Performance Evaluation Model of Landport and Seaport Collaboration Using the Support Vector Machine

Author:

Xu Dehong1,Zhang Yue2,Liang Chengji2

Affiliation:

1. Business College, Xi’an International University, Xi’an 710077, China

2. Institutes of Logistics Science and Technology, Shanghai Maritime University, Shanghai 201308, China

Abstract

This study delves into the pivotal role of shipper satisfaction in cultivating efficacious cooperation between dry ports and seaports. The research endeavors herein present a comprehensive indicator system tailored to evaluate the efficacy of the cooperation of the sea ports and dry ports. This system encompasses 14 key indicators, thoughtfully categorized into four dimensions, offering a holistic perspective on the multifaceted factors that underscore the synergy between dry ports and seaports. The establishment of a performance evaluation model for this collaborative nexus draws upon the support vector machine (SVM) technique, a choice substantiated by its suitability for the available dataset and its relevance within the research context. Leveraging the indicator data as a training dataset, the SVM approach culminates in the construction of a cooperative matrix, ultimately facilitating the discernment of performance rankings within dry port and seaport collaboration. This research methodology not only yields valuable insights into the evaluation of this distinct collaboration but also presents a versatile framework with potential application for addressing various challenges encountered within the cooperative milieu of dry ports and seaports.

Funder

“The Belt and Road initiative” International Inland Port Logistics Joint Research Center

National Natural Science Foundation of China

Shanghai Sailing Program

Shanghai Rising-Star Program

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference20 articles.

1. Zhang, S., and Gao, Y. (2012, January 24–28). Study on problems of dry ports planning based on supply chain management. Proceedings of the World Automation Congress 2012, Puerto Vallarta, Mexico.

2. Management Strategy for Seaports Aspiring to Green Logistical Goals of IMO: Technology and Policy Solutions;Le;Pol. Marit. Res.,2023

3. (2023, September 10). Office of Fossil Energy and Carbon Management, “LNG Annual Report—2020”. Available online: https://www.igu.org/resources/2020-world-lng-report/.

4. The Experience and Implications for Constructing International Dry Ports;Yang;J. Ocean. Univ. China,2010

5. A novel three-stage fuzzy GIS-MCDA approach to the dry port site selection problem: A case study of Shahid Rajaei Port in Iran;Raad;Comput. Ind. Eng.,2022

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