Microdynamics of collaboration and influence in small teams
Teams are commonly described as complex and dynamic systems. Among other things, this means that the “outcomes” which emerge from and within teams (i.e., performance, cohesion, knowledge, norms, culture, etc.) are purportedly a function of the unique characteristics of individual members, the manner by which those individual members interact over time, and the constraints/requirements of the task environments in which those individual members operate. Efforts directed towards developing generalizable theory and models that seek to demonstrate how these complex processes unfold exist and have been fruitful. However, empirically measuring, analyzing, and capturing evidence of these processes and their emergent consequences has been slow and only rarely pursued in the organizational sciences. A key contributor to this slower progress is the need to move beyond conventional measurement techniques that rely on static low-dimensional data (e.g., surveys, self-reports) and analytic techniques (e.g., structural equation modeling, random coefficient modeling) that aggregate across people and meaningful temporal patterns.
A primary goal of this research is to explore the emergence of collaboration and influence in small teams. A unique aspect of this work are efforts to collect several unique sources of data relevant to capturing team “microdynamics.” These include wearable eye tracking technology to record individual’s visual attention, audio recordings to capture communication and vocal patterns, video recordings to capture behavioral sequences/interactions, and sociometric measures to capture the emergence of interpersonal belief networks. Through analyzing these data sources in isolation and in conjunction, we hope to better understand teams as complex systems and better understand ways to assess, predict, and improve the effectiveness by which individuals work together towards collective goals.