Design and implementation of a case-based reasoning system for marketing plans |
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| Affiliation: | 1. Institute of Electronic Commerce, National Chung-Hsing University, 250 Kuo Kuang Road, 403 Taichung, Taiwan, ROC;2. Department of Information Management, Chaoyang University of Technology, 168 Gifeng E. Road, Wufeng, Taichung County, Taiwan, ROC;1. School of Civil Engineering and Built Environment, Queensland University of Technology, Australia;2. School of Design and the Built Environment, Curtin University, Australia;3. Faculty of Computing, Engineering and the Built Environment, Birmingham City University, UK;4. School of Design, Queensland University of Technology, Australia;1. Department of Information Management and Decision Sciences, School of Business Administration, Northeastern University, Shenyang 110819, China;2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China;3. Department of E-commerce, School of Management, Henan University of Technology, Zhenzhou 450001, China;4. Department of Operations and Logistics Management, School of Business Administration, Northeastern University, Shenyang 110819, China;1. Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan;2. Department of Computer and Communication Engineering, Ming Chuan University, Taoyuan, Taiwan |
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| Abstract: | Unstructured intangible experiences and knowledge are usually difficult to represent and instantiate, which engenders the hardship of knowledge transfer and sharing. Past marketing plans are such valuable documents containing strategic planning knowledge and experiences.Case-Based Reasoning (CBR), which consists of retrieving, reusing, revising, and retaining cases, has been proved effective in retrieving information and knowledge from prior situations and being widely researched and applied in a great variety of problem territories.This paper targets at designing a CBR architecture and a method that facilitate the sharing and retrieving of cases of great concern to the marketing personnel. After an intensive survey of CBR methods and applications, a CBR system embedding multi-attribute decision making method, which provides both overall similarity level and similarity level of each selected attribute, is proposed to enhance the adaptation of a new marketing plan. In addition, a multi-attribute gap analysis diagram is developed to visualize the similarity along with the gap between candidate and target cases, so as to better support interaction and group decision making in the process of strategically formulating a new marketing plan. The CBR system was implemented and successfully demonstrated on case retrieval of a telecommunication company. |
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