TY - JOUR
T1 - Dissecting the Second-hand Luxury Market Dynamics
T2 - Insights from E-commerce versus Brick-and-Mortar
AU - Shao, Tengfei
AU - Ieiri, Yuya
AU - Takahashi, Shingo
N1 - Publisher Copyright:
© 2025 Information Processing Society of Japan.
PY - 2025
Y1 - 2025
N2 - This study introduces and validates the Network Motifs and Multiple Attributes (NMMA) model, an analytical approach designed to explore and analyze multi-attribute network motifs in the context of secondary luxury products markets by systematically constructing transaction topologies and analyzing interactions through various attributes such as profit, cost, Return on Investment (ROI), transaction frequency, brand, and item type. The model leverages real-world data collected in collaboration with a commercial partner encompassing both e-commerce (EC) and brick-and-mortar transactions. Statistical methods were employed to analyze the validation results, highlighting distinct performance and strategic implications of various trading types in EC versus traditional retail settings Findings suggest a generally higher ROI in EC, attributed to online sales’ efficiency and lower operational costs. The study also examines how brand and item types influence consumer purchasing behavior and market trends through network motifs. Applying the NMMA model enhances understanding of market dynamics and supports optimizing business strategies, particularly in improving transaction efficiency and market share.
AB - This study introduces and validates the Network Motifs and Multiple Attributes (NMMA) model, an analytical approach designed to explore and analyze multi-attribute network motifs in the context of secondary luxury products markets by systematically constructing transaction topologies and analyzing interactions through various attributes such as profit, cost, Return on Investment (ROI), transaction frequency, brand, and item type. The model leverages real-world data collected in collaboration with a commercial partner encompassing both e-commerce (EC) and brick-and-mortar transactions. Statistical methods were employed to analyze the validation results, highlighting distinct performance and strategic implications of various trading types in EC versus traditional retail settings Findings suggest a generally higher ROI in EC, attributed to online sales’ efficiency and lower operational costs. The study also examines how brand and item types influence consumer purchasing behavior and market trends through network motifs. Applying the NMMA model enhances understanding of market dynamics and supports optimizing business strategies, particularly in improving transaction efficiency and market share.
KW - Return on Investment
KW - brick-and-mortar
KW - e-commerce
KW - network analysis
KW - second-hand luxury market
UR - https://www.scopus.com/pages/publications/105000616467
UR - https://www.scopus.com/inward/citedby.url?scp=105000616467&partnerID=8YFLogxK
U2 - 10.2197/ipsjjip.33.219
DO - 10.2197/ipsjjip.33.219
M3 - Article
AN - SCOPUS:105000616467
SN - 0387-5806
VL - 33
SP - 219
EP - 230
JO - Journal of information processing
JF - Journal of information processing
ER -