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Impact Of Quantity And Timeliness Of EWOM Information On Consumer’s Online Purchasing Intention Under C2C Environment

Posted on:2012-01-11Degree:MasterType:Thesis
Country:ChinaCandidate:L L XiaoFull Text:PDF
GTID:2249330377454135Subject:Marketing management
Abstract/Summary:PDF Full Text Request
According to the data from China Internet Network Information Center (CNNIC), the number of China’s netizens has reached457millions in the December of2010, and the trade size of Chinese online retail market has reached513.1billion yuan, which has been doubled compared with250billion yuan in2009. There will be more and more people shopping on the network along with the rapid popularization of the Internet and the boom of e-commerce, especially with the rapid development of C2C transactions. The Taobao, as a typical representative of C2C, has absorbed370million registered users in2010, and its online commodities had reached800millions, whereas the sales scale in2010was4,000billion yuan. Even more, the sales scale of Taobao on November11,2010(i.e., Singles Day) reached to19.5billion yuan in one day, which is more than the total sales in Hong Kong shopping malls of the whole day. However, as the rapid development of C2C e-commerce, the hidden problems have also been exposed at the same time. In the environment of C2C, there’s no actual sales people, so the main problem is lack of the information communication with each other, and meanwhile there is no guarantee of business reputation. The searching, comparison and evaluation of network information, and the web word of mouth information, especially the reviewing words left by the customers after shopping, are becoming the main factors affecting the behavior of consumers who will go shopping online. Park&Lee pointed out that the comment on Internet is one type of word of mouth, that is, the positive or negative comment the customer giving on the product, and such evaluation information is very helpful for the consumers’purchasing decisions. The research in this dissertation is launched just in this background.This paper point of research:according to the domestic and foreign literature review and study, the network word-of-mouth information at present research involves the main dimensions:ewom dissemination of information direction, types, quality, quantity, length and timeliness. This article will discuss ewom’s quantity and timeliness on the basis of customers’response pattern of " Recognize-emotions-behavior and relative assumptions. The article will establish the" ewom-trust-behavior" relationship model and make the product type as a variable to test if it has a significant regulatory role. At the same time using experimental method to do empirical research on relationship between ewom and customer’s trust, intermediary variables(customer trust), adjust variable(product type) and the relationship between customer’s trust and desire to shop online.Based on the reaction model of consumers’"cognitive→affective→behavior", and under the environment of C2C, this dissertation builds the relational model among electronic word-of-mouth (eWOM) information, customer trust and purchase intention from two dimensions of quantity and timeliness. The experimental verification shows that the quantity and timeliness of eWOM information have significant influences on customer trust; customer trust has significantly positive influence on purchase intention; and given the difference of products category, the quantity and timeliness of eWOM information have the significant different influence on customer trust; while buying fashion products (such as fashionable dress), the influence of the quantity and timeliness of eWOM information on customer trust is greater than that while purchasing functional products (such as books).There are some innovation reflected in this dissertation in the following aspects:(1) Based on the response pattern of the consumer’s "cognitive-affective-behavior", a relationship among the network word of mouth information, trust and shopping behavioral intention is built, so as to enrich the current theoretical model in the network word of mouth.(2) This dissertation takes the categories (i.e., fashion type and funtion type) of the products as adjustment variables to analyze the adjustment effect on the relation between the Internet word of mouth and consumer online shopping behavior.(3) On the selection on the dimensions of the word of mouth information, two dimensions, i.e., the amount and the timeliness of network word of mouth, are selected to study the impact of this two dimensions on consumers’online shopping behavior, which is rather lack currently in related research in China.Deficiencies of this paper:Although this study in ewom information research has some contributions and innovative, it still has some limitations:(1) This article has conducted experiments with only online shopper, the application on people with no online shopping experience is still unknown;(2) This paper only conduct assessment on positive information rather than negative information. It could not tell how the customer will response if there is a portion of negative information. For example,when the portion is20%,50%or80%. It did not reveal what is the portion to make the customer trust meets the maximum, and have strongest desire to purchase as well.The prospect of research:(1) The article only analyze a general shopping assessment.The information from different sources, such as Jingdong Mall, Dangdang net can be re-assessed and become the attached assessment of original one or sub-assessment. It will be valuable to test how the shopping assessment affect shopping desire.(2) To tackle the problem that how to test customer’s shopping desire when the ewom information is overload, it is valuable to do research on how much information is the best level to make customer receive the shopping assessment information to the maximum.(3) It need further study on how the ewom affect the popular group shopping online nowadays.
Keywords/Search Tags:C2C, eWOM, Product category, Customer trust, Purchase intention
PDF Full Text Request
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