The Influence of Machine Learning Chatbots on Consumer Purchase Intention in the Fashion Industry

This study explores the role of machine learning chatbots in influencing consumer purchase intentions within the fashion industry.The aim of this study is to identify the factors that influence consumer purchase intentions, analyze their relationships, and pinpoint the chatbot attributes that have the greatest impact.A quantitative approach was employed, involving a survey of 384 participants with prior experience using chatbots on fashion e-commerce platforms.The structured questionnaire assessed variables such as perceived usefulness (PU), ease of use (PEU), system quality (SQ) and information quality (IQ), with consumer purchase intention as the dependent variable.Data were analyzed using descriptive statistics, regression analysis, and correlation studies to determine the relationships between variables.The results reveal that system quality (SQ) significantly influences purchase intention, followed by perceived ease of use (PEU), information quality (IQ) and perceived usefulness (PU).High-quality chatbot systems foster trust and enhance user experiences, contributing to increased engagement and conversion rates.The study concludes that optimizing chatbot attributes can significantly improve consumer decision-making and satisfaction in ecommerce.These findings offer actionable insights for fashion businesses seeking to leverage AI technologies to enhance customer interactions and drive sales.Future research could explore integrating advanced features such as augmented reality to further enhance chatbot effectiveness.