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Original scientific paper

https://doi.org/10.7307/ptt.v36i2.411

Eco-Efficiency Evaluation of Integrated Transportation Hub Using Super-Efficiency EBM Model and Tobit Regressive Analysis – Case Study in China

Ling Wang ; School of Traffic and Transportation Engineering, Dalian Jiaotong University
Qi Wang ; School of Traffic and Transportation Engineering, Dalian Jiaotong University


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Abstract

The transportation industry is a key area for ecological civilisation construction and low-carbon development. As the core support of the national integrated transportation system, the ecological development level of integrated transportation hub (ITH) is crucial for enhancing the sustainable development capacity of the national integrated transportation. An eco-efficiency evaluation index system of ITH is established in this study and the eco-efficiencies of twenty international ITHs in China are comprehensively evaluated based on the super-efficient epsilon-based measure (EBM) model. Then the panel Tobit regression model is adopted to analyse the influencing factors of eco-efficiency. The results show that the average eco-efficiency of ITHs in China during 2011–2021 declines first and then rises, with a relatively high level overall but not efficient yet, and there is an obvious gradient distribution characteristic in all eco-efficiencies. Among them, Guangzhou ranks first, followed by Haikou, and Harbin ranks last. It is found that integrated transportation efficiency, urban green coverage, level of opening-up and economic development improve eco-efficiency significantly, while urbanisation rate, industrial structure and technology input have a negative impact. The results are consistent with the actual situation, verifying the practicality of models, and can be used to promote the sustainable development of integrated transportation.

Keywords

integrated transportation hub; eco-efficiency; super-efficient EBM model; Tobit regression model

Hrčak ID:

318709

URI

https://hrcak.srce.hr/318709

Publication date:

30.4.2024.

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