When Reviews are No Information : The Moderating Role of Default Reviews in the Relationship Between Perceived Risk, Online Trust, and Purchase Intention and Enhancing Purchase Intention
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This study examines how default reviews—auto-generated five-star ratings posted when consumers do not leave feedback—moderate the link between perceived risk, online trust, and purchase intention in e-commerce. Grounded in the trust–risk framework, we conceptualize the default-review ratio as a contextual cue that shifts information processing. We ran MG-SEM on survey data (N = 400) from participants viewing simulated product pages with varying default-review prevalence. Results show that perceived risk significantly reduces online trust, which in turn positively influences purchase intention. Critically, the default-review ratio strengthens the risk → trust linkage and amplifies trust’s mediating role. To validate these findings, we analyze product-level data from Taobao; regressions show higher default-review ratios predict lower sales, especially in utilitarian categories (electronics, home appliances). Integrating perceptual modeling with behavioral data, we extend theories of digital trust and review credibility and offer implications for platform design, review governance, and category-specific trust strategies.
Abstract
This study examines how default reviews—auto-generated five-star ratings posted when consumers do not leave feedback—moderate the link between perceived risk, online trust, and purchase intention in e-commerce. Grounded in the trust–risk framework, we conceptualize the default-review ratio as a contextual cue that shifts information processing. We ran MG-SEM on survey data (N = 400) from participants viewing simulated product pages with varying default-review prevalence. Results show that perceived risk significantly reduces online trust, which in turn positively influences purchase intention. Critically, the default-review ratio strengthens the risk → trust linkage and amplifies trust’s mediating role. To validate these findings, we analyze product-level data from Taobao; regressions show higher default-review ratios predict lower sales, especially in utilitarian categories (electronics, home appliances). Integrating perceptual modeling with behavioral data, we extend theories of digital trust and review credibility and offer implications for platform design, review governance, and category-specific trust strategies.