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- A Comparative Analysis of the 2017 and 2024 Global Internal Auditing Standards and Their Implementation Challenges in Developing Countries: Toward Adapting to ChangePublication . Attaf, Wala FaridThe mandatory implementation of the Global Internal Audit Standards issued by the Institute of Internal Auditors (IIA) in 2024 marks a significant transformation in the regulation and practice of internal auditing worldwide, particularly in developing-country contexts. This study provides a comparative analysis of the 2017 International Professional Practices Framework (IPPF) standards and the 2024 Global Internal Audit Standards, with a focus on structural changes, conceptual evolution, and implementation challenges. Methodologically, the study employs a qualitative documentary analysis, combined with a descriptive and comparative approach. It analyzes official IIA standards and supporting documents, complemented by professional reports and recent peer-reviewed academic literature published between 2022 and 2025. The findings reveal that the 2024 Standards introduce a unified, principle-based framework that strengthens governance integration, quality management, stakeholder engagement, and the strategic role of internal audit, while embedding emerging priorities such as digital transformation, sustainability, and risk-based value creation. However, the analysis also indicates that the increased prescriptiveness and strategic expectations of the 2024 Standards pose significant implementation challenges in developing countries, where institutional maturity, regulatory support, technological readiness, and professional capacity often remain limited. The study contributes to the internal auditing literature by providing a critical synthesis of the evolution of global internal audit standards and by advancing an interpretive, context-sensitive perspective on their adoption in developing-country contexts. It provides insights for Chief Audit Executives, regulators, and policymakers on how to balance global standardization with contextual adaptation, capacity building, and phased implementation strategies.
- Computer Learning SystemsPublication . Teixeira, Cristiane; Teixeira, Marcelo; Farias-Júnior, Ivaldir; Lima, SidneyComputational learning systems are configured as digital platforms, specialized tools, or systematized methodologies aimed at facilitating, organizing, and optimizing educational processes in virtual environments. Learning Content Management Systems (LCMS) focus on the creation, structuring, storage, and reuse of learning objects, enabling educators to develop personalized, modular, and scalable instructional materials. In turn, Learning Management Systems (LMS) are designed to operationalize the administration of the teaching and learning process, encompassing functionalities such as enrollment management, content delivery, student performance tracking, and assessment implementation. In this context, the present study qualitative in nature and based on an empirical- descriptive approach proposes a comparative analysis between LCMS and LMS, considering technical and pedagogical features, operational limitations, and contributions to the consolidation of innovative practices in higher education, specifically within the undergraduate programs in Computing Education and Software Engineering at the University of Pernambuco – Garanhuns Campus.
- Determinants of R&D investment under Uncertainty: An Empirical Study of Saudi FirmsPublication . Saif, Abdullah Abdulhafedh Abdullah; An, Nguyen Ngoc Minh; Mohammed, Mohammed Abdeulglel Mansoor; Abduljalil, Abdullah Mohammed Abdulnoor; Altahery , Akram Ali Abdullah; Abdullah, Adam Ali Ahmed; Dawood, Mariam Mourise Saad GhattasThis study aims to examine the financial determinants of research and development (R&D) investment in Saudi industrial firms, with particular emphasis on periods of economic crises. The 2008 Global Financial Crisis and the COVID-19 pandemic are employed as representative examples of major economic shocks to assess firms’ innovation responses. To achieve this objective, the analysis incorporates firm-specific variables using panel data for a sample of thirty industrial firms over the period 2007–2020. The sample selection is based on firms’ strategic engagement in R&D activities and the critical contribution of the industrial sector to the national economy. The dataset, covering fourteen years, was compiled from audited financial statements of the selected firms, obtained from their official websites. The study adopts a purposive sampling approach and an explanatory (causal) research design, employing quantitative data within a multiple regression framework. Using STATA for empirical analysis, the study utilizes one dependent variable R&D investment, measured as the ratio of R&D expenditure to total assets and eight independent variables: cash , sales growth rate, gross profit from sales, return on assets, return on equity, internal financing rate, external financing rate, and the debt-to-equity ratio. The results reveal a statistically significant positive relationship between sales growth rate, gross profit from sales, return on assets, and internal financing, and R&D investment. Conversely, the findings indicate a negative relationship between cash holdings, return on equity, external financing, and the debt-to-equity ratio, and R&D investment.Although crises explains only a small share of R&D variation (R² ≈ 13%), financial variables consistently demonstrate far greater explanatory power ( 87%), confirming that firms’ financial conditions are the key drivers of R&D investment in times of economic turmoil. Finally, the study recommends that Saudi industrial firms adopt optimal business portfolio diversification strategies to reduce exposure to crisis-related risks and mitigate their adverse effects. To enhance their investment portfolios, firms should move beyond traditional income sources and diversify into alternative, non-interest-based revenue streams.
- Diaspora networks and export performance of small-scale agroprocessing firms in NigeriaPublication . Isichei, Ejikeme Emmanuel; Mohammed, Awwal Mohammed; Isichei,This study examines how diaspora networks influence the export performance of small-scale agro-processing firms in the Federal Capital Territory, Abuja, Nigeria. Drawing on social network theory and diaspora entrepreneurship theory, the study conceptualises diaspora networks through three dimensions: remitting behaviour, diaspora knowledge transfer, and diaspora trade facilitation. Primary data were collected through a structured questionnaire administered to owners and managers of small-scale agro-processing firms, and the hypothesised relationships were analysed using partial least squares structural equation modelling. The results indicate that remitting behaviour, diaspora knowledge transfer, and diaspora trade facilitation each exhibit positive and statistically significant relationships with export performance. The findings highlight the multidimensional role of diaspora communities as providers of financial capital, market-relevant knowledge, and cross-border trade support that can strengthen the international competitiveness of small firms. The study contributes to the diaspora networks and small firm internationalisation literature by providing firm-level evidence from an emerging economy context and by clarifying actionable pathways through which diaspora engagement can be leveraged to improve export outcomes. Policy and managerial implications are discussed, particularly regarding programmes that support productive remittance channelling, structured knowledge exchange platforms, and diaspora-enabled trade linkages.
- The Evaluating the Financial Impact of Predictive Maintenance in Manufacturing: An Integrative Literature ReviewPublication . Sibeko, Feresane MatthewEven if measuring the ROI (Returns-on-Investment) of predictive equipment maintenance is essential for discerning whether the manufacturing entity is overspending or underspending on equipment maintenance, most manufacturing executives often do not bother to measure the ROI of their equipment maintenance. This affects decisions on the improvement initiatives that can be adopted. To address such a problem, this study used integrative review to evaluate insights from the existing studies about the techniques, values, and limitations of measuring the ROI of predictive manufacturing equipment’s maintenance. The research was a qualitative study based on content analysis of articles retrieved primarily through Google searches as the major search engine. After predictive maintenance, findings from the analysis indicated the financial metrics to measure the financial gains obtained since the introduction of predictive machine maintenance. It evaluates the benefits and advantages so far attained as compared to the costs incurred in the application of predictive maintenance. Apart from ROI, some of the commonly used financial metrics were found to encompass cost-benefit analysis and net present value (NPV). ROI analysis seeks to evaluate the benefits gained against the costs incurred in the use of predictive machine maintenance. However, findings indicated the major inhibitors of measuring the ROI of predictive machine maintenance to often arise from cost, poor data utilization culture, and ignoring predictive maintenance. Unless management is able to deal with such challenges, they may never get to understand the returns on investment generated from the expenditure on predictive equipment maintenance. From these findings, this study has contributed to changing the general perception of predictive maintenance as an expenditure rather than an investment.
- Evaluation contests in Portuguese: Linguateca’s contributionPublication . Santos, DianaThis paper presents four initiatives for fostering and jointly evaluating the progress of Portuguese language processing, organized for a decade (2002-2012) by Linguateca, concerning a) morphological analysis, b) named entity recognition, c) (crosslingual) information retrieval and question-answering, and d) Wikipedia search. In addition to summarize, for an international audience, the most important data and results coming from these activities, I discuss some issues critically and reflect on what was learned, also about the challenges of organizing language-specific venues.
- Generative AI in Teacher Training: A Study of Pre-Service Teachers’ Engagement and PerspectivesPublication . Couto, Filipe; Martins, RosaThis study aimed to understand how future teachers are integrating generative artificial intelligence into their academic routines during initial teacher education. Using a mixed-methods approach, quantitative data were collected through a Likert-scale questionnaire administered to 94 students at a School of Education in Portugal, complemented by a qualitative analysis of open-ended responses. The findings reveal widespread use of tools such as ChatGPT for clarifying doubts, supporting study practices, and enhancing academic writing. At the same time, ethical and pedagogical concerns emerge, particularly around plagiarism, the reliability of information, and the impact on critical thinking. Students show a simultaneously receptive and critical attitude, acknowledging the value of generative AI as a support tool while calling for transparency, regulation, and proper training to ensure its ethical and responsible use. The study highlights the importance of integrating critical digital literacy and ethical reflection on AI into initial teacher education programs, preparing future educators for an increasingly technological educational landscape that must remain focused on human and pedagogical development.
- Generative Artificial Intelligence in Higher Education: Challenges, Opportunities and Pedagogical ImplicationsPublication . Vieira, Ana; Mesquita, AnabelaGenerative Artificial Intelligence (GAI) is transforming Higher Education (HE), impacting academic writing, teaching methodologies and institutional practices. This study presents a literature review on the use of GAI in HE between 2024 and 2025, analyzing its strengths, weaknesses, opportunities and challenges. GAI improves productivity, student engagement, and personalization, but raises concerns about academic integrity, envy, and over-reliance on this technology. The results highlight the need for clear institutional policies, ethical guidelines and continuous training for teachers, ensuring a responsible integration of GAI. Future research should address pedagogical strategies, ethical issues, and long-term impacts of GAI on learning.
- How AI Tools Affect the Customer Experience: a case studyPublication . Boulkara, Amina; Khadich, GhadaUsing an integrative review, this study provides a hypothetical-deductive approach of the effects of adopting AI tools on enhancing customer experience. The study was motivated by the observation that, in today’s competitive business environment, organizations often struggle to fully leverage AI technologies to understand and address customer needs, which can limit the effectiveness of customer experience strategies. To address this issue, this study employed an integrative review as a qualitative research method, structured around literature search, data extraction, and thematic analysis. From the analysis of relevant literature, findings suggest that the effective implementation of AI tools including chatbots, recommendation systems, and predictive analytics is closely linked with the personalization and efficiency of customer interactions. Proper integration of AI enables organizations to anticipate customer needs, optimize service processes, and foster stronger relationships. However, insufficient adoption or misalignment of AI strategies may hinder customer engagement and satisfaction. By examining the role of AI adoption in enhancing customer experience, this study sheds light on the mechanisms through which intelligent technologies bridge the gap between businesses and clients. Future research could employ exploratory empirical methods to develop a structured model that further elucidates how specific AI tools contribute to improved customer experiences across different industries.
- The Impact of Risk Management Strategies on the Financial Performance of Yemeni Banks under Economic Turbulence: Evidence from 2014–2024Publication . Saif, Abdullah Abdulhafedh Abdullah; Al-mafleh, Mohammed Qasem; Mohammed, Mohammed Abdeulglel Mansoor; Abduljalil, Abdullah Mohammed Abdulnoor; Altahery, Akram Ali Abdullah; IADITIThe prolonged economic turbulence in Yemen has posed significant challenges to the stability and resilience of its banking sector, highlighting the critical need for effective risk governance mechanisms. In this context, the study examines how liquidity, market, credit, and operational risks the core dimensions of risk management affect return on assets (ROA). A balanced panel dataset was constructed from the annual reports of ten banks covering the period 2014 to 2024, selected based on data availability. The analysis employs pooled OLS, fixed-effects, and random-effects estimations, followed by Feasible Generalized Least Squares (FGLS) to ensure robustness. Correlation results indicate positive associations between all risk dimensions and ROA, with operational risk management showing the strongest relationship, followed by market and liquidity risk management, while credit risk exhibits a weaker link. Regression findings consistently confirm that operational, market, and liquidity risk management significantly enhance profitability, with operational risk management exerting the largest effect. Credit risk management demonstrates a positive but statistically insignificant influence, suggesting a more gradual or delayed impact on financial performance. Collectively, these findings highlight that integrated and well-coordinated risk management practices are essential for sustaining profitability in economically fragile environments.