Working Paper: CEPR ID: DP17392
Authors: Alfonso Gambardella; Arnaldo Camuffo; Fabio Maccheroni; Massimo Marinacci; Andrea Pignataro
Abstract: We show that grounding low-frequency high-impact strategic decisions under uncertainty on the development and test of theories is a foundational strategic choice of firms, and an important determinant of performance. Our normative Bayesian model shows that decision-makers benefit from comparing alternative theories and when theories are reliable (less uncertain) they should not experiment and they should focus on their most plausible theory (highest prior). Otherwise, they ought to experiment with their less reliable theories because they learn more. We also show that the variability of the optimal experiment matches the variability of the prior. In particular, large scale experiments may be overprecise and penalize radical new theories with more variable priors. Overall, our framework explains how structured exploration improves strategic decisions by reducing model mis-specification and why performance heterogeneity and competitive advantage is created by exploring theories with higher variance
Keywords: decision problem; experiments; exploration; framing; strategy; theory; uncertainty
JEL Codes: L21; L26; M13; M21
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| robustness of the chosen theory (C52) | firm's performance outcomes (L25) |
| reliable theories (D80) | focus on these theories rather than experiment (C90) |
| less reliable theories (D80) | experimentation is encouraged (C90) |
| variability of the optimal experiment (C90) | variability of the prior probabilities (C46) |
| structured exploration (C99) | reduces model misspecification (C52) |
| structured exploration (C99) | enhances decision-making quality (D80) |
| structured exploration (C99) | creates competitive advantages (P12) |