管理评论

›› 2019, Vol. 31 ›› Issue (10): 133-141.

• 电子商务与信息管理 • 上一篇    下一篇

基于社交团购的电商平台引导拼团策略研究

张阳1, 徐兵1,2   

  1. 1. 南昌大学管理学院, 南昌 330031;
    2. 南昌大学中国中部经济社会发展研究中心, 南昌 330031
  • 收稿日期:2018-11-12 出版日期:2019-10-28 发布日期:2019-11-05
  • 通讯作者: 徐兵(通讯作者),南昌大学管理学院教授,博士生导师,博士
  • 作者简介:张阳,南昌大学管理学院博士研究生,讲师。
  • 基金资助:

    国家自然科学基金项目（71561018）；2017年度教育部人文社会科学重点研究基地重大项目（17JJD790012）；江西省高校人文社会科学重点研究基地项目（JD1501）。

Study of Group-buying-induced Strategies for E-commerce Platform Based on Social Group-buying

Zhang Yang1, Xu Bing1,2   

  1. 1. School of Management, Nanchang University, Nanchang 330031;
    2. Central China Economic and Social Development Research Center, Nanchang University, Nanchang 330031
  • Received:2018-11-12 Online:2019-10-28 Published:2019-11-05

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摘要：

电商中广泛存在社交团购与平台引导消费者拼团的现象。针对由单个社交团购平台和单个电商企业组成的供应链，考虑社交成本和流量溢出效应的影响，分别建立了平台不采取引导拼团下电商企业的决策模型，平台引导拼团下平台和企业的Stackelberg博弈模型，利用KT方法得到电商企业的最优团购定价策略和平台引导拼团的实施条件及激励策略。研究表明：仅当消费者社交难度较小及平台抽成和流量溢出较高时，平台才应采取引导拼团策略；平台引导拼团的力度（引导金额）应随流量溢出和价格弹性增大而增大，随社交难度增大而减小；平台实施引导拼团下，电商企业定价、参团人数均比无引导拼团时更高。最后，运用导函数方法和数值仿真技术，验证了结论的有效性，并对主要参数进行了敏感度分析。平台实施引导拼团，可实现平台和电商企业的双赢，此时电商企业应给予平台更高抽成等方式积极配合平台运作。

关键词: 社交团购, 流量溢出效应, 引导拼团, 决策模型, KT条件

Abstract:

There is a widespread phenomenon of social group-buying and platform inducing consumers to join groups in e-commerce. Considering the influence of social cost and flow spillover effect in the supply chain consisting of a single social group-buying platform and a single e-commerce enterprise, we establish the decision model of e-commerce enterprises when platform doesn't induce group-buying and the Stackelberg game model between platform and enterprise when platform induces group-buying respectively. Then, we use KT method to obtain the optimal group-buying pricing strategy of the e-commerce enterprise, the implementation conditions and incentive strategies of the platform guiding group-buying. The results show that the platform should adopt the strategy of inducing group-buying only when the social acceptability of consumers, the push money and flow spillover effect of platform are high; the strength of inducing such as the amount of inducing money, should increase with the increase of flow spillover and price elasticity, and decrease with the increase of social acceptability difficulty; the sale price determined by e-commerce companies and the number of customers participating in groupbuying are higher when platform induces group-buying than those when platform doesn't induce group-buying. Finally, the validity of the conclusions is verified by using the derivative method and numerical simulation, and the sensitivity analysis of the key parameters is carried out. The platform inducing group-buying can realize a win-win situation for both the platform and the e-commerce enterprise. So, the e-commerce enterprise should actively cooperate with the platform by giving the platform a higher push money and so on.

Key words: social group-buying, flow spillover effect, group-buying-induced, decisions model, KT method