Applications of machine learning methods in port operations–A systematic literature review

S Filom, AM Amiri, S Razavi - Transportation Research Part E: Logistics and …, 2022 - Elsevier
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 …

[HTML][HTML] Emerging approaches applied to maritime transport research: Past and future

R Yan, S Wang, L Zhen, G Laporte - Communications in Transportation …, 2021 - Elsevier
Maritime transport is the backbone of international trade and globalization. Maritime
transport research can be roughly divided into two categories, namely the shipping side and …

Toward digitalization of maritime transport?

PL Sanchez-Gonzalez, D Díaz-Gutiérrez, TJ Leo… - Sensors, 2019 - mdpi.com
Although maritime transport is the backbone of world commerce, its digitalization lags
significantly behind when we consider some basic facts. This work verifies the state-of-the …

[Retracted] Human Resource Demand Prediction and Configuration Model Based on Grey Wolf Optimization and Recurrent Neural Network

NK Rajagopal, M Saini, R Huerta-Soto… - Computational …, 2022 - Wiley Online Library
Business development is dependent on a well‐structured human resources (HR) system
that maximizes the efficiency of an organization's human resources input and output. It is …

Machine learning for international freight transportation management: A comprehensive review

L Barua, B Zou, Y Zhou - Research in Transportation Business & …, 2020 - Elsevier
Abstract Machine learning (ML) offers a promising avenue for international freight
transportation management (IFTM) given its capability to harness the power of data that …

[HTML][HTML] The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions

R Raeesi, N Sahebjamnia, SA Mansouri - European Journal of Operational …, 2023 - Elsevier
Abstract Container Terminals (CTs) are continuously presented with highly interrelated,
complex, and uncertain planning tasks. The ever-increasing intensity of operations at CTs in …

Domain driven data mining in human resource management: A review of current research

S Strohmeier, F Piazza - Expert Systems with Applications, 2013 - Elsevier
An increasing number of publications concerning data mining in the subject of human
resource management (HRM) indicate the presence of a prospering new research field. The …

[HTML][HTML] Technological trajectories and scenarios in seaport digitalization

T Inkinen, R Helminen, J Saarikoski - Research in Transportation Business …, 2021 - Elsevier
Digitalization has become a widely used term both in professional language and in scientific
literature. It may be seen as a manifestation of technological progression which has been …

Key factors for the success of smart ports during the post-pandemic era

CT Hsu, MT Chou, JF Ding - Ocean & Coastal Management, 2023 - Elsevier
In view of the complexity of maritime transport and the lack of a unified indicator system to
evaluate smart ports, this study analyzed the basic characteristics and service quality of …

[PDF][PDF] Intelligent human resource information system (i-HRIS): A holistic decision support framework for HR excellence.

AKM Masum, LS Beh, MAK Azad, K Hoque - Int. Arab J. Inf. Technol., 2018 - iajit.org
Nowadays, Human Resource Information System (HRIS) plays a strategic role in the
decision making process for effective and efficient Human Resource Management (HRM) …