Ports are pivotal nodes in supply chain and transportation networks, in which most of the
existing data remain underutilized. Machine learning methods are versatile tools to utilize …

Over the last two decades, application of Data envelopment analysis (DEA) in transportation
problems have gained considerable research attention. This paper presents a literature …

In recent years there has been an exponential growth in the number of publications related
to theory and applications of Data Envelopment Analysis (DEA). Charnes, Cooper, and …

Although the application of blockchain technology in maritime industry can improve the
customs clearance efficiency and logistics transparency in the container cargo supply …

The current study proposes a new DEA model to evaluate the efficiency of 39 Chinese
commercial banks over the period 2010–2018. The paper also, in the second stage …

The rapid development of China's port industry has caused numerous problems, among
which the most significant is environmental pollution. A major goal for government and port …

Abstract Foreign Direct Investment (FDI) inflows to emerging nations exhibit a big variation.
To what extent do host-country regulatory and institutional variables attract or repel FDI? We …

Purpose–The purpose of this paper is to measure a port's green performance. The literature
is reviewed and a survey is carried out to identify major green port performance indicators …

This paper investigates how the involvement of foreign and local ownerships, intra-and inter-
port competition and hinterland affect the container terminal efficiency in China and its …

This study develops a new port performance measurement model by taking the perspectives
from different port stakeholders. The novelty lies in the modelling of interdependencies …