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Review article

The use and potential of Q method in environmental planning and management

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Pages 2721-2747 | Received 30 May 2022, Accepted 24 Apr 2023, Published online: 09 May 2023
 

Abstract

Stakeholder engagement is critical to bridge gaps between academic knowledge production and application for environmental resources. Q Methodology, a qualitative and quantitative protocol, is well suited to address environmental planning and management issues through rigorous analysis of stakeholder perspectives. We review several methodological applications that have been used with or within Q Methodology aiming to improve environmental management, inform decision-making and policy, and build consensus. We review their deployment across six domains: (1) Q-set: discourse identification and concourse creation; (2) P-set: strategies to select participants and promote stakeholder engagement; (3) Q-sorts: interaction with respondents during data production; (4) Comparisons: geographic and temporal comparisons; (5) Graphics: visualization techniques to improve interpretation and dissemination; and (6) Methods: the use of complementary and mixed methods. We discuss their utility for environmental planning and management and provide recommendations for integrating these procedures into future research.

Acknowledgments

We would like to thank Texas A&M University and the Office of the President’s Excellence Grants for financial support for the project “Pathways to Urban Water Security: Desalination and Water Reuse in the twenty first Century.” Lucas Seghezzo acknowledges support from the National Research Council of Argentina (CONICET) and the National University of Salta (UNSa), Argentina.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by Texas A&M University and the Office of the President’s Excellence Grants through project “Pathways to Urban Water Security: Desalination and Water Reuse in the twenty first Century.” Lucas Seghezzo acknowledges support from the National Research Council of Argentina (CONICET) and the National University of Salta (UNSa), Argentina.

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