.png){kind=icon}
.png){kind=icon}
Return
Decision Centralization and Learning from Experience in Groups: Separating Context from Aggregation Effects
.png){kind=icon}
PRE
AI
DOI：10.1287/mnsc.2022.01507.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Organizational learning often involves groups that learn from feedback on their decisions over time (also known as learning by doing or learning from experience). Although organizational learning is frequently assumed to resemble individual learning from experience, there is limited evidence to validate this assumption. Furthermore, groups in organizations often have centralized rather than decentralized decision making, but we know little about how they differ in learning from experience. Using a combination of experimental data and computational modeling, we compare individuals to groups that are either decentralized or centralized in their decision making. We find that centralized groups behave like hyper-individuals: They update and explore more than individuals (who, in turn, update and explore more than decentralized groups). Our evidence shows that not only do groups differ from individuals because of aggregation processes but also that individuals change their behaviors simply by virtue of being in a group (a context effect). Specifically, we find that participants assigned as leaders in centralized groups become proactive learners who seek novel information to learn by deviating from experience. Implications are drawn for how this might alter the way we conceptualize and model organizational learning.
Keywords:
learning
decision structure
organization design
microfoundations