論文：Cognitive Map Knowledge application used to Study Supply Chain System

論文：Cognitive Map Knowledge application used to Study Supply Chain System
Robust Wang
(Enics Electronics (Beijing) Limited,
A6 *in Cheng Industrial Park Ke Chuang No.2 Street, 100023, China)

Abstract: The paper clarifies one way of calculate the Supply chain Management (SCM in brief) comple*ity which use cognitive map for PO intention decision process based on the actual whole SCM parameters;
Key Words: Cognitive map, SCM;

Cognitive maps can illustrate causal relationships among the factors describing a given object and/or proble
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payment conditions, etc. Meanwhile, UNTs have causal relationships with SNTs: resource availability, vender preference, labor management relationships, corporative culture, etc. the role of SNTs in the process of the negotiation has long been a subject of analysis. It is therefore essential to incorporative the causal relationships among SNTs and UNTs into the negotiation process, both objectively and systematically, However, it is very difficult for decision-akers to perform negotiation effectively, because the number of SNTs and UNTs to be considered is huge, and the causal relationships that e*ist among them are very complicated to deal with effectively.
We are proposing a new type of negotiation support system based on cognitive maps as the knowledge representation mechanism and inference engine. A cognitive map is designed to e*amine whether the state of one element has an influence on the state of another.
It is easy to see that positive causal links (denoted as ‘+’ in the cognitive map) can be regarded as e*citatory relationships, while negative causal links (denoted as ‘-’ in the cognitive map) can be regarded as inhibitory relationships between nodes.
In the final cognitive map depicted in the figure 2 below, we conclude that the new problem can be described by the cause-and effect relationships between si* SNTs (SP, OQ, PC, PQ, A/S, DD) and the nine UNTs (IS, BS, TS, LS, CF, ER, OP, PR). The abbreviations for each SNT and UNT are e*plained in the Table below. Our goal here is to determine the combination of SNTs that will give the highest intention to order (IO), considering the effects that the UNTs create simultaneously. We still now elaborate on the detailed negotiation terms for each SNT so that we can describe the e*periments more practically. The table shows node values for SNTs and UNTs from the side of the buyer company. To perfo ……（未完，全文共8900字，當(dāng)前僅顯示2431字，請(qǐng)閱讀下面提示信息。收藏《論文：Cognitive Map Knowledge application used to Study Supply Chain System》）