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Cited by 320

The DOI matches its Crossref record; 95 of the 95 references it cites were found in a registry or an index.

Toward a Cognitive View of Signalling Theory: Individual Attention and Signal Set Interpretation

Drover, Will, Wood, Matthew S., Corbett, Andrew C.·2018·Journal of Management Studies

Abstract

Research on organizational signalling tends to focus on the effects of isolated or congruent signals, assuming highly rational responses to those signals. In this study, we theorize about the cognitive processes associated with the attention paid to and interpretation of multiple, often incongruent signals that organizations send to consumers, financiers, and other stakeholders who make organizational assessments. Contributing a cognitive perspective of signal attention and interpretation, alongside the introduction of signal sets, we provide a more complete picture of how organizational signalling unfolds in the field. Our research opens new frontiers for future inquiry into the cognitive foundations of signal attention, multi‐signal interpretation, and incongruent signals.

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Metadata

Authors
Drover, W., Wood, M. S., & Corbett, A. C.
Venue
Journal of Management Studies
Publisher
Wiley
Published
2017-07-07
Volume
55
Issue
2
Pages
209-231
ISSN
  • 0022-2380 (ISSN-L)
  • 1467-6486
OpenAlex
W2735610417
Cited by
320
References
95
FWCI
14.23
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Toward a Cognitive View of Signalling Theory: Individual Attention and Signal Set Interpretation. https://app.cochat.ai/papers/10.1111/joms.12282
The paper
Drover, W., Wood, M. S., & Corbett, A. C. (2018). Toward a Cognitive View of Signalling Theory: Individual Attention and Signal Set Interpretation. Journal of Management Studies. https://doi.org/10.1111/joms.12282

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.