EconPapers    
Economics at your fingertips  
 

MIKTA maritime research gaps: Data-driven machine learning approach for sustainable collaboration

Yong-Jae Lee

Journal of Transport Geography, 2025, vol. 128, issue C

Abstract: The maritime industry is a cornerstone of global trade but faces significant sustainability challenges. International collaboration is crucial to address these issues, particularly for middle-income nations like MIKTA countries. This study employs a data analytics and machine learning approach to identify potential areas for collaborative research in sustainable maritime technology within MIKTA. By utilizing Latent Dirichlet Allocation (LDA) topic modeling, we categorized research papers into sub-fields and identified potential collaborations. Network and self-organizing map (SOM) analyses further refined these findings, revealing three priority areas with high collaboration potential but limited research: (1) developing a Sustainable Maritime Economy Realization Model (Indonesia-Korea), (2) creating an environmentally friendly and efficient port operation system (Mexico-Australia), and (3) establishing a Sustainable Management System for port workforce safety and health (Indonesia-Turkey). These insights can inform research and policy agendas, accelerating the development and adoption of sustainable maritime technologies within MIKTA and contributing to global maritime sustainability.

Keywords: Maritime sustainability; MIKTA; Research gap; Research collaboration; Machine learning; Data analytics (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0966692325002662

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:128:y:2025:i:c:s0966692325002662

DOI: 10.1016/j.jtrangeo.2025.104375

Access Statistics for this article

Journal of Transport Geography is currently edited by Frank Witlox

More articles in Journal of Transport Geography from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-09-09
Handle: RePEc:eee:jotrge:v:128:y:2025:i:c:s0966692325002662