Analysis on the Impact of Recommender Systems on Consumer Decision Making on China's Online Shopping Platforms

With the popularization of online shopping platforms across China and in order to maximize profits, online shopping platforms developed various recommender systems (RS), which played an important role in consumers' decision-making process. Therefore, the impact of RS on consumers' decision-making process is worthy of studying. In this paper, the RS of online shopping platforms and two examples of them were introduced. This paper firstly analyzed the ethical challenges related to the RS, including algorithmic opacity, privacy concerns, and bias and behavior manipulation and provided solutions accordingly. Besides, the paper through a method of online questionnaire and data analysis, illustrated RS' ability to influence consumers' decision making by providing them with personalized recommendations during online shopping. In addition, with the help of an online questionnaire filled out by more than 128 Chinese consumers across different ages and occupations, the author also analyzed people's attitudes towards the RS. According to the research results, this overall finding implies that recommender systems in contemporary electronic commerce are not merely decision aids for lowering search costs, but may also play a substantial part in economic decision making. A randomised trial strategy was used in this work to support the idea that internet recommendations may influence willingness-to-pay judgements, even when the two are tested on distinct scales.