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Article Dans Une Revue European Management Review Année : 2018

DESIGNING DECISIONS IN THE UNKNOWN: TOWARDS A GENERATIVE DECISION MODEL FOR MANAGEMENT SCIENCE

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Pascal Le Masson
Armand Hatchuel
Mario Le Glatin
Benoit Weil

Résumé

This study examines how design theory enables us to extend decision-making logic to the "unknown," which often appears as the strange territory beyond the rationality of the decision-maker. We contribute to the foundations of management by making the unknown an actionable notion for the decision-maker. To this end, we build on the pioneering works in "managing in the unknown" and on design theory to systematically characterize rational forms of action to structure the exploration of the unknown from a decision-making perspective. We show that action consists of designing decisions in the unknown and can be organized on the basis of the notion of a "decision-driven design path," which is not yet a decision but helps to organize the generation of a better decision-making situation. Our decision-design model allows us to identify four archetypes of decision-driven design paths. Two involve generating "wishful decisions," either by improvement or by genericity, while the other two involve generating "decision-changing states" by generating a "best-choice hacking state" or an "all-decisions hacking state." These archetypes correspond to forms of collective action characterized by a specific strategy of knowledge acquisition, a specific performance, and specific organizations. In particular, they enable us to discuss the variety of known organizational forms that managers can rely on to explore the unknown. Le Masson, P., Hatchuel, A., Le Glatin, M., and Weil, B. (2018). "Designing decisions in the unknown: towards a generative decision model for management science." European Management Review, To be published, pp.
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Dates et versions

hal-01937103 , version 1 (27-11-2018)

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Pascal Le Masson, Armand Hatchuel, Mario Le Glatin, Benoit Weil. DESIGNING DECISIONS IN THE UNKNOWN: TOWARDS A GENERATIVE DECISION MODEL FOR MANAGEMENT SCIENCE. European Management Review, inPress, ⟨10.1111/emre.12289⟩. ⟨hal-01937103⟩
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