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中国管理科学 ›› 2018, Vol. 26 ›› Issue (4): 108-119.doi: 10.16381/j.cnki.issn1003-207x.2018.04.013

• 论文 • 上一篇    下一篇

基于轨迹和波动的新生网商成长模式及特征研究

何玉梅1,2, 郭迅华1,2, 陈国青1,2   

  1. 1. 清华大学经济管理学院, 北京 100084;
    2. 清华大学现代管理研究中心, 北京 100084
  • 收稿日期:2017-01-23 修回日期:2017-07-14 出版日期:2018-04-20 发布日期:2018-06-22
  • 通讯作者: 郭迅华(1976-),男(回族),福建人,清华大学经济管理学院,副教授,研究方向:信息系统与电子商务,E-mail:guoxh@sem.tsinghua.edu.cn E-mail:guoxh@sem.tsinghua.edu.cn
  • 基金资助:

    国家自然科学基金资助项目(71490721,71572092,71110107027);教育部人文社会科学重点研究基地基金项目(12JJD630001)

Research on the Growth Patterns and Characteristics of Start-up Online Sellers Based on Trajectory and Volatility Analyses

HE Yu-mei1,2, GUO Xun-hua1,2, CHEN Guo-qing1,2   

  1. 1. School of Economics and Management, Tsinghua University, Beijing 100084, China;
    2. ResearchCenterforContemporaryManagement, TsinghuaUniversity, Beijing 100084, China
  • Received:2017-01-23 Revised:2017-07-14 Online:2018-04-20 Published:2018-06-22

摘要: 新生网商是网络零售市场的重要经济主体,研究其成长模式及特征有助于揭示电子商务环境下新生企业成长的内在机制。本文依据Penrose企业成长理论及新生网商成长特点的相关研究,提出以成长轨迹(具有路径依赖特征)和成长波动的二维框架对成长模式进行识别,并针对新生网商成长不连续特征提出相对扩张指标来描述其时序轨迹。对电子商务平台上5582家新生网商的相对扩张轨迹进行时序k-means聚类发现,新生网商存在三类典型成长轨迹(加速/匀速/减速),同时对成长波动划分高/低水平,从而在二维矩阵框架下得到六类成长模式的网商。分析表明网商成长模式与其所经营的产品类型、初始主营类目、从属主营类目和类目转换次数具有统计显著的相关性,其中初始主营类目对成长模式的影响最大;"珠宝手表"类目中减速/低波动模式的新生网商占比远高于其他类目,"服装"类目中匀速/高波动模式的新生网商占比高于其他类目。同时,不同成长模式的网商在销售绩效及信誉等级指标上存在统计显著差异,其中,加速/高波动的新生网商与其他类别网商之间的销售绩效差异最大,加速/低波动的网商与其他成长模式网商的信誉等级差异最大。本文为电子商务平台评价新生网商成长过程和提供个性化服务提供了理论基础。

关键词: 新生网商, 成长模式, 成长轨迹, 成长波动, 产品类目, 网商绩效

Abstract: Online start-ups are the engines of growth, innovation, and wealth creation on electronic marketplaces. Although it is expected that the growth patterns of online start-up swill be different from their offline counterparts, the extant research has not paid sufficient attention to this unique group of firms. In this paper, the typical growth patterns and characteristics of start-up online sellers are explored.Drawing upon Penrose's growth theory, it is theorized that start-up online sellers' growth pattern can be conceptualized by the growth trajectory and the growth volatility. Moreover, their choice of product categories will also shape their growth patterns, leading to diverse performance.Based on a longitudinal clustering analysis, three types of growth trajectories are identified, namely "accelerating", "constant", and "decelerating". Consolidating with the volatility levels(high/low), typology of six types of growth patterns is formulated. The Chi-square test shows that the growth patterns are significantly associated with both the sellers'product types (search/experience good), initial product categories, and their primary product categories. In addition, the ANOVA and Kruskal-Walls analyses show that seller performance (sales and rating levels) significantly differs between growth patterns. The "accelerating/high volatility" sellers' performance is the most prominent distinctive one.Our findings contribute to firm growth pattern research by exploring the context of online start-ups. Moreover, our work provides implications for e-commerce platforms to evaluate the start-up online sellers and supportspecialized service according to their growth patternp/>

Key words: online start-ups, growth patterns, growth trajectory, growth volatility, product category, seller performance

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