Article ID: | iaor20119191 |
Volume: | 134 |
Issue: | 1 |
Start Page Number: | 177 |
End Page Number: | 187 |
Publication Date: | Nov 2011 |
Journal: | International Journal of Production Economics |
Authors: | Carpinetti Luiz Cesar Ribeiro, Ganga Gilberto Miller Devs |
Keywords: | fuzzy logic |
The aim of this paper is to propose a supply chain performance model based on fuzzy logic to predict performance based on causal relationships between metrics of the Supply Council Operations Reference model (SCOR) model. The main contribution and originality of this proposal relates to the application of Fuzzy logic to predict performance based on performance metrics levels 1 and 2 of the SCOR model. Fuzzy logic is a technique suitable for dealing with uncertainty and subjectivity, which becomes an interesting auxiliary approach to manage performance of supply chains. A descriptive quantitative approach was adopted as research method, based on the prediction model. Statistical analysis of the prediction model results confirmed the relevance of the causal relationships embedded in the model. The findings reinforce the proposition that the adoption of a prediction model based on fuzzylogic and on metrics of the SCOR model seems to be a feasible technique to help managers in the decision making process of managing performance of supply chains.