Abstract

The objective of this research is to assess the impact of ethics on research productivity within laboratories of public universities. To achieve this objective, neural networks’ method is used to highlight impacting and impacted variable modalities. Findings show ethical variables having the greatest impact on research productivity are ethics supporting document and transparency, while the variables most impacted by ethics are publications and scientific projects. Finally, the originality of this work lies in the reconciliation of two dimensions that appear to be irreconcilable a priori, namely, ethics which has a social connotation and productivity which has an economic connotation. It also resides in employing neural networks’ method, with is rarely used in social sciences.