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The purpose of this study is to investigate the pricing strategies for knowledge payment products, taking into account the quality level of pirated knowledge products, in the context of platform copyright supervision.

This study abstracts the knowledge payment transaction process and aims to maximize producer's revenue by constructing a pricing model for knowledge payment products. It discusses pricing strategies for knowledge payment products under two scenarios: traditional supervision and blockchain supervision. The analysis explores the impact of pirated knowledge products quality level and blockchain technology on pricing strategies and consumer surplus, while providing threshold conditions for effective strategies.

Deploying blockchain technology in platform operations can significantly reduce costs and increase efficiency. In both scenarios, knowledge producer needs to balance factors such as the quality of pirated knowledge products, the supervision level of platform, and consumer surplus to dynamically adjust pricing strategies in order to maximize his own revenue.

This study enriches the literature on the pricing models of knowledge payment products and has practical significance in guiding knowledge producer to develop effective pricing strategies under copyright supervision.

This paper aims to investigate the lubrication characteristics of siliconized graphite with a wavy-tilt-dam (WTD) pattern applied to the hydrodynamic face seals.

It focuses on two friction pairs, carbon graphite versus tungsten carbide (CG-TC) and siliconized graphite versus siliconized graphite (SG-SG), through a three-dimensional elastic hydrodynamic lubrication numerical model that integrates finite difference method and finite element method. The consequence of axial elastic deformation of sealing pair materials on film thickness, film pressure, cavitation and sealing performance for a WTD mechanical face seal under full working conditions of ΔP = 0.8, 5.3 and 15.8 MPa are analyzed theoretically.

The nuclear hydrodynamic WTD face seal generates a convergent gap and exhibits a dual-characteristic behavior of hydrodynamic and hydrostatic effects under various ΔP. Compared to the CG-TC, the SG-SG shows a lower minimum film thickness, decreasing by 3.9%, 17.3% and 35.1%. The flow leakage rate decreases by 47.8%, 52.1% and 75.4%. In addition, the film stiffness increases by 46.8%, 49.8% and 97.8%. Thus, the SG-SG better deals with the dynamic tracking problem, and the sealing performance is stable. The strength and hardness of siliconized graphite enhance WTD sealing performance and improve cavitation control in high-pressure applications.

The lubrication characteristics of the siliconized graphite with a WTD pattern could inform the future design of hydrodynamic shallow groove wavy seals in boiler feedwater engineering implements under high-pressure conditions for the nuclear power industry.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0382/

The purpose of this study is to reveal the significant contribution of MXene on enhancing tribological properties and to obtain the influence mechanism of various factors on friction characteristics of rolling bearing under extreme conditions.

Under extreme working conditions, the friction characteristics of rolling bearings directly determine the safety and reliability of the transmission system. In this study, MXene is added to the origin lubricating grease (OLG) of rolling bearing to enhance their friction characteristics. Then, the effects of inner ring speed, radial load, grease filling volume and other factors on the friction coefficient of rolling bearing are analyzed using the Taguchi method.

The results indicate that the ranking of various factors affecting the friction coefficient is: radial load, inner ring speed, MXene additive content in grease and grease filling volume. Especially, the radial load and inner ring speed exhibit extremely significant effects, while the MXene additive content in grease (P < 0.05) has a significant influence on the friction coefficient of rolling bearing. The optimal condition for rolling bearing lubricated with MXene additives lubricating grease (MALG) achieves the lowest friction coefficient of 0.0049 under 1,000 rpm, 9 kN and 35% grease filling volume.

This study could offer reference solution for utilizing MXene nano-lubrication to fufill the demands of precision, heavy-load, or long-lifespan bearings. Furthermore, the lubrication approach has the potential to be expanded into aerospace, defense, and various industrial fields, thereby significantly promoting its practial engineering applications.

The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis.

Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender.

The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations.

This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.

The carbon complementary supply chain (CCSC) is a collaborative framework that facilitates internal carbon credit trading agreements among supply chain agents in compliance with prevailing carbon regulations. Such agreements are highly beneficial, prompting agents to consider joint investment in emission reduction initiatives. However, capital investments come with inevitable opportunity costs, compelling agents to weigh the potential revenue from collaborative investments against these costs. Thus, this paper mainly explores carbon abatement strategies and operational decisions of the CCSC members and the influence of opportunity costs on the strategic choice of cooperative and noncooperative investment.

The authors propose a novel biform game-based theoretical framework that captures the interplay of pricing competition and investment cooperation among CCSC agents and assesses the impact of opportunity costs on CCSC profits and social welfare. Besides, the authors also compare the biform game-based collaborative scenario (Model B) to the noncooperative investment scenario (Model N) to investigate the conditions under which collaborative investment is most effective.

The biform game-based collaborative investment strategy enhances the economic performance of the traditional energy manufacturer, who bears the risk of opportunity costs, as well as the retailer. Additionally, it incentivizes the renewable energy manufacturer to improve environmental performance through renewable projects.

This research contributes significantly by establishing a theoretical framework that integrates the concepts of opportunity costs and biform game theory, offering new insights into the strategic management of carbon emissions within supply chains.

This study introduces the heritage city risk dimension of the urban rail transit (URT) projects. It aims to identify the risk factors affecting URT projects within the unique context of heritage-rich cities, exploring their interrelation and evaluating critical factors.

The research adopts a multi-case exploratory study to identify the unique challenges faced by URT projects in heritage-rich environments, followed by a comprehensive risk assessment framework integrating Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), Analytic Network Process (ANP) and Risk Interaction Network (RIN) analysis to assess identified risks in the context of Kathmandu Valley. Additionally, a risk response action is simulated using RIN analysis.

About 16 risk factors were identified from the case studies and evaluated using the proposed risk assessment methodology. The study reveals a highly interconnected risk environment, with heritage impact-related factors exerting the strongest causative influence on cost and social engagement factors. Community opposition (R8) shows the highest betweenness centrality, indicating its central position in risk propagation across the network. Cost-related risk, social demand contingency (R2) ranked as the most critical. Simulations of a targeted risk avoidance strategy showed that addressing only three key high-betweenness centrality factors (R5, R8 and R15) reduced overall risk interactions by 46%, simplifying the risk network, reducing project complexity and improving manageability.

The findings emphasize that project managers, urban planners and policymakers should integrate heritage preservation concerns when planning and executing URT projects in heritage-rich cities. Moreover, the research highlights that effective community engagement serves as a key strategy for reducing risk propagation and plays a crucial role in overall project risk management.

The study contributes to the underexplored context of URT projects in heritage-rich cities, providing a comprehensive risk management framework for identifying and assessing project risks intersecting with urban development imperatives and heritage conservation objectives.

(1) The shear lag effect and its additional deflection contribution to composite beams based on spatial grid elements were presented. (2) A refined spatial grid element analysis method that can simultaneously obtain the internal forces, displacements and stresses of various parts of a composite beam.

A refined spatial grid element analysis method.

The proposed method can directly obtain the internal forces and displacements of the joints of the composite beam roof, floor and web.

To comprehensively comprehend the mechanical behavior of double-girder steel plate composite girder bridge structures and facilitate refined analysis, this paper introduces a refined spatial grid element analysis model applicable to both the global and local domains.

This contribution investigates the numerical solution of Volterra integral equations with auto-convolution of the third kind (AVIE). The numerical method applied in this investigation employs a collocation method based on the moving least squares (MLS) approximation. The MLS approximation is an effective way of approximating an unknown function by taking a disordered dataset. This method is a mesh-free approach since it does not require background interpolation or approximation cells, and is independent of domain geometry. The proposed method reduces the solution of third-kind AVIEs to the solution of systems of algebraic equations. By employing the Gauss–Legendre integration formula, we can estimate all the integrals of these equations. The applicability and validity of this method are demonstrated by numerical experiments, and its efficiency and robustness are proven by comparison with existing methods.

The numerical method applied in this study uses a collocation method based on moving least squares (MLS) approximation. This method is a mesh-free approach since it requires no background interpolation or approximation cells and is independent of domain geometry. Using the Gauss–Legendre integration formula, we can estimate all the integrals of these equations.

The authors declare that they have no known competing financial interests.

The manuscript has not been copyrighted or published previously and is not under consideration for publication elsewhere.

The purpose of this paper is to analyze whether and how intergovernmental fiscal transfers (IFTs) affect technological innovation.

China’s provincial panel data from 2007 to 2019 are used in an empirical study to examine the effect of IFTs on technological innovation and the role of fiscal spending policy in the relationship between the two by using the spatial Durbin model.

Results show an evident spatial correlation for the effect of IFTs on technological innovation, indicating that IFTs have a significant negative influence on technological innovation in local and surrounding regions. IFTs also inhibit technological innovation by negatively affecting science and technology spending and education spending.

These findings can aid policymakers in advancing technological innovation by improving the system of fiscal transfers and optimizing the structure of fiscal spending.

Although the determinants of technological innovation have been analyzed, no studies have investigated the effect of IFTs on technological innovation. Thus, this paper aims to address this gap.

This research aims to explore how policymakers manage the information and communication of green behavior on social platforms to support their growth in corporate social responsibility (CSR). Social platforms play a strategic and interactive role through electronic word-of-mouth (eWOM), which brings unprecedented green purchase opportunities.

Based on stakeholder theory, a conceptual framework is designed to investigate the influence of green behavior interactions (GBIs) on CSR under the mediating effects of eWOM subfactors (eWC = eWOM communication, eWIA = eWOM information adoption and eWSC = eWOM source credibility). Data from 414 regular stakeholders of logistics firms were analyzed via structural equation modeling.

The results reveal positive influences of the GBI on eWC, eWIA, eWSC and CSR, with path coefficients of 0.329, 0.713, 0.809 and 0.316, respectively. The mediating effects of eWC and eWSC from the GBI to CSR were discovered with path coefficients of 0.105 and 0.226, respectively. Coincidentally, the mediating role of eWIA was positive but not supported. The outcomes of this study indicate that the administration of GBI and eWOM from a green purchase perspective is essential for a firm. The CSR practices of green logistics firms can be successfully supported by the administration of the GBI and eWOM indicators.

This study develops a novel multidimensional framework that illustrates the impact of eWOM on reducing information asymmetry, enhancing credibility, supporting informed decision-making and improving green consumer behavior. By amplifying positive reviews, increasing engagement and establishing a feedback loop, this framework aims to provide comprehensive insights into the efficacy of eWOM for firms’ products and services.