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1 – 10 of 599Yen Sun, Citra Amanda and Berty Caroline Centana
This research aims to determine the factors that affected Bitcoin price return in the period before and during the COVID-19 pandemic.
Abstract
Purpose
This research aims to determine the factors that affected Bitcoin price return in the period before and during the COVID-19 pandemic.
Design/methodology/approach
The independent variables used in this study are hashrate, transaction volume, social media and some macroeconomics variables. The data are processed using the vector error correction model (VECM) to determine the short-term and long-term relationships between variables.
Findings
The research shows that (1) Twitter and Gold significantly affected Bitcoin in the short term before the COVID-19 pandemic; (2) hashrate, transaction volume, Twitter and the financial stress index had a significant effect on Bitcoin in the long term before the COVID-19 pandemic; (3) the volatility index had a significant effect on Bitcoin in the short term during the COVID-19 pandemic; and (4) hashrate, transaction volume, Twitter and CHF/USD had a significant effect on Bitcoin in the long term during the COVID-19 pandemic.
Research limitations/implications
This research provides explanation about factors affecting Bitcoin so investors and regulators can pay more attention and prepare for the potential risks as well as to get a good understanding of market conditions for greater crypto adoption in the future.
Originality/value
The novelty in this study is the various factors driving the Bitcoin price were analyzed before and during the COVID-19 pandemic including the social media, as sentiment, interestingly, is being a predictive power for Bitcoin price return.
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Armando Di Meglio, Nicola Massarotti and Perumal Nithiarasu
In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the…
Abstract
Purpose
In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.
Design/methodology/approach
To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.
Findings
The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.
Originality/value
The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.
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In the early 1930s, Nicholas Kaldor could be classified as an Austrian economist. The author reconstructs the intertwined paths of Kaldor and Friedrich A. Hayek to disequilibrium…
Abstract
Purpose
In the early 1930s, Nicholas Kaldor could be classified as an Austrian economist. The author reconstructs the intertwined paths of Kaldor and Friedrich A. Hayek to disequilibrium economics through the theoretical deficiencies exposed by the Austrian theory of capital and its consequences on equilibrium analysis.
Design/methodology/approach
The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.
Findings
The integration of capital theory into a business cycle theory by the Austrians and its shortcomings – e.g. criticized by Piero Sraffa and Gunnar Myrdal – called attention to the limitation of the theoretical apparatus of equilibrium analysis in dynamic contexts. This was a central element to Kaldor’s emancipation in 1934 and his subsequent conversion to John Maynard Keynes’ The General Theory of Employment, Interest, and Money (1936). In addition, it was pivotal to Hayek’s reformulation of equilibrium as a social coordination problem in “Economics and Knowledge” (1937). It also had implications for Kaldor’s mature developments, such as the construction of the post-Keynesian models of growth and distribution, the Cambridge capital controversy, and his critique of neoclassical equilibrium economics.
Originality/value
The close encounter between Kaldor and Hayek in the early 1930s, the developments during that decade and its mature consequences are unexplored in the secondary literature. The author attempts to construct a coherent historical narrative that integrates many intertwined elements and personas (e.g. the reception of Knut Wicksell in the English-speaking world; Piero Sraffa’s critique of Hayek; Gunnar Myrdal’s critique of Wicksell, Hayek, and Keynes; the Hayek-Knight-Kaldor debate; the Kaldor-Hayek debate, etc.) that were not connected until now by previous commentators.
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Is there a secret recipe for economic growth?
Abstract
Purpose
Is there a secret recipe for economic growth?
Design/methodology/approach
No, there is no recipe, but we can extrapolate some pieces of advice from Adam Smith.
Findings
An economy can leave behind its “dull” stagnant state and grow when its markets expand, when the productivity of its workers increases thanks to high compensations, which are seen as incentives to work harder and when lobbying and cronyism are kept at bay. Luck plays a role too, but these three ingredients are necessary, even if not sufficient, for an economy to grow and thus be “cheerful.”
Originality/value
These three aspects – expansion of market, liberal compensation of workers and lobbying – especially combined, have often been underestimated in Smith’s understanding of the possible sources of economic growth.
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Germana Giombini, Francesca Grassetti and Edgar Sanchez Carrera
The authors analyse a growth model to explain how economic fluctuations are primarily driven by productive capacities (i.e. capacity utilization driven by innovations and…
Abstract
Purpose
The authors analyse a growth model to explain how economic fluctuations are primarily driven by productive capacities (i.e. capacity utilization driven by innovations and know-how) and productive inefficiencies.
Design/methodology/approach
This study’s methodology consists of the combination of the economic growth model, à la Solow–Swan, with a sigmoidal production function (in capital), which may explain growth, poverty traps or fluctuations depending on the relative levels of inefficiencies, productive capacities or lack of know-how.
Findings
The authors show that economies may experience economic growth, poverty traps and/or fluctuations (i.e. cycles). Economic growth is reached when an economy experiences both a low level of inefficiencies and a high level of productive capacities while an economy falls into a poverty trap when there is a high level of inefficiencies in production. Instead, the economy gets in cycles when there is a large level of the lack of know-how and low levels of productive capacity.
Originality/value
The authors conclude that more capital per capita (greater savings and investment) and greater productive capacity (with less lack of know-how) are the economic policy keys for an economy being on the path of sustained economic growth.
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This paper introduces a new mathematical model for analyzing the economic benefits of incorporating the fourth party logistics (4PL), which is a contractor (i.e. agent) for the…
Abstract
This paper introduces a new mathematical model for analyzing the economic benefits of incorporating the fourth party logistics (4PL), which is a contractor (i.e. agent) for the supply chain coordination and construction based on the division of community and the outsourcing development. Based on the physical theory and the wave-particle duality, a supply chain is the special organization whose characteristic has wave-particle duality. The mathematical model enriches the connotation of 4PL and it broadens the thought for 4PL development. Secondly, the proposed mathematical model predicated on transaction costs, is supported by Transaction Cost Theory (TCT) and acts as the theoretical analysis tool of 4PL for coordinating 3-party generic supply chain. Through the model, some trendy conclusions can be drawn to provide theoretical support for 4PL’s practices. Finally, a case illustrates our conclusions.
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Sharika J. Hegde, Hani Mahmassani and Karen Smilowitz
The purpose of this paper is to develop a framework to evaluate and assess the performance of the COVID-19 vaccine distribution process that is sensitive to the unique supply-side…
Abstract
Purpose
The purpose of this paper is to develop a framework to evaluate and assess the performance of the COVID-19 vaccine distribution process that is sensitive to the unique supply-side and demand-side constraints exhibited in the US vaccine rollout.
Design/methodology/approach
A queuing framework that operates under two distinct regimes is formulated to analyze service rates that represent system capacity to vaccinate (under the first regime) and hesitancy-induced throughput (under the second regime). These supply- and hesitancy-constrained regimes form the focus of the present paper, as the former reflects the inherent ability of the nation in its various jurisdictions to mobilize, whereas the latter reflects a critical area for public policy to protect the population’s overall health and safety.
Findings
The two-regime framework analysis provides insights into the capacity to vaccinate and hesitancy-constrained demand, which is found to vary across the country primarily by politics and region. The framework also allows analysis of the end-to-end supply chain, where it is found that the ability to vaccinate was likely constrained by last-mile administration issues, rather than the capacity of the manufacturing and transportation steps of the supply chain.
Originality/value
This study presents a new framework to consider end-to-end supply chains as dynamic systems that exhibit different regimes because of unique supply- and demand-side characteristics and estimate rollout capacity and underlying determinants at the national, state and county levels.
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Sarath Radhakrishnan, Joan Calafell, Arnau Miró, Bernat Font and Oriol Lehmkuhl
Wall-modeled large eddy simulation (LES) is a practical tool for solving wall-bounded flows with less computational cost by avoiding the explicit resolution of the near-wall…
Abstract
Purpose
Wall-modeled large eddy simulation (LES) is a practical tool for solving wall-bounded flows with less computational cost by avoiding the explicit resolution of the near-wall region. However, its use is limited in flows that have high non-equilibrium effects like separation or transition. This study aims to present a novel methodology of using high-fidelity data and machine learning (ML) techniques to capture these non-equilibrium effects.
Design/methodology/approach
A precursor to this methodology has already been tested in Radhakrishnan et al. (2021) for equilibrium flows using LES of channel flow data. In the current methodology, the high-fidelity data chosen for training includes direct numerical simulation of a double diffuser that has strong non-equilibrium flow regions, and LES of a channel flow. The ultimate purpose of the model is to distinguish between equilibrium and non-equilibrium regions, and to provide the appropriate wall shear stress. The ML system used for this study is gradient-boosted regression trees.
Findings
The authors show that the model can be trained to make accurate predictions for both equilibrium and non-equilibrium boundary layers. In example, the authors find that the model is very effective for corner flows and flows that involve relaminarization, while performing rather ineffectively at recirculation regions.
Originality/value
Data from relaminarization regions help the model to better understand such phenomenon and to provide an appropriate boundary condition based on that. This motivates the authors to continue the research in this direction by adding more non-equilibrium phenomena to the training data to capture recirculation as well.
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This paper aims to present the basic assumptions for creation of social Fröhlich condensate and attract attention of other researchers (both from physics and socio-political…
Abstract
Purpose
This paper aims to present the basic assumptions for creation of social Fröhlich condensate and attract attention of other researchers (both from physics and socio-political science) to the problem of modeling of stability and order preservation in highly energetic society coupled with social energy bath of high temperature.
Design/methodology/approach
The model of social Fröhlich condensation and its analysis are based on the mathematical formalism of quantum thermodynamics and field theory (applied outside of physics).
Findings
The presented quantum-like model provides the consistent operational model of such complex socio-political phenomenon as Fröhlich condensation.
Research limitations/implications
The model of social Fröhlich condensation is heavily based on theory of open quantum systems. Its consistent elaboration needs additional efforts.
Practical implications
Evidence of such phenomenon as social Fröhlich condensation is demonstrated by stability of modern informationally open societies.
Social implications
Approaching the state of Fröhlich condensation is the powerful source of social stability. Understanding its informational structure and origin may help to stabilize the modern society.
Originality/value
Application of the quantum-like model of Fröhlich condensation in social and political sciences is really the novel and original approach to mathematical modeling of social stability in society exposed to powerful information radiation from mass-media and Internet-based sources.
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Keisuke Kaneko, Fumihito Sasamori, Masao Okuhara, Suchinda Jarupat Maruo, Kazuki Ashida, Hisaaki Tabuchi, Hisaki Akasaki, Kazuki Kobayashi, Yuya Aoyagi, Noriaki Watanabe, Tomoyuki Nishino and Koji Terasawa
This study aims to evaluate a human rights-informed dementia prevention program promoting better health and social care among older adults. In this study, the authors examined…
Abstract
Purpose
This study aims to evaluate a human rights-informed dementia prevention program promoting better health and social care among older adults. In this study, the authors examined whether a dual-task training would improve cognition in healthy older adults.
Design/methodology/approach
Individuals attending the systematic health education program for older adults based in Japan were recruited for study inclusion, and divided into a dual-task training group (TG) and a control group (CG). The TG underwent 90 min of a weekly dual-task training for 12 weeks. Severity of dementia was measured using the Mini-Mental State Examination (MMSE) test. Brain function was assessed using a go/no-go task paradigm, during which cerebral blood flow was additionally measured using functional near-infrared spectroscopy to quantify oxyhemoglobin (oxy-Hb).
Findings
MMSE total score, number of errors in the go/no-go tasks and oxy-Hb values showed significant improvements in the TG.
Research limitations/implications
Owing to the small number of participants allocated to the CG, the results must be interpreted with caution. Replication and further validation based on large-scale, randomized-controlled trials is warranted.
Practical implications
This study highlights potential benefits of incorporating an early prevention training for dementia into a human rights-friendly health education program.
Social implications
This study suggests a potential means to reduce costs of social security and health care by introducing a human rights-informed dementia prevention program.
Originality/value
The results suggest that dual-task training may improve cognitive function in healthy older adults, thereby contributing to better health and improvement of social health care, based on a human rights-informed health education program for the prevention of dementia.
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