Sustainability issues in the field of shipping, port and maritime logistics, commonly known as the maritime transport and logistics industry, have historically received less stakeholder attention as compared to aviation and overland freight sectors. However, as International Maritime Organization (IMO) regulations on ships and port/city interaction has increased since 1997, the stakeholders in the industry have gradually started paying attention to sustainability issues, across all the sectors, such as, aviation, land transport, and supply chain. As a result, the industry has accumulated a significant body of academic research outcomes over the last two decades. This Special Issue aims to examine the various themes in recent sustainability studies, particularly relating to shipping, port, and maritime logistics, and identify and discuss the key topics emerging in sustainability in the industry. It will contribute to increasing industry stakeholders’ understanding of the current situation in sustainability, assist them in the design of appropriate managerial insights and help them develop appropriate sustainability policies for the industry.

The possibilities of applying Operations Research (O.R.) techniques in the design of real-world systems are vast. The optimization and design of the supply chain network (SCN) is one of the relevant topics that has directed the attention of many scholars. Sound decisions in this regard, including the proper selection of the facility’s location, transportation modes and routes and inventory management policies, can noticeably improve the systems performance. Over 380 articles published between 2005 and 2016 in the ISI/Web of Science database have applied advanced O.R. techniques in SCN optimization studies. This paper offers a systematic review of these published contributions by focusing on two categories of O.R. approaches most recently applied for the design of SC systems: integrated mathematical modeling and simulation-optimization (S-O) frameworks. A taxonomy analysis of the mentioned approaches is presented based on the supply chain elements. A bibliometric analysis is also conducted to provide technical insights into the possible gaps in the field. Moreover, the relevant studies on SC sustainability are highlighted. The research results are supportive of the S-O frameworks as either an alternative approach or an effective solution method for the integrated problems. The research outcomes can provide researchers in the field with useful details of the integrated problems and S-O frameworks as the most recent O.R. methodologies in the field of SC optimization.

Since the world’s first Earth Summit in Rio de Janeiro in 1992, sustainability has become a focal point of significant debate for industry, government, and international organizations. As a result, research on sustainability of maritime logistics is on the rise, yet fragmented in terms of conceptual development, empirical testing and validation, and theory building. The aim of this paper is therefore two-fold: the first aim is to present a literature review of key journal articles in the field of maritime studies published between 1993 and 2017 using a technique of topic modelling; and the second is to provide future research directions with respect to major topics, themes and co-authorship patterns. Mapping and consolidation of sustainability issues are achieved by conducting a generative probabilistic text-mining technique, called latent Dirichlet allocation (LDA), for latent data discovery and relationships among text document data. Moreover, bibliometric analysis is conducted to visualize the landscape of sustainability research. Based on the results, a new intellectual structure of sustainability research is created, the underlying themes are identified, key trends and patterns are extracted and future research development trajectories are mapped for the field of maritime studies.

Supply chains can be vulnerable to sudden disruptions, especially when it emphasizes efficient operation. In this regard, supply chain resilience (SCR) has received attention recently to cope with disruptions and improve competitiveness. This paper presents a novel methodology to measure resilience between different configurations of a supply chain network (SCN), based on a number of influential factors. For this reason, data envelopment analysis (DEA) is employed to identify the best-practice and less-performing SCN configurations among a group of alternatives. On this basis, the extent to which a current configuration can improve its resiliency is also measured. The methodology is applied to the case of E1, a liquefied petroleum gas (LPG) company in Korea. Topological and operational measures were used as variables to assess resilience. The results suggest that the LPG supply chain in the case study requires an addition in the number and capacity of supply nodes in its network.

This editorial establishes the broader context for debating how the COVID-19 pandemic is affecting the global supply chains, logistics, and transportation networks in the world. The COVID-19 pandemic is an unknown-unknown risk whereby the probability of its occurrence and the possible consequences of a risk event cannot be foreseen. Furthermore, the characteristics of COVID-19 differentiate it from previous disasters in terms of the geographic scope of the impact, and the supply- and demand-side impacts, and are making relevant research challenging. In this special issue, the interwoven relationships between the COVID-19 pandemic and the challenges facing global supply chains, logistics, and transportation are discussed, along with a literature review. Selected papers on air transportation networks, emergency logistics, and digital trade are theoretically and empirically probed.

Data envelopment analysis (DEA) has many advantages for analyzing the efficiency of decision-making units, as well as drawbacks, such as a lack of discrimination power. This study applied bi-objective multiple-criteria data envelopment analysis (BiO-MCDEA), a programming approach used to overcome the limitations of traditional DEA models, to analyze the efficiency of 20 Brazilian ports with a consideration of six input and one output variables from 2010 to 2016. Two time-related variables were included to reflect current problems faced by Brazilian ports experiencing long wait times. The results reveal a significant disparity in port efficiency among Brazilian ports. The top five most efficient ports are those with the highest cargo throughput. A clustering analysis also confirmed a strong correlation between cargo throughput and port efficiency scores. Total time of stay, pier length, and courtyard also had strong correlations with the efficiency scores. The clustering method divided Brazilian ports into three groups: efficient ports, medium efficient ports, and inefficient ports.