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Effect of internal supply chain drivers on green supply chain management attributes

Effect of internal supply chain drivers on green supply chain management attributes With the growing importance for less polluting, cleaner and efficient processes, green supply chain management has grown in prominence in general. This has presented an important requirement for their study in a systematic manner. In an attempt to fulfil this requirement, this study puts forth several ideas. The impact of the variables, namely, anticipation of benefits and customer orientation on green supply chain management (GSCM) attributes has been taken up for an intensive study. These variables have impact on the GSCM attributes to varying degrees. Partial least squares structural equations modelling were used for the study and the open source statistical tool R for the analysis. The former is an appropriate tool when the data size is small and there are no assumptions about the characteristics of the data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Business Performance and Supply Chain Modelling Inderscience Publishers

Effect of internal supply chain drivers on green supply chain management attributes

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1758-9401
eISSN
1758-941X
DOI
10.1504/IJBPSCM.2019.105702
Publisher site
See Article on Publisher Site

Abstract

With the growing importance for less polluting, cleaner and efficient processes, green supply chain management has grown in prominence in general. This has presented an important requirement for their study in a systematic manner. In an attempt to fulfil this requirement, this study puts forth several ideas. The impact of the variables, namely, anticipation of benefits and customer orientation on green supply chain management (GSCM) attributes has been taken up for an intensive study. These variables have impact on the GSCM attributes to varying degrees. Partial least squares structural equations modelling were used for the study and the open source statistical tool R for the analysis. The former is an appropriate tool when the data size is small and there are no assumptions about the characteristics of the data.

Journal

International Journal of Business Performance and Supply Chain ModellingInderscience Publishers

Published: Jan 1, 2019

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