Impacts of user-generated images in online reviews on customer engagement: A panel data analysis

Visual content has become an integral component of customers' experience sharing, with customers increasingly searching for visual content in online reviews prior to making purchases. This study examines the effects of customer-generated images in online reviews on subsequent customer engagement using a multimethod design combining computer vision technique and panel data analysis. Based on online review data for 300 restaurants, findings revealed the following: 1) the ratio of pictorial reviews positively influenced subsequent review volume and average review length, whereas the effect on subsequent review valence was not significant; 2) review text-photo sentiment disparity had a complex impact on customer engagement (i.e., an inverse U-shaped relationship with subsequent review volume and a positive and negative linear relationship with subsequent average review length and review valence, respectively); and 3) business price level could mitigate the above effects. This study contributes to the literature on electronic word of mouth and customer engagement.

Automated summary

This study examines the effects of customer-generated images in online reviews on subsequent customer engagement, using computer vision technique and panel data analysis. Findings reveal that the ratio of pictorial reviews positively influences review volume and average review length, while the disparity between review text and photo sentiment has a complex impact on customer engagement. Business price level can mitigate these effects.