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This paper aims to investigate the non-overlapped winding dual stator electrically excited flux switching machine (NOW-DSEEFSM) for wind energy applications. To reduce the cost of conventional design, several rotor pole topologies of low cost have been examined, and finally, an optimum design is compared with conventional design.

In this paper, NOW-DSEEFSM is designed, optimized, evaluated and compared with different rotor poles. Initially, the electromagnetic performance of the proposed machine is investigated on the 8, 10, 14, 20 and 22 rotor poles based on the finite element analysis by using JMAG software. From the initial results, 8-, 10- and 14-pole machines are further selected for parametric optimization to enhance the electromagnetic performance. After optimization, the result indicates that the machine with 14 poles can be considered as the overall most appropriate design for the proposed wind generator. Furthermore, analysis has been used on different armature and field current densities to study the effect on electromagnetic performances. Finally, a comparison is performed between the proposed machine and the conventional machine.

In the proposed machine to reduce the copper losses and overhang effect, the NOW topology is used against the well-known overlap winding and provides excellent flux regulation capability due to the existence of field winding, and to obtain high torque and power densities, the presented machine has two stator units and a single robust rotor.

The dual stator flux switching machine with NOW is designed, evaluated and compared to get high torque and power densities.

The heat transport phenomenon in which energy transfers due to temperature differences is an important topic of interest for scientists in recent times. It is because of its wide range of applications in numerous domains such as electronics, heat dispersion, thermoregulation, cooling mechanism, the managing temperature in automotive mobile engines, climate engineering, magnetoresistance devices, etc. On account of such considerations, the magnetohydrodynamic (MHD) entropy rate for nanomaterial (CoFe₂O₄/C₂H₆O₂) and hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) is analyzed. The Darcy–Forchheimer relation is utilized to describe the impact of a porous medium on a stretched sheet. Two nanoparticles molybdenum (MoS₄) and cobalt ferrite (CoFe₂O₄) are combined to make hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂). Heat flux corresponds to the Cattaneo–Christov model executed through heat transfer analysis. The influence of dissipation and heat absorption/generation on energy expression for nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) and hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) is described.

Nonlinear partial differential expressions have been exchanged into dimensionless ordinary differential expressions using relevant transformations. Newton’s built-in shooting method is employed to achieve the required results.

Concepts of fluid flow, energy transport and entropy optimization are discussed. Computational analysis of local skin friction and Nusselt number against sundry parameters for nanomaterial (CoFe₂O₄/C₂H₆O₂) and hybrid nanomaterial (CoFe₂O₄+MoS₄/C₂H₆O₂) is engrossed. Larger magnetic field parameters decay fluid flow and entropy generation, while an opposite behavior is observed for temperature. Variation in magnetic field variables and volume fractions causes the resistive force to boost up. Intensification in entropy generation can be seen for higher porosity parameters, whereas a reverse trend follows for fluid flow. Heat and local Nusselt numbers rise with an increase in thermal relaxation time parameters.

No such work is yet published in the literature.

This study aims to analyze the impact of board gender diversity (BGD) on a bank’s financial stability. Moreover, it also examines whether digitalization and income diversification act as mediators (individual and serial) in this relationship.

Hypotheses were tested using data from Pakistan’s banking sector financial statements from 2017 to 2021. A two-step analytical approach was used: panel regression in STATA for initial hypothesis examination, followed by mediation analyses using bootstrapping in SPSS. In addition, mixed-effect ML regression was conducted to verify causation and ensure robust findings.

Results demonstrate that BGD, digitalization and income diversification are positively associated with higher financial stability. Moreover, as hypothesized, both digitalization and income diversification individually and sequentially mediate the relationship between BGD and banks’ financial stability.

It is important to acknowledge the study’s limited five-year timeframe. Further investigation is needed to determine the optimal board compositions, especially considering the study’s inclusion of up to 25% female directors on boards.

Policymakers and top management should prioritize increasing the number of female directors on boards for diversity. Banks that involve female directors can benefit from the synergies between gender diversity and digitization, along with the unique perspectives these women offer. This cooperative dynamic enables banks to explore and capitalize on innovative income diversification opportunities, enter new markets and ensure financial stability.

Research findings emphasize promotion of gender equality and meritocracy through increased female director representation. This fosters a more inclusive and cooperative decision-making culture, benefiting individual banks and setting a model for other sectors. Ultimately, it contributes to greater social acceptance of women executives.

The study reveals a novel mechanism, emphasizing the revolutionary impact of active female directors in tandem with digitalization, amplifying chances for income diversification and accelerating increased bank viability.

In this digital age, the rapid technological innovation and adoption, with the increasing use of big data analytics, has raised concerns about the ability of small and medium enterprises (SMEs) to sustain the competition and innovation performance (IP). To narrow the research gap, this paper investigates the role of big data analytics capability (BDAC) in moderating the relationship between digital innovation (DI) and SME innovation performance.

This research has been carried forward through a detailed theory and literature analysis. Data were analyzed through confirmatory factor analysis and structural equation models using a two-stage approach in smartPLS-4.

Results highlight that digital service capability (DSC) significantly mediates the relationship between DI and IP. Additionally, value co-creation (VCC) directly affects digital transformation (DT), while DI has a stronger effect on DSC than IP. Furthermore, BDAC significantly moderates the relation between DSC → IP and DT → IP, whereas it has a detrimental effect on the relation between DI and IP. In addition to that, VCC, DSC, DT, DI and BDAC have a direct, significant and positive effect on IP.

This research was motivated by the practical relevance of supporting SMEs in adopting DT and the resource-based view (RBV) and technology acceptance model (TAM). This study shows that all direct and indirect measures significantly affect innovation performance, including BDAC as moderator. These findings refresh the perspective on what DT, DI, VCC, DSC and BDAC can bring to a firm's innovation performance.

This paper has contributed to DT by empirically validating a theoretical argument that suggests the acceptance and adoption of new technology. This paper aims to fill theoretical gaps in understanding BDAC and DT by incorporating the RBV and TAM theories on BDAC and DT.

Research on decision rights partitioning and its impact on platform performance has predominantly focused on single rights, leading to inconclusive results. This study is driven by a more nuanced objective of exploring diverse governance models that can enhance the performance of sharing platforms across different contexts. Rather than delegating single decision right to users, this approach partitions several essential decision rights concurrently throughout the transaction process. By examining the complex relationships between multiple decision rights partitioning and platform performance, this study identifies and explains suitable governance models that are tailored to specific contextual factors for improving the performance of sharing platforms.

Collecting data from 60 sharing platforms in China, this study employs a combination of cluster and configuration analyses to address research questions.

The study explores three strategic decision rights partitioning modes widely adopted by sharing platforms. It further identifies four governance models for sharing platforms, which are termed as conservative seller model, conservative buyer model, aggressive seller model and aggressive buyer model, related to certain contextual factors.

In addressing platform governance as key to sharing platform success, the study contributes to the literature by investigating how multiple-rights partitioning portfolios and strategic differentiation in decision rights partitioning can enhance platform performance.

This paper explores the linkage of digital infrastructure to the cost of debt.

This study uses the implementation of the “Broadband China” policy that improves digital infrastructure as an exogenous shock and exploits the difference-in-differences method (DID).

Empirical analyses show that digital infrastructure leads to increased firms’ borrowing costs, which is robust to several robustness checks. In addition, we find that this unfavourable effect can be attributed to intensified market competition led by digital infrastructure construction. Cross-sectional analysis shows that this effect is greater for non-SOEs and smaller firms. Finally, we offer additional evidence of the unfavourable effect by showing that digital infrastructure construction leads to decreased fundamentals.

Our paper unveils how digital infrastructure construction affects firms’ business strategy in using private debts and extends the determinants of firms’ borrowing costs.