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首先使用德尔菲法，结合熵法和层次分析法共同确定顾客数据不同指标的价值权重，其次基于信息规则和高斯函数引入稀缺性指数、.zip （1个子文件）

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B2C电商企业下顾客购物信息定价模式研究.pdf 971KB

B2C 电商企业下顾客购物信息定价模式研究

摘要

随着精准营销崭露头角，其实现基础——顾客购物信息的热度也水涨船高，且顾客购物

信息交易平台在世界各地如雨后春笋般涌现，定价策略的制定对于其交易尤为重要。

在梳理数据与信息商品定价文献的基础上，通过结合顾客购物信息商品特点，提出了顾

客购物信息价值模型：首先使用德尔菲法和访问调查法来获取专家意见，结合熵法和 AHP 共

同确定顾客不同指标的价值权重，其次基于信息规则和高斯函数引入稀缺性指数、信息关联

价值和信息即时性价值，继而得到单独顾客购物信息价值模型。在此基础上通过 logistic 增长

函数来表示网络效应并引入数据饱和的概念，得到动态的、包含多个单独购物信息的数据包

价值模型。

当 B2C 电商平台将其数据包作为商品出售时，依据 Philip Kotler 的定价理论:首先确定定价

方法为成本加成定价法，其次通过需求弹性函数和市场生命周期来估计市场需求，接下来考

虑影响定价的其他因素（市场管控政策、隐私政策和外部效应），最后说明如何执行与控制价

格。

在关于顾客购物信息定价文献较少的情况下，通过此定价模式的研究，在一定程度上弥

补了学术空白，并可以为交易平台定价提供借鉴，具有一定的理论和现实意义。

关键词：顾客购物信息；数据商品；定价模式

Pricing personal information of E-consumers

Abstract

With the emergence of precision marketing on B2C e-commerce platform, its foundation of

realization, personal information of E-consumers has become a hot data commodity. At the same

time, personal information trading platform is springing up all over the world, and the pricing

strategy is particularly important for the trading. However, in China, a mature pricing mechanism

has not yet been formed.

In this paper, on the basis of sorting out relevant research literature on data and information

product pricing at home and abroad, combining with the status quo of customer shopping

information trading and existing pricing strategies. The customer shopping information value model

under the B2C e-commerce platform based on the cost-plus pricing method was proposed, and the

Delphi method and the interview survey method were innovatively used to obtain expert opinions.

Based on this, entropy method and AHP are combined to determine the value weight of different

customer indicators, and then the scarcity index, information correlation value and information

immediacy value are introduced based on information rules and Gaussian function. On this basis,

the concept of data saturation was introduced by combining the logistic growth function, so as to

calculate the total number of samples needed when the K value was reached in different fields, and

then the value model of packets containing multiple personal shopping information was obtained

dynamically.

When B2C e-commerce platform sells customers' shopping information packet as data

commodity, its price should not be determined only according to its value. Combined with Philip

Kotler's pricing process, this paper divides the enterprise pricing process from a strategic perspective

into five steps: First, the pricing method is cost plus pricing. Then the market demand is estimated

by the demand elasticity function and the market life cycle. Next, combined with the customer

shopping information value model, other factors affecting pricing (market control policies, privacy

policies and externalities) are briefly described. Finally, how to implement and control the price is

explained.

In this paper, the customer shopping information pricing model under the B2C e-commerce

platform is proposed, which makes up the research gap to a certain extent and has certain academic

and theoretical significance. At the same time, the pricing model proposed in this paper can provide

reference for setting the pricing mechanism of shopping information trading platform for domestic

and foreign customers, which has certain practical and practical significance.

Key words: Customer shopping information, Data commodity, Pricing model.

III 
目录 
摘要 ................................................................ I 
Abstract ........................................................... II 
第 1 章 绪论 ......................................................... 1 
1 选题背景 ..................................................... 1 
2 选题意义 ..................................................... 2 
3 国内外研究现状综述 ........................................... 2 
3.1 国内研究现状综述 ....................................... 2 
3.2 国外研究现状综述 ....................................... 2 
3.3 研究评述 ............................................... 3 
4 研究内容和方法 ............................................... 6 
4.1 相关概念界定 ........................................... 6 
4.2 研究内容 ............................................... 6 
4.3 研究方法 ............................................... 7 
5 研究技术路线 ................................................. 8 
6 本章小结 ..................................................... 8 
第 2 章 顾客购物信息市场分析 ......................................... 9 
1 顾客购物信息市场参与主体 ..................................... 9 
1.1 顾客购物信息交易平台 ................................... 9 
1.2 顾客购物信息提供方 ..................................... 9 
1.3 顾客购物信息买方 ....................................... 9 
2 顾客购物信息交易流程 ........................................ 10 
3 顾客购物信息商品特性 ........................................ 11 
4 顾客购物信息交易现状 ........................................ 12 
5 本章小结 .................................................... 14 
第 3 章 B2C 电商企业下顾客购物信息价值模型 ........................... 15 
1 单个顾客购物信息价值模型 .................................... 15 
1.1 基于熵法与 AHP 的权重确定 .............................. 15 
1.3 顾客购物信息的总价值 .................................. 19 
2 顾客购物信息数据包价值 ...................................... 20 
2.1 网络效应 .............................................. 20 
2.2 数据饱和 .............................................. 20 
2.3 数据包总价值 .......................................... 21 
3 本章小结 .................................................... 21 
第 4 章 数据包交易定价策略 .......................................... 22 
1 成本加成定价法 ............................................. 22 
2 数据包价值的需求弹性 ....................................... 22 
2.1 市场生命周期 .......................................... 22 
2.2 需求弹性函数 .......................................... 22 
3 影响定价的其他因素 ......................................... 23 