Citation

Nara EOB, Sordi DC, Schaefer JL, Schreiber JNC, Baierle IC, Sellitto MA, Furtado JC. Safety Sci. 2019; 118: 826-834.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.ssci.2019.06.017

PMID

unavailable

Abstract

This research wanted to provide evidence that health and worker safety affects the competitiveness of companies and to identify the KPIs that influence the competitive results. For this, we choose to study the Brazilian slaughterhouse industry, which is characterized by an extensive and dangerous work. We identified 33 key performance indicators (KPI) of Occupational Health and Safety (OHS) based on Norm 36 of the Ministry of Labor in Brazil. With the application of the Multi Attribute Utility Theory (MAUT) method we determined the values of Individual Competitiveness Rate (ICR) of each company and ranked them. For ranking and verification purposes we used Artificial Neural Networks (ANN), which allowed the identification of relevant KPIs and to rank, identify, and visualize the differences in relative importance among them. The results show that the Global Competitiveness Rate (GCR) ideal for companies as provided by specialists is 3.48 (1 to 4 scale), and that only 10% of companies have ICR equal to or greater than the GCR pointed out as ideal by specialists. With this data, you can make the companies act in a more targeted way on the indicators, always looking to raise their ICR. The originality of this article is that, through the integration of MAUT and ANN, we can accelerate probabilistic calculations and through the information gain we can identify which KPIs have the most influence on competitiveness and therefore need special attention.

Language: en