In today's information age, companies collect massive amount of asymmetric flow data at individual customer level. Examples include customer-by-customer data (e.g., money, phone call and email flows among customers), product-by-product data (e.g., sequential purchase data), and web traffic data, etc. Asymmetric flow data carries meaningful customer intelligence and yet, it is under-explored. When combined with other data (such as customer profile and sales, etc.), this flow data can provide valuable understanding on individual customers, and thus enable marketers to trigger marketing actions at individual-customer level. / Simulation results show that the proposed algorithms yield promising model fitting performance within reasonable time. The LAS algorithm can successfully analyze 100,000 subjects in less than 10 hours. The CAS algorithm analyzes 50,000 subjects in 18 hours. The TAS algorithm analyzes 5,000 subjects within one hour. The proposed models are also applied on two real datasets (i.e., email data and web log data) to investigate the network structure among researchers and web pages. Results of simulation experiments and real data analyses suggest the proposed asymmetric scaling methods are viable ways of analyzing massive asymmetric flow data in marketing. / This thesis proposes three asymmetric scaling methods to analyze asymmetric flow data in marketing, namely Linear Asymmetric Scaling (LAS), Circular Asymmetric Scaling (CAS), and Two-dimensional Asymmetric Scaling (TAS). To visualize and analyze the asymmetric relationship among subjects, we assume that each subject has two relationship roles (i.e., as a source and as a destination of relationship flows). The LAS, CAS and TAS models represent asymmetric relationship among subjects by linear, circular and two-dimensional representations respectively. / Ho Ying. / "February 2007." / Adviser: Kin-Nam Lau. / Source: Dissertation Abstracts International, Volume: 68-09, Section: A, page: 3969. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 230-241). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_343842 |
| Date | January 2007 |
| Contributors | Ho, Ying., Chinese University of Hong Kong Graduate School. Division of Business Administration. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, theses |
| Format | electronic resource, microform, microfiche, 1 online resource (x, 241 p. : ill.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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