
SciEnggJ 19 (Supplement) 156-165
available online: 04 August 2026
DOI: https://doi.org/10.54645/202619SupWKY-53
*Corresponding author
Email Address: christy.b2008@gmail.com
Date received: 03 July 2026
Dates revised: 02 August 2026
Date accepted: 29 July 2026
Scaling circularity from campus to globe: The roles of resident attitudes and community participation in Kinabalu UNESCO Global Geopark
Circular economy discussions have increasingly moved beyond materials efficiency and environmental management. However, more attention should be paid to the social factors that support circular and sustainable development in community-based tourism. This conceptual paper examines Kinabalu UNESCO Global Geopark in Sabah, Malaysia, as a rural geopark context for advancing social circularity in sustainable tourism. Drawing on Social Exchange Theory, Stakeholder Theory, and Social Representations Theory, this paper develops a conceptual framework to explain residents' support for sustainable tourism. The framework proposes that residents’ sustainable tourism attitudes influence their support for tourism. These attitudes include perceived economic benefits, environmental sustainability, perceived social costs, cultural sustainability, and visitor satisfaction. The framework also proposes that these attitudes influence residents’ support for tourism both directly and indirectly through place image. Furthermore, community participation is included as a moderating variable that may strengthen the relationship between residents’ attitudes and support for tourism. The paper contributes to circular economy and sustainable tourism literature by introducing social circularity as a conceptual lens. This lens focuses on residents’ attitudes, place-based perceptions, participation, and support as social feedback mechanisms that help sustain tourism development. The paper also positions geoparks as community-based living laboratories where higher education institutions can support campus-to-globe knowledge transfer, participatory governance, and local value retention. Finally, the proposed framework provides a basis for future empirical testing using quantitative methods such as Partial Least Squares Structural Equation Modeling (PLS-SEM).
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