【作者】 王欢；

【导师】 李萍；

【作者基本信息】 哈尔滨工业大学 ， 工商管理， 2020， 硕士

【摘要】 本文选择电子商务平台生态系统为主要研究对象,探究系统主要价值创造主体之间的博弈关系。以价值理论、竞合理论等为依据对所研究范围及主体进行界定;以电子商务平台生态系统演化发展过程作为依据进行阶段划分,采用演化博弈的方法探究不同阶段主要价值创造参与人之间的策略选择,识别关键影响因素,以探究实现系统长期价值最大化和价值分配均衡稳定的最佳策略组合;以阿里巴巴集团中的B2C电子商务平台生态系统天猫商城为例,通过访谈获取一手数据,同时根据企业官方网站、行业协会等途径获取二手数据,采用Matplotlib进行模型模拟仿真检验;最终以改变博弈的思维改进价值创造主体之间的博弈模型,并从核心平台企业视角为其进行平台生态系统的管理和监督提出合理对策及建议。本研究以价值网寻找演化博弈参与人,研究发现:在创建初始阶段,用户是系统创建初期最重要的资源,平台企业为实现网络效应将不遗余力以吸引用户加入系统以实现价值创造;影响供应商抉择的主要因素为入驻成本与入驻收益;影响平台企业是否选择对某供应商开放的主要因素为入驻管理费用及其对系统声誉的影响;期望达到实现系统长期价值最大化的良好状态为(入驻,开放)的策略组合。在发展运营阶段,由信息不对称带来的信用问题影响系统成员策略选择和价值创造,经演化博弈分析得出,影响用户是否退货的主要因素为正品售价及其所认为的购买正品而退货的损失;影响供应商是否守规生产的主要因素为各项收益与损失之间的权衡;影响平台企业是否进行积极管治系统违规行为的主要因素为声誉损失;最终得出在发展运营阶段期望达到实现系统长期价值最大化的良好状态为(不退货,守规)和(守规,积极管治)的策略组合。采用模拟仿真的方式证实了三个博弈模型的可信性、有效性及行业适用性,在此基础上基于改变博弈思维,改变博弈参与人、增加值、规则、利用合适战术及合理适时调整博弈范围等方式调整博弈模型,实现电子商务平台生态系统长期价值最大化及价值分配均衡稳定的长远目标。更多还原

【Abstract】 This article selects the e-commerce platform ecosystem in the Internet industry as the main research object,and explores the relationship between the main value creation subjects of the system.Based on the value theory,and competition theory,the research scope and subject are defined;the e-commerce platform ecosystem evolution process is divided into stages,and the evolutionary game method is used to explore the main value creation participants at different stages.Strategy selection,identify key influencing factors,and explore the best strategy combination to achieve long-term value maximization and value distribution balance and stability;take Tmall Mall,a B2 C e-commerce platform ecosystem under the Alibaba Group,as an example,through interviews Obtain first-hand data and second-hand data from the company’s official website,industry associations,etc.,and use Matplotlib for model simulation and simulation verification;finally,change the game thinking to improve the game model between value creation subjects,and carry out a platform ecology for it from the perspective of core platform companies Systematic management and supervision propose reasonable countermeasures and suggestions.This research uses value networks to find players in evolutionary games.The study found that in the initial stage of creation,users are the most important resources in the early stages of system creation.Platform companies will spare no effort to achieve network effects to attract users to join the system to achieve value creation;affecting suppliers The main factors in the decision are the cost of entry and the revenue of the entry;the main factors affecting whether the platform company chooses to open to a supplier are the entry management cost and its impact on the system’s reputation;it is expected that a good state that maximizes the long-term value of the system is(entry,Open)strategy mix.In the development and operation stage,the credit problem caused by the asymmetry of information affects the system member’s strategy selection and value creation.Through evolutionary game analysis,it is found that the main factors affecting whether users return goods are the genuine product price and what they consider to be genuine products.The main factor affecting whether the supplier is in compliance with production is the comparison between various gains and losses;the main factor affecting whether platform companies are actively managing system violations is reputation loss;and finally it is expected that during the development and operation stage,it is expected to achieve The good state of maximizing the long-term value of the system is a combination of strategies(non-return,compliance)and(compliance,active governance).The simulation appraisal method has confirmed theindustry applicability and effectiveness of the three game models.Based on changes in game thinking,changing game participants,changing value-added,changing rules,using appropriate tactics,and adjusting the scope of the game in a timely and reasonable manner.Adjust the game model to achieve the goals of maximizing the long-term value of the e-commerce platform ecosystem and achieving a balanced and stable value distribution.更多还原