本文選題：電子商務(wù) + 網(wǎng)上購(gòu)物交易量��； 參考：《哈爾濱工業(yè)大學(xué)》2011年碩士論文

【摘要】：隨著我國(guó)互聯(lián)網(wǎng)普及率的節(jié)節(jié)攀升以及人們消費(fèi)意識(shí)的轉(zhuǎn)變,網(wǎng)絡(luò)購(gòu)物的用戶規(guī)模及市場(chǎng)規(guī)模均達(dá)到了一個(gè)新的高度,其中更是以C2C電子商務(wù)的發(fā)展最為迅猛。在網(wǎng)上交易中,買(mǎi)家可以通過(guò)瀏覽商品的網(wǎng)頁(yè)獲取商品的價(jià)格、商家信用等級(jí)、賣(mài)家好評(píng)率等信息,研究其中各個(gè)因素對(duì)于不同類別商品的網(wǎng)上購(gòu)物交易量究竟如何影響很有現(xiàn)實(shí)意義。本文針對(duì)這一問(wèn)題,對(duì)這些影響交易量的因素進(jìn)行了實(shí)證性研究。 本文首先從電子商務(wù)網(wǎng)店經(jīng)營(yíng)者的視角出發(fā),結(jié)合我國(guó)C2C網(wǎng)上交易平臺(tái)的現(xiàn)行客觀情況,建立了網(wǎng)上交易量影響因素的模型,并提出了九個(gè)研究假設(shè)。之后利用MetaSeeker數(shù)據(jù)抓取工具,根據(jù)本文研究需要在淘寶網(wǎng)抓取了搜索型、體驗(yàn)1型、體驗(yàn)2型、信任型、數(shù)字型五類商品的代表商品所需研究數(shù)據(jù),并編寫(xiě)了數(shù)據(jù)入庫(kù)程序以實(shí)現(xiàn)數(shù)據(jù)的處理。本文還根據(jù)所需研究?jī)?nèi)容對(duì)回歸方程的變量做了定義和取值,并對(duì)各交易量影響因素進(jìn)行了描述性分析,根據(jù)其均值及變異系數(shù)分析了各影響因素?cái)?shù)據(jù)之間所存在的差異性的原因。之后根據(jù)本文研究建立了多元回歸模型,對(duì)所抓取的數(shù)據(jù)進(jìn)行多元回歸分析并對(duì)結(jié)果進(jìn)行了探討。 本文的研究結(jié)果表明賣(mài)家信用等級(jí)對(duì)于五類商品的網(wǎng)上購(gòu)物交易量都有著顯著影響;賣(mài)家好評(píng)率、服務(wù)態(tài)度評(píng)分高低、賣(mài)家發(fā)貨速度評(píng)分高低及付款方式的多少對(duì)于五類商品的網(wǎng)上購(gòu)物交易量均沒(méi)有顯著的影響;對(duì)于除數(shù)字型商品外的其他四類商品,價(jià)格的高低對(duì)于網(wǎng)上購(gòu)物交易量的影響都很顯著;商品描述相符評(píng)分對(duì)于體驗(yàn)1型商品及信任型商品的網(wǎng)上交易量有顯著影響,對(duì)于其他三種類型商品影響不顯著。最后本文根據(jù)所得結(jié)果對(duì)銷售不同類型商品的C2C電子商務(wù)網(wǎng)店主提出了一些改進(jìn)建議。
[Abstract]:With the increasing popularity of Internet in China and the change of people's consumption consciousness, the scale of users and the market scale of online shopping have reached a new height, and the development of C2C e-commerce is the most rapid. In online transactions, buyers can obtain information about the price of goods, the credit rating of merchants, the favorable rating of sellers, and so on by browsing the web page of the goods. It is of practical significance to study the influence of various factors on the online shopping volume of different types of commodities. In order to solve this problem, this paper makes an empirical study on the factors that affect the trading volume. This paper first from the perspective of e-commerce shop operators, combined with the current situation of China's C2C online trading platform, established the online trading volume impact factors model, and put forward nine research hypotheses. Then using the MetaSeeker data capture tool, according to the research needs of Taobao to grab the search type, experience 1 type, experience 2 type, trust type, digital type of five types of goods on behalf of the research data, In order to realize the data processing, the program of data storage is written. In this paper, the variables of regression equation are defined and evaluated according to the research contents, and the influencing factors of each trading volume are analyzed in a descriptive way. According to the mean value and coefficient of variation, the reason of the difference between the factors is analyzed. Then, the multivariate regression model is established according to the research in this paper, and the multivariate regression analysis of the captured data is carried out and the results are discussed. The results of this study show that the credit rating of sellers has a significant impact on the online shopping volume of five categories of goods, the seller's praise rate, service attitude score, The seller's delivery speed score and payment method had no significant effect on the online shopping volume of the five categories of goods, while for the other four categories of goods except digital goods, The effect of price on online shopping volume is significant, while the score of commodity description matching has a significant impact on the online trading volume of type 1 and trust type commodities, but not on the other three types of commodities. Finally, according to the results, this paper puts forward some suggestions for the improvement of C2C e-commerce network shopkeepers selling different types of goods.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：F724.6;F224

【引證文獻(xiàn)】

相關(guān)期刊論文 前1條

1 周晗;樊青青;;淘寶箱包產(chǎn)品交易數(shù)量的影響因素研究[J];企業(yè)導(dǎo)報(bào);2012年23期

，

本文編號(hào)：1852135