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To explore how the blockchain affects the pricing and financing decisions in a low-carbon platform supply chain.

Considering the dual roles of the e-commerce platform as a seller and an initiator, a typical game-theoretical method is applied to analyze the behavior of supply chain decision-makers and the impact of key variables on equilibriums.

When loan interest rates are symmetric, whether blockchain is used or not, the e-commerce platform financing mode will always produce higher wholesale price and unit carbon emission reduction, while the retail price is the opposite. Higher unit additional income brought by the blockchain can bring higher economic and environmental performances, and the e-commerce platform financing mode is superior to bank financing mode. The application of blockchain may cause the manufacturer to change his/her financing choice. For bank financing, with the increase of loan interest rates, the advantages brought by blockchain will gradually disappear, but this situation will not occur under e-commerce platform financing.

Blockchain is known for its information transparency properties and its ability to enhance user trust. However, the impacts of applying blockchain in a low-carbon platform supply chain with different financing options are not clear. The authors examine the manufacturer's strategic choices for platform financing and bank financing, whether to adopt blockchain, and the impact of these decisions on carbon emissions reduction, consumer surplus and social welfare. The research conclusion can provide reference for the operation and financing decisions of platform supply chain under the carbon reduction target in the digital economy era.

This research focuses on the controlling irreversibilities in a radiative, chemically reactive electromagnetohydrodynamics (EMHD) flow of a nanofluid toward a stagnation point. Key considerations include the presence of Ohmic dissipation, linear thermal radiation, second-order chemical reaction with the multiple slips. With these factors, this study aims to provide insights for practical applications where thermal management and energy efficiency are paramount.

Lie group transformation is used to revert the leading partial differential equations into nonlinear ODE form. Hence, the solutions are attained analytically through differential transformation method-Padé and numerically using the Runge–Kutta–Fehlberg method with shooting procedure, to ensure the precise and reliable determination of the solution. This dual approach highlights the robustness and versatility of the methods.

The system’s entropy generation is enhanced by incrementing the magnetic field parameter (M), while the electric field (E) and velocity slip parameters (ξ) control its growth. Mass transportation irreversibility and the Bejan number (Be) are significantly increased by the chemical reaction rate (C_r). In addition, there is a boost in the rate of heat transportation by 3.66% while 0.05⩽ξ⩽0.2; meanwhile for 0.2⩽ξ⩽1.1, the rate of mass transportation gets enhanced by 12.87%.

This paper presents a novel approach to analyzing the entropy optimization in a radiative, chemically reactive EMHD nanofluid flow near a stagnation point. Moreover, this research represents a significant advancement in the application of analytical techniques, complemented by numerical approaches to study boundary layer equations.

This investigation delves into the rationale behind the preferential applicability of the non-Newtonian nanofluid model over alternative frameworks, particularly those incorporating porous medium considerations. The study focuses on analyzing the mass and heat transfer characteristics inherent in the Williamson nanofluid’s non-Newtonian flow over a stretched sheet, accounting for influences such as chemical reactions, viscous dissipation, magnetic field and slip velocity. Emphasis is placed on scenarios where the properties of the Williamson nanofluid, including thermal conductivity and viscosity, exhibit temperature-dependent variations.

Following the use of the OHAM approach, an analytical resolution to the proposed issue is provided. The findings are elucidated through the construction of graphical representations, illustrating the impact of diverse physical parameters on temperature, velocity and concentration profiles.

Remarkably, it is discerned that the magnetic field, viscous dissipation phenomena and slip velocity assumption significantly influence the heat and mass transmission processes. Numerical and theoretical outcomes exhibit a noteworthy level of qualitative concurrence, underscoring the robustness and reliability of the non-Newtonian nanofluid model in capturing the intricacies of the studied phenomena.

Available studies show that no work on the Williamson model is conducted by considering viscous dissipation and the MHD effect past over an exponentially stretched porous sheet. This contribution fills this gap.

This study investigates the behavior of viscous hybrid ferromagnetic fluids flowing through plain elastic sheets with the magnetic polarization effect. It examines flow in a porous medium using Stefan blowing and utilizes a versatile hybrid ferrofluid containing MnZnFe₂O₄ and Fe₃O₄ nanoparticles in the C2H2F4 base fluid, offering potential real-world applications. The study focuses on steady, laminar and viscous incompressible flow, analyzing heat and mass transfer aspects, including thermal radiation, Brownian motion, thermophoresis and viscous dissipation with convective boundary condition.

The governing expression of the flow model is addressed with pertinent non-dimensional transformations, and the finite element method solves the obtained system of ordinary differential equations.

The variations in fluid velocity, temperature and concentration profiles against all the physical parameters are analyzed through their graphical view. The association of these parameters with local surface friction coefficient, Nusselt number and Sherwood number is examined with the numerical data in a table.

This work extends previous research on ferrofluid flow, investigating unexplored parameters and offering valuable insights with potential engineering, industrial and medical implications. It introduces a novel approach that uses mathematical simplification techniques and the finite element method for the solution.

Recent advancements in technology have led to the exploration of solar-based thermal radiation and nanotechnology in the field of fluid dynamics. Solar energy is captured through sunlight absorption, acting as the primary source of heat. Various solar technologies, such as solar water heating and photovoltaic cells, rely on solar energy for heat generation. This study focuses on investigating heat transfer mechanisms by utilizing a hybrid nanofluid within a parabolic trough solar collector (PTSC) to advance research in solar ship technology. The model incorporates multiple effects that are detailed in the formulation.

The mathematical model is transformed using suitable similarity transformations into a system of higher-order nonlinear differential equations. The model was solved by implementing a numerical procedure based on the Wavelets and Chebyshev wavelet method for simulating the outcome.

The velocity profile is reduced by Deborah's number and velocity slip parameter. The Ag-EG nanoparticles mixture demonstrates less smooth fluid flow compared to the significantly smoother fluid flow of the Ag-Fe3O4/EG hybrid nanofluids (HNFs). Additionally, the Ag-Ethylene Glycol nanofluids (NFs) exhibit higher radiative performance compared to the Ag-Fe3O4/Ethylene Glycol hybrid nanofluids (HNFs).

Additionally, the Oldroyd-B hybrid nanofluid demonstrates improved thermal conductivity compared to traditional fluids, making it suitable for use in cooling systems and energy applications in the maritime industry.

The originality of the study lies in the exploration of the thermal transport enhancement in sun-powered energy ships through the incorporation of silver-magnetite hybrid nanoparticles within the heat transfer fluid circulating in parabolic trough solar collectors. This particular aspect has not been thoroughly researched previously. The findings have been validated and provide a highly positive comparison with the research papers.

Performance optimization algorithms based on node attributes are of great importance for sharding blockchain systems. Currently, existing studies on blockchain sharding algorithms consider only random selection sharding strategies. However, the random selection strategy does not perfectly utilize the performance of a node to break the bottleneck of blockchain performance.

This paper proposes a blockchain sharding algorithm called TOPSIS Optimization Sharding System (TOSS), which is based on entropy weight method, relative Euclidean distance and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). It defines a multi-attribute matrix to assess node performance and applies TOPSIS for scoring nodes. Then, an algorithm based on the TOPSIS method is proposed to calculate the performance score of each data node. In addition, an entropy weighting method is introduced to obtain the weights of each attribute to balance the impact of dimensional differences of attributes on the attribute weights. Nodes are ranked by composite scores to guide partitioning.

The effectiveness of the proposed algorithm in this paper is verified by comparing it with various comparative algorithms. The experimental results show that the TOSS algorithm outperforms the comparison algorithms in terms of performance improvement for the blockchain system, and the throughput metrics are improved by about 20% in comparison.

This study introduces a novel approach to blockchain sharding by incorporating the entropy weight method and relative Euclidean distance TOPSIS into the sharding process. This approach allows for a more effective utilization of node performance attributes, leading to significant improvements in system throughput and overall performance, addressing the limitations of the random selection strategy commonly used in existing algorithms.

Interconnections among banks are an essential feature of the banking system as it helps in an effective payment system and liquidity management. However, it can be a nightmare during a crisis when these interconnections can act as contagion channels. Therefore, it becomes essentially important to identify good links (non-contagious channels) and bad links (contagious channels).

The article estimated systemic risk using quantile regression through the ΔCoVaR approach. The interconnected phenomenon among banks has been analyzed through Granger causality, and the systemic network properties are evaluated. The authors have developed a fixed effect panel regression model to predict interconnectedness. Profitability-adjusted systemic index is framed to identify good (non-contagious) or bad (contagious) channels. The authors further developed a logit model to find the probability of a link being non-contagious. The study sample includes 36 listed Indian banks for the period 2012 to 2018.

The study indicated interconnections increased drastically during the Indian non-performing asset crisis. The study highlighted that contagion channels are higher than non-contagious channels for the studied periods. Interbank bad distance dominates good distance, highlighting the systemic importance of banking network. It is also found that network characteristics can act as an indicator of a crisis.

The study is the first to differentiate the systemic contagious and non-contagious channels in the interbank network. The uniqueness also lies in developing the normalized systemic index, where systemic risk is adjusted to profitability.

The Belt and Road Initiative (BRI) was launched in 2013 and implemented the following year, marking 11 years since its inception. During this time, numerous research papers have been published that analyse the initiative’s objectives, targets and potential outcomes. This study aims to assess India’s resilience in joining the BRI by examining its net foreign direct investment (FDI) compared to a counterfactual scenario involving participation in the initiative.

The synthetic control method (SCM) will be used using a panel of 27 countries from 1990 to 2021.

The findings reveal that India’s FDI trajectory has decreased compared to that of synthetic India constructed from BRI member countries.

This research outcome can assist India and other nations that are contemplating joining the BRI to systematically evaluate the potential political and economic risks and benefits associated with the initiative. This evaluation can guide individual decision-making processes regarding the BRI on a case-by-case basis and with other outcomes that are deemed viable to each country.

This research is distinct from other studies because it uses a novel SCM analysis, which is a quasi-experimental technique that assesses actual outcomes rather than predicting them, as in conventional regression models. In addition, previous research has primarily focused on the political aspects of the initiative; however this study focuses on the economic aspect of the BRI by evaluating its impact on FDI.

This study aims to explore the influence of corporate sustainability on organizational value, specifically focusing on companies ranked in the Just Capital Market ranking. The aim is to establish whether higher sustainability rankings are associated with increased firm value and to investigate how corporate social responsibility (CSR) activities affect both financial and non-financial outcomes.

This study uses the Ohlson model to assess the value-generation potential of the top and bottom ten companies in the Just Capital Market ranking from 2013 to 2018. The analysis involves evaluating stock prices and other financial metrics and incorporating non-financial indicators related to CSR activities to gain a comprehensive understanding of their impact on firm valuation.

The results indicate a strong connection between high sustainability rankings and increased market value. Companies such as Microsoft, Intel and Alphabet, which have robust CSR initiatives, have shown significant improvements in market performance due to greater stakeholder engagement and detailed non-financial disclosures. On the other hand, companies with low sustainability ratings have demonstrated weaker market performance, which indicates the financial risks associated with neglecting CSR activities. This study underscores the critical importance of integrating CSR into fundamental business strategies to create sustainable value.

This study addresses the limitations of traditional financial indicators by incorporating non-financial factors into the valuation process. The study offers a more comprehensive assessment of firm value, reflecting modern business practices and the evolving global economy landscape. Integrating nonfinancial indicators enhances valuation accuracy and provides a holistic view of company performance, enabling stakeholders to make informed decisions based on a broader range of factors. This innovative method may reshape firm valuations, leading to more accurate and reliable assessments in contemporary business contexts.