Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/246347 
Year of Publication: 
2018
Citation: 
[Journal:] Operations Research Perspectives [ISSN:] 2214-7160 [Volume:] 5 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2018 [Pages:] 150-160
Publisher: 
Elsevier, Amsterdam
Abstract: 
The objective of this research is to show an innovative way for processing the collected data and measurement of practice and performances of supply chain by means of transformation of the obtained linguistic values, using the appropriate fuzzy methods, into crisp values of research variable dimensions. The methodology was applied for the measurement of the influence of an independent supply chain practice variable on the dependent supply chain performance variable and the research included the food industry companies. In order to apply the multivariate analysis methods, it is necessary to have the dimensions of the variable, but not the claims. Fuzzy logic enables the weighting of each claim and determining its weight, and determining the research variable dimension value in order to be able to use the multivariate analysis methods. The use of this methodology enables realistic evaluation of the dimensions and the results obtained show a statistically significant influence proving to be suitable for further testing using various statistical methods. The hypotheses about the relationships between supply chain practices and supply chain performances are confirmed.
Subjects: 
Fuzzy logic
Fuzzy entropy
FTOPSIS
Supply chain practices
Supply chain performances
JEL: 
C44
M11
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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