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This study aims to explore the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19.

This research analyzes the impact of cryptocurrencies (Bitcoin, Ethereum, Monero and Ripple) on the gold, WTI, VIX index, G7 and the BRICS index before and during COVID-19, using the quantile regression approach for the 2016–2020 period. In addition, to catch long- and short-run asymmetries of cryptocurrencies on aforementioned dependent variables, an asymmetric nonlinear co-integration (nonlinear autoregressive distributed lag [NARDL]) approach is applied.

The result of the quantile regression shows that in a high market, which corresponds to the 90th quantile, the FTSE MIB, CAC40, SSE, BSE 30, and BVSP stock market showed a statistically insignificant negative coefficient, on the Bitcoin price. In a middle and low markets, which correspond to the 0.2, 0.3 and 0.5th quantiles, the BVSP, FTSE MIB, S&P/TSX, SSE and Nikkei stock markets show statistically significant and positive on Bitcoin. Evidence from the NARDL shows a statistically significant positive impact of cryptocurrencies on the gold, WTI, VIX index, G7 and BRICS indices before and during COVID-19 pandemic.

These results can provide investors with valuable analysis and information and help them make the best decisions and adopt the best strategies. Therefore, future investigations may concentrate and examine the monetary and governmental policies to be adapted to face the COVID-19 pandemic’s dangerous effects on both the society and the economy. For this reason, investors should take this into account when making their asset allocation decisions. Moreover, the portfolio managers, such as index funds, may consider few eligible cryptocurrencies for their inclusion into the portfolio. However, the speculators present in both stock and crypto markets may opt for a spread strategy to improve their portfolio returns.

The purpose of this study is to evaluate whether a diversification by grape varieties may help wine producers reduce uncertainty in quantity and quality variations due to increasingly erratic climate conditions.

This study hand-collects granular quantity and quality data from wine harvest reports for vintages 2003 to 2017 for the Valais region in Switzerland. The data allows us to obtain detailed data on harvested kilograms/liters and Oechsle/Brix degrees. It is then merged with precise meteorological data over the same sample period. The authors use this data set to capture weather conditions and their impact on harvested quantities and quality. Finally, they build portfolios including different grape varieties to evaluate whether this reduces variations in quality and quantity over vintages.

The findings highlight that the weather varies relatively strongly over the sample period and that climate hazards such as hail, frost or ensuing vine diseases effectively occur. These strongly impact the harvested quantities but less the quality of the wine. The authors further show that planting different grape varieties allows for a significant reduction in the variation of harvested quantities over time and thus acts as a good solution against climate risk.

The effect of climate change on viticulture is becoming increasingly important and felt and bears real economic and social consequences. This study transposes portfolio diversification which is central to reducing risk in the finance industry, into the wine industry and shows that the same principle holds. The authors thus propose a novel idea on how to mitigate climate risk.

Thermo-magnetic convective flow analysis under the impact of thermal radiation for heat and entropy generation phenomena is an active research field for understanding the efficiency of thermodynamic systems in various engineering sectors. This study aims to examine the characteristics of convective heat transport and entropy generation within an inverted T-shaped porous enclosure saturated with a hybrid nanofluid under the influence of thermal radiation and magnetic field.

The mathematical model incorporates the Darcy-Forchheimer-Brinkmann model and considers thermal radiation in the energy balance equation. The complete mathematical model has been numerically simulated through the penalty finite element approach at varying values of flow parameters, such as Rayleigh number (Ra), Hartmann number (Ha), Darcy number (Da), radiation parameter (Rd) and porosity value (e). Furthermore, the graphical results for energy variation have been monitored through the energy-flux vector, whereas the entropy generation along with its individual components, namely, entropy generation due to heat transfer, fluid friction and magnetic field, are also presented. Furthermore, the results of the Bejan number for each component are also discussed in detail. Additionally, the concept of ecological coefficient of performance (ECOP) has also been included to analyse the thermal efficiency of the model.

The graphical analysis of results indicates that higher values of Ra, Da, e and Rd enhance the convective heat transport and entropy generation phenomena more rapidly. However, increasing Ha values have a detrimental effect due to the increasing impact of magnetic forces. Furthermore, the ECOP result suggests that the rising value of Da, e and Rd at smaller Ra show a maximum thermal efficiency of the mathematical model, which further declines as the Ra increases. Conversely, the thermal efficiency of the model improves with increasing Ha value, showing an opposite trend in ECOP.

Such complex porous enclosures have practical applications in engineering and science, including areas like solar power collectors, heat exchangers and electronic equipment. Furthermore, the present study of entropy generation would play a vital role in optimizing system performance, improving energy efficiency and promoting sustainable engineering practices during the natural convection process.

To the best of the authors’ knowledge, this study is the first ever attempted detailed investigation of heat transfer and entropy generation phenomena flow parameter ranges in an inverted T-shaped porous enclosure under a uniform magnetic field and thermal radiation.

The study unravels the effects of climate-induced variations in staple crop yields on various migratory inflows in India while adjusting for seasonal weather and sociodemographic factors.

The instrumental variable approach is used to assess the potential effects of climate and nonclimate parameters on various migration types, exploiting panel data at the district level from the 2001 and 2011 Census years, with agriculture acting as the mediator.

As weather-driven variations in rice and wheat yield increase by 10%, the share of migration within and between districts to population decreases by 0.017 and 0.002, respectively. However, rice and wheat yields increase by 494.60 and 524.40%, respectively, with a marginal increase in the share of migration within states to population. Also, the elasticities of disadvantaged groups, literate locals and agricultural workers vary for different relocations.

The current study affirms climate migration through the agricultural channel at a finer spatial scale, asserting the sensitivity aspect of disparate movements to periodic weather and heterogeneous clusters. This is critical for effectively implementing targeted public policies in the face of increasing climate risks.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-10-2022-0710

The aim of this study is to illuminate the perceptions of the essential factors for sustaining Learning Study of the curriculum leaders who have led Learning Study in schools over a sustained period.

This study adopted a case study research approach to explore the perspectives of the curriculum leaders regarding the sustainability of Learning Study. Data were collected through interviews, observations and document analysis. To analyse the data, thematic analysis was conducted to identify themes related to the research aim.

Four themes were deemed crucial by the curriculum leaders for sustaining Learning Study: (1) integrating Learning Study into the overall development plan of the school, with milestones recognisable by all stakeholders; (2) developing a shared understanding of and patience towards the different developmental needs of stakeholders; (3) developing a sustained programme of professional development for teachers regarding variation theory of learning, which underpins Learning Study; and (4) creating an improvement culture and a safe environment for sustaining professional development. We argue that Learning Study models should be flexible that they fit various school contexts while retaining the aim of enabling learning.

Sustaining Learning Study in schools becomes a challenge if support in the form of government funding and research involvement from tertiary institutions is withdrawn. This study is the first to voice the opinions of school curriculum leaders regarding this complex issue, who play a key role in initiating, implementing and sustaining Learning Study.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

Metaverse, that is extended reality (XR)-based technologies such as augmented reality (AR) and virtual reality (VR), are increasingly believed to facilitate fundamental human practice in the future. One of the vanguards of this development has been the consumption domain, where the multi-modal and multi-sensory technology-mediated immersion is expected to enrich consumers' experience. However, it remains unclear whether these expectations have been warranted in reality and whether, rather than enhancing the experience, metaverse technologies inhibit the functioning and experience, such as cognitive functioning and experience.

This study utilizes a 2 (VR: yes vs no) × 2 (AR: yes vs no) between-subjects laboratory experiment. A total of 159 student participants are randomly assigned to one condition — a brick-and-mortar store, a VR store, an AR store and an augmented virtuality (AV) store — to complete a typical shopping task. Four spatial attention indicators — visit shift, duration shift, visit variation and duration variation — are compared based on attention allocation data converted from head movements extracted from recorded videos during the experiments.

This study identifies three essential effects of XR technologies on consumers' spatial attention allocation: the inattention effect, acceleration effect and imbalance effect. Specifically, the inattention effect (the attentional visit shift from showcased products to the environmental periphery) appears when VR or AR technology is applied to virtualize the store and disappears when AR and VR are used together. The acceleration effect (the attentional duration shift from showcased products to the environmental periphery) exists in the VR store. Additionally, AR causes an imbalance effect (the attentional duration variation increases horizontally among the showcased products).

This study provides valuable empirical evidence of how VR and AR influence consumers' spatial bias in attention allocation, filling the research gap on cognitive function in the metaverse. This study also provides practical guidelines for retailers and XR designers and developers.

The mixing of fuel and air plays a pivotal role in enhancing combustion in supersonic regime. Proper mixing stabilizes the flame and prevents blow-off. Blow-off is due to the shorter residence time of fuel and air in the combustor, as the flow is in supersonic regime. The flame is initiated in the local subsonic region created using a flameholder within the supersonic combustor. This study aims to design an effective flameholder which increases the residence time of fuel in the combustor allowing proper combustion preventing blow-off and other instabilities.

The geometry of the strut-based flameholder is altered in the present study to induce a streamwise motion of the fluid downstream of the strut. The streamwise motion of the fluid is initiated by the ramps and grooves of the strut geometry. The numerical simulations were carried out using ANSYS Fluent and are validated against the available experimental and numerical results of cold flow with hydrogen injection using plain strut as the flameholder. In the present study, numerical investigations are performed to analyse the effect on hydrogen injection in strut-based flameholders with ramps and converging grooves using Reynolds-averaged Navier–Stokes equation coupled with Menter’s shear stress transport k-ω turbulence model. The analysis is done to determine the effect of geometrical parameters and flow parameter on the flow structures near the base of the strut where thorough mixing takes place. The geometrical parameters under consideration include the ramp length, groove convergence angle, depth of the groove, groove compression angle and the Mach number. Two different strut configurations, namely, symmetric and asymmetric struts were also studied.

Higher turbulence and complex flow structures are visible in asymmetric strut configuration which develops better mixing of hydrogen and air compared to symmetric strut configuration. The variation in the geometric parameters develop changes in the fluid motion downstream of the strut. The fluid passing through the converging grooves gets decelerated thereby reducing the Mach number by 20% near the base of the strut compared to the straight grooved strut. The shorter ramps are found to be more effective, as the pressure variation in lateral direction is carried along the strut walls downstream of the strut increasing the streamwise motion of the fluid. The decrease in the depth of the groove increases the recirculation zone downstream of the strut. Moreover, the increase in the groove compression angle also increases the turbulence near the base of the strut where the fuel is injected. Variation in the injection port location increases the mixing performance of the combustor by 25%. The turbulence of the fuel jet stream is considerably changed by the increase in the injection velocity. However, the change in the flow field properties within the flow domain is marginal. The increase in fuel mass flow rate brings about considerable change in the flow field inducing stronger shock structures.

The present study identifies the optimum geometry of the strut-based flameholder with ramps and converging grooves. The reaction flow modelling may be performed on the strut geometry incorporating the design features obtained in the present study.

While digital transformation holds immense promise, organizations often fail to realize its benefits. This study aims to address how policies for digital transformation benefits realization are translated into practice.

The authors apply a qualitative, comparative case study of two large, public-sector health care organizations in Sweden. Through document and interview data, the authors analyze the process of translation.

The study finds that practice variation is primarily caused by two types of decoupling: policy-practice and means-ends. Contrary to previous studies, coercion in policy compliance is not found to decrease practice variation.

The limitations primarily stem from the empirical selection of two large public health-care organizations in Sweden, affecting the study’s generalizability. Reducing practice variation is more effectively achieved through goal alignment than coercion, leading to implications for the design of governance and control.

Policymakers should, instead of focusing on control-related compliance, work to align organizational objectives and policies to decrease practice variation for successful benefits realization.

The study contributes to better benefits realization of digital transformation initiatives in health care. As such, the authors contribute to a better functioning and more transformative health care in times of increased demand and decreased supply of health-care services.

The study challenges conventional wisdom by identifying that coercion is less effective than goal alignment in reducing practice variation, thereby enhancing the understanding of policy implementation dynamics in health-care settings.

This study aims to utilise Six Sigma in an Irish-based red meat processor to reduce process variability and improve yields.

This is a case study within an Irish meat processor where the structured Define, Measure, Analyse, Improve and Control (DMAIC) methodology was utilised along with statistical analysis to highlight areas of the meat boning process to improve.

The project led to using Six Sigma to identify and measure areas of process variation. This resulted in eliminating over-trimming of meat cuts, improving process capabilities, increasing revenue and reducing meat wastage. In addition, key performance indicators and control charts, meat-cutting templates and smart cutting lasers were implemented.

The study is one of Irish meat processors' first Six Sigma applications. The wider food and meat processing industries can leverage the learnings to understand, measure and minimise variation to enhance revenue.

Organisations can use this study to understand the benefits of adopting Six Sigma, particularly in the food industry and how measuring process variation can affect quality.

This is the first practical case study on Six sigma deployment in an Irish meat processor, and the study can be used to benchmark how Six Sigma tools can aid in understanding variation, thus benefiting key performance metrics.