Search Results (491)

This study explores the role of artificial intelligence (AI) in human resource management (HRM), with a focus on recruitment, employee retention, and performance optimization. Through a PRISMA-based systematic literature review, the paper examines many machine learning algorithms including XGBoost, SVM, random forest, and linear regression in decision-making related to employee-attrition prediction and talent management. The findings suggest that these technologies can automate HR processes, reduce bias, and personalize employee experiences. However, the implementation of AI in HRM also presents challenges, including data privacy concerns, algorithmic bias, and organizational resistance. To address these obstacles, the study highlights the importance of adopting ethical AI frameworks, ensuring transparency in decision-making, and developing effective integration strategies. Future research should focus on improving explainability, minimizing algorithmic bias, and promoting fairness in AI-driven HR practices. Full article

The Research Integrity Risk Index (RI²), introduced as a tool to identify universities at risk of compromised research integrity, adopts an overly reductive methodology by combining retraction rates and delisted journal proportions into a single, equally weighted composite score. While its stated aim is to promote accountability, this commentary critiques the RI² index for its flawed assumptions, lack of empirical validation, and disproportionate penalization of institutions in low- and middle-income countries. We examine how RI² misinterprets retractions, misuses delisting data, and fails to account for diverse academic publishing environments, particularly in Indonesia, where many high-performing universities are unfairly categorized as “high risk” or “red flag.” The index’s uncritical reliance on opaque delisting decisions, combined with its fixed equal-weighting formula, produces volatile and context-insensitive scores that do not accurately reflect the presence or severity of research misconduct. Moreover, RI² has gained significant media attention and policy influence despite being based on an unreviewed preprint, with no transparent mechanism for institutional rebuttal or contextual adjustment. By comparing RI² classifications with established benchmarks such as the Scimago Institution Rankings and drawing from lessons in global development metrics, we argue that RI², although conceptually innovative, should remain an exploratory framework. It requires rigorous scientific validation before being adopted as a global standard. We also propose flexible weighting schemes, regional calibration, and transparent engagement processes to improve the fairness and reliability of institutional research integrity assessments. Full article

The construction industry has been troubled by a shortage of skilled labor and safety accidents in recent years. Therefore, more and more robots are introduced to undertake dangerous and repetitive jobs, so that human workers can concentrate on higher-value and creative problem-solving tasks. Nevertheless, although human–robot collaboration (HRC) shows great potential, most existing evaluation methods still focus on the single performance of either the human or robot, and systematic indicators for a whole HRC team remain insufficient. To fill this research gap, the present study constructs a comprehensive evaluation framework for HRC team performance in construction projects. Firstly, a detailed literature review is carried out, and three theories are integrated to build 33 indicators preliminarily. Afterwards, an expert questionnaire survey (N = 15) is adopted to revise and verify the model empirically. The survey yielded a Cronbach’s alpha of 0.916, indicating excellent internal consistency. The indicators rated highest in importance were task completion time (µ = 4.53) and dynamic separation distance (µ = 4.47) on a 5-point scale. Eight indicators were excluded due to mean importance ratings falling below the 3.0 threshold. The framework is formed with five main dimensions and 25 concrete indicators. Finally, an AHP-TOPSIS method is used to evaluate the HRC team performance. The AHP analysis reveals that Safety (weight = 0.2708) is prioritized over Productivity (weight = 0.2327) by experts, establishing a safety-first principle for successful HRC deployment. The framework is demonstrated through a case study of a human–robot plastering team, whose team performance scored as fair. This shows that the framework can help practitioners find out the advantages and disadvantages of HRC team performance and provide targeted improvement strategies. Furthermore, the framework offers construction managers a scientific basis for deciding robot deployment and team assignment, thus promoting safer, more efficient, and more creative HRC in construction projects. Full article

Traditional energy conservation policies have primarily relied on economic incentives and informational campaigns. However, recent insights from behavioral and social sciences indicate that subtle behavioral interventions, particularly social nudges, can significantly influence household electricity use. This paper presents a structured review of 23 recent field studies examining how social nudging strategies, such as peer comparison, group identity, and normative messaging, have contributed to measurable reductions in electricity consumption. By analyzing intervention outcomes across different regions and formats, we identify key success factors, limitations, and policy implications. Special attention is given to ethical considerations, fairness in implementation, and potential challenges in sustaining behavior change. This study offers a framework for integrating social nudges into future energy policies, emphasizing their role as low-cost, scalable tools for promoting sustainable energy behavior. Full article

Semantic modeling of legal reasoning is an important research direction in the field of artificial intelligence and law (AI and law), aiming to enhance judicial transparency, fairness, and the consistency of legal applications through structured semantic representations. This paper proposes a semantic judicial reasoning framework based on the “Data–Information–Knowledge–Wisdom–Purpose” (DIKWP) model, which transforms the conceptual expressions of traditional legal judgment into DIKWP graphs enriched with semantics. The framework integrates the objective content of legal norms with stakeholders’ subjective cognition through a DIKWP×DIKWP bidirectional mapping mechanism, achieving “semantic justice”. Specifically, we define a DIKWP-based legal knowledge representation method and design a mapping algorithm from traditional legal concepts to the DIKWP semantic structure. To validate the effectiveness of the framework, we use a real administrative law case as an example and construct DIKWP (normative content) and DIKWP (subjective cognition) graphs to model legal rules, evidence, and various perspectives. The results indicate that the intention-driven semantic transformation mechanism can harmonize legal reasoning with stakeholders’ cognitive backgrounds, thereby enhancing the interpretability and fairness of judicial interpretation. Case analysis further demonstrates that reasoning within the DIKWP semantic space can reveal underlying assumptions, bridge cognitive gaps, and promote judicial fairness by aligning legal intentions. This study provides new theoretical and methodological support for the explainable reasoning of intelligent judicial systems. Full article

In higher education, the employability and entrepreneurship services play an essential role in the labor market insertion of graduates. The management of public relations promotes institutional projection, the creation of networks with companies, and the dissemination of initiatives to strengthen professional skills. This research analyzes how the communication strategies of Andalusian public universities improve employability and encourage entrepreneurship. A methodological triangulation is used: literature review, analysis of social networks with Fanpage Karma, and study of corporate websites. The results show a focus on counseling, training, workshops, job fairs, and networking events, strengthening the brand of universities and their commitment to the professional development of students. Full article

According to Victor Ernest Shelford’s ‘Law of Tolerance,’ organisms within ecosystems thrive optimally when environmental conditions are favorable. Applying this principle to ecosystems and agro-ecosystems facing water scarcity or environmental challenges can significantly enhance their productivity. In these ecosystems, phytocenosis adjusts its conditions by utilizing water with varying salinity levels. Moreover, establishing optimal drinking water conditions for human populations within an ecosystem can help mitigate future negative succession processes. The purpose of this study is to evaluate the quality of two distinct water sources in the Amudarya district of the Republic of Karakalpakstan, Uzbekistan: collector-drainage water and groundwater at depths of 10 to 25 m. This research is highly relevant in the context of climate change, as improper management of water salinity, particularly in collector-drainage water, may exacerbate soil salinization and degrade drinking water quality. The primary methodology of this study is as follows: The Food and Agriculture Organization of the United Nations (FAO) standard for collector-drainage water is applied, and the water quality index is assessed using the CCME WQI model. The Canadian Council of Ministers of the Environment (CCME) model is adapted to assess groundwater quality using Uzbekistan’s national drinking water quality standards. The results of two years of collected data, i.e., 2021 and 2023, show that the water quality index of collector-drainage water indicates that it has limited potential for use as secondary water for the irrigation of sensitive crops and has been classified as ‘Poor’. As a result, salinity increased by 8.33% by 2023. In contrast, groundwater quality was rated as ‘Fair’ in 2021, showing a slight deterioration by 2023. Moreover, a comparative analysis of CCME WQI values for collector-drainage and groundwater in the region, in conjunction with findings from Ethiopia, India, Iraq, and Turkey, indicates a consistent decline in water quality, primarily due to agriculture and various other anthropogenic pollution sources, underscoring the critical need for sustainable water resource management. This study highlights the need to use organic fertilizers in agriculture to protect drinking water quality, improve crop yields, and promote soil health, while reducing reliance on chemical inputs. Furthermore, adopting WQI models under changing climatic conditions can improve agricultural productivity, enhance groundwater quality, and provide better environmental monitoring systems. Full article

There is a growing global interest in making existing buildings more energy-efficient. However, stakeholders seem to have differing views on the matter, especially in developing countries, thus raising the issue of awareness amongst key stakeholders at the operational stage of existing buildings. This study aimed to examine stakeholders’ awareness of the benefits of passive retrofit in residential buildings using a convergent mixed-methods approach. Quantitative data were collected from 118 property managers and 163 owners of residential buildings, and qualitative data were collected from six government officials in Lagos State, Nigeria. The quantitative data collected were analysed using fuzzy synthetic evaluation, which addresses the fuzziness in judgement-making on multi-criteria phenomena. The results revealed that property managers and owners had a moderately high level of awareness of the environmental, economic, and social benefits of the passive retrofitting of residential buildings. However, while property managers generally had a higher level of awareness than owners, a significant gap was found in their awareness of environmental benefits. Conversely, the qualitative analysis results showed that government officials demonstrated a strong awareness of environmental benefits (energy reduction, air quality, and natural lighting) and economic advantages (cost savings and lower implementation costs). In contrast, their awareness of social benefits was limited to health improvements. The findings have practical implications for policy development and awareness campaigns. Building agencies need to further reinforce their targeted awareness programmes for owners, who demonstrated fair awareness of environmental benefits while leveraging the intermediary role of property managers in promoting home retrofit practices. Economic benefits should also be an integral part of policy frameworks to drive wider adoption across all stakeholder groups. Full article

Educational process data offers valuable opportunities to enhance teaching and learning by providing more detailed insights into students’ learning and problem-solving processes. However, its large size, unstructured format, and inherent noise pose significant challenges for effective analysis. Machine learning (ML) has emerged as a powerful tool for tackling such complexities. Despite growing interest, a comprehensive review of ML applications in process data analysis remains lacking. This study contributes to the literature by systematically reviewing 38 peer-reviewed publications, dated from 2013 to 2024, following PRISMA 2020 guidelines. The findings of this review indicate that (1) clickstream data is the most widely used processing data type, (2) process data analysis offers actionable insights to support differentiated instruction and address diverse student needs, and (3) ML typically serves as a tool for coding process data or estimating student ability. Persistent challenges, including feature extraction and interpreting results for practical applications, are also discussed. Finally, implications for future research and practice are discussed with a focus on enhancing personalized learning, improving assessment accuracy, and promoting test fairness. Full article

Implementing hybrid carbon policies is crucial for supply chains’ low-carbon transition. However, the downstream retailer is often passive in low-carbon strategies, leading to fair issues that may influence the decision-making of channel members. Therefore, this study integrates green technology, remanufacturing, retailer’s fairness concerns, low-carbon preference, and hybrid carbon policies into a manufacturer-led supply chain through differential game theory. Then, the equilibrium solutions for each member are analyzed under the centralized case and decentralized case involving a cost-sharing contract for low-carbon promotion. Our results show that centralized decision-making can optimize both the economic and environmental performances of channel members; retailer’s fairness concerns can enhance low-carbon promotional efforts and the cost-sharing ratio for such initiatives, but do not impact low-carbon production efforts. Additionally, a threshold exists on the relationship between retailer’s fairness concerns and the cost-sharing ratio; increased low-carbon preference motivates more efforts in low-carbon production and promotion. Moreover, stricter carbon policies motivate the manufacturer to increase low-carbon efforts, but the retailer tailors its low-carbon promotional strategy according to the unit carbon emissions of products to maintain an adequate level of low-carbon goodwill. Full article

This study explores how Human Resource Management (HRM) can help organizations to face the challenges of digital transformation, focusing on reducing digital inequalities and improving employee performance. As digital tools become more important in workplaces, many employees still experience digital exclusion, which affects not only their productivity but also their sense of fairness and inclusion, as well. To investigate these issues, quantitative research was conducted using a structured questionnaire distributed online to employees across EU-based companies. The data were analyzed through PLS-SEM, including IPMA and mediation analysis, to understand the relations between HRM practices, digital skills, and perceptions of organizational justice. The findings show that HRM strategies have a significant impact on bridging the digital divide, especially by promoting digital adaptability and supporting inclusive work environments. Inclusion was also found to mediate the relation between HRM and employee performance. This research offers practical suggestions, like using Key Performance Indicators (KPIs) to monitor digital participation and encouraging continuous learning. The study adds value by connecting digital empowerment with HRM policies in a way that supports both organizational efficiency and equality. Future research could focus on specific sectors or use longitudinal data to better capture how digital inclusion develops over time. Full article

Objectives/Background: With increasing awareness of the association between physical activity and mental health, promoting youth health has gained prominence. For this, education and support are needed. As psychological school-based factors could be key to affecting this behavior, this study investigates middle school students’ trust in their physical education teachers and their grit, analyzing their effects on health-promoting behaviors that could follow these adolescents through adulthood. Methods: Middle school students, aged 12–14, were recruited from three schools in Sejong City, Korea, in May 2025; 420 survey questionnaires were distributed and 390 were returned (response rate: 92.86%). After eliminating those with insincere responses, 369 valid questionnaires (boys = 186, girls = 183) were analyzed. The analysis covered the descriptive statistics, Pearson’s correlation, and structural equation modeling, with grit, trust in physical education teachers, and health-promoting behaviors as variables. Results: The correlation analysis verified multicollinearity between trust in physical education teachers (closeness, fairness, teaching method, and physical ability), grit (effort, perseverance, and interest consistency), and health-promoting behaviors (self-actualization, health management, and stress management). A positive significant correlation was found between all subfactors (p < 0.05). The research model’s fit was confirmed through several fit indices; specifically, normed χ² = 4.138, goodness-of-fit-index = 0.942, root mean square residual = 0.033, root mean square error of approximation = 0.092, incremental fit index = 0.965, Tucker–Lewis index = 0.947, and comparative fit index = 0.965, and all values were judged acceptable. The standardized coefficients of each latent variable explaining the measurement variables were 0.707 or higher. Therefore, the explanatory power of the measurement variables was also satisfactory; thus, the research model was appropriate and could be used for analysis. The model findings revealed that trust in physical education teachers had a positive effect on student grit (β = 0.505, p < 0.001) and that grit had a positive effect on health-promoting behaviors (β = 0.743, p < 0.001); however, trust in physical education teachers did not have a direct effect on health-promoting behaviors (statistically insignificant [β = 0.103, p > 0.05]). Thus, grit had a mediating effect between trust in physical education teachers and health-promoting behaviors (β = 0.375, p < 0.01). Conclusions: This study highlights the educational implications for physical education teachers of building trust and strengthening student grit as key factors in achieving sustainable health-promoting behaviors among adolescents. Full article

This inquiry articulates a conceptually cohesive framework to explore the interplay between ethical leadership–affective commitment, particularly in settings characterized by socio-environmental volatility. Central to the analysis is the examination of how ethical climate functions as a psychological conduit and how psychological empowerment modulates this pathway. Empirical validation was carried out with a sample of 448 employees (175 women, 273 men) from Colombia’s electricity sector, a context where institutional fragility elevates the salience of ethical practices. The study employed structural equation modeling to test the model’s robustness. Results underscore that ethical leadership cultivates a benevolent ethical climate, which in turn reinforces affective commitment. Importantly, this sequence is not fixed but is contingent upon psychological empowerment. The influence of ethical leadership on ethical climate and especially on affective commitment is amplified when empowerment is high; likewise, the ethical climate–affective commitment link becomes more salient under elevated empowerment conditions. These findings highlight the influence of ethical dynamics in organizations. Beyond model validation, this research contributes to broader conversations on social sustainability. Ethical leadership is shown to foster organizational climates rooted in fairness, stakeholder sensitivity, and moral coherence—factors essential for long-term institutional legitimacy. In environments such as Colombia’s electricity industry, where governance infrastructures are evolving, such leadership emerges as a necessary condition for rebuilding trust and promoting shared ethical standards. Accordingly, this study advocates for the systematic cultivation of ethical leadership as a means to enhance organizational loyalty and public credibility. The theoretical model presented here offers fertile ground for cross-cultural replication and further inquiry across industries in emerging economies. Full article

Object detectors often rely on multiple metrics to reflect their accuracy and speed performances independently. This article introduces object detector efficiency index (ODEI), a hardware-agnostic metric designed to assess object detector efficiency based on speed-normalized accuracy, utilizing established concepts including mean average precision (mAP) and floating-point operations (FLOPs). By defining seven mandatory parameters that must be specified when ODEI is invoked, the article aims to clarify long-standing confusions within literature regarding evaluation metrics and promote fair and transparent benchmarking research in the object detection space. Usage demonstration of ODEI using state-of-the-art (SOTA) YOLOv12 and RT-DETRv3 studies is also included. Full article

This study explores the development of reflective thinking among Physical Education Teachers (PETs) through a professional development program grounded in Paralympic values and inclusive education. Employing a qualitative action research design, the study involved seven PETs teaching in Greek primary schools. The intervention lasted ten weeks and comprised 20 Physical Education lessons, during which data were collected via semi-structured interviews, reflective journals, and non-participatory observation. The findings indicate a progressive shift in the teachers’ reflective thinking—from Technical Reflection to Practical and Critical Reflection—as defined in van Manen’s theoretical model. Most participants initially demonstrated a practical orientation but gradually developed a critical stance, incorporating values such as fairness, inclusion, and respect for diversity into their pedagogical thinking. Furthermore, the results revealed increased student sensitivity toward inclusive practices and a more democratic classroom climate. These findings suggest that targeted professional development programs can foster deeper reflective engagement and promote inclusive practices within Physical Education. This study highlights the potential of Paralympic values as meaningful educational content and reinforces the role of Physical Education as a catalyst for social inclusion and teacher professional growth. Full article