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Cited by 310

The DOI matches its Crossref record; 87 of the 87 references it cites were found in a registry or an index.

Coping With Paradox: Multistakeholder Learning Dialogue as a Pluralist Sensemaking Process for Addressing Messy Problems

Calton, Jerry M., Payne, Steven L.·2003·Business & Society

Abstract

A notable feature of paradox is recognition that seemingly contradictory terms are inextricably intertwined and interrelated—holding out the hope that something new can be learned from the cognitive tension contained within. Aram has characterized the central concern of the business and society field as the paradox of interdependent relations. Our study argues that this and related paradoxes can be addressed by engaging with others and trying to gain shared insight via an interactive, developmental, exploratory sensemaking process that can inform the governance of stakeholder networks. We advocate multistakeholder learning dialogues (MSLDs) as a means for both scholars and practitioners to construct meanings that can guide joint efforts to cope with messy problems that help shape complex, paradoxical relationships within stakeholder networks.

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Metadata

Authors
Calton, J. M., & Payne, S. L.
Venue
Business & Society
Published
2003-03
Volume
42
Issue
1
Pages
7-42
ISSN
  • 0007-6503 (ISSN-L)
  • 1552-4205
OpenAlex
W2055806454
Cited by
310
References
87
FWCI
16.13
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Coping With Paradox: Multistakeholder Learning Dialogue as a Pluralist Sensemaking Process for Addressing Messy Problems. https://app.cochat.ai/papers/10.1177/0007650302250505
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Calton, J. M., & Payne, S. L. (2003). Coping With Paradox: Multistakeholder Learning Dialogue as a Pluralist Sensemaking Process for Addressing Messy Problems. Business & Society. https://doi.org/10.1177/0007650302250505

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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.