User engagement on global social networks: Examining the roles of perceived brand globalness, identification and global identity

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2022-08Keyword
Active and passive user engagementBrand globalness
Global identity
User identification
Social networks
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© 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)Peer-Reviewed
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Building on the global branding literature, brand relationship theory and social identity theory, this study investigates the relationship between perceived brand globalness (PBG) and user engagement (active/passive) on global social networks (GSN). Additionally, the study investigates the mediating effects of two distinct forms of user identification (i.e., user identification with the GSN brand and user identification with the GSN community) as well as the moderating effects of user global identity on the relationship between PBG and user engagement with such brands. Covariance-based structural equation modeling was used to analyse data collected from users of a GSN (i.e., Facebook) in the United Kingdom (UK) and India. The results indicate that PBG significantly influences both active and passive user engagement. This relationship is mediated by users' identification with a GSN brand and community. Additionally, the findings indicate that the associations between PBG and user engagement (active/passive) on GSN vary as a function of users' global identity. The results also demonstrate some country-specific variations in key relationships. Finally, the study offers useful recommendations for social media managers to rethink and redesign their user engagement strategies, keeping in mind global cultural diversity.Version
Published versionCitation
Akram MS, Malhotra N, Goraya MAS et al (2022) User engagement on global social networks: Examining the roles of perceived brand globalness, identification and global identity. Technological Forecasting and Social Change. 181: 121771.Link to publisher’s version
https://doi.org/10.1016/j.techfore.2022.121771Type
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