Social Movements & Employee Activism

Employees are increasingly attempting to affect societal change via or through the organizations they work for. Through staging public walkouts at their places of work to using their organizations’ communication channels to reach broader stakeholder audiences, employees are relying on and using their organizations to promote change more than ever before.While employee activism and social movements have previously been examined in management research, we lack a comprehensive understanding of the predictors and outcomes of such public and far-reaching employee activism. This research program uses a novel dataset stemming fromthe National Football League’s “Take a Knee” movement–a protest movement aligned with the larger Black Lives Matter movement–to introduce the concept of “organization-as-platform”activism as well as unpack the antecedents and outcomes of such activism.

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Led by: Travis Grosser

Social Network Dynamics

The informal relationships that employees form with one another constitute an important means by which knowledge is disseminated in organizations. Although the importance of social networks is well established in management research, our understanding of how organizational networks change over time is still in its infancy. This program of research therefore examines the antecedents and outcomes of social network change in organizations. Active field research projects include: 1) examining the impact of network change on employee attitudes in the wake of a merger at a large consumer goods firm, 2) a multi-year examination of the coevolution of networks and employee attachment at a large governmental agency, and 3) a longitudinal study of social networks and creativity at a Chinese engineering organization.

Close-up of a young office worker listening to her boss criticise one of her colleagues

Led by: Jo Oh

Mistreatment in the workplace

Whether it’s your boss, coworker, subordinate, or customer, people can be one of the most common sources for workplace stress. Research and practice indicate that employees, managers, and organizations suffer from various forms of mistreatment in the workplace (e.g., abusive supervision, customer mistreatment). As such, my research aims to better understand how mistreatment unfolds in the workplace, and by doing so, help remedy its destructive effects. Ongoing research projects regarding mistreatment include: 1) examining the effects of status on abusive supervision, 2) abusive supervision, emotions, and the moderating effects of emotional expressivity and perspective taking, 3) how resilient people learn from mistreatment, 4) abusive supervision and workplace dynamics.


In an increasingly fast-paced world, scholars and practitioners alike have begun to recognize the need to slow down and focus on the present moment. Inasmuch, the study and practice of mindfulness have received increasing attention in recent years. At the same time, we still know relatively little about how the practice and benefits of mindfulness are brought into workplace interactions and relationships. This research program uses a unique dataset consisting of qualitative interviews with workplace leaders and employees, who use mindfulness in the workplace, to unpack the individual and relational processes and benefits of being mindful at work.

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Led By: John Mathieu

Field-Based Learning

In conjunction with our colleagues at the Group for Organizational Effectiveness, and with support from the Army Research Institute, we are conducting a program of research focused on enhancing Field-Based Learning (FBL). The majority of learning and development during one’s career occurs as a result of experience, not in formalized training settings. Yet simply having an experience does not mean that a person will learn from it and not everyone is inherently good at maximizing learning from their field-based experiences. In short, there is a vital need to understand better how individuals learn in the field and developing mechanisms to facilitate that learning.

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Led By: John Mathieu

Unobtrusive Measures of Team Dynamics

Together with our colleagues at the Group for Organizational Effectiveness and with support from the Army Research Institute and NASA, this program of research focuses upon developing unobtrusive measures of team dynamics (processes and emergent states) that will enable the study of team and multi-team effectiveness related phenomena over time. We first advance a measurement fit process whereby the construct validity concerns associated with leveraging different types of behavioral information streams with team and MTS constructs is detailed. Using this framework, we developed methods to index team processes and emergent states (e.g., resilience; using Computer Aided Text Analysis (CATA), and with voice and position information gleaned from wearable sensor data. We also advanced theory for how collective emergent processes can be modeled and understood using such techniques.


Led By: John Mathieu

Optimizing Team Composition

In conjunction with our colleagues at the Group for Organizational Effectiveness, and with support from the Army Research Institute, we are developing algorithms to optimize team composition. Determining the ideal combination of team members’ knowledge, skills, abilities, and other (e.g., personality) characteristics is a very complex endeavor. Optimal profiles go way beyond simple averages or variances (i.e., diversity indices), and require a time-sensitive understanding of the team task environment. We are employing a combination of inductive and deductive approaches to identify such combinations as related to different team processes and outcomes over time. Moreover, given that team memberships often change over time, establishing an ideal team composition must also consider members’ movement in and out of teams, as well as the redistribution of individuals into different team positions or roles. We are also developing optimization routines to distribute potential member to multiple teams so as to maximize the benefit of organizational human capital. These algorithms serve to bridge insights from team composition research with those from the Strategic Human Resource Management literature.