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This study aims to propose a cloud platform architecture considering information sharing based on blockchain to realize the security and convenience of enterprise information sharing in the automotive supply chain.

A bilateral matching model considering enterprises information contribution stimulates information sharing and improves the efficiency and quality of supply and demand matching. Three smart contracts are used to complete the information sharing process and match supply and demand in the automotive supply chain.

The system is tested on the local Ganache private chain, and the decentralized web page is designed based on the architecture prototype.

Solve the problem of information island in automobile supply chain.

This study aimed to examine the impact of learning organization (LO) on job satisfaction and individual performance in Vietnamese enterprises. The study further explores the mediating effect of job satisfaction on the relationship between learning organization and employee performance.

Data were collected from 653 employees from various types of organizations in Vietnam. Structural equation modeling was implemented to test the hypotheses.

The results revealed that the proposed research model was supported. Results indicated that LOs positively influenced employees’ job satisfaction and the broader range of their individual performance. In addition, employees’ job satisfaction motivated them to achieve higher performance levels. The study also found a mediating effect of job satisfaction on the relationship between LO and employee performance. The results underscore the importance of implementing an LO culture for individual outcomes such as job satisfaction and employee performance in the Vietnamese cultural context, which is based on socialism and Confucianism.

To the best of the authors’ knowledge, this is the first study to examine the relationships among LO, job satisfaction and individual employee performance in the Vietnamese context. The results offer a deeper understanding of the LO concept in the Vietnamese cultural context and highlight the cultural impact on the LO concept and its effects. The results suggest how the LO concept is applied in the Vietnamese context.

This research tests how the social context of meals influences the sense of responsibility for serving healthy meals and food choices, taking into account the role of gender.

An online between-subject scenario experiment was conducted with parents of young children (under 12 years old) in Flanders, Belgium (N = 288, 67.4% women). Participants envisioned serving and consuming food in three social contexts: alone, with core family members, or with peers.

The social context in which meals take place significantly influences participants’ sense of responsibility for serving healthy meals, which influences their food choices. Moreover, the influence of the social context varies by gender. Women feel more responsible for serving healthy meals than men when eating alone or among core family members. Men feel more responsible for serving healthy meals when eating with others, irrespective of whether these others are core family members or peers, than when eating alone.

One’s sense of responsibility serves as a significant positive determinant in making healthy food choices. However, this sense is context dependent. In a family context, and irrespective of gender, sense of responsibility correlates only weakly to moderately with the perceived healthfulness of food choices. Consequently, the question arises as to whether emphasizing responsibility is the most effective strategy for promoting healthy food choices.

This paper provides new insights into how the social context shapes parents’ sense of responsibility for serving healthy meals and how this, in turn, affects food choices.

This paper aims to examine the connection between digital payments, ownership structure, and bank performance in Jordan, as well as investigate the moderating role of the independent director in the said relationship.

The study uses data from 12 Amman stock exchange-listed commercial banks, covering the period from 2010 to 2023. This paper employs econometric analysis of panel data, including ordinary least squares (OLS) regression as the primary approach, as well as the generalised method of moments, the two-stage least square (2SLS), and the dynamic model to deal with causality and endogeneity issues in the proposed equations. This ensures that the results are valid.

The results indicate that digital payments and ownership structure have a significant positive connection with bank performance. Additionally, the independent director variable appears to play a substantial and positive moderating role in the link between ownership structure (e.g. institutional ownership) and bank performance. These results strengthen and support the claims of agency theory and the information systems success model.

Overall, this research helps stakeholders, bankers, managers, investors, customers, and policymakers, identify the influence of digital payment and ownership structure on bank performance in developing economies such as that of Jordan.

This investigation offers a unique understanding by illuminating how digital payment and ownership structure affect bank performance in a developing country such as Jordan. Additionally, it opens avenues for future research to delve into this literature domain in North African and Middle Eastern nations, with a particular focus on Jordan. This investigation is among the initial explorations in Jordan that aim to elucidate these relationships. On the theoretical level, it adds to the agency theory and IS model. It provides new insights into the dynamics of industry banking in developing nations (i.e. Jordan).

There are various uncertain and nonlinear problems in hydraulic legged robot systems, including parameter uncertainty, unmodeled dynamics and external disturbances. This study aims to eliminate uncertainties and improve the foot trajectory tracking control performance of hydraulic legged robots, a high-performance foot trajectory tracking control method based on fixed-time disturbance observers for hydraulic legged robots is proposed.

First, the robot leg mechanical system model and hydraulic system model of the hydraulic legged robot are established. Subsequently, two fixed-time disturbance observers are designed to address the unmatched lumped uncertainty and match lumped uncertainty in the system. Finally, the lumped uncertainties are compensated in the controller design, and the designed motion controller also achieves fixed-time stability.

Through simulation and experiments, it can be found that the proposed tracking control method based on fixed-time observers has better tracking control performance. The effectiveness and superiority of the proposed method have been verified.

Both the disturbance observers and the controller achieve fixed-time stability, effectively improving the performance of foot trajectory tracking control for hydraulic legged robots.

This paper aims to study the influence of different seal structure parameters and working conditions on the air-oil two-phase flow characteristics and leakage characteristics of the seal cavity in the bearing cavity of the aero-engine spindle bearing tester.

In this paper, the VOF method and RNG k-ε turbulence model are used to explore the flow characteristics and leakage characteristics of the labyrinth seal cavity of an aero-engine spindle bearing tester under the condition of air-oil two-phase flow.

The distribution of the lubricating oil is related to the sealing clearance and the air-oil ratio. The amount of oil leakage increases with increasing of sealing chamber clearance, air-oil ratio and inlet velocity and decreases with increasing curvature and speed. The amount of air leakage increases with sealing clearance and inlet velocity.

In comparison to the pure air-phase flow field, the air-oil two-phase flow field can more accurately simulate the lubricating oil flow in the sealing chamber.

As China is on an inevitable march into the digital era, firms have accumulated abundant digital assets, such as algorithms and data. Facing the possibility of using digital assets as a new type input, besides traditional inputs such as capital and labor, would powerful managers perform better? Would managerial power help managers increase the efficiency of how a firm combines traditional and digital inputs and converts them into outputs? Thus, the purpose of this study is to investigate whether powerful managers promotes corporate productivity by using digital assets as a new input.

Using data from listed Chinese firms between 2008 and 2020, the authors constructed panel regressions with three-way fixed effects to examine whether and how managerial power influences corporate productivity in the current digital context, particularly under market uncertainty.

The findings reveal no consistent relationship between managerial power and corporate productivity. The results explain this from two contrasting effects: while managerial power promotes technological change it hinders technical efficiency – two components of total productivity. Moreover, this study identifies market uncertainty as a significant external contingency. In uncertain markets, strong managerial power positively impacts corporate productivity.

The results extend extant theoretical insights in the literature on how managerial power might influence corporate productivity.

Considering the relevance of “green” as well as of “intellectual capital” in the current economy, scholars and practitioners are increasingly interested into the so-called Green Intellectual Capital (GIC). Against this backdrop, as the research is at an early stage with still no clear evidence, this article intends to investigate the relationship between GIC disclosure and firm’s performance, also analyzing the moderation role of CEO gender.

Taking into account the theoretical background, the quali-quantitative analysis focuses on a sample of Italian listed companies during the period 2020–2022. To check the relationships, a content analysis has been conducted to measure the level of GIC disclosed and then generalized least squares, ordinary least squares and lasso regression have been employed to test the hypotheses.

Results show that GIC disclosure produces a negative relationship with financial performance. In the meantime, findings point out that a female CEO moderates this relationship, boosting financial outcomes.

The study offers actionable managerial implications thanks to the proposed set of items to monitoring GIC. At the same time, it underlines how leadership styles can contribute to leverage green knowledge. Moreover, it seeks to contribute to the current literature and offers intriguing insights for policymakers.

This paper addresses the still unclear relationship between GICD and performance, providing new cues regarding the role of women in CEO positions. Furthermore, in doing so, it focuses on Italian listed companies, a context still uncharted. Finally, the methodology represents a novelty in approaching these topics.

This study’s aim is to introduce a high-performance sorbent for the removal of both anionic (Congo red; CR) and cationic (methylene blue; MB) dyes from aqueous solutions.

Sodium silicate is adopted as a substrate for GO and AgNPs with positive charge are used as modifiers. The synthesized nanocomposite is characterized by FTIR, FESEM, EDS, BET and XRD techniques. Then, some of the most effective parameters on the removal of CR and MB dyes such as solution pH, sorbent dose, adsorption equilibrium time, primary dye concentration and salt effect are optimized using the spectrophotometry technique.

The authors successfully achieved notable maximum adsorption capacities (Qmax) of CR and MB, which were 41.15 and 37.04 mg g⁻¹, respectively. The required equilibrium times for maximum efficiency of the developed sorbent were 10 and 15 min for CR and MB dyes, respectively. Adsorption equilibrium data present a good correlation with Langmuir isotherm, with a correlation coefficient of R2 = 0.9924 for CR and R2 = 0.9904 for MB, and kinetic studies prove that the dye adsorption process follows pseudo second-order models (CR R2 = 0.9986 and MB R2 = 0.9967).

The results showed that the proposed mechanism for the function of the developed sorbent in dye adsorption was based on physical and multilayer adsorption for both dyes onto the active sites of non-homogeneous sorbent.

The as-prepared nano-adsorbent has a high ability to remove both cationic and anionic dyes; moreover, to the high efficiency of the adsorbent, it has been tried to make its synthesis steps as simple as possible using inexpensive and available materials.

This study aims to develop an accurate option pricing model for car leases by introducing a put option valuation framework based on the Weibull distribution. Traditional models typically assume asset values follow a lognormal distribution, failing to capture the left-skewed nature and bounded dynamics. To address this limitation, this study compares the performance of the Weibull distribution with that of the lognormal model using residual value data from two popular car models in South Korea, evaluating each model’s ability to reflect unique depreciation patterns. The findings demonstrate that the Weibull distribution provides a superior fit to the data, leading to more precise option pricing. This enhanced accuracy is crucial for auto finance companies navigating uncertainties in used car prices, particularly as the mobility services and car leasing markets continue to expand. Moreover, the practical implications of this research extend beyond the auto finance industry; insights from this study can inform sectors dealing with skewed or bounded assets, such as insurance products and financial derivatives, thereby enabling improved risk assessment and decision-making processes. This research introduces a novel approach to modeling put option values using the Weibull distribution, filling a significant gap in the existing literature on car lease option pricing. However, as this is the first study to model put option values using the Weibull distribution, further research is necessary. Specifically, investigating volatility patterns over the lifecycle of used cars could significantly enhance the value of this framework.