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<p>This study examines how social media influencers affect pricing dynamics in electronic marketplaces. Drawing on platform ecosystem theory and differentiated demand models as a theoretical lens, we conceptualise influencers as attention brokers who reallocate consumer attention within algorithmic marketplace environments, thereby reducing effective price sensitivity among exposed consumers. Using a panel dataset combining YouTube influencer campaign data and Amazon product-level data (price, sales rank, reviews, and ratings), we employ a two-stage least squares (2SLS) framework to assess how influencer exposure alters the observed price-demand relationship. Our findings indicate that products featured in influencer campaigns exhibit meaningfully lower observed price responsiveness in sales rank-based demand proxies compared to non-featured products. These results are consistent with the theoretical prediction that influencer-driven attention shifts reduce the slope of the effective demand curve, enabling sellers to maintain higher price positions with limited sales rank deterioration. We interpret these results as reduced-form evidence of altered competitive price pressure rather than structurally identified causal elasticity estimates, and we acknowledge the limitations of the identification strategy. The study contributes to platform pricing theory and influencer marketing research by providing empirical evidence that social influence processes can reshape pricing power in highly transparent electronic marketplaces.</p>

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Influencers’ effects on electronic marketplace pricing strategies: An empirical analysis

  • 期刊论文

  • 发表日期：

    2026年4月30日

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  • Anup Kumar,
  • Parijat Upadhyay,
  • Praveen K. Choudhary

摘要

This study examines how social media influencers affect pricing dynamics in electronic marketplaces. Drawing on platform ecosystem theory and differentiated demand models as a theoretical lens, we conceptualise influencers as attention brokers who reallocate consumer attention within algorithmic marketplace environments, thereby reducing effective price sensitivity among exposed consumers. Using a panel dataset combining YouTube influencer campaign data and Amazon product-level data (price, sales rank, reviews, and ratings), we employ a two-stage least squares (2SLS) framework to assess how influencer exposure alters the observed price-demand relationship. Our findings indicate that products featured in influencer campaigns exhibit meaningfully lower observed price responsiveness in sales rank-based demand proxies compared to non-featured products. These results are consistent with the theoretical prediction that influencer-driven attention shifts reduce the slope of the effective demand curve, enabling sellers to maintain higher price positions with limited sales rank deterioration. We interpret these results as reduced-form evidence of altered competitive price pressure rather than structurally identified causal elasticity estimates, and we acknowledge the limitations of the identification strategy. The study contributes to platform pricing theory and influencer marketing research by providing empirical evidence that social influence processes can reshape pricing power in highly transparent electronic marketplaces.