基于SCP范式的我国网络零售市场组织现状与绩效影响因素研究

发布时间：2018-06-09 20:37

本文选题：网络零售业 + 市场结构　；参考：《兰州财经大学》2017年硕士论文

【摘要】：我国网络零售业发展迅猛,网络购物逐渐成为人们日常生活重要的购物形式,网络零售对于扩大内需、促进产业结构转型具有深远的意义,成为经济增长新的突破口。本文在前人研究的基础上研究基于SCP范式分析网络零售市场的组织现状,并讨论了影响市场绩效的影响因素,对网络零售业研究有一些补充。首先研究我国网络零售市场组织的现状。市场结构上,我国网络零售业B2C超过C2C占据主要地位,以CR4和赫尔芬达-赫希曼指数测算的网络零售业市场集中度很高,同时也因为资金壁垒高使得网络零售业的进入壁垒很高。由于网络零售业的“轻资产”的特点使得行业退出壁垒较低。在网络零售业发展初期,网络零售商类型较为单一,差异化较大,随着规模扩大逐渐发展为综合化差异化开始缩小,近些年因为细分领域的逐渐发展,差异化又开始逐渐扩大。在市场行为方面,低价竞争是主要的价格行为,在广告方面,网络零售商纷纷在广告费用上花重金来给自己的品牌宣传,网络零售业的兼并行为也成为市场行为的重要部分,横向兼并使得网络零售商兼并同类型的电商增加自身的市场份额,产生规模效应,纵向兼并使得网络零售商在整个网络零售产业链上更具竞争力,降低成本,包括兼并快递企业等。市场绩效方面,近些年网络零售业的交易总额不断大幅度提高,占据社会消费品零售总额的比例也在不断的提高,网络零售商利润率普遍较低,技术进步对于网络零售业发展有很大推动,然后基于数据包络分析法对我国网络零售业企业效率进行测度分析,结果表明我国网络零售企业管理和技术水平、企业规模效率、综合资源配置效率较高。然后分析了我国网络零售业市场绩效的影响因素,通过多元回归模型分析出网络零售业市场绩效和货物周转量、互联网宽带接入用户数、市场行为移动终端使用占比显著正相关,和人均支出、市场集中度CR4没有显著相关关系。然后利用灰色关联度法研究网络零售业市场结构、市场行为中10个因素对于市场绩效的关联度排行。关联度序列依次为:第三方互联网在线支付规模、电商网络广告投入、快递业务总量、移动客户端网络零售占比、互联网宽带接入用户数、网络零售业中B2C类型占比、货运周转量、市场集中度CR4、电子商务并购总额、电子商务PE/VC总额。最后,本文研究指出,提升我国网络零售市场绩效,相关部门应加大市场监管力度、大力发展农村电商和跨境电商。
[Abstract]:With the rapid development of our country's network retailing, online shopping has gradually become an important shopping form in people's daily life. It is of far-reaching significance to expand domestic demand and promote the transformation of industrial structure, and it has become a new breakthrough in economic growth. On the basis of previous studies, this paper analyzes the organizational status of online retail market based on SCP paradigm, and discusses the influencing factors of market performance, which is complementary to the research on online retailing. Firstly, the present situation of network retail market organization in China is studied. In the market structure, the B2C of our country's network retail trade occupies the main position, and the market concentration degree of the network retail trade measured by CR4 and Hull Fanta-Hirschmann index is very high. At the same time, because of the high capital barrier, the entry barrier of network retailing is very high. Because of the "light assets" characteristic of the network retail trade, the industry exit barrier is lower. In the early stage of the development of network retailing, the types of network retailers are relatively single and the differentiation is large. With the expansion of the scale, the differentiation is gradually reduced to the comprehensive differentiation. In recent years, because of the gradual development of the subdivision field, the differentiation began to expand gradually. In terms of market behavior, low price competition is the main price behavior. In advertising, online retailers spend a lot of money on advertising expenses to promote their own brands. The merger behavior of online retailing has also become an important part of market behavior. Horizontal mergers make online retailers to increase their own market share and produce scale effect. Vertical mergers make online retailers more competitive and lower costs in the entire online retail industry chain. Including the merger of express delivery enterprises and so on. In terms of market performance, in recent years, the total transaction volume of online retailing has been greatly increased, and the proportion of the total retail sales of social consumer goods has also been increasing, and the profit margins of online retailers are generally low. The technological progress has greatly promoted the development of network retailing, and then based on the data envelopment analysis method, the paper measures and analyzes the efficiency of our country's network retailing enterprises. The results show that the management and technology level of our country's network retailing enterprises, the scale efficiency of enterprises, and so on. Comprehensive resource allocation efficiency is high. Then it analyzes the influencing factors of the market performance of our country's network retailing industry, analyzes the market performance of network retailing industry, the turnover of goods and the number of Internet broadband access users through the multiple regression model. There is a significant positive correlation between the proportion of mobile terminals used in market behavior and per capita expenditure and market concentration CR4. Then the grey correlation degree method is used to study the market structure of network retailing, and the correlation degree of 10 factors to the market performance is ranked in the market behavior. The related degree sequence is as follows: third party Internet online payment scale, e-commerce network advertising investment, express service total, mobile client network retail proportion, Internet broadband access user number, network retail type B2C ratio. Freight turnover, market concentration CR4, e-commerce M & A total, E-commerce PEP / VC total. Finally, this paper points out that to improve the performance of China's online retail market, relevant departments should strengthen market supervision and vigorously develop rural e-commerce and cross-border e-commerce.
【学位授予单位】：兰州财经大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F724.2

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