Carnegie Mellon University

Research

The following are examples of the center's current research projects.


  • “Is Failure Always the Mother of Success? Examination of Learning from Failure in the Context of Heart Surgeons,” coauthored by Sunkee Lee (Carnegie Mellon University) and Jisoo Park (Carnegie Mellon University). This research aims to better understand the processes and outcomes associated with learning from failure experiences. On the one hand, failure experiences provide opportunities for individuals to learn and improve their performance. However, on the other hand, the accumulation of failures could impair individuals’ motivation to learn by inducing negative emotions such as the sense of helplessness. This research uses data on cardiothoracic surgeons to examine this tension in learning from failures.

  • “Organizational Routines and Adaptability: The Effects of Routines in Buildings TMS and Enabling Team Performance,” a dissertation by Jerry Guo, now at Aarhus University. This dissertation investigates how organizational routines, analogous to standard operating procedures or processes, facilitate the emergence of transactive memory systems and thereby enable performance on new tasks. Results from the study suggest that organizations can remain adaptive to changing tasks if they store knowledge in routines and procedures, if those routines enable members of teams to learn about one another’s skills.
  • “Personnel Mobility and Organizational Performance: The Effects of Specialist vs. Generalist Experience and Organization Work Structure,” coauthored by Erin Fahrenkopf (Stanford), Jerry Guo (Aarhus University), and Linda Argote (Carnegie Mellon University), examines the factors predicting whether a new organization member can transfer their knowledge to the organization. The project focuses on the division of work in organizations, arguing that experience working as a specialist endows new members with different knowledge than experience working as a generalist. Specialist movers are less likely to transfer knowledge to their new organizations, and experience a particular disadvantage when they join generalist organizations, leading to worse performance when compared to generalist movers. These results suggest that new employees with broad experience may be better contributors to their new organizations.
  • “Transactive Memory Systems and Trauma Resuscitation Team Performance,” coauthored by Linda Argote (CMU), Jerry Guo (Aarhus University), Ki-Won Haan (CMU) and Matthew Rosengart, Cindy Teng and Jeremy Kahn (University of Pittsburgh Medical Center), investigates the effect of transactive memory systems on the performance of hospital trauma resuscitation teams. Known colloquially as knowledge of who knows what, a transactive memory system (TMS) enables teams to assign tasks to the most qualified members and to rely on those members to perform and coordinate their tasks effectively. Behavioral indicators of transactive memory are coded from video recordings of trauma resuscitations in a hospital emergency department. Objective measures of team performance, patient lengths of stay in the intensive care unit and in the hospital, are obtained from hospital records. Results of analyzing data from 121 patients reveal that patients treated by trauma teams with strong TMS experience significantly shorter lengths of stay in the ICU and in the hospital than patients treated by trauma teams with weaker TMS. Reductions in length of stay benefit patients, reduce health care costs, and free up hospital resources to care for other patients, an outcome that is especially valuable in times such as the current pandemic.

  • “Well-Being and Collaboration: Team Well-Being Facilitates Team Performance and Team Member Satisfaction via Transactive Memory Systems” coauthored by Matthew A. Diabes (CMU) and Taya R. Cohen (CMU). In this research, the authors conducted a laboratory experiment in which ad hoc teams created product marketing plans to test whether teams whose members have higher levels of well-being (i.e., a combination of self-esteem, satisfaction with life, positive social relations with others, and low depression) develop greater transactive memory systems (TMS), have better performance outcomes, and greater team member satisfaction. The authors manipulated whether explicit information about members’ individual training (i.e., expertise) was provided to the team to compare the degree to which team well-being predicts TMS and team performance in contexts in which knowledge about team members’ expertise in different areas is common knowledge or unspecified. In support of their hypotheses, the authors find that teams with relatively higher (versus lower) levels of well-being have greater TMS, better performance, and more satisfied members. Both team performance and team member satisfaction were mediated by the coordination component of TMS; team member satisfaction was also mediated by the credibility component of TMS. All teams, regardless of the well-being of their members, benefited from high expertise explicitness through increases in the specialization component of TMS, but expertise explicitness did not amplify or attenuate the observed effects of well-being on team performance or team member satisfaction (i.e., there was no evidence of moderation). This study demonstrates that the well-being of team members is an important compositional characteristic of teams that impacts TMS, team performance, and team member satisfaction, and is not substituted by providing information about the expertise of individual team members.
  • “Jack of All, Master of Some: Knowledge Networks and Innovation,” coauthored by Elina Hwang (University of Washington), Param Singh (Carnegie Mellon University) and Linda Argote (Carnegie Mellon University), investigates whether synergies exist between innovation crowdsourcing and customer support crowdsourcing communities such that individuals who provide customer support are better equipped to develop new ideas. We hypothesized that individuals who help other customers within crowdsourcing communities would have access to the needs and means required for generating ideas. To empirically test this hypothesis, we evaluated an innovation crowdsourcing community and customer support community hosted by a telecommunication company and analyzed 8,110 new product ideation projects conducted by 2,643 individuals within the community over three years. Natural language processing was used to construct individuals’ information networks based on the help they provided in a customer support community. Results indicate that generalists who offer support to other customers on broad topics are more likely to contribute novel ideas to an innovation crowdsourcing community than are non-generalists. Additionally, generalists who have accumulated deep knowledge in at least one topic domain outperform non-generalists in their ability to generate successful ideas as well as generalists who have accumulated only shallow knowledge. Thus, we find evidence of knowledge transfer across innovation crowdsourcing and customer support crowdsourcing communities. The study also contributes to the question of whether it is better to be a generalist or a specialist. When the criterion is developing novel ideas, deep generalists outperform either shallow generalists or non-generalists.

    Hwang, E.H., Singh, P. V., & Argote, L. (2019). Jack of All, Master of Some: Knowledge Networks and Innovation. Information Systems Research, 30(2), 389-410.
  • “Learning across Product, Work Group and Geographic Boundaries,” a research project co-investigated by Carolyn Egelman, Erica Fuchs, Dennis Epple and Linda Argote, funding received from the National Science Foundation, the Science of Science and Innovation Policy program and the Innovation and Organization Science program. The researchers study organizational learning and knowledge transfer in a multi-product offshore production facility.

    Egelman, C. D., Epple, D., Argote, L., & Fuchs, E. R. H. (2017). Learning by Doing in Multi-Product Manufacturing: Variety, Customizations and Overlapping Product Generations. Management Science, 63(2), 405-423.

  • ”Mindlab Project,” Linda Argote (Tepper School of Business) and Rich Burton (Fuqua School of Business, Duke University) collaborate with colleagues on the Mindlab project at Aarhus University: Borge Obel, Dorthe Hakonsson, Dan Monster and Jacob Eskildsen. The research aims to determine the effect of emotion and performance on the tendency to explore and adopt a new routine. A strength of the work is the incorporation of physiological as well as behavioral measures. The project is funded by the Danish government.

    Hakonsson, D. D., Eskildsen, J. K., Argote, L., Monster, D., Burton, R. M., & Obel, B. (2016). Exploration versus Exploitation: Emotions and Performance as Antecedents and Consequences of Team Decisions. Strategic Management Journal, 37(6), 985-1001.
  • ”Social Networks, Turnover, Transactive Memory Systems and Team Performance,” Jonathan Kush (Carnegie Mellon University), Brandy Aven (Carnegie Mellon University) and Linda Argote (Carnegie Mellon University). The research examines how social networks and turnover affect the development of transactive memory systems, which in turn affect team performance. Teams perform a collaborative computing task in a distributed environment. The research is funded by the National Science Foundation's Human-Centered Computing Program.

    Argote, L., Aven, B., & Kush, J. A. (2018).  The Effects of Communication Networks and Turnover on Transactive Memory and Group Performance. Organization Science, 29(2), 191-201.

  • "The Two Wonders of Experience Working Together: Unpacking How Matching Work Responsibilities and Individual Expertise and Having a Common Language Contribute to Team Performance," coauthored by Ray Reagans (Sloan, MIT), Ella Miron-Spektor (Technion) and Linda Argote (Tepper, Carnegie Mellon University). This project examines the effect of differentiated expertise and shared language on the emergence of Transactive Memory Systems and group performance. This work is funded by the National Science Foundation (IOS).

    Reagans, R., Miron-Spektor, E., & Argote, L. (2016). Knowledge Utilization, Coordination and Team Performance. Organization Science, 233-248.