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Mold offer decision support system

Author: QiaoYanWen
Tutor: ChenQingXin
School: Guangdong University of Technology
Course: Mechanical and Electronic Engineering
Keywords: Mould & Die Bidding Decision Support System Customer Relationship Management Self-explicated Model Customer Behavior
CLC: TP399
Type: Master's thesis
Year: 2002
Downloads: 123
Quote: 0
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Abstract


In the new era that customer is regarded as the core, customers become the most important resource for any enterprise. Enterprise must manage their customers effectively in order to survive in the severe strife. Following the manufacture ideas like MRPII (Manufacture Resource Plan) and ERP (Enterprise Resource Plan ), CRM(Customer Relationship Management) become the new hot point in the research field.In this paper, first, the relationship between quotation and CRM is expatiated, and the advantage and disadvantage of the Mould & Die quotation system in use is analyzed; A new framework is provided serving mould enterprise and mould customer through building a Mould-industry center portal. This framework is feasible because there are two aspects of reasons. One is that we adopt the idea making the small Mould&Die enterprises buildup into a AVE(Agile Virtual Enterprise) based on their core capability. Another reason is that the character of Mould&Die enterprise in china is considered seriously. The multi-model DSS(Decision Support System) framework is provided for bidding system. At the same time, the function of every module is described in detail. The method and mathematics model to build Enterprise Self-explicated Mode based on Hybrid Conjoint Analysis is analyzed, which is realized in the way of wizard in the system; A win-win optimized model to satisfy both mould enterprise and mould customer is provided in the paper.Customer behavior is another very important problem in CRM. The more you understand your customers, the more chance you will win the customers. In the last of the paper, the status of customer behavior is described in detail, and a new model of customer behavior is provided. Customer behavior is analyzed including customer static behavior which is based on information of customers and customer dynamic behavior which is based on somequestionnaires to detect the behavior. The customer static behavior is analyzed using fuzzy decision method. A method to explore and modify the customer dynamic behavior is put forward.

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