Perception, attractiveness, and engagement: a multi-criteria decision support framework for city branding via social media
Year: 2026
Type: article
Abstract: With the growing forces of decentralization and globalization, cities face increasing competition to differentiate themselves through strategic city branding. Social media has emerged as a transformative tool, enabling cities to dynamically engage with global audiences and enhance their branding practices. Despite extensive research on various aspects of city branding, such as brand attributes and online branding efforts, a significant gap remains in developing a comprehensive measurement framework tailored specifically for city branding via social media. To address this gap, this study introduces the “City Branding on Social Media Measurement” (CBSMM) framework, which evaluates city branding through three critical dimensions: city brand perception, city brand attractiveness, and city brand engagement. These dimensions are further operationalized into ten measurable criteria. By incorporating the Fuzzy Best Worst Method (FBWM), the proposed framework effectively prioritizes the relative importance of these dimensions and criteria based on input from key experts. A case study conducted in Hong Kong demonstrates that city brand engagement is the most critical dimension in the context of social media, with user involvement, loyalty, and culture emerging as the top three criteria. The CBSMM framework provides valuable decision-support insights and establishes internal consistency. By assisting city decision-makers in identifying priority areas for strategic city branding on social media, this framework lays the groundwork for further research and application in diverse contexts. This study not only addresses an important gap in the literature but also offers practical recommendations for leveraging social media to strengthen city branding in today’s digital era.
Authors: Yanlin Li, Xinrui Li, YP Tsang, CH Wu, CKM Lee
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,890
Funder: Hong Kong Polytechnic University
OpenAlex ID: W7168409276
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