33,810 research outputs found

    Global Risks 2014, Ninth Edition.

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    The Global Risks 2014 report highlights how global risks are not only interconnected but also have systemic impacts. To manage global risks effectively and build resilience to their impacts, better efforts are needed to understand, measure and foresee the evolution of interdependencies between risks, supplementing traditional risk-management tools with new concepts designed for uncertain environments. If global risks are not effectively addressed, their social, economic and political fallouts could be far-reaching, as exemplified by the continuing impacts of the financial crisis of 2007-2008

    Global Risks 2015, 10th Edition.

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    The 2015 edition of the Global Risks report completes a decade of highlighting the most significant long-term risks worldwide, drawing on the perspectives of experts and global decision-makers. Over that time, analysis has moved from risk identification to thinking through risk interconnections and the potentially cascading effects that result. Taking this effort one step further, this year's report underscores potential causes as well as solutions to global risks. Not only do we set out a view on 28 global risks in the report's traditional categories (economic, environmental, societal, geopolitical and technological) but also we consider the drivers of those risks in the form of 13 trends. In addition, we have selected initiatives for addressing significant challenges, which we hope will inspire collaboration among business, government and civil society communitie

    Lean and green – a systematic review of the state of the art literature

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    The move towards greener operations and products has forced companies to seek alternatives to balance efficiency gains and environmental friendliness in their operations and products. The exploration of the sequential or simultaneous deployment of lean and green initiatives is the results of this balancing action. However, the lean-green topic is relatively new, and it lacks of a clear and structured research definition. Thus, this paper’s main contribution is the offering of a systematic review of the existing literature on lean and green, aimed at providing guidance on the topic, uncovering gaps and inconsistencies in the literature, and finding new paths for research. The paper identifies and structures, through a concept map, six main research streams that comprise both conceptual and empirical research conducted within the context of various organisational functions and industrial sectors. Important issues for future research are then suggested in the form of research questions. The paper’s aim is to also contribute by stimulating scholars to further study this area in depth, which will lead to a better understanding of the compatibility and impact on organisational performance of lean and green initiatives. It also holds important implications for industrialists, who can develop a deeper and richer knowledge on lean and green to help them formulate more effective strategies for their deployment

    Big Data and the Internet of Things

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    Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

    Can Industry 5.0 Technologies Overcome Supply Chain Disruptions? - A Perspective Study on Pandemics, War, and Climate Change Issues

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    Industry 5.0 (I5.0) is the next industrial revolution that will leverage human intervention in collaboration with intelligent, logical, and smart machines to attain even more user-preferred and resource-efficient manufacturing and supply chain solutions. The main aim of this article is to study I5.0 technologies in supply chains when these are affected by disruptive phenomena such as those created by wars, climate change or pandemics. A systematic literature review methodology was conducted to understand the present knowledge connected with this theme. This study summarises 194 research articles from the period 2009 to 2022 to understand the present knowledge connected with this theme. The research findings show a significant gap related to the adoption of I5.0 technologies to prevent or overcome supply chain disruptions. 194 articles, including journal and review articles, were identified in the literature. The study provides a novel and insightful concept related to I5.0 within the context of supply chain disruptions. The potential applications of I5.0 and Industry 4.0 are elaborately discussed in three areas, namely: (1) disruptions in supply chains due to pandemics; (2) disruptions in supply chains due to war; and (3) disruptions in supply chains due to climate change. Finally, this study highlights research implications and proposes future research avenues that will contribute to further exploring the adoption of I5.0 technologies to prevent, manage and overcome disruptions in supply chains

    Research and Education in Computational Science and Engineering

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    Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie
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