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Writer's pictureJose Arrieta

7. Learning Curves and Team Learning (Linda Argote)

Updated: Aug 24, 2023

By Linda Argote - Carnegie Mellon

Prerecorded session

Live session


Required readings

Argote, L. (2013). Organizational learning: Creating, retaining and transferring knowledge. Springer (especially Chapters 1, 2, 4 and 6)

Argote, L., Lee, S., & Park, J. (2021). Organizational Learning Processes and Outcomes: Major Findings and Future Research Directions. Management Science, 67(9), 5399-5429.

Edmondson, A. C., Dillon, J. R., & Roloff, K. S. (2007). Three Perspectives on Team Learning, The Academy of Management Annals, 1(1), 269- 314.

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.

Lee S., & Meyer-Doyle, P. (2017). How performance incentives shape individual exploration and exploitation: Evidence from microdata. Organization Science, 28(1), 19-38.

Reagans, R., Argote, L., & Brooks, D. (2005). Individual experience and experience working together: Predicting learning rates from knowing what to do and knowing who knows what. Management Science, 51, 869-881.

Ren, Y., & Argote, L. (2011). Transactive memory systems 1985-2010: An integrated framework of dimensions, antecedents and consequences. Academy of Management Annals, 5(1), 189-229.


Discussion questions

One of the biggest challenges in social science research in the field, including work on organizational learning, is endogeneity, which can lead to biased coefficient estimates. We will discuss ways to mitigate the endogeneity problem through the choice of field settings (e.g., see Reagans et al., 2005), the use of statistical techniques such as instrumental variables (e.g., see Egelman et al., 2017) or the use of quasi experiments or experiments in the field (e.g., Lee & Meyer-Doyle, 2017) or laboratory.

Some current and emerging research questions

  1. When is experience a “good teacher” and when is it a poor one? That is, when does experience have a positive or negative effect on organizational learning?

  2. How can the biases that can occur in organizational learning (e.g., superstitious learning) be overcome?

  3. What is the relationship between the three subprocesses of organizational learning: learning from direct experience, learning from indirect or vicarious experience, and retaining knowledge? When are the processes substitutes and when are they complements?

  4. How do move from group learning to organizational learning? For example, how does the concept of transactive memory scale from the group to the organizational level?

  5. What is the relationship between artificial and human intelligence?

    1. Which tasks are humans particularly well-suited for and which tasks are more effectively performed by machine-learning tools?

    2. What are the conditions under which humans accept and rely on advice from machines?

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