工业工程 ›› 2021, Vol. 24 ›› Issue (3): 10-17.doi: 10.3969/j.issn.1007-7375.2021.03.002

• 专题论述 • 上一篇    下一篇

考虑最优定价与质量决策的平台销售模式选择研究

官振中, 黄丘杰, 张爱凤   

  1. 西南交通大学 经济管理学院,四川 成都 610031
  • 收稿日期:2020-02-28 发布日期:2021-06-26
  • 作者简介:官振中(1975-),男,四川省人,教授,博士,主要研究方向为供应链管理
  • 基金资助:
    国家自然科学基金资助项目(71572154);中央高校基本科研业务团队资助项目(26816WTD25)

A Research on Platform-Selling Mode Selection Considering Optimal Pricing and Quality Decision

GUAN Zhenzhong, HUANG Qiujie, ZHANG Aifeng   

  1. School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2020-02-28 Published:2021-06-26

摘要: 为了研究电商平台与制造商的销售模式选择问题,在产品质量外生和内生情况下,分别建立制造商领导的转售与平台零售商领导的代理销售动态博弈模型,通过逆序归纳法求解出各决策方的最优定价与质量水平,并运用数值分析法验证结论的有效性。研究发现,平台边际运营成本与市场异质性共同决定产品市场覆盖率,平台与制造商可根据市场环境参数的不同选择最优的销售策略。质量外生时,平台与制造商的产品零售价格相同,但两者的最优销售模式选择总是不一致。质量内生时,当平台边际运营成本较低,且市场异质性较大时,平台与制造商均选择代理销售模式,此时双方均实现帕累托改进。

关键词: 电商平台, 产品质量, 定价, 销售模式

Abstract: In order to study e-commerce platform and the manufacturer's choice of product selling mode, four mathematical models, the reselling and the agency selling model with product quality endogenous and quality exogenous respectively, are set up. The optimal pricing and quality strategies are formulated through backward induction. And the validity of main results is verified through a numerical analysis. The results indicate that the platform marginal operating costs and market heterogeneity codetermine the market coverage. The platform and the manufacturer can choose the optimal selling strategy according to different sales environments. When the product quality is exogenous, the platform and the manufacturer make the same retailing price, and are in conflict with each other in the choice of product selling mode. With endogenous quality, when the marginal operating cost of the platform is low and the market consumer heterogeneity is large, both the platform and the manufacturer choose the agency selling mode, and both realize Pareto improvement.

Key words: e-commerce platform, product quality, pricing, selling mode

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