In order to answer to the new market demand industry turn to software vendors looking for specific ERP systems and starting specific projects for supporting Business Process Redesign (BPR). In such a context authors identified a lack of anticipatory models able to drive the ERP implementation process to the right thus proposing a meta-modeling approach able to bridge this gap. Proposed methodology integrates Data Analysis, Regression Meta-Modeling and Artificial Neural Networks processing, in order to identify hidden relationships among KPI guiding BPR decision makers. The paper presents the methodology as well as a practical application. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Revetria, R., & Tonelli, F. (2010). Neural networks and regressive KPI metamodels for business corporate management: Methodology and case study. In Business Performance Measurement and Management: New Contexts, Themes and Challenges (pp. 343–356). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-04800-5_22
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