USST_Arts_112480746 电子商务销售网络中的消费者行为动力学研究

VIP免费

3.0 赵德峰 2024-11-11 4 4 2.98MB 52 页 15积分

侵权投诉

电子商务销售网络中的消费者行为

动力学研究

摘要

随着计算机技术和互联网的发展，电子商务在人们的消费领域所占的比重越

来越大。电子商务以其迅猛的增长速度和广阔的发展前景成为诸多企业的必然选

择。那么，基于复杂性科学理论对电子商务网络和消费者网购行为进行研究就有

了理论意义和实际价值。

电子商务具有客户多变性、消费行为多样性的特征，是一个很复杂的系统。不

管是 B to B、B to C 还是 C to C，都是供应链的组成部分。本文运用复杂性科学理

论，通过数据实证与理论分析来研究销售网络的特性。结合长尾理论，对电子商

务中商品销售量的分布进行研究。此外，针对消费者的网络购物行为，基于个体

层面和群体层面进行深入挖掘，分析消费者的在线购物行为模式和行为动机。得

出如下结论：

首先，在电子商务销售网络中，不管是从行业角度还是单件商品角度来考察，

其销售量排名分布都体现出幂律特性，销售曲线呈现出长长的尾巴。这表明，大

部分店铺（商品）的销售量都比较低，但是少部分店铺（商品）的销售量极大。

这种无标度性的形成机制在于：网络销售平台给消费者提供了海量的选择，商品

的“销售量”成为一个综合的考核指标，销售量越大，被再次购买的概率也就越

大。这就产生了“富者愈富”的现象。在这种情况下，销售网络体现出对随机攻击

的鲁棒性和对恶意攻击的脆弱性。生产商需要重点维护销售量极大的几家店铺，

但是，根据长尾理论，海量的利基产品（Niche Product）也创造了可观的利润，

且边际成本很低。所谓的利基产品，是指和大热门相对应的普通产品，它们构成

了长尾的主要部分。因此，生产商需要在热门店铺（商品）和非热门之间进行利

益分配，并合理看待两者之间的转换关系。

其次，本文分析了消费者在线购物行为的动力学特征。根据多名志愿者 1~5

年的淘宝购物记录和两家店铺的销售记录，统计了个体消费者和群体消费者的购

物时间间隔，发现群体消费者和大部分个体消费者的购物时间间隔分布都呈现出

幂律性，即消费者的购物行为体现出长久的静默和短暂的爆发。也有少部分个体

消费者的购物时间间隔服从指数分布或以指数截断的幂律分布。这表明，消费者

的在线购物行为体现出一定的规律，但是也体现出复杂性和多样性。卖家可以根

据不同的消费者类型提供不同的营销策略，制定针对性的方案。以上的研究表明

在电子商务活动中，不均匀性（幂律分布）体现在诸多方面，包括销售量的分布

以及消费者购物时间间隔的分布，这两者之间也存在一定的内在关系。

最后，根据可视算法，本文将两家店铺的消费购物时间序列转化成复杂网络。

通过计算分析网络的拓扑参数，发现构造的网络体现出小世界特性和无标度性。

且两家店铺的参数非常接近，表明不同的消费群体的购物行为具有一定的相似性。

关键词：复杂性科学　长尾理论　电子商务人类动力学购物行为

ABSTRACT

With the development of computer science and the internet technology, the

proportion of e-commerce in people's consumption is growing. The rapid growth of e-

commerce and its broad development prospect make it the inevitable choice of many

enterprises. So, it has a theoretical and practical value to study the online shopping

networks and the law of consumer behavior based on the theories of complexity science

and human dynamics.

E-commerce has some characteristics including customer variability and the

diversity of consumers’ behavior, so it is a very complex system. Whether the business

model is B to B, B to C or C to C, it is a part of the supply chain. In this paper, through

empirical data testing and theoretical analysis, it explors the characteristics of the sales

networks using the theory of complexity science. Combined with the long tail theory,

this paper studies the distribution of e-commerce merchandising. In addition, it also

analyzes in-depth the behavior patterns and motivations of consumers’ online shopping

behavior from collective and individual perspectives. The following conclusions:

First, in the e-commerce sales networks, the sales ranking obeys a power law

distribution in both perspectives of the entire industry and single items. The sales curve

shows a long tail. This indicates that most stores (commodities) have relatively low

sales, but a small portion of stores (commodities) have a high volume. The formation

mechanism of this scale-free property lies: Online stores give consumers vast choice of

goods, and " sales" becomes a comprehensive assessment index: the greater the volume

is, the probability of being re-purchased will be higher. This results a "rich get richer"

phenomenon. In this case, the sales networks reflect robustness to random attacks and

vulnerability to malicious attacks. Manufacturers need to focus on maintaining the few

shops which have great sales. But according to the long tail theory, mass niche products

also create substantial profit with low marginal cost. Niche products are the

corresponding ordinary products with the most popular products, which constitute the

main part of the long tail. Therefore, manufacturers need allocate interest between

popular stores (commodities) and non-popular stores (commodities), and view the

conversion relationship between the two reasonably.

Then, this article analyzes the dynamics characteristics of consumers’ online

shopping behavior. Through collecting the 1 to 5 years’ shopping records of some

volunteers and the selling records of two stores, it analyzes the time interval of online

shopping of both individual consumers and group consumers. It finds that shopping

time distribution of group consumers and the majority of individual consumers exhibits

a power law, namely consumers’ shopping behavior reflects long silence and a brief

outbreak. There are also a small number of individual consumers whose shopping time

interval is exponentially distributed or shows power-law distribution with index ended.

This suggests that consumers’ online shopping behavior reflects a certain degree of

regularity, but also reflects its complexity and diversity. Sellers can offer different

marketing strategies according to different types of consumers, developping targeted

programs. The above study shows that in e-commerce activities, the inhomogeneity(the

power law distribution) is reflected in many aspects, including the distribution of sales

and the distribution of consumers’ shopping time interval, and there are some inherent

relationship between the two.

At last, according to the visualization algorithms, this paper consumes the

shopping time series of the two shops into complex networks. Through calculating the

topology parameters of the networks, it finds that the networks show the characteristics

of small world and scale-free property. And the parameters of two shops are very close,

indicating that consumers’ shopping behavior of different groups has a certain

similarity.

Key Word ：complexity science, the long tail theory, e-commerce,

human dynamics, consumer behavior

目  录
中文摘要
ABSTRACT
第一章 绪 论.......................................................1
1 选题背景和研究意义...........................................1
2 本文所做的工作...............................................2
第二章 幂律分布和长尾理论概述......................................5
1 幂律分布的含义和动力学机制...................................5
1.1 幂律分布的含义...........................................5
1.2 幂律分布的动力学机制.....................................7
2 长尾理论的概念以及实证体现...................................7
2.1 从二八原理到长尾理论.....................................8
2.2 无标度性和长尾理论的关系.................................8
第三章 人类动力学理论和模型分析...................................10
1 优先权决定机制模型..........................................11
2 截止时间的影响..............................................13
3 基于兴趣调整的人类动力学模型................................13
4 非齐次泊松过程的模型........................................15
第四章 电子商务销售网络特性研究...................................17
1 数据来源和实证分析..........................................17
1.1 行业整体销售量分布情况..................................17
1.2 单件商品销售量分布规律..................................18
1.3 单家店铺的销售量分布规律................................20
2 电子商务销售网络的形成机制..................................21
3 电子商务销售网络的特性研究..................................22
3.1 销售长尾的经济价值......................................22
3.2 电子商务销售网络的特性..................................23
4 本章小结....................................................24
第五章 消费者在线购物行为的人类动力学模式.........................26
1 数据来源和实证分析..........................................27
2 个体网络购物行为的统计特征..................................28
2.1 时间间隔服从幂律分布的消费者类型........................29
2.2 时间间隔服从指数分布的消费者类型........................31

5.2.3 时间间隔服从指数截断的幂律分布的消费者类型..............32
5.2.4 三种类型消费者行为模式的对比............................33
5.3 消费者群体购物行为的人类动力学模式..........................35
5.4 本章小结....................................................36
第六章 在线购物行为的可视图分析...................................37
6.1 可视算法的原理概述..........................................37
6.2 群体购物行为的可视图分析....................................39
第七章 结束语.....................................................42
参考文献 ……………………………………………………………………………44

文档加载中……请稍候！
如果长时间未打开，您也可以点击刷新试试。

下载文档到电脑，查找使用更方便

15 积分 4人已下载

立即下载 VIP免费下载

摘要：

电子商务销售网络中的消费者行为动力学研究摘要随着计算机技术和互联网的发展，电子商务在人们的消费领域所占的比重越来越大。电子商务以其迅猛的增长速度和广阔的发展前景成为诸多企业的必然选择。那么，基于复杂性科学理论对电子商务网络和消费者网购行为进行研究就有了理论意义和实际价值。电子商务具有客户多变性、消费行为多样性的特征，是一个很复杂的系统。不管是BtoB、BtoC还是CtoC，都是供应链的组成部分。本文运用复杂性科学理论，通过数据实证与理论分析来研究销售网络的特性。结合长尾理论，对电子商务中商品销售量的分布进行研究。此外，针对消费者的网络购物行为，基于个体层面和群体层面进行深入挖掘，分析消费者的在...

展开>> 收起<<

USST_Arts_112480746 电子商务销售网络中的消费者行为动力学研究.doc

共52页,预览6页

还剩页未读，继续阅读

USST_Arts_112480746 电子商务销售网络中的消费者行为动力学研究

相关推荐

开通VIP享超值会员特权

作者详情

相关内容

推荐作者

热门标签

举报选择: