Objective: This study synthesizes current evidence on the role of Artificial Intelligence (AI) and, where relevant, Open Science (OS) practices in enhancing Human Resource Management (HRM) performance. It focuses on recruitment processes, ethical considerations, and employee participation. Methodology: A systematic literature review was conducted in Scopus covering the period 2019–2024, following PRISMA guidelines. The initial search yielded 1486 records. After de-duplication and screening using Rayyan, 66 studies (≈ 4.4%) met the inclusion criteria, which targeted peer-reviewed works addressing AI-supported HR decision-making. A combined content and bibliometric analysis was performed in R (Bibliometrix) to identify thematic patterns and conceptual structures. Results: Analysis revealed four thematic clusters: 1) Implementation and employee participation emphasizing human-in-the-loop approaches and effective change management; 2) ethical challenges including algorithmic bias, transparency gaps, and data privacy risks; 3) data-driven decision-making delivering higher accuracy, fewer errors, and personalized recruitment and performance assessment; 4) operational efficiency enabling faster workflows and reduced administrative workloads. AI tools consistently improved selection quality, while OS practices promoted transparency and knowledge sharing. Implications: The successful adoption of AI in HRM requires employee engagement, strong ethical safeguards, and transparent data governance. Future research should address the long-term cultural, organizational, and well-being impacts of AI integration, as well as its sustainability.

The sense of belonging in any organization is vital to generate a work motivation with the objective of a good organizational performance, because of this, companies usually take this point into account, ensuring that this leads to greater performance. For this reason, the objective of this article is to determine the relationship between the sense of belonging and the work motivation in the workers of a small Peruvian research company. For this purpose, a quantitative methodology was used, with a cross-sectional descriptive design. The instrument used was a survey consisting of 10 items, which were interpreted using the Likert scale. The survey was conducted and delivered to 24 workers, who were selected by non-probabilistic convenience sampling. After verifying the validity of the instrument and the study variables by means of Cronbach's Alpha statistic, we proceeded to determine the existence of correlation between the variables, which, using Spearman's Rho coefficient, obtained a 70.2% which demonstrates a moderate positive correlation, therefore it indicates that employees feel highly motivated as they feel an indispensable part of the company, therefore they feel job satisfaction by being part of the organization.

The aim of this study was to elucidate the expected moderating effect exerted by institutional owners on the intricate correlation between the characteristics of boards of directors and the issue of earnings management, as gauged by the loan loss provisions.The sample encompassed all the banks listed on the Amman Stock Exchange (ASE) over the period between 2010 and 2022, representing a total of 151 observations. The results derived from the examination clearly demonstrate that the institutional owners have a key impact on augmenting the monitoring tasks and responsibilities of the boards of directors across the study sample. The results revealed the fundamental role of such owners in strengthening the supervisory tasks carried out by boards of directors in Jordan. A panel data model has been used in the analysis. The results of this study show that the presence of the owner of an institution has a discernible moderating role in the banks' monitoring landscape. Indeed, their presence strengthens the monitoring tasks of the banks’ boards by underscoring the quest to restrict the EM decisions. Interestingly, the results support the monitoring proposition outlined by agency theory, which introduced CG recommendations as a deterrent tool to reduce the expectation gap between banks' owners and their representatives.

Farm households in developing countries are often involved in a variety of livelihood income-generating activities to achieve basic needs and enhance food security. However, little attention has been given to investigating the effect of livelihood diversification strategies on the adoption of agricultural land management practices. This study explored the nexus between livelihood diversification and Agricultural Land Management (ALM) practices in the Southern Ethiopian Highlands. Data for this study were gathered through a structured questionnaire, interviews, and focus group discussions. A total of 423 sample respondents were selected by using multistage random sampling techniques. The data were analyzed using the Inverse Herfindahl Hirschman Diversity Index (IHHDI), the multinomial logit model (MNL), and the probit regression model. The findings of the study revealed that on-farm income activities are the most dominant livelihood income strategies (69.1%), followed by non-farm (21%) and off-farm (9.64%). The multinomial logit model analysis demonstrated that variables such as sex, education, family size, distance to market, land size, extension contact, membership in cooperatives, and household income were the major drivers of farmers income diversification activities (p<0.05). The results of the probit analysis indicated that income from crop production, daily labor work, rents from farmland, and farm assets have a positive and significant effect on households' decisions to implement ALM practices. In contrast, incomes from remittance and migrant sources have a negative but statistically significant impact on the adoption of ALM measures. The farm household sources of income-generating strategies substantially affected the adoption intensity of ALM measures. Income generated from the on-farm sector alone cannot be considered a core income-generating activity for households or a means of achieving food security. Therefore, land management policies and program implementations should consider farmers’ livelihood diversification and income-generating strategies. In addition, such interventions need to promote sustainable farming practices, enhance innovation, and related measures for the adoption of ALM measures to ensure land sustainability.

The rapid growth of portable electronics and electric vehicles has intensified the global demand for high-performance energy storage devices with superior power density, energy density, and long cycle life. Among transition metal oxide-based electrode materials with potential for energy storage, we report the development of MnO2–V2O5 nanocomposite electrodes for supercapacitor applications. Pure MnO2 and V2O5 were successfully fabricated via a simple and economical sol–gel method, while (MnO2)x–(V2O5)1−x (x = 1, 0.75, 0.50, and 0) nanocomposites were fabricated through an ex situ method. Analytical techniques, including X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy, and UV-visible spectroscopy, were employed to investigate the structural, morphological, and optical properties of the electrodes. Furthermore, the electrochemical properties were systematically analysed using cyclic voltammetry, galvanostatic charge–discharge measurements, and electrochemical impedance spectroscopy. The (MnO2)0.75–(V2O5)0.25 nanocomposite demonstrated a remarkable specific capacitance of 666 F/g at a current density of 0.5 A/g in 1 M KOH electrolyte. Additionally, the electrode material exhibited an energy density of 23 Wh/kg and a power density of 450 W/kg, while maintaining a capacitance retention of 95% after 1,500 cycles. The incorporation of V2O5 boosted the conductivity and significantly optimised the number of lattice defects. This work substantially reinforces the importance of metal oxide-based nanocomposites for future energy storage devices.