Searching for great strategies

There is a tension between answers that emphasize favorable outcomes under conditions of uncertainty and those that assert intentionality.

Strategy Science 2, 272 (2017)

T. Fink, P. Ghemawat, M. Reeves

LQ placeholderThere is a tension between answers that emphasize favorable outcomes under conditions of uncertainty and those that assert intentionality.

We focus on answering the question posed for this special issue by elaborating a specific perspective, involving information-enabled search, in which firms add capabilities (or components) that expand what they can accomplish in the product market arena, and the key strategic choices concern the kinds of capabilities that are added. We establish that measuring how a new candidate component interacts with the components we already have can be a reasonable proxy for how they will combine with new components which we don’t yet have. This allows us to compare the performance of “impatient strategies” focused on the current usefulness of a new component and “patient strategies” focused on anticipated long-term usefulness. Their relative performance depends on how far the innovation process has progressed, and on the structure of the innovation space itself. In particular, a flattening in the increase of complexity implies an increase in the relative attractiveness of patient strategies over impatient ones, i.e., constitutes a signal to a switch strategies. It is therefore possible to construct information-based adaptive search strategies, which outperform either random strategies or fixed (patient or impatient) strategies for component selection. And there are broader implications for strategy as well.

LQ placeholderNetwork valuation in financial systems

Network valuation in financial systems

P. Barucca, M. Bardoscia, F. Caccioli, M. D’Errico, G. Visentin, G. Caldarelli, S. Battiston

Mathematical Finance

LQ placeholderThe space of functions computed by deep layered machines

The space of functions computed by deep layered machines

A. Mozeika, B. Li, D. Saad

Sub. to Physical Review Letters

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Replica analysis of overfitting in generalized linear models

T. Coolen, M. Sheikh, A. Mozeika, F. Aguirre-Lopez, F. Antenucci

Sub. to Journal of Physics A

LQ placeholderTaming complexity

Taming complexity

M. Reeves, S. Levin, T. Fink, A. Levina

Harvard Business Review

LQ placeholderReplica analysis of Bayesian data clustering

Replica analysis of Bayesian data clustering

A. Mozeika, T. Coolen

Journal of Physics A

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Degree-correlations in a bursting dynamic network model

F. Vanni, P. Barucca

Journal of Economic Interaction and Coordination

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