A Study of Customer and Product Network Centrality

• Main Authors: Yi-chun Chen, 陳伊君
• Other Authors: Hsiu-wen Liu
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/90604455105928403378

碩士 === 東吳大學 === 企業管理學系 === 100 === In recent years, enterprises leave customer information actively, using customer's sales history and other marketing materials to create a database, and provide individual service of products recommendation by analyzing the data. Many companies have recommendation and evaluation mechanism, and customers never expect themselves could have such a depth of interaction with the company and even with other customers. However there are still a lot of information in database, for example, relationship between customers, product and customer or products, that is, there is the existence of the network. Social Network Analysis can be used in this issue. It often has been used in organizational research, and this study will be used in database marketing. This study use centrality concept to analysis the sales data of the books in e-commerce website, and learn how centrality indicators apply and its implications in the marketing. Research results show that degree centrality differ from the concept of bestselling product, degree centrality can simply point out that the situation of most people buying. Modified degree centrality point out it is no longer best for the customer buying the most or the book saled the most, but also taking the node behind the link into consideration. Eigenvector centrality takes overall structure of the network into consideration, and managers should maintain good relations with suppliers of these important books to retain customers. Betweenness centrality can find key books and customers of the network. Closeness centrality point out managers can take advantage of core customers and products to stimulate the public. This study brings up two scatter plot of betweenness centrality and modified degree centrality and betweenness centrality and eigenvector centrality to understand the distribution situation and implications of products and customers in the fourth quadrant. This study help enterprises find more opportunities and strengthen relationships with customers and build customer loyalty.