skip to content

Faculty of Economics

Journal Cover

Feduzi, A., Faulkner, P., Runde, J., Cabantous, L. and Loch, C

Heuristic Methods for Updating Small World Representations in Strategic Situations of Knightian Uncertainty

Academy of Management Review, forthcoming


Abstract: Recent studies on the construction and use of “small world representations” in strategic decision-making under Knightian uncertainty say little about how such representations should be updated over the implementation phase. This paper draws on the psychology of reasoning to take a step towards answering this question. We begin by theorizing small world representations and how the scenario spaces they contain are constructed and may be updated over time. We then introduce two well-known heuristic methods of inquiry, disconfirmation and counterfactual reasoning, translate them into practical procedures for updating scenario spaces, and compare the relative performance of these procedures in strategic situations of Knightian uncertainty. Our principal findings are that the procedure based on counterfactual reasoning is superior to the one based on disconfirmation with respect to (1) counteracting the confirmation bias, (2) promoting the exploration of the set of imaginable scenarios, and (3) facilitating action to mitigate or exploit the consequences of what would otherwise have been Black Swans. We close with some broader implications for the study of strategic decision-making under Knightian uncertainty.

Author links: Phil Faulkner  

Papers and Publications

Recent Publications

Fruehwirth, J., Iyer, S. and Zhang, A. Religion and Depression in Adolescence Journal of Political Economy [2019]

Ambrus, A. and Elliott, M. Investments in Social Ties, Risk Sharing, and Inequality Review of Economic Studies [2020]

Acconcia, A., Corsetti, G. and Simonelli, S. Liquidity and Consumption: Evidence from Three Post-earthquake Reconstruction Programs in Italy American Economic Journal: Macroeconomics [2020]

Ai, C., Linton, O., Motegi, K. and Zhang, Z. A Unified Framework for Efficient Estimation of General Treatment Models Quantitative Economics, forthcoming [2021]