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The Third Party Logistics Financial Credit Evaluation Model Research Based on Uncertain Information

Xingui, Liu / Ming, Luo

Supervision risk of the third party logistics enterprise logistics and logistics financial operating condition is taken as the investigation object in this paper. Through the selection of indicators and determination of the weight coefficient, we build a comprehensive and practical evaluation index system of logistics finance risk. Fuzzy comprehensive evaluation method is used to construct logistics financial risk assessment model. The proposed model risk is less than the traditional logistics finance business model.

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The Third Party Logistics Financial Credit Evaluation Model Research Based on Uncertain Information

Xingui, Liu / Ming, Luo

Supervision risk of the third party logistics enterprise logistics and logistics financial operating condition is taken as the investigation object in this paper. Through the selection of indicators and determination of the weight coefficient, we build a comprehensive and practical evaluation index system of logistics finance risk. Fuzzy comprehensive evaluation method is used to construct logistics financial risk assessment model. The proposed model risk is less than the traditional logistics finance business model.

The Third Party Logistics Financial Credit Evaluation Model Research Based on Uncertain Information

Xingui, Liu / Ming, Luo

Supervision risk of the third party logistics enterprise logistics and logistics financial operating condition is taken as the investigation object in this paper. Through the selection of indicators and determination of the weight coefficient, we build a comprehensive and practical evaluation index system of logistics finance risk. Fuzzy comprehensive evaluation method is used to construct logistics financial risk assessment model. The proposed model risk is less than the traditional logistics finance business model.

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Titel:

The Third Party Logistics Financial Credit Evaluation Model Research Based on Uncertain Information

Beteiligte:

Xingui, Liu (Autor:in) / Ming, Luo (Autor:in)

Erschienen in:

2015 International Conference on Intelligent Transportation, Big Data and Smart City ; 935-938

Erscheinungsdatum:

01.12.2015

Format / Umfang:

147753 byte

ISBN:

978-1-5090-0463-8 , 978-1-5090-0464-5

DOI:

https://doi.org/10.1109/ICITBS.2015.237

Medientyp:

Aufsatz (Konferenz)

Format:

Elektronische Ressource

Sprache:

Englisch

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