What does this research mean for the field?

Pre-valuation categorical architectures in decision-making systematically induce optimistic bias and compress perceived variance, distortions that are amplified in highly volatile environments. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.ESTABLISHES_NEW_DIRECTION.

What question did this study set out to answer?

This paper examines how organizational evaluation architectures influence strategic sensing quality within volatile, uncertain, complex, and ambiguous (VUCA) environments.

September 8, 2026Journal of strategy and management

Sensing resolution in VUCA environments: how information structure shapes strategic choices

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Authors

ZMZhu Mei

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Overview

Theoretical and comparative case analysis reveals that pre-valuation labeling distorts strategic evaluation in volatile environments, highlighting the need for high-resolution architectures.

Key Points

This paper examines how organizational evaluation architectures influence strategic sensing quality within volatile, uncertain, complex, and ambiguous (VUCA) environments.
Combined deductive theory development with formal probabilistic modeling under a Gaussian baseline to derive propositions on pre-valuation truncation.
Conducted a comparative archetype analysis of Fujifilm and Polaroid during the analog-to-digital transition to illustrate contrasting evaluation structures.
The formal model shows that pre-valuation categorical labeling systematically produces optimistic bias in perceived expected value while compressing perceived variance.
Distortions in strategic evaluation amplify as environmental volatility increases, with theoretical intensification under heavy-tailed Paretian distributions.
Comparative case archetypes demonstrate that differences in information architecture align with divergent strategic trajectories in the same high-VUCA regime.

Cite This Study

Zhu Mei (2026) studied this question.

synapsesocial.com/papers/6a9fd80458e84d0ff5b4724e https://doi.org/10.1108/jsma-02-2026-0062

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September 8, 2026Journal of strategy and management

Sensing resolution in VUCA environments: how information structure shapes strategic choices

View Full Paper

Ask AI

Bookmark

Authors

ZMZhu Mei

Discussion

Member takes

Overview

Theoretical and comparative case analysis reveals that pre-valuation labeling distorts strategic evaluation in volatile environments, highlighting the need for high-resolution architectures.

Key Points

This paper examines how organizational evaluation architectures influence strategic sensing quality within volatile, uncertain, complex, and ambiguous (VUCA) environments.
Combined deductive theory development with formal probabilistic modeling under a Gaussian baseline to derive propositions on pre-valuation truncation.
Conducted a comparative archetype analysis of Fujifilm and Polaroid during the analog-to-digital transition to illustrate contrasting evaluation structures.
The formal model shows that pre-valuation categorical labeling systematically produces optimistic bias in perceived expected value while compressing perceived variance.
Distortions in strategic evaluation amplify as environmental volatility increases, with theoretical intensification under heavy-tailed Paretian distributions.
Comparative case archetypes demonstrate that differences in information architecture align with divergent strategic trajectories in the same high-VUCA regime.

Cite This Study

Zhu Mei (2026) studied this question.

synapsesocial.com/papers/6a9fd80458e84d0ff5b4724e https://doi.org/10.1108/jsma-02-2026-0062

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