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Beyond Gaussian Averages: Redirecting Organization Science Toward Extreme Events and Power Laws

by Pierpaolo Andriani and Bill McKelvey. Reading for Tuesday, 28 August.

In power law functions the exponent stays constant whereas in normal exponentials the exponential varies. On occasion, deviation amplifying mutual causal processes among interdependent data points cause extreme events characterized by power laws. They seem ubiquitous; we list 80 kinds of them—half each among natural and social phenomena. We draw a “line in the sand” between Gaussian (based on independent data points, finite variance and emphasizing averages) and Paretian statistics (based on interdependence, positive feedback, infinite variance, and emphasizing extremes). Quantitative journal publication depends almost entirely on Gaussian statistics. After noting that practicing managers live in a world of “extremes,” we draw on complexity and earthquake sciences to propose redirecting organization science. Conclusion: No statistical findings should be accepted into organization science if they gain significance via some assumption-device by which extreme events and infinite variance are ignored. The cost is false science and irrelevance to practitioners.

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