How multiteam systems learn

Valerie I. Sessa, Manuel London, Marlee Wanamaker

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Purpose: Extending a model of how teams learn, this paper aims to present a model of multiteam system (MTS) learning, comparing similarities and differences between how MTSs learn and how component teams learn. The paper describes the value of adaptive, generative and transformative learning for increasing MTS development over time. Design/methodology/approach: The model proposes that environmental demands trigger adaptive, generative and transformative MTS learning, which is further increased by the MTS’s readiness to learn. Learning can happen during performance episodes and during hiatus periods between performance episodes. Findings: Learning triggers coupled with readiness to learn and the cycle and phase of MTS process influence the learning process (adaptive, generative or transformative), which in turn influences the learning outcomes. Research/limitations implications: The study offers a number of research propositions with the idea that the model and propositions will stimulate research in this area. Practical implications: This model allows MTS and component team leaders and facilitators to recognize that MTS learning is a process that is needed to help component teams work together and help the MTS as a whole perform in current and future situations, thereby improving MTS effectiveness. Originality/value: Little attention has been given to the notion that MTSs learn and develop. This manuscript is the first to emphasize that MTSs learn and identify processes that can improve learning. Adaptive, generative and transformative processes describe how MTSs learn and produce changes in MTS structure and actions.

Original languageEnglish
Pages (from-to)138-156
Number of pages19
JournalTeam Performance Management
Issue number1-2
StatePublished - 7 Mar 2019


  • Learning
  • Multi team systems
  • Performance episodes


Dive into the research topics of 'How multiteam systems learn'. Together they form a unique fingerprint.

Cite this