Towards stable model bases for causal strategic decision support systems

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Hillbrand, C. (2009). Towards stable model bases for causal strategic decision support systems. In M. Hunter (Ed.), Strategic Information Systems: Concepts, Methodologies, Tools, and Applications (pp. 2223-2243). Hershey PA: Information Science Reference.

Publication type

Chapter in Edited Book


Most decision support systems (DSS) based on causal models fail to analyze the empirical validity of the underlying cause-and-effect hypotheses, but instead concentrate on numerous analysis techniques within the method base. However, the soundness of these cause-and-effect-relations as well as the knowledge of the approximate shape of the functional dependencies underlying these associations turns out to be the biggest issue for the quality of the results of decision supporting procedures. Therefore this article strives towards an approach to prove the causality of nomologic cause-and-effect-hypotheses by empirical evidence as a prerequisite for the approximation of the mostly unknown causal functions. Since the latter very often show non-linear influences, it is necessary to employ universal function approximators for this purpose: consequently the proposed approach adopts artificial neural networks (ANN) as an inductive method to learn a calculational model of cause-and-effect functions from empirical time series.


Planning and Controlling Cockpit for Entrepreneurs
FFF-Förderprojekt, January 2006 until April 2008 (finished)

In der Literatur existiert eine Vielzahl von Planungsansätzen für die strategische Ausrichtung eines Unternehmens. Allerdings integrieren diese meist keine passenden Controlling-Instrumente. Es ist ... more ...


Organizational Units

  • Institute for Entrepreneurship
  • Van Riemsdijk Chair in Entrepreneurship