Combining system dynamics and conjoint analysis for strategic decision making with an automotive high-tech SME

2002 ◽  
Vol 18 (3) ◽  
pp. 359-379 ◽  
Author(s):  
Markus J. Schmidt ◽  
Michael Shayne Gary
Keyword(s):  
Decision Making ◽  
System Dynamics ◽  
Conjoint Analysis ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
High Tech

Expanding Data Mining Power with System Dynamics

2008 ◽  
pp. 2688-2696
Author(s):  
Edilberto Casado
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Pattern Recognition ◽  
System Dynamics ◽  
Knowledge Discovery ◽  
Strategic Decision ◽  
Knowledge Discovery In Databases ◽  
Strategic Decision Making ◽  
The World ◽  
Mathematical Techniques

Business intelligence (BI) is a key topic in business today, since it is focused on strategic decision making and on the search of value from business activities through empowering a “forward-thinking” view of the world. From this perspective, one of the most valuable concepts within BI is the “knowledge discovery in databases” or “data mining,” defined as “the process of discovering meaningful new correlations, patterns, and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques” (SPSS, 1997).

Expanding Data Mining Power with System Dynamics

2005 ◽  
pp. 1155-1161
Author(s):  
Edilberto Casado
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Pattern Recognition ◽  
System Dynamics ◽  
Knowledge Discovery ◽  
Strategic Decision ◽  
Knowledge Discovery In Databases ◽  
Strategic Decision Making ◽  
The World ◽  
Mathematical Techniques

Business intelligence (BI) is a key topic in business today, since it is focused on strategic decision making and on the search of value from business activities through empowering a “forward-thinking” view of the world. From this perspective, one of the most valuable concepts within BI is the “knowledge discovery in databases” or “data mining,” defined as “the process of discovering meaningful new correlations, patterns, and trends by sifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques” (SPSS, 1997).

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