Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/74657
Title: Identification of success factors for green shipping with measurement of greenness based on ANP and ISM
Authors: Ren, J 
Lützen, M
Rasmussen, HB
Keywords: Analytic network process
Green shipping
Interpretative structuring modeling
Structural self-interaction matrix
Success factors
Issue Date: 2018
Publisher: Springer
Source: International series in operations research and management science, 2018, v. 260, p. 79-103 How to cite?
Journal: International series in operations research and management science 
Abstract: Green shipping as an emerging concept which aims to mitigate the negative environmental impacts caused by shipping activities has received more and more attentions recently. However, there is a gap in knowledge how to take the efficacious measures, which makes it difficult for the stakeholders of shipping activities to promote green shipping. In order to fill this gap, this chapter proposed a generic methodology for establishing a criterion evaluation system for greenness assessment of shipping, including the identification of the success factors, the development of some strategic measures, and the analysis of the measures for enhancing the greenness of shipping. A criterion evaluation system which consists of multiple criteria in five aspects including: technological aspect, economic aspect, environmental aspect, social aspect, and managerial aspect has been firstly established. Subsequently, Analytic Network Process (ANP) has been employed to determine the relative importance of these factors in green shipping with the consideration of the interdependences and interactions among these criteria for evaluating the greenness of shipping, and they have been ranked from the most important to the least. Accordingly, the key success factors for green shipping have been obtained. Then, some strategic measures for helping the stakeholders enhance the greenness of shipping have been proposed. Finally, Interpretative Structuring Modeling (ISM) has been employed to analyze the cause-effect relationships among these measures and the features of these measures.
URI: http://hdl.handle.net/10397/74657
ISSN: 0884-8289
DOI: 10.1007/978-3-319-62338-2_4
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