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Basic set-up of a fuzzy system

Basically, Zadeh (2008 2754) distinguishes between the logical, the fuzzy-set-theoretic, the epistemic and the relational facets. [Pg.37]

3 Methodological ftmdamentals of the research on the value determination of SCIs [Pg.38]

The properties of fuzzy logic make it suitable for application within the conducted research presented in the work at hand. The cause-and-effect chain between an SCI and revenues is determined by the value driver customer satisfaction and, thus, is of a qualitative nature. Fuzzy logic makes it possible to utilize practical knowledge, which is based in this context in marketing, sales and logistics, to gain a quantifiable relationship. Thus, the technique of fuzzy logic is employed in a model for the determination of an SCTs revenue contribution.  [Pg.38]

In general, there are two basic approaches to using system dynamics (Sterman, 2000 107). The first category encompasses approaches that map dynamic relationships and employ various methods for analyzing the consequences of those links. The second category is formed by approaches that simulate the dynamic relationships. As a result, the effect of differences in interventions, timing, delays and feedback on the system [Pg.38]

In comparison, in system dynamics-based simulations, just the initial values are given for all variables while in econometric approaches variables are determined for the whole forecasting horizon (Schwarz Ewaldt, 2002 163). [Pg.38]


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