The current Coronavirus infection (COVID-19) outbreak has had a substantial impact on many aspects of general life. Although a number of studies have been published on the topic already, there has not been a critical review of studies on the impacts of COVID-19 by and on environmental factors. The current study fills this gap by presenting a critical analysis of 57 studies on the nexus between COVID-19 and the environment, published in nine journals up to May 2020. Majority of the studies in our sample are published in Science of the Total Environment (74%), and studies used mostly descriptive statistics and regression as research methods. We identified four underlying research clusters based on a systematic content analysis of the studies. The clusters are: (1) COVID-19 and environmental degradation, (2) COVID-19 and air pollution, (3) COVID-19 and climate/metrological factors and (4) COVID-19 and temperature. Besides a critical analysis of the studies in each cluster, we propose research questions to guide future research on the relationship between COVID-19 and the environment.

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Considering 91 countries with seaports, this study conducted an empirical inquiry into the broader economic contribution of seaborne trade, from a port infrastructure quality and logistics performance perspective. Investment in quality improvement of port infrastructure and its contribution to economy are often questioned by politicians, investors and general public. A structural equation model (SEM) is used to provide empirical evidence of significant economic impacts of port infrastructure quality and logistics performance. Furthermore, analysis of a multigroup SEM is performed by dividing countries into developed and developing economy groups. The results reveal that it is vital for developing countries to continuously improve the quality of port infrastructure as it contributes to better logistics performance, leading to higher seaborne trade, yielding higher economic growth. However, this association weakens as the developing countries become richer.

Purpose Earlier firms were evaluated mostly from their financial performance perspective, but with the increasing attention to sustainability goals, environmental, social and governance (ESG) performance of firms became key concerns to stakeholders. The purpose of this paper is to explore the effects of ESG performance of banks on their financial performance, in the context of emerging markets. Design/methodology/approach This study employs the generalised method of moments technique for estimation purpose due to the dynamic nature of the data and to correct for endogeneity. This study uses the ESG performance data of 93 emerging market banks from 2015 to 2018, available in Asset4 ESG database of Refinitiv, formerly known as Thompson Reuters. The accounting and financial data are collected from Refinitiv Datastream database. Findings The findings indicate a positive association of emerging market banks’ environmental and social performance with their financial performance, but governance performance does not influence financial performance. Originality/value While many studies exist on the association of ESG concerns of an organisation with their financial profitability, the literature on in the context of banking is still limited. To the best of the authors’ knowledge, this is the first study that examines the effect of ESG practices of banks on their financial performance in the context of emerging economies.

This study provides a bibliometric review of 279 studies on the applications of big data and artificial intelligence (AI) in the maritime industry, published in 214 academic outlets, authored by 842 scholars. We extracted bibliographical data from the Web of Science database and analysed it using the Bibliometrix tool in R software. Based on citation analysis metrics, we revealed the most influential articles, journals, authors and institutions. Using the bibliographic coupling methodology, we identified four underlying research clusters: (1) digital transformation in maritime industry, (2) applications of big data from AIS, (3) energy efficiency and (4) predictive analytics. We analysed these clusters in detail and extracted future research questions. Besides, we present research collaboration networks on the institution and author level.

PurposeThe study identifies nine important research areas and critically maps the structural relationships among supply chain resilience (SCRES) dimensions, namely, vulnerabilities, capabilities, strategies and performance metrics. The analysis also revealed various influential authors, journals, institutions and trending articles, across SCRES literature.Design/methodology/approachThis study performs a bibliometric analysis of 771 articles published over the 32 years from 1988 to 2020, and network analysis in combination with content analysis of 90 most cited articles published in research fronts of SCRES.FindingsThe results demonstrate the underlying research areas within the SCRES, which are clustered into nine research themes: (1) conceptual development of SCRES, (2) recent developments of designing resilient supply chain (SC) networks, (3) focus on identifying drivers of SC vulnerability and risks, (4) impact of risks on network resilience, (5) risk assessment to avoid breakdowns/disruptions, (6) measuring resilience approaches/drivers to improve SC performance, (7) building resilient capabilities by integrating other SC dimensions, (8) quantification of SC network and (9) emphasis on developing robustness in SC networks.Practical implicationsThis research offers implications for classifying the works in literature based on bibliometric information and network analysis techniques. This can help researchers and practitioners to understand the prominent areas in SCRES and provide guidelines for future research in this area.Originality/valueThis study provides an overview of the evolution of SCRES over time in the domain of supply chain management and also outlines a future research agenda claimed by the trending articles to encourage further investigations in the field of SCRES.