BUILDING PROVEN CAUSAL MODEL BASES FOR STRATEGIC DECISION SUPPORT

Christian Hillbrand

2004

Abstract

Since many Decision Support Systems (DSS) in the area of causal strategy planning methods incorporate techniques to draw conclusions from an underlying model but fail to prove the implicitly assumed hypotheses within the latter, this paper focuses on the improvement of the model base quality. Therefore, this approach employs Artificial Neural Networks (ANNs) to infer the underlying causal functions from empirical time series. As a prerequisite for this, an automated proof of causality for nomothetic cause-and-effect hypotheses has to be developed.

Paper Citation

in Harvard Style

Hillbrand C. (2004). BUILDING PROVEN CAUSAL MODEL BASES FOR STRATEGIC DECISION SUPPORT . In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 972-8865-00-7, pages 178-183. DOI: 10.5220/0002625101780183

in Bibtex Style

@conference{iceis04,
author={Christian Hillbrand},
title={BUILDING PROVEN CAUSAL MODEL BASES FOR STRATEGIC DECISION SUPPORT},
booktitle={Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2004},
pages={178-183},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002625101780183},
isbn={972-8865-00-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - BUILDING PROVEN CAUSAL MODEL BASES FOR STRATEGIC DECISION SUPPORT
SN - 972-8865-00-7
AU - Hillbrand C.
PY - 2004
SP - 178
EP - 183
DO - 10.5220/0002625101780183