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Improving decision making through visual knowledge calibration

Christian Muntwiler (Institute of Media and Communication Management, University of St Gallen, St Gallen, Switzerland)
Martin J. Eppler (Institute of Media and Communication Management, University of St Gallen, St Gallen, Switzerland)

Management Decision

ISSN: 0025-1747

Article publication date: 29 March 2023

Issue publication date: 24 July 2023

246

Abstract

Purpose

This article aims to explore the so-called illusion of explanatory depth (IOED) of managers regarding their understanding of digital technologies and examines the effect of knowledge visualization one’s current understanding and decision making. Its purpose is to show that managers think they know more than they do and that this affects decision making but can be reduced through knowledge visualization.

Design/methodology/approach

In two experiments with experienced managers, the authors investigate the size and impact of the IOED bias in decision making and examine if sketched self-explanations are as effective as written self-explanations to reduce the bias.

Findings

The findings show that experienced managers suffer from a significant illusion concerning their explanatory understanding of digital technologies and that sketching one’s current level of explanatory understanding of these technologies supports the accurate calibration of one’s knowledge. The findings indicate that sketching knowledge is a helpful modality for the detection and subsequent recalibration of biased knowledge in domain-dependent decision making.

Originality/value

This article is the first to explore the effect of sketched knowledge externalization on the calibration of explanatory knowledge of managers. It extends the literature on both, the IOED and on knowledge visualization as an instrument of knowledge calibration.

Keywords

Citation

Muntwiler, C. and Eppler, M.J. (2023), "Improving decision making through visual knowledge calibration", Management Decision, Vol. 61 No. 8, pp. 2374-2390. https://doi.org/10.1108/MD-07-2022-1018

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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