We examine the force of three types of behavioral dynamics in quantity-setting triopoly experiments: (1) mimicking the successful firm, (2) rules based on following the exemplary firm, and (3) rules based on belief learning. Theoretically, these three types of rules lead to the competitive, the collusive, and the CournotNash outcome, respectively. In the experiment we employ three information treatments, each of which is hypothesized to be conducive to the force of one of the three dynamic rules. To a large extent, the results are consistent with the hypothesized relationships between treatments, behavioral rules, and outcomes.

We propose an operational concept of Constrained Strategic Equilibrium (CSE) applicable to a broad class of games of incomplete information. We show that a sequence of CSEs approximates an analytically untractable Bayesian Nash equilibrium under standard conditions. In addition, the CSE approach provides a theoretic framework to extend the bounded rationality concept of ”Rule of Thumb ” to games of incomplete information. We also propose a powerful algorithm based upon Monte-Carlo simulations to compute the CSEs numerically at a very high level of generality. Finally, we illustrate the flexibility of the CSE approach in a procurement from the French aerospace industry characterized by a complex allocation mechanism.

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