Chimera heuristics: Generative rational heuristics for the unknown from design theory

Agathe Gilain (), Pascal Le Masson () and Benoit Weil ()
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Agathe Gilain: CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique, IRT SystemX
Pascal Le Masson: CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique
Benoit Weil: CGS i3 - Centre de Gestion Scientifique i3 - Mines Paris - PSL (École nationale supérieure des mines de Paris) - PSL - Université Paris Sciences et Lettres - I3 - Institut interdisciplinaire de l’innovation - CNRS - Centre National de la Recherche Scientifique

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Abstract: The learning strategies offered by science for discovering the world by generating and testing hypotheses have been used abundantly to build decision‐making heuristics. In contrast, decision‐making heuristics for (re)designing the world are rarer. This paper develops a heuristic combining the exploratory power of chimeras with a design logic. Chimeras have long been used to foster imagination and build initially unknown futures. And recent advances in design theory show that in decision‐making situations, chimeras can be generated as nonfalsifiable existential statements about desirable alternatives and events. Moreover, design theory offers learning operations that handle nonfalsifiable statements to generate new real objects. This paper uses these operations to build a rational heuristic that may or may not transform initial chimeras into reality. Its main effect is to ensure that stimulated learning leads to decision alternatives (whether pre‐existing or novel) that surpass the initial optimal one. This paves the way for a class of design‐based heuristics extending the main functions of Bayesian learning to a non‐Bayesian world.

Date: 2023-11-21
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Published in European Management Review, 2023, Special issue on Expanding the boundaries of rationality, ⟨10.1111/emre.12621⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04349425

DOI: 10.1111/emre.12621

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