Dissecting the Second-hand Luxury Market Dynamics: Insights from E-commerce versus Brick-and-Mortar

• Item type: Journal(1)
• 公開日: 2025-03-15
• タイトル / 言語: ja
• タイトル: Dissecting the Second-hand Luxury Market Dynamics: Insights from E-commerce versus Brick-and-Mortar
• タイトル / 言語: en
• タイトル: Dissecting the Second-hand Luxury Market Dynamics: Insights from E-commerce versus Brick-and-Mortar
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集:若手研究者] second-hand luxury market, e-commerce, brick-and-mortar, Return on Investment, network analysis
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Graduate School of Creative Science and Engineering, Waseda University
• 著者所属: Graduate School of Information, Production, and Systems, Waseda University
• 著者所属: Graduate School of Creative Science and Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Graduate School of Creative Science and Engineering, Waseda University
• 著者所属(英): en
• 著者所属(英): Graduate School of Information, Production, and Systems, Waseda University
• 著者所属(英): en
• 著者所属(英): Graduate School of Creative Science and Engineering, Waseda University
• 著者名: Tengfei,Shao; Yuya,Ieiri; Shingo,Takahashi
• 著者名(英): Tengfei Shao; Yuya Ieiri; Shingo Takahashi
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: 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.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.33(2025) (online); DOI http://dx.doi.org/10.2197/ipsjjip.33.219; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: 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.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.33(2025) (online); DOI http://dx.doi.org/10.2197/ipsjjip.33.219; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 66, 号 3, 発行日 2025-03-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764
• 公開者 / 言語: ja
• 公開者 / 出版者: 情報処理学会