Business failure in post-pandemic era: New challenges for industrial networks, emerging insights and market opportunities

We would like to express our gratitude to the reviewers for helping us in shaping these valuable contributions. We are also very grateful to the IMM Co-Editors-in-Chief, Prof. Adam Lindgreen and Prof. Anthony Di Benedetto, for their unwavering support and guidance throughout this process and the opportunity to guest-edit to bring these issues to the forefront of scholarly discourse.Peer reviewedPostprin

Artificial Intelligence in Engineering Risk Analytics

Risks exist in every aspect of our lives, and can mean different things to different people. While negative in general they always cause a great deal of potential damage and inconvenience for stakeholders. Recent engineering risks include the Fukushima nuclear plant disaster from the 2011 tsunami, a year that also saw earthquakes in New Zealand, tornados in the US, and floods in both Australia and Thailand. Earthquakes, tornados (not to mention hurricanes) and floods are repetitive natural phenomenon. But the October 2011 floods in Thailand were the worst in 50 years, impacting supply chains including those of Honda, Toyota, Lenovo, Fujitsu, Nippon Steel, Tesco, and Canon. Human-induced tragedies included a clothing factory fire in Bangladesh in 2012 that left over 100 dead. Wal-Mart and Sears supply chains were downstream customers. The events of Bhopal in 1984, Chernobyl in 1986, Exxon Valdez in 1989, and the Gulf oil spill of 2010 were tragic accidents. There are also malicious events such as the Tokyo Sarin attach in 1995, The World Trade Center and Pentagon attacks in 2001, and terrorist attacks on subways in Madrid (2004), London (2005), and Moscow (2010). The news brings us reports of such events all too often. The next step up in intensity is war, which seems to always be with us in some form somewhere in the world. Complex human systems also cause problems. The financial crisis resulted in recession in all aspects of the economy. Risk and analytics has become an important topic in today’s more complex, interrelated global environment, replete with threats from natural, engineering, economic, and technical sources (Olson and Wu, 2015)

IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation

During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture

Closing Blank Spots and Illuminating Blind Spots in Research on Emerging Contaminants: The Source–Pathway–Receptor–Impact–Mitigation (SPRIM) Continuum as an Organizing Framework

Emerging contaminants (ECs) include: (1) high-technology rare earth elements, (2) nanomaterials, (3) antibiotic/antimicrobial resistance, (4) microplastics, and (5) synthetic organic chemicals, which are currently unregulated. ECs continue to attract considerable research and public attention due to their potential human and ecological health risks. However, an organizing conceptual framework for framing research on ECs is currently missing. Lacking a conceptual framework, only a few aspects are frequently well-studied (i.e., bandwagon/Matthew effect), while other equally important topics receive only cursory attention. In this Editorial perspective, the Source–Pathway–Receptor–Impact–Mitigation (SPRIM) continuum is proposed as an organizing framework to guide research on ECs. First, a description of the SPRIM continuum and its components is presented. Compared to the prevailing and seemingly ad hoc approach predominant in research on emerging contaminants, the potential novelty of applying the proposed SPRIM continuum framework is that it addresses the bandwagon, or Matthew, effect. As a decision-support tool, the SPRIM continuum framework serves a dual function as (1) a checklist to identify key knowledge gaps and frame future research, and (2) a primer for promoting the collaborative research and application of emerging big data analytics in research on emerging contaminants. Collectively, it is envisaged that the SPRIM continuum framework will provide a comprehensive and balanced understanding of various aspects of emerging contaminants relative to the current approach. The challenges of the SPRIM continuum framework as a framing and decision-support tool are also discussed. Future research directions on ECs are discussed in light of the SPRIM continuum concept. This Editorial closes with concluding remarks and a look ahead. The issues discussed are cross-cutting or generic, and thus relate to several groups of ECs, including emerging organic contaminants (EOCs), which are the focus of the current Special Issue. This Special Issue, entitled ‘Emerging Organic Contaminants in Aquatic Systems: A Focus on the Source–Pathway–Receptor–Impact–Mitigation Continuum’, calls for high-quality contributions addressing several aspects of EOCs in aquatic systems. As a Guest Editor, I welcome and look forward to several high-quality contributions addressing at least one component or the entire spectrum of the SPRIM continuum