 A fuzzy logic approach to supply chain performance managementGilberto Miller Devós Ganga and Luiz Cesar Ribeiro Carpinetti International Journal of Production Economics, 2011, vol. 134, issue 1, 177-187 Abstract: 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. Keywords: Supply; chain; management; Fuzzy; logic; Performance; measurement; Decision; processes (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:134:y:2011:i:1:p:177-187 Access Statistics for this article International Journal of Production Economics is currently edited by Stefan Minner More articles in International Journal of Production Economics from Elsevier |
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