Factors Influencing User’s Adoption of Conversational Recommender System Based on Product Functional Requirements

Abstract: Conversational recommender system (CRS) helps customers get products fitted their needs by repeated interaction mechanisms. When customers want to buy products having many and high techfeatures (e.g., cars, smartphones, notebook, etc.), most users are not familiar with product technicalfeatures. The more natural way to elicit customers’ needs is by asking what they really want to use with the product they want (we call as product functional requirements). In this paper, we analyze four factors, e.g., perceived usefulness, perceived ease of use, trust and perceived enjoyment associated to user’s intention to adopt the interaction model (in CRS) based on product functional requirements. Result of experiment using technology acceptance model (TAM) indicates that, for users who aren’t familiar with technical features, perceives usefulness is a main factor influencing users’ adoption. Meanwhile, perceived enjoyment plays a role on user’s intention to adopt this interaction model, for users who are familiar with technical features of product.
Keywords: conversational recommender system, technology acceptance model, online shoping, ecommerce
Author: Z.K. Abdurahman Baizal
Journal Code: jptkomputergg160042

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