Regulatory Dynamics My primary research program focuses on the dynamics of organizational behavior across multiple levels of analysis. Longitudinal data are increasingly important in the study of organizational behavior. However, the current models used to represent the patterns present in longitudinal data are largely limited to the study of recursive relations (i.e., HLM and SEM). This is inconsistent with what we know about the self-regulated functioning of organizations, teams, and individuals where feedback loops and cyclical processes are thought to be the norm. My current research utilizes multivariate time series analyses to explore the dynamic cycles underlying regulatory processes in individuals (i.e., motivation) and teams (i.e., coordination and interdependence). Multilevel Theory Although my primary research focus is on the functioning of dynamic systems within a particular level of analysis (e.g., individual motivation or team coordination), I am fascinated with the process through which aggregate functioning of micro-level units yields macro-level phenomena and behavior (i.e., emergence). In fact, it becomes difficult to ignore this process when using fully dynamic, multivariate models. I am currently developing a new approach to the study of multilevel phenomena in organizational science that allows one to see how the dynamic functioning of micro-units yields emergent phenomena at the macro-level of analysis. This approach also has strong implications for the current process of aggregating micro-unit responses to represent macro-level phenomena in organizational science. Methodology I enjoy exploring and evaluating new methods for conducting organizational science research. In this area my research clusters into two distinct approaches. First, I invest considerable energy into exploring the applicability and utility of models and research paradigms developed in physics, biology, engineering, and economics for improving organizational science research. Examples of these efforts are the application of diffusion models to the study of motivation and the application of power law dynamics to the study of team performance. Second, I continue striving to identify new measurement approaches that can be used productively in organizational science. My current approach explores individual and team cognitive representations of key organizational science constructs and the way respondents transform these representations into quantitative estimates.