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This study aims to provide a qualitative framework for satisfactory sustainable education for international accounting students using a meta-synthetic approach.

To determine the components and indicators of satisfactory sustainable education for international accounting students, a meta-synthesis allows for the attainment of the objectives of study. In the first phase of study, international related literature was reviewed (n = 2,176). After several screenings for measuring the quality of the related literature including Critical Appraisals Skills Program (CASP), the total number of selected papers was 48, and 2,128 were excluded.

The present research proposed a comprehensive conceptual model for sustainable education and international accounting students’ satisfaction, with seven components and 63 indicators. To assess the credibility of phases, the indicators were presented to five experts independently. The reliability of the proposed conceptual model was tested using Cohen’s Kappa coefficient and analyzed in SPSS. Kappa’s coefficient showed that the agreement level was high and the reliability was high too.

Sustainable education and student satisfaction are crucial for maintaining a competitive international education market. There are ongoing debates about accounting education, particularly accreditation challenges and the need for clear regulations on academic interaction with practice. Accounting education has also been criticized for being outdated, promoting surface-level learning and neglecting the development of broader skills in university graduates. Therefore, it is important to understand sustainable education for international accounting students. The present study aims to identify the aspects of accounting educational services that international accounting students perceive important for increasing satisfaction. This research provides empirical evidence and suggests potential avenues for future research in other countries.

This study aims to analyse the existing literature on the utilisation of financial technology (FinTech) in the Islamic social finance (ISF) sector, focusing on tools, applications and benefits. From this study, it is to provide insights for literature or for practitioners on how FinTech can be used in ISF, such as using blockchain (tools) in waqf (application) that can help to enhance transparency and trust (benefits) with donors. It is important to explore new available tools or applications in ISF markets so that such effort can benefit the industry in promoting its growth.

A systematic literature review (SLR) was carried out using Reporting Standards for Systematic Evidence Syntheses (ROSES) which has been based on quality evaluation criteria, beginning with 41,945 entries in Scopus, 25,386 entries in the Web of Science and 1,590 entries in the Google Scholar databases and ending with 35 articles from data abstraction and analysis, all of which focus on tools, applications and benefits of FinTech in ISF sector.

This review yielded three primary themes and eleven sub-themes addressing FinTech, namely applications (four sub-themes: crowdfunding, blockchain, banking service and peer-to-peer (P2P), tools (three sub-themes: waqf, zakat and sadaqah), as well as benefits (four sub-themes: transparency, innovation, inclusiveness and efficiency).

This study emphasises on innovative application of FinTech used in ISF industry which focuses on applications, tools and benefits of FinTech to the industry. However, the findings indicate that there is plenty of room for future investigation. The current work outlines several methodological issues and concerns as well as provides recommendations for future research. Various challenges associated with FinTech applications include inadequate regulations, complex permit application procedures, misuse of FinTech for terrorist financing, the existence of fraudulent FinTech companies and consumer disputes in the FinTech sector concerning ISF. There are few in-depth studies on the possible use of FinTech models in ISF, compared to studies focusing on upcoming challenges. This study also highlights the methodological limitations in previous research efforts, which can be used to improve future studies in this area. To offer a more comprehensive analysis, additional search keywords and engines that have not been included in this study could be used in future investigations with different methodologies.

For practitioners, the paper has significant managerial consequences. The analysis provides insights into real-life opportunities, limits and solutions for improving performance management by looking at FinTech applications from a larger and more diverse perspective. The practitioners, especially the State Islamic Religious Council, can recognise the benefits of using FinTech technology in ISF (waqf, zakat and sadaqah), namely under their jurisdiction.

This systematic literature assessment identifies critical knowledge gaps that must be addressed such as the applications of FinTech that are still ambiguous, with certain applications not completely embraced in the ISF industry. This study uses SLR technique to categorise literature, identify gaps in current studies and provide recommendations for the research issue (Paul and Criado, 2020), instead of using the other previous methodology such as content analysis or qualitative review. Hence, FinTech is considered an innovative or new approach in ISF industry.

As lubricating oils are used, their performance deteriorates and they become contaminated. The purpose of this paper is to investigate the lubrication performance of reclaimed 5 W-30 a fully synthetic used engine oil (UEO) with wear tests after refining it from a solvent-based extraction method using solvent (1-PrOH) and adsorbent materials such as cement, celite and deep eutectic solvent (DES).

The treated oil mixtures were prepared by blending engine oils with various adsorbent materials at 5% (w/w) in organic 1-PrOH solvent at a UEO: solvent ratio of 1:2 (w/w). The measurement of kinematic viscosity, density, the total acid number (TAN) and elemental analysis of oil samples was done by the ASTM standards D445/D446, D4052, D974 and D6595, respectively. Adsorbents and treated oil samples characterized by SEM-EDX, FTIR and UV analysis, respectively. Meanwhile, lubricating performance in tribological applications was evaluated through the wear test device using a rotating steel alloy 1.2379 cylinder and a stationary 1.2738 pin under 20, 40 and 80 kg load conditions. Worn surface analysis was done with SEM and 2.5D images.

It was found that when using the combination of cement and celite as an adsorbent in the reclamation of used engine oil demonstrated better lubricant properties. The properties of used engine oil were improved in the manner of kinematic viscosity of 32.55 from 68.49 mm²/s, VI (Viscosity index) value of 154 from 130, TAN of 3.18 from 4.35 (mgKOH/g) and Fe content of 11 from 32 mg/L. The anti-wear properties of used engine oil improved by at least 32% when 5% cement and 5% celite adsorbent materials were used together.

The paper is based on findings from a fully synthetic 5 W-30 A5 multi-grade engine lubrication oil collected after driving approximately 12.000 km.

The results are significant, as they suggest practical regeneration of used engine oil is achievable. Additionally, blending fresh oil with reclaimed used engine oil in a 1:1 ratio reduced wear loss by over 10% compared to fresh oil.

Reusing used engine oils can reduce their environmental impact and bring economic benefits.

This study showed that the properties of UEO can be enhanced using the solvent extraction-adsorption method. Furthermore, the study provided valuable insights into the metal concentrations in engine oil samples and their impact on lubrication performance. The order of the number of the grooves quantity and the possibility of the observed scuffing region trend relative to the samples was UEO > 5W-30 fresh oil > Treated oil sample with the adsorbent cement and celite together.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0209/

This study aimed to examine the mediating role of corporate financial reporting quality in the impact of corporate social responsibility (CSR) on corporate green innovation, based on the integration of stakeholder theory, opportunity cost theory, innovation diffusion theory and signaling theory.

A deductive quantitative approach was used as the research methodology. Following a survey design, questionnaire responses were collected from a purposively chosen sample of 308 employees in China. The data was analyzed using partial least squares structural equation modeling, performed with SmartPLS4.0 software.

The findings show that CSR promotes green innovation, and that financial reporting quality mediates this relationship. It was further revealed that compared to employees’ CSR perception, consumers’ perception of firms’ CSR performance has a stronger positive effect on firms’ corporate financial reporting quality and green innovation. These findings provide insights into the impact of both internal and external CSR performance on corporate green innovation.

This study only sampled Chinese employees, meaning that the findings may not be representative of other regions. Also, as this study employed only the questionnaire instrument, future research may collect data through multiple sources, including financial reports, surveys and interviews, to better understand and estimate variations in the positive impact of CSR on green innovation.

This study establishes the mediating role of corporate financial reporting quality in linking CSR to corporate green innovation. It further examines green innovation in multiple dimensions (i.e. product, process, organizational), while also measuring CSR in dual perspectives, namely internal (employee awareness) and external (consumer awareness). The results of this study offer guidance to firms in improving their green innovation in various aspects, thus promoting sustainability and environmental friendliness in corporate development.

This study aims to identify the location of the micropyle, the role of the micropyle in seed germination and the association between the micropyle size and seed weight of grass peas.

First, the micropyle was identified by cutting the seed in half and observing the seeds under the electron microscope. Second, the micropyle was covered by lanolin to block water imbibition. The rate of imbibition and germination was then observed. Lastly, micropyle sizes of various grass pea genotypes were identified by capturing seed images under a light microscope and converting the sizes to mm² using computer software (ImageJ).

The location of micropyle was located nearby the hilum, similar to soybean seeds. Seed imbibition was significantly lower in lanolin application (<87%) than in the control (>124%) after 24 hours of submergence. Germination was a day delay for lanolin application on the micropyle compared to lanolin application on the non-micropyle. The germination delay resulted in a significantly lower germination percentage at <57% on the micropyle lanolin application than at >79% on the non-micropyle lanolin application after 10 days of sowing. There is no correlation between the micropyle size and seed weight.

These findings add information on the location and the role of the micropyle for grass pea seed germination.

This paper addresses the under-explored collateral damage of economic sanctions, shedding light on the disproportionate harm endured by the most vulnerable segments of societies, which at the same time lack political influence to effect the ruling government into change. The primary objective is to review the literature on humanitarian repercussions associated with sanctions, concluding if they really are a comparably human way of international interference.

Employing a systematic literature review, adhering to the PRISMA approach, and incorporating key term definitions and clear selection criteria, this review analyses 52 studies sourced from Scopus and EconBiz.

The surveyed literature reveals profound adverse impacts of sanctions on health, economic well-being, inequality, and education. Critical gaps in the literature such as disproportional focus on extreme cases like Iran and Iraq, scarce literature on effects on education and inequality, and predominantly inadequate control groups are identified, limiting the generalizability of existing findings.

This paper is the first systematic and replicable review of the literature on the effects of sanctions using a capabilistic approach to define poverty. Highlighting gaps in the current research landscape underscores the limited generalizability of reviewed results. Providing a well-structured summary of existing literature, this work serves as a foundation for future research.

The paper aims to enhance Arabic machine translation (MT) by proposing novel approaches: (1) a dimensionality reduction technique for word embeddings tailored for Arabic text, optimizing efficiency while retaining semantic information; (2) a comprehensive comparison of meta-embedding techniques to improve translation quality; and (3) a method leveraging self-attention and Gated CNNs to capture token dependencies, including temporal and hierarchical features within sentences, and interactions between different embedding types. These approaches collectively aim to enhance translation quality by combining different embedding schemes and leveraging advanced modeling techniques.

Recent works on MT in general and Arabic MT in particular often pick one type of word embedding model. In this paper, we present a novel approach to enhance Arabic MT by addressing three key aspects. Firstly, we propose a new dimensionality reduction technique for word embeddings, specifically tailored for Arabic text. This technique optimizes the efficiency of embeddings while retaining their semantic information. Secondly, we conduct an extensive comparison of different meta-embedding techniques, exploring the combination of static and contextual embeddings. Through this analysis, we identify the most effective approach to improve translation quality. Lastly, we introduce a novel method that leverages self-attention and Gated convolutional neural networks (CNNs) to capture token dependencies, including temporal and hierarchical features within sentences, as well as interactions between different types of embeddings. Our experimental results demonstrate the effectiveness of our proposed approach in significantly enhancing Arabic MT performance. It outperforms baseline models with a BLEU score increase of 2 points and achieves superior results compared to state-of-the-art approaches, with an average improvement of 4.6 points across all evaluation metrics.

The proposed approaches significantly enhance Arabic MT performance. The dimensionality reduction technique improves the efficiency of word embeddings while preserving semantic information. Comprehensive comparison identifies effective meta-embedding techniques, with the contextualized dynamic meta-embeddings (CDME) model showcasing competitive results. Integration of Gated CNNs with the transformer model surpasses baseline performance, leveraging both architectures' strengths. Overall, these findings demonstrate substantial improvements in translation quality, with a BLEU score increase of 2 points and an average improvement of 4.6 points across all evaluation metrics, outperforming state-of-the-art approaches.

The paper’s originality lies in its departure from simply fine-tuning the transformer model for a specific task. Instead, it introduces modifications to the internal architecture of the transformer, integrating Gated CNNs to enhance translation performance. This departure from traditional fine-tuning approaches demonstrates a novel perspective on model enhancement, offering unique insights into improving translation quality without solely relying on pre-existing architectures. The originality in dimensionality reduction lies in the tailored approach for Arabic text. While dimensionality reduction techniques are not new, the paper introduces a specific method optimized for Arabic word embeddings. By employing independent component analysis (ICA) and a post-processing method, the paper effectively reduces the dimensionality of word embeddings while preserving semantic information which has not been investigated before especially for MT task.

This study investigates the level and correlation between talent management and teacher personal qualities among MICSS (Malaysian Independent Chinese Secondary School) teachers by integrating the talent management model proposed by Davies and Davies (2011) and the Big Five Structure established by Lewis R. Goldberg (1992).

The researcher conducted quantitative research methods in this study, collecting numerical data through the use of questionnaires and utilizing the stratified random sampling technique. The sample consisted of 357 Malaysian teachers who are employed by MICSS throughout the whole Malaysian context.

In essence, the survey revealed a significant degree of proficiency in talent management and teacher personal qualities among teachers. In addition, this study also revealed a moderate correlation between talent management and the personal traits of teachers across MICSS teachers in Malaysia.

Limiting the investigation solely to MICSS is a noteworthy limitation. The examination also utilizes AMOS structural equation modeling (SEM) analysis, and it may be considered a restriction of this research that quantitative survey research is employed.

Academic establishments and universities that nurture prospective educators should incorporate talent management strategies and the personal qualities of teachers into the modules of teacher training to ensure that these individuals are not only adequately prepared but also assured of their ability to execute all duties assigned to them in a professional manner.

This research is notably innovative in the context of the Malaysian MICSS, where little evidence exists regarding talent management and teacher personality traits in education. This study, to the best of our knowledge, is the first attempt to investigate the practices and correlation between talent management and teacher personality traits in the entire Malaysian context. The research focuses on the practices of talent management towards MICSS teachers in Malaysia as well as the personal qualities of MICSS teachers.

The purpose of this paper is to propose a new method that allows to compare the magnetic pressures of different pulse width modulation (PWM) strategies in a fast and efficient way.

The voltage harmonics are determined using the double Fourier integral. As for current harmonics and waveforms, a new generic model based on the Park transformation and a dq model of the machine was established taking saturation into consideration. The obtained analytical waveforms are then injected into a finite element software to compute magnetic pressures using nodal forces.

The overall proposed method allows to accelerate the calculations and the comparison of different PWM strategies and operating points as an analytical model is used to generate current waveforms.

While the analytical expressions of voltage harmonics are already provided in the literature for the space vector pulse width modulation, they had to be calculated for the discontinuous pulse width modulation. In this paper, the obtained expressions are provided. For current harmonics, different models based on a linear and a nonlinear model of the machine are presented in the referenced papers; however, these models are not generic and are limited to the second range of harmonics (two times the switching frequency). A new generic model is then established and used in this paper after being validated experimentally. And finally, the direct injection of analytical current waveforms in a finite element software to perform any magnetic computation is very efficient.

Blockchain’s potential is so significant that business activities across all industries can be drastically altered. Furthermore, the characteristics of blockchain appear to be well-suited to accounting requirements. However, accounting professionals’ attitude and intention toward blockchain adoption are not clear, particularly in India. Thus, this study aims to investigate and evaluate accountants’ intention to adopt blockchain technology in accounting activities.

This study examined and assessed accountants’ intention to use blockchain in accounting. To effectively measure usage intention, this study extended the unified theory of acceptance and use of technology (UTAUT) model by including context-specific constructs. To empirically test and validate the proposed model, data were collected from “369” professional accountants in India.

The findings revealed that facilitating conditions, performance expectancy and initial trust had a significant impact on adoption. Furthermore, the regulatory framework materially moderated the association between usage intention and its predictors.

These findings provide new empirical evidence about the impact of different predictors of usage intention by extending the UTAUT model. Relevant stakeholders can refer to this pioneering study to increase the adoption of blockchain as an efficient and trustworthy system among professional accountants, particularly in developing countries such as India.