2017
Working Paper
HBS Working Paper Series

Rationalizing Outcomes: Mental-Model-Guided Learning in Competitive Markets

By: Anoop R. Menon and Dennis Yao

Format:Print
| Language:English
| Pages:40

Abstract

This paper explores how mental models affect the analysis of dynamic strategic interactions. We develop an explanation-based view of mental models founded on a regression analogy and implement this view in simulations involving market competition between two firms with possibly differing mental models regarding the structure of demand. The paper addresses the following questions: (1) How sticky are incorrect mental models, and how are market observations interpreted in such models? (2) What is the impact of the interaction of different mental models on each firm’s learning? (3) Can firms with less accurate mental models outperform firms with more accurate mental models and, if so, why? We find that incorrect mental models can easily “rationalize” market outcomes and shape how a firm and its rival learns. Furthermore, this learning process does not push the firms to make increasingly convergent output choices, but rather causes those choices to diverge slowly. Finally, we identify situations where the firm with the less accurate mental model outperforms the firm with the more accurate mental model.