Qualitative company performance evaluation: Linear discriminant analysis and neural network models

✍ Scribed by K. Bertels; J.M. Jacques; L. Neuberg; L. Gatot

• Book ID: 104339806
• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 139 KB
• Volume: 115
• Category: Article
• ISSN: 0377-2217
• DOI: 10.1016/s0377-2217(98)00161-1

✦ Synopsis

In this paper, we present a classi®cation model to evaluate the performance of companies on the basis of qualitative criteria, such as organizational and managerial variables. The classi®cation model evaluates the eligibility of the company to receive state subsidies for the development of high tech products. We furthermore created a similar model using the backpropagation learning algorithm and compare its classi®cation performance against the linear model. We also focus on the robustness of the two approaches with respect to uncertain information. This research shows that backpropagation neural networks are not superior to LDA-models (Linear Discriminant Analysis), except when they are given highly uncertain information.