Evaluating the impact of online influencers on retail property rent : a case study in New York City

Abstract

This study proposes a framework of analyzing online influencer behavior and evaluating its impact on retail rent using spatial econometric methods, in which we also examined the spatial autocorrelation and heterogeneity in New York's retail rent market. We use social media data mining and network analysis techniques to examine influencers and information diffusion in Instagram and develop metrics to quantify the impact. Using spatial econometric models, we construct models of retail rents that include the effect of online influencers and traditional hedonic features. The result suggests that online influencer behavior have a significant correlation with effective rents of retail real estate in the case study area of New York. We also examine the spatial spillover effect and spatial heterogeneity of the influencer effect. Our results provide the first analysis to link online behavior to retail real estate, it also proposes a framework to study the real estate by linking online and offline world, which is meaningful for retail real estate challenged by e-commerce and other forms of new economy.