Dynamical memristors for higher-complexity neuromorphic computing

Nature Reviews Materials, Journal Year: 2022, Volume and Issue: 7(7), P. 575 - 591

Published: April 8, 2022

Language: Английский

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The Evolution of the Dynamic Capabilities Framework

FGF studies in small business and entrepreneurship, Journal Year: 2022, Volume and Issue: unknown, P. 113 - 129

Published: Oct. 29, 2022

Abstract The chapter sketches the past, present, and potential future of dynamic capabilities framework. This essay is more by way a personal reflection on progress that has been made to date work remaining be done. framework proved fertile ground for research there no evidence its momentum slowing. In addition, I see having numerous applications, several which have addressed in my own writing: (1) can serve as an overarching paradigm teaching business schools; (2) potentially built into theory firm; (3) policy tool industrializing economies help them understand difference between accumulation assimilation. Finally, innovation, including digital transformation, corporate entrepreneurship, organizational behavior also contribute theoretical soundness

Language: Английский

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Bifurcation analysis and complex dynamics of a Kopel triopoly model

Journal of Computational and Applied Mathematics, Journal Year: 2023, Volume and Issue: 426, P. 115089 - 115089

Published: Jan. 24, 2023

Language: Английский

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Simulating institutional heterogeneity in sustainability science

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(8)

Published: Feb. 15, 2024

Sustainability outcomes are influenced by the laws and configurations of natural engineered systems as well activities in socio-economic systems. An important subset human activity is creation implementation institutions, formal informal rules shaping a wide range behavior. Understanding these codifying them computational models can provide missing insights into why function way they do (static) pace structure transitions required to improve sustainability (dynamic). Here, we conduct comparative synthesis three modeling approaches— integrated assessment modeling, engineering–economic optimization, agent-based modeling—with underexplored potential represent institutions. We first perform experiments on climate mitigation that specific aspects heterogeneous including policies institutional coordination, attitudes norms. find measurable but uneven aggregate impacts, while more politically meaningful distributional impacts large across various actors. Our results show omitting institutions influence costs miss opportunities leverage forces speed up emissions reduction. These allow us explore capacity each approach insitutions lay out vision for next frontier endogenizing change science models. To bridge gap between theories, empirical evidence social this research agenda calls joint efforts modelers who wish incorporate detail, scientists studying socio-political economic foundations transitions.

Language: Английский

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Agent-Based Modeling in Economics and Finance: Past, Present, and Future

Journal of Economic Literature, Journal Year: 2025, Volume and Issue: 63(1), P. 197 - 287

Published: March 1, 2025

Agent-based modeling (ABM) is a novel computational methodology for representing the behavior of individuals in order to study social phenomena. Its use rapidly growing many fields. We review ABM economics and finance highlight how it can be used relax conventional assumptions standard economic models. has enriched our understanding markets, industrial organization, labor, macro, development, public policy, environmental economics. In financial substantial accomplishments include clustered volatility, market impact, systemic risk, housing markets. present vision ABMs might future build more realistic models economy some hurdles that must overcome achieve this. (JEL C63, D00, E00, G00)

Language: Английский

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Lessons from COVID-19 for managing transboundary climate risks and building resilience

Climate Risk Management, Journal Year: 2022, Volume and Issue: 35, P. 100395 - 100395

Published: Jan. 1, 2022

COVID-19 has revealed how challenging it is to manage global, systemic and compounding crises. Like COVID-19, climate change impacts, maladaptive responses them, have potential disrupt societies at multiple scales via networks of trade, finance, mobility communication, impact hardest on the most vulnerable. However, these complex systems can also facilitate resilience if managed effectively. This review aims distil lessons related transboundary management risks from experience, inform policy building. Evidence diverse fields synthesised illustrate nature our evolving understanding resilience. We describe research methods that aim capture complexity better practices increase Finally, we recommend specific, practical actions for improving risk These include mapping direct, cross-border cross-sectoral impacts extremes, adopting adaptive strategies embrace heterogenous decision-making uncertainty, taking a broader approach which elevates human wellbeing, including societal ecological

Language: Английский

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Complexity in Epidemiology and Public Health. Addressing Complex Health Problems Through a Mix of Epidemiologic Methods and Data

Epidemiology, Journal Year: 2023, Volume and Issue: 34(4), P. 505 - 514

Published: April 12, 2023

Public health and the underlying disease processes are complex, often involving interaction of biologic, social, psychologic, economic, other that may be nonlinear adaptive have features complex systems. There is therefore a need to push boundaries public beyond single-factor data analysis expand capacity research methodology tackle real-world complexities. This article sets out way operationalize systems thinking in health, with particular focus on how epidemiologic methods can contribute towards this end. Our proposed framework comprises three core dimensions-patterns, mechanisms, dynamics-along which conceptualized. These dimensions cover seven key systems-emergence, interactions, nonlinearity, interference, feedback loops, adaptation, evolution. We relate examples traditionally used epidemiology. conclude systematic production knowledge issues benefit from: formulation questions programs terms we identify, as comprehensive capture crucial systems; integration traditional such computational simulation modeling; interdisciplinary work; continued investment wide range types. believe support problems, use epidemiology disciplines. will help us understand emergent phenomena, identify vulnerable population groups, detect leverage points for promoting health.

Language: Английский

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Decline processes in technological innovation systems: Lessons from energy technologies

Research Policy, Journal Year: 2025, Volume and Issue: 54(3), P. 105174 - 105174

Published: Jan. 24, 2025

Language: Английский

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Modelling the bioeconomy: Emerging approaches to address policy needs

Journal of Cleaner Production, Journal Year: 2021, Volume and Issue: 330, P. 129801 - 129801

Published: Nov. 23, 2021

With its update of the Bioeconomy Strategy and Green Deal, European Commission committed itself to a transformation towards sustainable climate-neutral Union. This process is characterised with an enormous complexity, which policymaking needs acknowledge for designing transition pathways. Modelling can support in dealing uncertainty complexity. article reviews emerging new developments approaches model development bioeconomy. We focused our review on how bioeconomy modelling addresses key enabling factors related (i) climate change, (ii) biodiversity, (iii) circular use biomass, (iv) consumer behaviour biomass bioproducts use, (v) innovation technological change. find that existing frameworks offer large possibilities extensions considerations analysing short-run impacts change circularity, lesser degree we identify developing further models. However, addressing processes societal changes more challenging existing/conventional approaches, as they specifically relate innovations transform economic structures consumers learn their preferences what kind dynamics are be expected. indicate techniques such Agent-Based could improve complement efforts by allowing consideration structural and, generally, metabolism. approach eclecticism asks better description targets, sound reflection meaning time horizons closer cooperation between different research communities. Furthermore, it will benefit from big data artificial intelligence expect valuable guideposts future strategies.

Language: Английский

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Digital Transformation and Sustainable Oriented Innovation: A System Transition Model for Socio-Economic Scenario Analysis

Sustainability, Journal Year: 2021, Volume and Issue: 13(21), P. 11564 - 11564

Published: Oct. 20, 2021

Sustainability and digitalization are essential duties for companies to perform in the current socio-economic landscape due risks caused by traditional manufacturing practices, rules imposed stakeholders governments. Tools that help exploring uncertain future scenarios address such a complex challenge of vital importance both businesses, governments, financial institutions. This paper presents IN4.0-SD, novel system dynamics model capture dynamic interplay industrial innovation, inequality, inflation. The IN4.0-SD is closed-economy System Dynamics composed three agents: sustainable oriented innovation business (SOIB), digital asset supplier (DASB), household. DASB SOIB assumed supply one product economy fundamentally differ among each other their models. While produces sells capital goods making revenue out sales, detaches concept production from sales moving toward an intangible economy, charging fee licence tools can be distributed via network economy. Simulations show level flexibility addressing variety scenarios, playing at threshold technology development, inequality rise, massive unemployment providing archetype transformation findings suggested analysis used infer conclusions wider society, including implications businesses transformation. These confirmed previous studies, around overall trend wealth creation large firms’ owners, potential impact employment labour market.

Language: Английский

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