Dynamic Analysis of the Second-hand Luxury Goods Market in an E-commerce Context: A Network Motif and Time-series Perspective

Abstract

This study introduces a groundbreaking Motif and Time-Based Analysis Model to unravel the intricate dynamics within the e-commerce second-hand luxury goods market. By meticulously analyzing transactional data through the lens of network motifs and temporal patterns, our model unveils distinct consumer behaviors and market trends that traditional analyses often overlook. We focus on the evolving e-commerce model's impact on luxury goods transactions, highlighting the pivotal role of Return on Investment as an essential metric for assessing market efficacy. Utilizing e-commerce data collected in collaboration with leading companies, we identify statistically significant network motifs that reflect complex interaction patterns between consumers and goods. Our novel algorithm efficiently mines these motifs despite multiple constraints, offering new insights into transactional networks. Through rigorous statistical validation, our findings demonstrate the model's effectiveness in capturing the market's multifaceted nature. The study not only contributes to our understanding of the second-hand luxury goods market's dynamics but also provides actionable strategies for businesses aiming to enhance consumer experiences and market trend forecasting.