Analyzing cargo loss severity of electronics products with decision tree

Mu-Chen Chen; Pei Ju Wu; Chih Kai Tsau

doi:10.1007/978-3-662-47200-2_51

Analyzing cargo loss severity of electronics products with decision tree

Mu-Chen Chen, Pei Ju Wu, Chih Kai Tsau

Department of Transportation and Logistics Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Supply chain risk management has been an essential issue in recent years. Cargo loss in supply chain and logistics activities has been the major cause of delays and supply chain disruption; however, rarely do studies provide comprehensive studies focusing on cargo loss analysis and prevention in various modes of transportation. Hence, this study aims to investigate the cargo loss severity of an electronics company. Decision tree analysis is adapted to develop classification models for cargo loss severity of electronics products. The empirical results with the classification rules can be utilized as a cargo loss prediction tool to help managers to make an effective plan on cargo loss prevention.

Original language	English
Title of host publication	Industrial Engineering, Management Science and Applications 2015
Editors	Kuinam J. Kim, Mitsuo Gen, Yabe Hiroshi, Xiaoxia Huang
Publisher	Springer Verlag
Pages	477-484
Number of pages	8
ISBN (Print)	9783662471999
DOIs	https://doi.org/10.1007/978-3-662-47200-2_51
State	Published - 1 Jan 2015
Event	International Conference on Industrial Engineering, Management Science and Applications, ICIMSA 2015 - Tokyo, Japan Duration: 26 May 2015 → 28 May 2015

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	349
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	International Conference on Industrial Engineering, Management Science and Applications, ICIMSA 2015
Country/Territory	Japan
City	Tokyo
Period	26/05/15 → 28/05/15

Keywords

Cargo loss prevention
Cargo loss severity
Decision tree
Supply chain risk management

Access to Document

10.1007/978-3-662-47200-2_51

Cite this

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title = "Analyzing cargo loss severity of electronics products with decision tree",

abstract = "Supply chain risk management has been an essential issue in recent years. Cargo loss in supply chain and logistics activities has been the major cause of delays and supply chain disruption; however, rarely do studies provide comprehensive studies focusing on cargo loss analysis and prevention in various modes of transportation. Hence, this study aims to investigate the cargo loss severity of an electronics company. Decision tree analysis is adapted to develop classification models for cargo loss severity of electronics products. The empirical results with the classification rules can be utilized as a cargo loss prediction tool to help managers to make an effective plan on cargo loss prevention.",

keywords = "Cargo loss prevention, Cargo loss severity, Decision tree, Supply chain risk management",

author = "Mu-Chen Chen and Wu, {Pei Ju} and Tsau, {Chih Kai}",

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Chen, M-C, Wu, PJ & Tsau, CK 2015, Analyzing cargo loss severity of electronics products with decision tree. in KJ Kim, M Gen, Y Hiroshi & X Huang (eds), Industrial Engineering, Management Science and Applications 2015. Lecture Notes in Electrical Engineering, vol. 349, Springer Verlag, pp. 477-484, International Conference on Industrial Engineering, Management Science and Applications, ICIMSA 2015, Tokyo, Japan, 26/05/15. https://doi.org/10.1007/978-3-662-47200-2_51

Analyzing cargo loss severity of electronics products with decision tree. / Chen, Mu-Chen; Wu, Pei Ju; Tsau, Chih Kai.
Industrial Engineering, Management Science and Applications 2015. ed. / Kuinam J. Kim; Mitsuo Gen; Yabe Hiroshi; Xiaoxia Huang. Springer Verlag, 2015. p. 477-484 (Lecture Notes in Electrical Engineering; Vol. 349).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Supply chain risk management has been an essential issue in recent years. Cargo loss in supply chain and logistics activities has been the major cause of delays and supply chain disruption; however, rarely do studies provide comprehensive studies focusing on cargo loss analysis and prevention in various modes of transportation. Hence, this study aims to investigate the cargo loss severity of an electronics company. Decision tree analysis is adapted to develop classification models for cargo loss severity of electronics products. The empirical results with the classification rules can be utilized as a cargo loss prediction tool to help managers to make an effective plan on cargo loss prevention.

AB - Supply chain risk management has been an essential issue in recent years. Cargo loss in supply chain and logistics activities has been the major cause of delays and supply chain disruption; however, rarely do studies provide comprehensive studies focusing on cargo loss analysis and prevention in various modes of transportation. Hence, this study aims to investigate the cargo loss severity of an electronics company. Decision tree analysis is adapted to develop classification models for cargo loss severity of electronics products. The empirical results with the classification rules can be utilized as a cargo loss prediction tool to help managers to make an effective plan on cargo loss prevention.

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ER -

Analyzing cargo loss severity of electronics products with decision tree

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Keywords

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