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Data, Expert Knowledge and Decisions: An Interdisciplinary by W. Gaul, M. Schader (auth.), Professor Dr. Wolfgang Gaul,

By W. Gaul, M. Schader (auth.), Professor Dr. Wolfgang Gaul, Professor Dr. Martin Schader (eds.)

Cross-disciplinary learn on how computer-assisted determination making could be supported via refined info research recommendations and up to date advancements in knowledge-based structures learn are defined during this quantity, with emphasis on advertising and marketing functions. facets handled contain market-share research (spreadsheet based), media making plans, stochastic marketplace modelling, advertising and marketing information research and new product advent administration (all knowledge-based, in part utilizing PROLOG). those contributions emphasize hyperlinks among determination aid, professional wisdom study and advertising. different program parts are debt and credits administration and group of workers disposition (KEE based), portfolio administration (PROLOG established) and car scheduling. Concrete interconnections among info research and advertising and marketing could be visible within the contributions on category and unfolding of industry facts, marketplace segmentation via compelled type, conjoint research functions, perfect aspect product mapping, MDS in telecommunications pricing and multi-mode advertising info evaluations.

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Additional info for Data, Expert Knowledge and Decisions: An Interdisciplinary Approach with Emphasis on Marketing Applications

Sample text

There are three vehicles for conveying to brand managers the implications of changes in elasticities. First, competitive maps (Cooper (1987)) are diagnostic tools to find out what events signal change in the competitive structure, and to visualize the patterns of competitive pressures corresponding to any set of conditions. Second, the logit idealpoint model (Cooper and Nakanishi (1983b)) provide diagnostic tools to help visualize how patterns of competitive pressures translate into sales. And third, the elasticities also provide the needed ingredients to perform equilibrium analyses (Carpenter, Cooper, Hanssens and Midgley (1987)), assessing optimal marketing-mix levels based on various assumptions about competitive reactions.

5% to 89%. 5% at the end of the planning span of time are prompted to the system. After the input part has been completed, output as shown in Figure 3 and Figure 4 is immediately available. Figure 3 shows a first output screen containing results like awareness rate (Produktkenntnis)' cumulative trial rate (Penetration Erstkaeufer), repeat purchase rate (Wiederkaeufer) and volume (Marktanteil, Menge) as well as revenue (Marktanteil, Wert) market shares which-because of the chosen price strategy (see Table 2)-are equal for the underlying situation.

Parts of these efforts are presented in the section which describes a demonstration of a prototype consultation session. ) is necessary (--4 testing). This phase is still being performed. In doing so, characteristics of the above mentioned types of knowledge engineering applications are met again in the concrete realization of the prototype. 45 First, the NPI-recommendations of the prototype depend on predicted developments of key characteristics and goal criteria (-+ prediction). Secondly, explanations of given and predicted time pattern of some of the mentioned key characteristics and goal criteria are provided (-+ interpretation).

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