Aaron Schecter

University of Georgia | UGA · Department of Management Information Systems

A fundamental assumption in the study of groups is that they are constituted by various interaction processes that are critical to survival, success, and failure. However, there are few methods available sophisticated enough to empirically analyze group interaction. To address this issue, we present an illustration of relational event modeling (REM...

The emergence of group constructs is an unfolding process, whereby actions and interactions coalesce into collective psychological states. Implicitly, there is a connection between these states and the underlying procession of events. The manner in which interactions follow one another over time describe a group's behavior, with different temporal...

Innovation is a cumulative process in which past knowledge created by others can be both a source for predictable outcomes and also a barrier to significant change. The recent literature on digital innovation suggests that open platforms, which encourage their developers to build upon each other's knowledge when innovating their add-on apps in the...

The widespread availability of digital trace data provides new opportunities for researchers to understand human behaviors at a large scale. Sequences of behavior, captured when individuals interface with an information system, can be analyzed to uncover behavioral trends and tendencies. Rather than assume homogeneity among actors, in this study we...

Despite the recognized need to prepare for a future of human-AI collaboration, the technical skills necessary to develop and deploy AI systems are considerable, making such research difficult to perform without specialized knowledge. To make human-AI collaboration research more accessible, we developed a novel experimental method that combines a st...

Algorithms provide recommendations to human decision makers across a variety of task domains. For many problems, humans will rely on algorithmic advice to make their choices and at times will even show complacency. In other cases, humans are mistrustful of algorithmic advice, or will hold algorithms to higher standards of performance. Given the inc...

Research on service center routing has largely assumed either fully codified automated routing, rational routing agents who can optimally route calls, or both. In practice, however, many routing scenarios are not fully codifiable, and human routing agents will likely exhibit biases in their routing decisions. In this paper, we explore the presence...

Social network data collected from digital sources is increasingly used to gain insights into human behavior. However, while these observable networks constitute an empirical ground truth, the individuals within the network can perceive the network's structure differently-and they often act on these perceptions. As such, we argue that there is a di...

Algorithms have begun to encroach on tasks traditionally reserved for human judgment and are increasingly capable of performing well in novel, difficult tasks. At the same time, social influence, through social media, online reviews, or personal networks, is one of the most potent forces affecting individual decision-making. In three preregistered...

We introduce the concept of preregistration for experiments in information systems. Preregistration is a way to commit to analytic steps before collecting or observing data, thus mitigating any biases authors may have (consciously or not) towards reporting significant findings. We explain why preregistration matters, how to preregister a study, the...

The relational event model (REM) solves a problem for organizational researchers who have access to sequences of time-stamped interactions. It enables them to estimate statistical models without collapsing the data into cross-sectional panels, which removes timing and sequence information. However, there is little guidance in the extant literature...

We propose a two by two experiment that investigates how humans respond to recommendations based on the difficulty of the task and the source of the recommendation. The two types of information sources which will provide recommendations in our experiment are algorithms and human crowds. We contribute to the burgeoning discourse on algorithmic appre...

Algorithms have long outperformed humans in tasks with objective answers. In medicine, finance, chess, and other objective fields, AI have been shown to consistently outperform human cognition. However, algorithms currently underperform human cognition in creative tasks, such as writing fiction or brainstorming ideas. We propose a study that invest...

Smart technology is everywhere; we are driving autonomous vehicles, talking to virtual assistants, and playing games in virtual reality. As artificial intelligence (AI) becomes more pervasive, we will interact with artificially intelligent agents more frequently and in deeper ways. Advances in AI and computer science are enabling intelligent, auton...

Crowd-based open innovation communities have received increasing attention, based on the premise that leveraging the power and diversity of the crowd can lead to innovative outcomes. However, we still know little about how work is coordinated over time in this context, especially as the innovation process moves from idea generation to elaboration....

The opioid epidemic has become a major topic of conversation in healthcare in the United States—in part because the statistics are staggering. According to the US Department of Health and Human Services (HHS), 2.1 million people had an opioid use disorder and 42,249 people died from overdosing on opioids in 2016. This pattern of abuse accounted for...

Effective teams are characterized by how skillfully they collaborate, coordinate, and interact while working towards their collective goals. These processes are inherently dynamic, and are best represented as a series of events (i.e. interactions). Whereas other methods for studying teams focus on the properties or structure of the group, an event-...

Multiteam systems are a unique organizational form in which two or more traditional teams must interface in order to achieve goals beyond the scope of the local units. These systems are important components of many modern organizations, from military to business to emergency response. This study presents a novel approach to understanding how the pe...

Research on groups and teams has spent more than sixty years trying to isolate the interaction processes that distinguish those groups who succeed from those who fail. This study advances a novel conceptualization of group process: the sequential structural signature (SSS), and an associated analytic approach: relational event network analysis. Seq...