Increasingly, search filters have become a constitutive feature of the digital retail experience for navigating ‘endless aisles’, while fundamentally shaping shoppers' product evaluation. Yet, the credibility of filters in curating a desired product assortment remains unexamined. Importantly, the existing retail scholarship lacks a theoretical understanding of how shoppers assess the diagnostic value of filters and their downstream consequences, especially when there is an inconsistency between the applied filters and the retrieved products. Drawing on rich theoretical underpinnings from cue-diagnosticity, we argue that inconsistent high-scope (i.e., Product attributes) and low-scope (i.e., Filters) cues can affect filter-diagnostic value, which, in turn, can influence purchase-decision. Using a multimethod approach involving five studies, including retail audits, experimental design, and a large archival dataset, we found that filter-product inconsistency can result in severe penalties for platforms and products. When the filter is inconsistent with product attributes, shoppers severely alleviate the filter-diagnosticity, purchase intention, and product ratings. Additionally, perceived consistency mediates the product-filter interaction effect on outcome variables. This study extends the existing theoretical discourse on cue-diagnosticity by examining how the temporal structure of cues shapes behavioral outcomes, a largely underexplored phenomenon. This study possesses implications for online retailers, sellers, and policymakers.
Sharma et al. (Thu,) studied this question.