The Impact of Demographic Factors on Persuasion Strategies in Personalized Recommender System

Abstract

A recommender system is an information filtering tool that copes with the growing volume of information and helps the user to make faster decisions by providing products and services matched with their needs and interests. However, a large number of users are not satisfied with the provided recommendations and do not accept them. Based on the Elaboration Likelihood Model (ELM), If supplementary information about recommendations is provided, those users having the low motivation and capability to analyze the usefulness of the recommended item can be persuaded to accept it. This paper focuses on analyzing the impact of demographic factors on increasing the acceptance of recommendations. This study was conducted by a web-based online survey. The movie's recommender system has been developed along with the explanations based on Cialdini's persuasion strategies as the peripheral cues. The collected data are analyzed through statistical techniques using the SPSS software. The results show that the persuasiveness degree of the persuasion strategies differs related to individuals with the different demographic factors.