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<p>This study leverages unique restaurant-level panel data from Facebook Business Pages, Yelp.com, and Walkscore.com to examine how social media engagement influences consumers’ patronage behavior. Drawing on the Elaboration Likelihood Model (ELM) and related information processing and digital marketing research, we also investigate how contextual and environmental factors moderate this relationship. The results show that Facebook Likes have a significant positive effect on Check-ins, a proxy for consumers’ offline patronage. This effect is stronger for chain restaurants than for independent ones and is amplified in highly competitive markets. Additional analyses using panel vector autoregression (VAR) models address potential endogeneity arising from reverse causality between Likes and Check-ins. This study advances the social media engagement literature by highlighting how Likes influence consumers’ real-world patronage beyond transactional and financial outcomes. It also provides actionable insights for social media and digital marketing practitioners seeking to leverage engagement metrics to enhance business performance.</p>

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Social Media Engagement and Consumer Patronage: The Moderating Role of Business Operation and Competition Intensity

  • 期刊论文

  • 发表日期：

    2025年12月12日

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  • Navid Aghakhani,
  • Chia-Wei Joy Lin,
  • Hamid Reza Nikkhah,
  • Michelle Carter

摘要

This study leverages unique restaurant-level panel data from Facebook Business Pages, Yelp.com, and Walkscore.com to examine how social media engagement influences consumers’ patronage behavior. Drawing on the Elaboration Likelihood Model (ELM) and related information processing and digital marketing research, we also investigate how contextual and environmental factors moderate this relationship. The results show that Facebook Likes have a significant positive effect on Check-ins, a proxy for consumers’ offline patronage. This effect is stronger for chain restaurants than for independent ones and is amplified in highly competitive markets. Additional analyses using panel vector autoregression (VAR) models address potential endogeneity arising from reverse causality between Likes and Check-ins. This study advances the social media engagement literature by highlighting how Likes influence consumers’ real-world patronage beyond transactional and financial outcomes. It also provides actionable insights for social media and digital marketing practitioners seeking to leverage engagement metrics to enhance business performance.