Artificial intelligent housekeeper based on consumer purchase decision: a case study of online E-commerce
电子商务
业务
广告
计算机科学
万维网
作者
Yan Guo,Qichao Tang,Haoran Wang,Mengjing Jia,Yan Guo
出处
期刊:Industrial Management and Data Systems [Emerald (MCB UP)] 日期:2024-06-18
标识
DOI:10.1108/imds-12-2023-0905
摘要
Purpose The rise of artificial intelligence (AI) and machine learning has largely promoted the emergence of “autonomous decision-making” (ADM). This paper aims to establish a personalized artificial intelligent housekeeper (AIH) that knows more about our hobbies, habits, personality traits, and shopping needs than ourselves and can replace us to do some habitual purchasing behavior. Design/methodology/approach We propose an AI decision-making method based on machine learning algorithm, a novel framework for personalized customer preference and purchase. First, the method uses interactive big data to predict a potential consumer’s decision possibility. Then, the method mines the correlation between consumer decision possibility and various factors affecting consumer behavior. Finally, the machine learning algorithm is used to estimate the consumer’s purchase decision according to the comprehensive influencing factors data of the target consumer. Findings The experimental results show that the method can predict the regular consumption behavior of consumers in advance and make accurate decision-making behavior. It can find correlations from a large amount of data to help predict many simple purchase decisions in our life, and become our AIH. Originality/value This study introduces a new approach that not only has the auxiliary decision-making function but also has the decision-making function. These findings contribute to the research on automated decision-making process of AI and on human–technology interaction by investigating how data attributes consumer purchase decision to AI.