RESEARCH OVERVIEW

A guiding principle of my scholarly activity is my belief in the significance of studying social and organizational phenomena as complex systems. This perspective recognizes that the internal states (e.g., beliefs, knowledge, perceptions) and outward expressions (e.g., behaviors, decisions) of individuals shape and are shaped by interactions with our environment and those within it. Played out over time and across individuals, these psychological processes and their resultant consequences can coalesce into emergent structures (e.g., temperaments, roles, relational networks) and experienced patterns (e.g., norms, culture, beliefs) capable of influencing the way in which individuals feel, think, and act. These recurrent “micro↔macro” forces inherent in complex dynamic systems are meaningful and relevant for understanding virtually all psychological phenomena across nearly all levels of explanation (i.e., individuals, teams, multi-team systems, organizations, etc.).

Irrespective of its focal application, the critical point emphasized by this perspective is that scientific knowledge is advanced by attempting to precisely describe, document, and study the generative processes that produce, sustain, and influence dynamic and emergent outcomes—or as Nobel Laureate and theoretical physicist Richard Feynman summarized: “What I cannot create, I do not understand.” Consequently, the research I conduct is directly motivated by (a) a desire to advance understanding of psychological phenomena from the perspective of dynamic processes rather than static effects; (b) advance, advocate for, and develop resources for methodologies that promote this perspective; and (c) contribute to foundational knowledge on substantive topics of interest from this perspective that can be leveraged to advance evidence-based solutions.

I identify as a scientist. To me, that means I derive my professional fulfillment from the pursuit of knowledge and efforts to better understand the natural world. The scientific community with which I am most closely affiliated and to whom I primarily contribute is the organizational sciences. However, I am inspired by and continually aspire to learn from several scientific communities, including the cognitive sciences, computer sciences, ecological sciences, planetary sciences, and applied physics/mathematics. It is important to me to devote time and effort into learning from scientific communities that are not my primary academic community as I believe it improves my scholarship, the questions I ask, and the methodologies I apply.

The broader philosophical orientation towards process in my substantive research is reflected in how I carry out my scholarly activities. Much of my research embraces and seeks to contribute to principles of computational social science that uses computational/quantitative modeling techniques to capture, analyze, and develop more rigorous, precise, and formal theories of social and organizational phenomena. Consequently, a significant thrust of my attention is directed towards basic theory development, validation, and advancing computational methodologies. Additionally, I also direct attention towards and participate in interdisciplinary collaborations on more applied research (primarily in emergency medicine and healthcare) that seeks to develop evidence-based solutions to “real world” issues.

The majority of data I collect for my research is original/primary source, though I also regularly make use of archival and simulated data as well. My research makes equal use of both laboratory (i.e., primarily college student populations) and field (i.e., working professionals) data. Furthermore, I strongly emphasize the collection of behavioral and/or observational data in all my research and, where applicable, longitudinal/within-unit data. Although perception/questionnaire-based data has a long and rich history in psychology, I believe that the organizational and social sciences relies too heavily on the use of cross-sectional, single-time point, and self-report survey methodologies. Consequently, much of my research relies on such data sources only for secondary/supplementary purposes.

For my research that is directed towards more “basic”/foundational knowledge, I typically prefer a more comprehensive publication strategy in which I present new (often computational) theory paired with one or more data sources designed to evaluate its core propositions. In my research that is directed towards more “applied”/evidence-based knowledge however, I typically prefer a more concise paper with a more tightly defined research foci and accompanying data. I generally prefer not to parse large datasets into multiple papers unless there is reasonable justification for doing so (e.g., paper would be too dense/large to effectively communicate all findings).

I am an advocate of and participant in open science practices that place greater emphasis on how research is accomplished (i.e., process) relative to its outcomes (i.e., publications, impact factors, citations). When I am not limited by either confidentiality or ethical concerns, I make every effort to share my research materials, data, and analyses using publicly accessible repositories (e.g., Open Science Framework, GitHub) and this website. I believe an essential component of my job as a scientist is to create clear and useful documentation, comments/notes, and guides for other researchers related to my data, analyses, and models. Further, I believe that replication, reproducibility, and related efforts to minimize the potential for questionable research practices are imperative to the long-term health and success of science. Nevertheless, I am also a strong advocate for inductive and abductive research that promotes idea generation and stimulates new perspectives. To the extent such research is recognized, discussed, and presented as the impetus for knowledge generation rather than a confirmatory/deductive evaluation, I believe such efforts are absolutely critical to the scientific ecosystem and should be recognized for their importance.

I believe strongly in the power and effectiveness of “team” science; that is, the quality (and enjoyment!) of research is greatly improved through collaborative efforts among diverse and engaged scholars. Furthermore, I believe there are very few (if any) reasons why institutions or policies should exist that discourage engaging in productive collaborations with other researchers and/or practitioners, including previous mentors/advisors or students. My job is to contribute to the development of knowledge, understanding, and evidence-based solutions; to the extent one accomplishes this though rich collaborations, they should be fostered and encouraged. I generally prefer to maintain a relatively small (~6-8) rather than a large network of collaborators when conducting my research. I believe strongly in investing and reciprocating my time, effort, and resources into developing high quality collaborative partnerships and find I am able to accomplish this more effectively working in smaller groups.

I attempt to adhere to the American Psychological Association’s code of ethics (Section 8.12) regarding authorship that relies on an individual’s contribution for determining author order. That said, I also do not believe that authorship order is as significant as we make it out to be. I believe that science and the generation of valued knowledge is frequently an emergent product of team-based collaboration. Dissecting and seeking to reduce this “whole” into the “parts” that members contributed to is often difficult at best and counterproductive at worst. Furthermore, there are occasions in which I may “undervalue” my contribution to provide opportunities and/or voice to those who would likely benefit more from the normative recognition that comes with higher authorship. In particular, I rarely list myself ahead of my graduate students on any publications together unless they only contributed to the collection/analysis of data. I also strongly encourage and advocate for my students to publish their theses/dissertations without me listed as an author unless they would prefer otherwise.