for the comparison of fuzzy cognitive maps (FCMs). As FCMs are widely used, and have specifically been used to demonstrate communication patterns in high and low performing teams, in order to best utilize these maps, it is necessary to understand how to analyze and compare them. As such, the first chapter of this dissertation provides a broad, although not comprehensive, review of literature on FCMs and their comparison. It pulls from different fields and gathers the different metrics and methods that have been used for the purpose of comparing FCMs. This first chapter demonstrates the usefulness of these different methods and metrics by providing an illustrative example on team communication FCMs.
The following chapters focus on testing different quantitative analyses on the same team communication data to understand the different findings that can be obtained from them. From testing and adapting well-known and used team communication quantitative methods for a different environment, to demonstrating other methods that have not been used in the team communication domain, this dissertation covers highlights the need for quantitative methods for the analysis of naturalistic team communication content. In addition, it starts the process by which quantitative methods may be adapted from structured team communication research or adopted from other fields. Not only does this dissertation provide researchers and practitioners methods for carrying out the analysis of their own teams, the findings from the application of the different methods provide insight on team coordination dynamics as well as potential avenues to explore in the quest for other team communication content quantitative analysis methods.
Recommended Citation
Engome Tchupo, Dominique, "Quantitative Methods for Analyzing Team Communication Patterns" (2022). Open Access Dissertations. Paper 1447.
https://digitalcommons.uri.edu/oa_diss/1447
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