AUTHOR=Liu Yu , Khan Muhammad Bashir , Ashraf Muhammad , Orangzab  , Sharif Wareesa , Ahmad Jamil 

TITLE=Customer’s decision and affective assessment of online product recommendation: A recommendation-product congruity proposition

JOURNAL=Frontiers in Psychology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.916520

DOI=10.3389/fpsyg.2022.916520

ISSN=1664-1078

ABSTRACT=Online Product Recommendation (OPR) systems gained prominence in the context of e-commerce over the past years. Despite the increased research on OPR use, less attention has been paid to examining how decision and affective assessment of the OPR are contingent upon the product type. This study proposes and examines a recommendation-product congruity proposition based on cognitive fit and schema congruity theories. The proposition states that when the content (i.e., a stimulus-based schema) of the OPR (either system-generated recommendation [SGR] or consumer generated recommendation [CGR]) matches the brain-stored schema initiated by a particular product (either search or experience product), then a consumer would use a schema-based information assessment strategy and experience favourable decision and affective assessment of the OPR. This then affects consumers’ intentions to purchase and reuse OPR. The proposition is tested via two × two between-respondents factorial design of a cross-sectional survey with 482 Amazon customers. The results support the two matching conditions of the proposition; (1) SGR describing a search product and (2) CGR describing an experience product, could lead consumers to perceive lower decision effort, greater decision quality and enjoyment with the OPR that subsequently have a significant impact on their intentions to purchase and reuse OPR. This study expands our understanding of how recommendation-product congruence influences the consumer's decision and affective assessment behaviour and provides practical implications to the identification and presentation of the recommendation type and product type for better customer’s decision.