广东工业大学 管理学院,广东,广州,510520
范梦婷(1994–),女,硕士研究生,主要研究方向为信息系统与商务智能
高鸿铭(1993–),男,博士研究生,主要研究方向为信息系统与商务智能. E-mail:hm.gao.normal@gmail.com
纸质出版:2019
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范梦婷, 刘洪伟, 高鸿铭, 何锐超. 电子商务平台下的竞争产品市场结构研究[J]. 广东工业大学学报, 2019, 36(6): 32-37.
Fan Meng-ting, Liu Hong-wei, Gao Hong-ming, et al. A Research on Competitive Product Market Structure of E-commerce Platform[J]. 2019, 36(6): 32-37.
范梦婷, 刘洪伟, 高鸿铭, 何锐超. 电子商务平台下的竞争产品市场结构研究[J]. 广东工业大学学报, 2019, 36(6): 32-37. DOI: 10.12052/gdutxb.190082.
Fan Meng-ting, Liu Hong-wei, Gao Hong-ming, et al. A Research on Competitive Product Market Structure of E-commerce Platform[J]. 2019, 36(6): 32-37. DOI: 10.12052/gdutxb.190082.
竞争产品市场结构的识别可以更好地分析主要竞争对手及产品竞争优势. 本文利用消费者浏览行为来研究消费者产品介入和产品销售之间的关系. 基于某电商网站的点击流数据
用多维尺度标记法(Multidimensional Scaling Technique
MDS)和K-mean聚类模型对产品市场结构进行建模. 结果表明
MDS处理的维度1直接揭示了产品销售与消费者对产品的介入程度呈正相关关系
体现了产品竞争优势的变化趋势. 这项研究将有助于通过消费者产品的介入行为了解产品市场结构
并帮助企业及时发现他们的产品定位及市场竞争优势
以调整产品供应链.
The purpose of identifying the competitive product market structure is to understand the competitors and the competitive edge of the products. Consumers’ browsing behavior is studied to discuss the relationship between consumer involvement and product sales. Resorting to the real clickstream data from an e-commerce website
the focal product market structure is modeled by multidimensional scaling technique (MDS) and K-mean clustering. It is found that dimension1 axis processed by MDS intuitively revealing product sales has a positive relation with the degree of consumer involving with product
that is
the competitive edge of the product. This study contributes to theoretically understanding product market structure through consumer involvement
and helps enterprises to detect their brand/product positioning and market competitive edge in time to adjust product supply plan.
DESARBO W S, WIND G J. Who competes with whom? A demand-based perspective for identifying and representing asymmetric competition [J]. Strategic Management Journal, 2006, 27(2): 101-129.
RINGEL D M, SKIERA B. Visualizing asymmetric competition among more than 1 000 products using big search data [J]. Marketing Science, 2016, 35(3): 511-534.
ERDEM, TULIN. A dynamic analysis of market structure based on panel data [J]. Marketing Science, 1996, 15(4): 359-378.
KIM J B, ALBUQUERQUE P, BRONNENBERG B J. Mapping online consumer search [J]. Journal of Marketing Research, 2011, 48(1): 13-27.
NETZER O, FELDMAN R, GOLDENBERG J, et al . Mine your own business: market-structure surveillance through text mining [J ] . Marketing Science, 2012, 31(3): 521-543.
LIU H W,LIANG Z Y,ZUO M H, et al . Research on identifying brand competition relationshipswith consumer browsing behavior [J ] . Journal of Guangdong University of Technology, 2019, 36(5): 1-6.
LIU Z H, LIU H W, ZHAN M J, et al . Privacy-preserving algorithm research on horizontally partitioned data of collaborative optimization decisions [J ] . Journal of Guangdong University of Technology, 2016, 33(5): 15-21.
GREWALDR. An alternative efficient representation of demand-based competitive asymmetry [J]. Strategic Management Journal, 2007, 28(7): 755-766.
LEE T Y, BRADLOW E T. Automated marketing research using online customer reviews [J]. Journal of Marketing Research, 2011, 48(5): 881-894.
NAM H, JOSHI Y V, KANNAN P K. Harvesting brand information from social tags [J]. Journal of Marketing, 2017, 81(4): 88-108.
LI B, LI X, LIU H. Consumer preferences, cannibalization, and competition: evidence from the personal computer industry [J]. MIS Quarterly: Management Information Systems, 2018, 42(1): 661-678.
ZAICHKOWSKY J L. Measuring the involvement construct [J]. Journal of Consumer Research, 1985, 12(3): 341-352.
LAURENT G, KAPFERER J N. Measuring consumer involvement profiles [J]. Journal of Marketing Research, 1985, 22(1): 41-53.
WULF K D, IACOBUCCI O S. Investments in consumer relationships: a cross-country and cross-industry exploration [J]. Journal of Marketing, 2001, 65(4): 33-50.
SANG H, XUE F, ZHAO J. What happens when satisfied customers need variety? Effects of purchase decision involvement and product category on chinese consumers' brand-switching behavior [J]. Journal of International Consumer Marketing, 2018, 30(3): 148-157.
BUCKLIN R E, SISMEIRO C. Click here for internet insight: advances in clickstream data analysis in marketing [J]. Journal of Interactive Marketing, 2009, 23(1): 35-48.
CORNELIUS B, WAGNER U, NATTER M. Managerial applicability of graphical formats to support positioning decisions [J]. Journal für Betriebswirtschaft, 2010, 60(3): 167-201.
LIU H W, SHI Y Q, LIANG Z Y, et al . Partial rotation perturbation for privacy-preserving clustering mining [J ] . Journal of Guangdong University of Technology, 2012, 29(3): 28-34.
KODINARIYA T M, MAKWANA P R. Review on determining number of cluster in k-means clustering [J]. International Journal, 2013, 1(6): 90-95.
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