Dissecting the Second-hand Luxury Market Dynamics: Insights from E-commerce versus Brick-and-Mortar
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 i...
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| Published in | Journal of Information Processing Vol. 33; pp. 219 - 230 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Information Processing Society of Japan
2025
一般社団法人 情報処理学会 |
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| Online Access | Get full text |
| ISSN | 1882-6652 1882-6652 |
| DOI | 10.2197/ipsjjip.33.219 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Ieiri, Yuya Takahashi, Shingo Shao, Tengfei |
| Author_xml | – sequence: 1 fullname: Shao, Tengfei organization: Graduate School of Creative Science and Engineering, Waseda University – sequence: 1 fullname: Takahashi, Shingo organization: Graduate School of Creative Science and Engineering, Waseda University – sequence: 1 fullname: Ieiri, Yuya organization: Graduate School of Information, Production, and Systems, Waseda University |
| BackLink | https://cir.nii.ac.jp/crid/1390866492597148416$$DView record in CiNii |
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| Cites_doi | 10.3390/su141811730 10.1587/transinf.2020EDP7258 10.1016/j.telpol.2019.101828 10.1108/IJRDM-07-2014-0087 10.1111/ijcs.12539 10.1108/09590551211274946 10.1108/JABS-08-2015-0118 10.1038/s41467-022-32913-w 10.1108/IMR-04-2021-0154 10.1145/3587828.3587873 10.1016/j.jbusres.2020.05.059 10.1108/SJME-06-2021-0105 10.1145/1281192.1281280 10.1007/978-3-031-04829-6_39 10.1002/jsc.2502 10.1016/j.gltp.2022.04.020 10.5539/ijbm.v14n8p41 10.1126/science.298.5594.824 10.1088/1742-5468/2008/10/P10008 10.2752/175174108X346931 10.1108/IJPPM-02-2021-0079 10.4018/978-1-5225-2697-1 10.1145/3433652 10.1017/9781108774116 10.1002/bse.2630 10.1103/PhysRevE.69.026113 10.1103/PhysRevE.69.066133 10.1186/1471-2288-14-135 10.1137/20M1361602 10.1038/35065725 10.1108/IJRDM-07-2014-0097 10.1126/science.1184819 10.3390/jtaer16070164 10.1007/978-981-97-3076-6_1 10.2197/ipsjjip.32.308 10.4135/9781446294413.n2 |
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| References | [8] Phillips, P.P.: Return on Investment (ROI) Basics, Association for Talent Development (2023). [15] Shao, T., Teraoka, F., Ishizaki, K. and Hishiyama, R.: Discovering Multiple Clusters of Second-Hand Luxury Goods for Profit Improvement Using Network Motif, Proc. World Conference on Information Systems and Technologies (WorldCIST '22), Vol.470, pp.438-448, Springer (2022). [24] Newman, M.E.: Fast algorithm for detecting community structure in networks, Physical Review E, Vol.69, No.6, pp.066133.1-066133.5 (2004). [2] Cervellon, M.-C., Carey, L. and Harms, T.: Something old, something used: Determinants of women's purchase of vintage fashion vs second-hand fashion, International Journal of Retail and Distribution Management, Vol.40, No.12, pp.956-974 (2012). [29] Maharana, K., Mondal, S. and Nemade, B.: A review: Data pre-processing and data augmentation techniques, Global Transitions Proceedings, Vol.3, No.1, pp.91-99 (2022). [14] Beard, N.D.: The branding of ethical fashion and the consumer: A luxury niche or mass-market reality?, Fashion Theory, Vol.12, No.4, pp.447-467 (2008). [13] Ozuem, W. and Azemi, Y. (Eds.): Digital marketing strategies for fashion and luxury brands, IGI Global (2017). [12] Aiolfi, S. and Sabbadin, E.: Fashion and new luxury digital disruption: The new challenges of fashion between omnichannel and traditional retailing, International Journal of Business and Management, Vol.14, No.8, pp.41-51 (2019). [22] Shao, T., Ieiri, Y. and Hishiyama, R.: Multiple Clusters Discovery Utilizing Network Motifs for Community Improvement: Insights from Tourism and Goods' Transactions, Journal of Information Processing, Vol.32, pp.308-318 (2024). [21] Schwarze, A.C. and Porter, M.A.: Motifs for processes on networks, SIAM Journal on Applied Dynamical Systems, Vol.20, No.4, pp.2516-2557 (2021). [27] Strogatz, S.H.: Exploring complex networks, Nature, Vol.410, No.6825, pp.268-276 (2001). [6] Shao, T. et al.: An Analysis of Opinions on AI Ethics Based on Network Motifs using the Case Method, Proc. 2023 12th International Conference on Software and Computer Applications, pp.302-308 (2023). [16] Kapferer, J.-N. and Tabatoni, O.: Are luxury brands really a financial dream, Journal of Strategic Management Education, Vol.7, No.4, pp.1-16 (2011). [18] Joy, A. et al.: Digital future of luxury brands: Metaverse, digital fashion, and non-fungible tokens, Strategic Change, Vol.31, No.3, pp.337-343 (2022). [31] Wan, X. et al.: Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range, BMC Medical Research Methodology, Vol.14, pp.1-13 (2014). [20] Newman, M.E. and Girvan, M.: Finding and evaluating community structure in networks, Physical Review E, Vol.69, No.2, Article 026113 (2004). [34] Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D. and Alon, U.: Network motifs: Simple building blocks of complex networks, Science, Vol.298, No.5594, pp.824-827 (2002). [10] Veloutsou, C., Christodoulides, G. and Guzmán, F.: Charting research on international luxury marketing: Where are we now and where should we go next?, International Marketing Review, Vol.39, No.2, pp.371-394 (2022). [25] Mucha, P.J. et al.: Community structure in time-dependent, multiscale, and multiplex networks, Science, Vol.328, No.5980, pp.876-878 (2010). [33] Lambiotte, R. and Schaub, M.T.: Modularity and Dynamics on Complex Networks, Cambridge University Press (2021). [35] Ribeiro, P. et al.: A survey on subgraph counting: Concepts, algorithms, and applications to network motifs and graphlets, ACM Computing Surveys (CSUR), Vol.54, No.2, pp.1-36 (2021). [23] Shao, T., Ieiri, Y. and Takahashi, S.: Time Series Network Analysis for Profit Dynamics in Pre-owned Luxury Goods Market Based on Network Motifs, JSAI-isAI 2024 Workshops, JURISIN, SCIDOCA, AI-BIZ, BIAS, Springer Nature (2024). [36] Scaillet, O., Treccani, A. and Trevisan, C.: High-frequency jump analysis of the bitcoin market, Journal of Financial Econometrics, Vol.18, No.2, pp.209-232 (2020). [32] Blondel, V.D., Guillaume, J.L., Lambiotte, R. and Lefebvre, E.: Fast unfolding of communities in large networks, Journal of Statistical Mechanics: Theory and Experiment, Vol.2008, No.10, Article P10008 (2008). [5] Bao, X. et al.: Impact of basic network motifs on the collective response to perturbations, Nature Communications, Vol.13, No.1, p.5301 (2022). [1] Hennigs, N. et al.: The complexity of value in the luxury industry: From consumers' individual value perception to luxury consumption, International Journal of Retail and Distribution Management, Vol.43, No.10/11, pp.922-939 (2015). [39] Kluge, P.N. and Fassnacht, M.: Selling luxury goods online: Effects of online accessibility and price display, International Journal of Retail & Distribution Management, Vol.43, No.10/11, pp.1065-1082 (2015). [9] Sheth, J.: Impact of Covid-19 on consumer behavior: Will the old habits return or die?, Journal of Business Research, Vol.117, pp.280-283 (2020). [7] Shao, T., Ieiri, Y. and Hishiyama, R.: Discovering Multiple Clusters of Sightseeing Spots to Improve Tourist Satisfaction Using Network Motifs, IEICE Trans. Information and Systems, Vol.104, No.10, pp.1640-1650 (2021). [38] Aleem, A., Loureiro, S.M.C. and Bilro, R.G.: Luxury fashion consumption: A review, synthesis and research agenda, Spanish Journal of Marketing-ESIC, ahead-of-print (2022). [41] Bouwman, H. et al.: Digitalization, business models, and SMEs: How do business model innovation practices improve performance of digitalizing SMEs?, Telecommunications Policy, Vol.43, No.9, Article 101828 (2019). [19] Kashav, S. et al.: Managing sustainability in luxury industry to pursue circular economy strategies, Business Strategy and the Environment, Vol.30, No.1, pp.432-462 (2021). [26] Xu, X. et al.: Scan: A structural clustering algorithm for networks, Proc. 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2007). [4] Bindi, B. et al.: Supply chain strategy in the luxury fashion industry: Impacts on performance indicators, International Journal of Productivity and Performance Management, Vol.72, No.5, pp.1338-1367 (2023). [17] Marin, A. and Wellman, B.: Social network analysis: An introduction, The SAGE Handbook of Social Network Analysis, pp.11-25 (2011). [3] Jain, S., Khan, M.N. and Mishra, S.: Understanding consumer behavior regarding luxury fashion goods in India based on the theory of planned behavior, Journal of Asia Business Studies, Vol.11, No.1, pp.4-21 (2017). [30] Rosário, A. and Raimundo, R.: Consumer marketing strategy and E-commerce in the last decade: A literature review, Journal of Theoretical and Applied Electronic Commerce Research, Vol.16, No.7, pp.3003-3024 (2021). [37] Bain & Company: Luxury Report 2021: From Surging Recovery to Elegant Advance — the Evolving Future of Luxury, available from <https://www.bain.com> (accessed 2024-04-22). [40] Lou, X. et al.: How do perceived value and risk affect purchase intention toward second-hand luxury goods? An empirical study of US consumers, Sustainability, Vol.14, No.18, p.11730 (2022). [28] Aronoff, M. and Fudeman, K.: What is Morphology?, John Wiley & Sons (2022). [11] Turunen, L. and Pöyry, E.: Shopping with the resale value in mind: A study on second-hand luxury consumers, International Journal of Consumer Studies, Vol.43, No.6, pp.549-556 (2019). 22 23 24 25 26 27 28 29 30 31 10 32 11 33 12 34 13 35 14 36 15 37 16 38 17 39 18 19 1 2 3 4 5 6 7 8 9 40 41 20 21 |
| References_xml | – reference: [32] Blondel, V.D., Guillaume, J.L., Lambiotte, R. and Lefebvre, E.: Fast unfolding of communities in large networks, Journal of Statistical Mechanics: Theory and Experiment, Vol.2008, No.10, Article P10008 (2008). – reference: [24] Newman, M.E.: Fast algorithm for detecting community structure in networks, Physical Review E, Vol.69, No.6, pp.066133.1-066133.5 (2004). – reference: [13] Ozuem, W. and Azemi, Y. (Eds.): Digital marketing strategies for fashion and luxury brands, IGI Global (2017). – reference: [22] Shao, T., Ieiri, Y. and Hishiyama, R.: Multiple Clusters Discovery Utilizing Network Motifs for Community Improvement: Insights from Tourism and Goods' Transactions, Journal of Information Processing, Vol.32, pp.308-318 (2024). – reference: [14] Beard, N.D.: The branding of ethical fashion and the consumer: A luxury niche or mass-market reality?, Fashion Theory, Vol.12, No.4, pp.447-467 (2008). – reference: [35] Ribeiro, P. et al.: A survey on subgraph counting: Concepts, algorithms, and applications to network motifs and graphlets, ACM Computing Surveys (CSUR), Vol.54, No.2, pp.1-36 (2021). – reference: [27] Strogatz, S.H.: Exploring complex networks, Nature, Vol.410, No.6825, pp.268-276 (2001). – reference: [10] Veloutsou, C., Christodoulides, G. and Guzmán, F.: Charting research on international luxury marketing: Where are we now and where should we go next?, International Marketing Review, Vol.39, No.2, pp.371-394 (2022). – reference: [38] Aleem, A., Loureiro, S.M.C. and Bilro, R.G.: Luxury fashion consumption: A review, synthesis and research agenda, Spanish Journal of Marketing-ESIC, ahead-of-print (2022). – reference: [17] Marin, A. and Wellman, B.: Social network analysis: An introduction, The SAGE Handbook of Social Network Analysis, pp.11-25 (2011). – reference: [33] Lambiotte, R. and Schaub, M.T.: Modularity and Dynamics on Complex Networks, Cambridge University Press (2021). – reference: [8] Phillips, P.P.: Return on Investment (ROI) Basics, Association for Talent Development (2023). – reference: [9] Sheth, J.: Impact of Covid-19 on consumer behavior: Will the old habits return or die?, Journal of Business Research, Vol.117, pp.280-283 (2020). – reference: [23] Shao, T., Ieiri, Y. and Takahashi, S.: Time Series Network Analysis for Profit Dynamics in Pre-owned Luxury Goods Market Based on Network Motifs, JSAI-isAI 2024 Workshops, JURISIN, SCIDOCA, AI-BIZ, BIAS, Springer Nature (2024). – reference: [4] Bindi, B. et al.: Supply chain strategy in the luxury fashion industry: Impacts on performance indicators, International Journal of Productivity and Performance Management, Vol.72, No.5, pp.1338-1367 (2023). – reference: [36] Scaillet, O., Treccani, A. and Trevisan, C.: High-frequency jump analysis of the bitcoin market, Journal of Financial Econometrics, Vol.18, No.2, pp.209-232 (2020). – reference: [40] Lou, X. et al.: How do perceived value and risk affect purchase intention toward second-hand luxury goods? An empirical study of US consumers, Sustainability, Vol.14, No.18, p.11730 (2022). – reference: [1] Hennigs, N. et al.: The complexity of value in the luxury industry: From consumers' individual value perception to luxury consumption, International Journal of Retail and Distribution Management, Vol.43, No.10/11, pp.922-939 (2015). – reference: [34] Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D. and Alon, U.: Network motifs: Simple building blocks of complex networks, Science, Vol.298, No.5594, pp.824-827 (2002). – reference: [28] Aronoff, M. and Fudeman, K.: What is Morphology?, John Wiley & Sons (2022). – reference: [21] Schwarze, A.C. and Porter, M.A.: Motifs for processes on networks, SIAM Journal on Applied Dynamical Systems, Vol.20, No.4, pp.2516-2557 (2021). – reference: [37] Bain & Company: Luxury Report 2021: From Surging Recovery to Elegant Advance — the Evolving Future of Luxury, available from <https://www.bain.com> (accessed 2024-04-22). – reference: [39] Kluge, P.N. and Fassnacht, M.: Selling luxury goods online: Effects of online accessibility and price display, International Journal of Retail & Distribution Management, Vol.43, No.10/11, pp.1065-1082 (2015). – reference: [20] Newman, M.E. and Girvan, M.: Finding and evaluating community structure in networks, Physical Review E, Vol.69, No.2, Article 026113 (2004). – reference: [3] Jain, S., Khan, M.N. and Mishra, S.: Understanding consumer behavior regarding luxury fashion goods in India based on the theory of planned behavior, Journal of Asia Business Studies, Vol.11, No.1, pp.4-21 (2017). – reference: [6] Shao, T. et al.: An Analysis of Opinions on AI Ethics Based on Network Motifs using the Case Method, Proc. 2023 12th International Conference on Software and Computer Applications, pp.302-308 (2023). – reference: [26] Xu, X. et al.: Scan: A structural clustering algorithm for networks, Proc. 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2007). – reference: [5] Bao, X. et al.: Impact of basic network motifs on the collective response to perturbations, Nature Communications, Vol.13, No.1, p.5301 (2022). – reference: [18] Joy, A. et al.: Digital future of luxury brands: Metaverse, digital fashion, and non-fungible tokens, Strategic Change, Vol.31, No.3, pp.337-343 (2022). – reference: [29] Maharana, K., Mondal, S. and Nemade, B.: A review: Data pre-processing and data augmentation techniques, Global Transitions Proceedings, Vol.3, No.1, pp.91-99 (2022). – reference: [25] Mucha, P.J. et al.: Community structure in time-dependent, multiscale, and multiplex networks, Science, Vol.328, No.5980, pp.876-878 (2010). – reference: [16] Kapferer, J.-N. and Tabatoni, O.: Are luxury brands really a financial dream, Journal of Strategic Management Education, Vol.7, No.4, pp.1-16 (2011). – reference: [2] Cervellon, M.-C., Carey, L. and Harms, T.: Something old, something used: Determinants of women's purchase of vintage fashion vs second-hand fashion, International Journal of Retail and Distribution Management, Vol.40, No.12, pp.956-974 (2012). – reference: [19] Kashav, S. et al.: Managing sustainability in luxury industry to pursue circular economy strategies, Business Strategy and the Environment, Vol.30, No.1, pp.432-462 (2021). – reference: [31] Wan, X. et al.: Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range, BMC Medical Research Methodology, Vol.14, pp.1-13 (2014). – reference: [12] Aiolfi, S. and Sabbadin, E.: Fashion and new luxury digital disruption: The new challenges of fashion between omnichannel and traditional retailing, International Journal of Business and Management, Vol.14, No.8, pp.41-51 (2019). – reference: [15] Shao, T., Teraoka, F., Ishizaki, K. and Hishiyama, R.: Discovering Multiple Clusters of Second-Hand Luxury Goods for Profit Improvement Using Network Motif, Proc. World Conference on Information Systems and Technologies (WorldCIST '22), Vol.470, pp.438-448, Springer (2022). – reference: [41] Bouwman, H. et al.: Digitalization, business models, and SMEs: How do business model innovation practices improve performance of digitalizing SMEs?, Telecommunications Policy, Vol.43, No.9, Article 101828 (2019). – reference: [11] Turunen, L. and Pöyry, E.: Shopping with the resale value in mind: A study on second-hand luxury consumers, International Journal of Consumer Studies, Vol.43, No.6, pp.549-556 (2019). – reference: [30] Rosário, A. and Raimundo, R.: Consumer marketing strategy and E-commerce in the last decade: A literature review, Journal of Theoretical and Applied Electronic Commerce Research, Vol.16, No.7, pp.3003-3024 (2021). – reference: [7] Shao, T., Ieiri, Y. and Hishiyama, R.: Discovering Multiple Clusters of Sightseeing Spots to Improve Tourist Satisfaction Using Network Motifs, IEICE Trans. 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| Title | Dissecting the Second-hand Luxury Market Dynamics: Insights from E-commerce versus Brick-and-Mortar |
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