Mining Customer Knowledge for Channel and Product Segmentation

[[abstract]]Segmentation is particularly challenging in current markets. Hence, companies operating on consumer markets face significant implementation complexities. However, successful implementation of market segmentation is reported problematic, despite being extensively researched and widely acknowledged as a powerful concept in practice. The desired outcome, and the knowledge discovery of market segmentation, is to reap the benefits of competitive advantage. This study takes Computers/Communications/Consumer (3C) products as an example and uses a two-step data mining approach to the cluster analysis and association rules to analyze customer channels and product segmentation. Moreover, we look at what kinds of products and brands customers of different segments prefer and how these preferences differ in relation to varying channel types. Thus, this study finds some 3C product-buying behavior patterns, including customer purchase preferences and customer purchase demands, in order to generate different 3C segmentation marketing alternatives.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙

Mining User Knowledge for Investigating the Facebook Business Model: The Case of Taiwan Users

[[abstract]]Social network sites (SNS), as web-based services, allow users to make open or semi-open profiles within the systems they are part of, to see lists of other people in the group and to see the relations of people within different groups. Facebook is essentially an online social network site in which individuals can share photographs, personal information, and join groups of friends. This study investigates the experiences on Facebook of various users in Taiwan. Their degrees of confidence were often demonstrated by word-of-mouth disseminations about the social network site. Further, this research looks at how the reputations of Facebook proprietors and their affiliates were disseminated through relationship marketing for formulated social network marketing in its business model concerns. Therefore, this study uses the a priori algorithm as an association rules approach, and cluster analysis for data mining. We divide Facebook users into two groups of contributors and lurkers by their profiles and then find each group’s social network community information utilization and online purchase behaviors for investigating the Facebook business models.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙

Mathematical Models and Stability Analysis of Cholera Dynamics

In this dissertation, we present a careful mathematical study of several epidemic cholera models, including the model of Codeco [11] in 2001, that of Hartley, Morris and Smith [22] in 2006, and that of Mukandavire, Liao, Wang and Gaff et al. [60] in 2010. We formally derive the basic reproduction number R0 for each model by computing the spectral radius of the next generation matrix. We focus our attention on the stability analysis at the disease-free equilibrium which determines the short-term epidemic behavior, and the endemic equilibrium which determines the long-term disease dynamics. Particularly, we incorporate the Volterra-Lyapunov matrix theory into Lyapunov functions to facilitate the analysis of the global endemic stability. Based on the previous cholera models, we propose a new and unified deterministic model which incorporates a general incidence rate and a general formulation of the pathogen concentration, to improve our understanding of cholera dynamics. In addition, we briefly discuss the changes of the dynamics for the cholera models when several control measures are incorporated