Data and Metadata

Introduction: Commodity management benefits from a variety of financial instruments and tools that allow companies to mitigate risks and optimize their operations. Among the most used are futures contracts, contracts for difference, risk management tools such as insurance and investment funds. The objective of this article is to analyze the scientific production on risks and financial instruments for the management of raw materials. Methodology: The research paradigm is mixed, through the combination of qualitative and quantitative methods. A bibliometric analysis was carried out which was complemented with a documentary review. The study was synthesized in three stages and was carried out in the Google Scholar, Scielo and SCOPUS databases, during the period from 1991 to 2024, without limitations in language. Results: The literature review shows an increase in the adoption of digital technologies to improve internal communication and employee engagement, with Brazil as a leader in the Latin American region. In addition, endomarketing is identified as a key element for attracting and retaining talent, especially in sectors with high competition and a shortage of specific skills. Likewise, its contribution to organizational sustainability is highlighted, focusing on the social dimension by promoting the well-being and development of employees. Conclusion: These findings reflect how endomarketing has been integrated into business strategies to align corporate objectives with the values ​​of social responsibility and job satisfaction, consolidating itself as an essential tool in improving productivity and long-term commitment.

Carlos Julio Rojas-Hermida

John Edisson García Peñaloza

Ricardo León Castro Zamora

Data & Metadata

Scientific production on risks and financial instruments for commodity management

商品管理中的风险与金融工具的科学产出

IntroductionThis research aims to explore the effectiveness and inclusivity of AI-powered recruitment tools in hiring people with disabilities within the United Arab Emirates. Such is the situation where AI integration into the arena of recruitment is increasingly rapid, while there are vital issues on the side of bias, accessibility, and fairness for applicants of diverse needs. MethodsThis study was a mixed-methods approach, examining sentiment analysis, emotion detection, and HR analytics of feedback from applicants with a disability, 415 in total. The research focused on scores referring to sentiment, the progression rate, and the outcome of the final hiring. ResultsThe sentiment score varied significantly across disability types (p-value &lt;0.05). The applicants with cognitive disability expressed the highest sentiment sore while applicants with hearing impairment had the lowest, which indicated the varying adaptability of AI. The emotion analysis depicted a mix of positive and negative emotions. A few applicants liked technology and have trust in it, while others report fear. Clearly, the applicants, both disabled and non-disabled did not differ in their rate of progression (p-value &gt;0.05), hence never indicating any significant difference within the initial steps of the process. The final hiring stage showed significant differences in results with (p-value &lt;0.05), where the proportionate number of disabled applicants was recorded to be lower than that of non-disabled applicants

Ambreen Iftikhar

Suleiman Ibrahim Mohammad

Mohammad N. Alqudah

Ahmad Samed Al-Adwan

Asokan Vasudevan

Imad Ali

Mohd Farhan

Evaluating Inclusivity and Fairness of AI Recruitment Tools for Hiring People with Disabilities in the United Arab Emirates(UAE)

评估阿拉伯联合酋长国（UAE）人工智能招聘工具对残障人士招聘的包容性和公平性

This study analyzes the financial performance of 17 ISO-certified, listed Moroccan companies for the year 2022. The primary goal is to assess the impact of various financial variables on these companies' profitability. The financial variables examined include the degree of financial indebtedness, self-financing, financial leverage, liquidity, guarantees, company size, and speed of capital turnover. The analysis focuses on the relationship between these variables and profitability models (ROE and ROA). The findings indicate that the profitability models have respective risk levels of 5% and less than 10%. Significant variables influencing the financial performance of the studied companies were identified. The results emphasize the importance of financial management and strategic decision-making based on these models to enhance company performance

Saad Saadouni

Amina Guennoun

Souad Habbani

The impact of financial structure on performance: The case of ISO-certified, listed Moroccan companies

财务结构对绩效的影响：以获得ISO认证的摩洛哥上市公司为例

Background:Cardiovascular disease (CVD) is a primary universal physical problem, with conventional prediction systems frequently being persistent and expensive. Modern advancements in machine learning (ML)offer a hopeful option for accurate CVD risk assessment by leveraging multifaceted relations among diverse risk factors.Aim:Their search proposes a novel deep learning (DL) system, Dynamic Owl Search algorithm-driven Adaptive Long Short-Term Memory (DOS-ALSTM), to enhance cardiovascular risk prediction utilizing electrocardiogram (ECG) data.Method:The study utilizes ECG data from a diverse population group to train and assess the proposed model. Data is cleaned and normalized employing standard techniques to handle lost values and ensure reliability. Relevant features are extracted using statistical and signal processing technique to detain crucial features from the ECG data. The DOS-ALSTM system integrates a DOS optimization algorithm for optimized parameter regulation and ALSTM networks to detain sequential dependencies in ECG data for accurate risk prediction. The recognized method is evaluated using Python software.Result:The DOS-ALSTM system demonstrates superior performance with superioraccuracy of 99%, recall of 98%, F1-Score of 97.9% and Precision of 98.8% in CVD risk assessment compared to traditional methods

Denghong Zhang

Benjamin Samraj Prakash Earnest

Ihab Elsayed Mohamed Ali Abdou

An Innovative algorithm framework for cardiovascular risk assessment based on ECG data

基于心电数据的心血管风险评估创新算法框架

Introduction: The globalisation of the economy, dynamic changes in financial markets, and the advent of big data have spurred the development and implementation of artificial intelligence (AI) and machine learning (ML) tools for forecasting economic trends. The purpose of this study is to evaluate the impact of AI and ML on the accuracy and effectiveness of economic trend forecasting. The authors analyse examples of AI and ML applications in various economic sectors during the period 2019–2023, including regional aspects. Methods: To achieve the objectives of this study, we conducted a comprehensive qualitative and quantitative analysis of the role of artificial intelligence (AI) and machine learning (ML) in predicting economic trends. Results: The findings indicate that the use of AI and ML improves the efficiency of economic trend forecasting and allows for quicker adaptation to market changes, thereby reducing risks and uncertainty. Conclusions: Thus, the integration of artificial intelligence and machine learning in economic analysis not only increases the effectiveness of forecasting but also lays the foundations for the sustainable development of economies in a globalised world.

Svitlana Marushchak

Iryna Fadyeyeva

Petar Halachev

Nursultan Zharkenov

Sergii Pakhomov

The role of artificial intelligence and machine learning in forecasting economic trends

人工智能与机器学习在预测经济趋势中的作用

This research examines the impact of management control systems on the competitive advantage of industrial companies, with a focus on the role of the blue ocean strategy as a mediating variable in this relationship. To achieve these objectives, a quantitative methodology was employed. Data was gathered through a structured questionnaire distributed online via Google Forms, and the analysis was performed using Smart PLS Version 4 software. The sample consisted of 405 Moroccan industrial companies. The analysis revealed that management control systems significantly impact competitive advantage, and the blue ocean strategy mediates this relationship. Based on these findings, future research should explore various approaches to implementing blue ocean strategies and their effects on company performance.

Mustapha RAZZOUKI

Rachid ZAMMAR

Adil GAROHE

Karima SALAH-EDDINE

The mediating effect of blue ocean strategy on the relationship between management control system and competitive advantage

管理控制系统与竞争优势关系中蓝海战略的中介作用

Introduction: This study uses bibliometric methods to evaluate research articles within the library and information science (LIS) domain. The focus is to uncover trends and patterns in social network analysis related to LIS, particularly examining research collaborations and content within highly cited articles. By analyzing these aspects, the study seeks to identify influential authors, prominent research themes, and key contributors in the LIS field. Methods: A dataset of 14,517 articles published between 1954 and 2023 was extracted from the Scopus database for bibliometric analysis. The study concentrated on publications in the LIS domain, focusing on the journal Library Philosophy and Practice. Multiple Correspondence Analysis (MCA) was used to identify clusters within the research field, while content analysis was performed to determine prevalent topics and disciplinary influences within the articles. Results: The analysis revealed that China is home to many of the most influential authors in the LIS domain, with the United States, China, and the United Kingdom identified as the top contributing countries to LIS research. Common research themes include information science, bibliometrics, academic libraries, information literacy, and LIS education. Two main clusters emerged from the MCA: one focused on information-related concepts and the other on bibliometrics and scholarly communication. Content analysis indicated a significant presence of topics from physics, computer science, and information technology within LIS research. Conclusions: This study highlights key trends and patterns in LIS research, with academic libraries, information literacy, LIS education, and librarians' roles identified as critical areas for future exploration. Expanding databases and refining keyword searches are recommended to enhance knowledge dissemination and educational adaptability in the LIS field. The findings aim to support LIS researchers, facilitate research planning, and promote global interinstitutional cooperation

Pornnisa Wattanasiri

Paiboon Manorom

Wirapong Chansanam

Emerging Themes, Leaders, and Collaboration in Library and Information Science Research

图书馆与信息科学研究中的新兴主题、领导者与合作

This study aims to establish the impact of employing Smart Home Training Kits as a new approach to developing Higher-Order Thinking Skills (HOTS) in vocational education. Using a quasi-experimental design, the study involved two groups of vocational students: supporting them by an experimental group applying Smart Home Training Kits and a control group using conventional methods of instruction. Standard pre-tests and post-tests were administered among the students to evaluate the enhancement in the level of higher-order thinking skills, for aspects of critical thinking, problem-solving solving, and creativity. The findings also showed a work improvement in the experimental group compared to the group control group. The experimental group of students who were trained using the Smart Home Training Kits performed better when it came to the analysis, evaluation, and Synthesis of possible solutions regarding smart homes. Also, a number of the activity kits characterized the technical thing being taught in a detailed way that allowed the students to gain a more realistic understanding of the principles at work. The findings of this paper suggest that Smart Home Training Kits are one of the ways through which Higher-Order Thinking Skills can be effectively taught within the technical education training regime while closing the gap between theory and practical. This indicates that the assimilation of these kits in curricula could help the effective development of critical thinking and innovation at the expense of students to face the current world workplace challenges.

None Sukardi

Oriza Candra

Emilham Mirshad

Mahesi Agni Zaus

Syaiful Islami

Leveraging Smart Home Training Kits as an Innovative Educational Tool to Foster Higher-Order Thinking Skills

利用智能家居训练套件作为创新教育工具培养高阶思维能力

In response to the COVID-19 pandemic, a Moroccan automotive glass company embarked on a strategic overhaul to improve its supply chain performance and resilience. Faced with excessive working capital tied up in inventory (Working Capital = $200M), the company chose to integrate advanced artificial intelligence (AI) technologies with Lean Manufacturing principles, including Just-In-Time (JIT) production and workload balancing. The goal was to lower inventory levels while maintaining a high service rate to meet customer demands. AI tools have played a crucial role in predicting quality defects and forecasting equipment availability, facilitating streamlined operations and cost reduction. This initiative also aims to enhance the supply chain's ability to withstand and adapt to future disruptions

Hatim Lakhouil

Aziz Soulhi

The fusion of Lean Manufacturing with Industry 4.0 technologies towards a new pillar for improving supply chain performance, the case of the automotive industry in Morocco

精益制造与工业4.0技术融合：提升供应链绩效的新支柱——以摩洛哥汽车行业为例

The Industrial Revolution 4.0 in the 21st century has necessitated a shift in learning experiences and self-development to adapt to evolving learning mindsets and digital literacy demands. Teachers are encouraged to reduce administrative workloads that are not aligned with the digital age and focus on adopting digital-based learning models and media that suit modern student needs. This study aimed to implement and analyze the impact of case-based projects integrated with Building Information Modeling (BIM) software on civil engineering students’ understanding of interior building design. This mixed-methods research utilized a sequential explanatory design. A sample of 60 civil engineering students was selected through random sampling. Quantitative data were analyzed using path analysis, while qualitative data were examined through data reduction, data display, and conclusion drawing/verification analysis. The findings indicate that the case-based project approach, integrated with BIM software, was effectively applied and positively impacted students’ skills in learning BIM. Students showed improved abilities to analyze, explore, and synthesize information through hands-on experience with real-world case-based projects. This study contributes a novel educational model by integrating technology with learning methods through case-based projects in BIM software. This innovation supports students in enhancing their analytical and problem-solving skills and aligns with the requirements of the Industrial Revolution 4.0

Resi Elfitri

Ambiyar Ambiyar

Fahmi Rizal

Rijal Abdullah

Asrul Huda

Rizky Ema Wulansari

Breaking Grounds in Civil Engineering Education: The Potential of Building Information Modelling Software as Catalyst for Improved Interior Design Learning

土木工程教育的新突破：建筑信息建模软件作为提升室内设计学习效果的催化剂的潜力

ISSN	2953-4917
h-index	15

出版信息	出版商: Editorial Salud, Ciencia y Tecnología，出版周期: ，期刊类型: journal，开源期刊: 否
基本数据	创刊年份: 2022，原创研究文献占比: ，自引率:， Gold OA占比:

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