Cognitive Misalignment Among Stakeholders and Governance Strategies in the Li River Karst Scene–Village System: A Q Methodology Study

This study addresses the intensifying conflict between conservation and tourism development in global natural World Heritage sites by exploring how cognitive misalignments among stakeholders obstruct scene–village symbiosis and by proposing governance strategies grounded in cognitive coordination to enhance sustainable governance effectiveness. Focusing on three representative villages located in the overlapping area of the Li River World Heritage protection zone and the scenic tourism area, which represent the consolidation/maturity, emerging incubation, and potential cultivation stages of tourism development, the study employs Q methodology to identify stakeholder cognitive clusters and their interactive logics. Four cognitive clusters are revealed: utilitarian landscape instrumentalism, livelihood entitlement-oriented, nostalgic disciplinary gaze, and institutional risk aversion. Their presence and combinations vary across different development stages, forming distinct cognitive configurations. These clusters exhibit both couplings and tensions in value preferences, benefit claims, and action logic, which shape rule acceptance and willingness to collaborate. By overcoming the limitations of conventional surveys in capturing latent perceptions, this study proposes an integrated “cognitive differences—strategic interactions—policy mechanisms” framework. The findings offer transferable insights for managing multi-stakeholder heritage destinations, particularly in ecologically fragile areas facing overtourism pressures and sustainability challenges.

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Publication Details

Journal
Sustainability
Published
2026-02-04
DOI
https://doi.org/10.3390/su18031569
Primary Topic
Q Methodology Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Cognitive Misalignment Among Stakeholders and Governance Strategies in the Li River Karst Scene–Village System: A Q Methodology Study

Bing Lin, Guoshu Bin, Lisha Zhu, Jiani Chen
Sustainability
Q Methodology Applications
article

Cognitive Misalignment Among Stakeholders and Governance Strategies in the Li River Karst Scene–Village System: A Q Methodology Study

Bing Lin, Guoshu Bin, Lisha Zhu, Jiani Chen
article en

Abstract

This study addresses the intensifying conflict between conservation and tourism development in global natural World Heritage sites by exploring how cognitive misalignments among stakeholders obstruct scene–village symbiosis and by proposing governance strategies grounded in cognitive coordination to enhance sustainable governance effectiveness. Focusing on three representative villages located in the overlapping area of the Li River World Heritage protection zone and the scenic tourism area, which represent the consolidation/maturity, emerging incubation, and potential cultivation stages of tourism development, the study employs Q methodology to identify stakeholder cognitive clusters and their interactive logics. Four cognitive clusters are revealed: utilitarian landscape instrumentalism, livelihood entitlement-oriented, nostalgic disciplinary gaze, and institutional risk aversion. Their presence and combinations vary across different development stages, forming distinct cognitive configurations. These clusters exhibit both couplings and tensions in value preferences, benefit claims, and action logic, which shape rule acceptance and willingness to collaborate. By overcoming the limitations of conventional surveys in capturing latent perceptions, this study proposes an integrated “cognitive differences—strategic interactions—policy mechanisms” framework. The findings offer transferable insights for managing multi-stakeholder heritage destinations, particularly in ecologically fragile areas facing overtourism pressures and sustainability challenges.

SustainabilityVol. 18(3)
Guilin University of Technology (CN)
National Natural Science Foundation of China, Guangxi Key Research and Development Program
Openalex Percentile: Top 70%
Q Methodology Applications
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