Fair East Publishers: E-Journals
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Current State of Training and Retraining for Workers Affected by Technological Innovation in Vietnam’s Textile and Garment Industry
No full textAs the Fourth Industrial Revolution rapidly transforms Vietnam’s textile and garment industry, advanced technologies such as automation, artificial intelligence, and smart manufacturing systems are increasingly replacing manual labor, putting many workers at risk of unemployment. In this context, training and retraining have become essential to maintaining workforce competitiveness and ensuring social security. This study examines the current state of training practices within textile and garment enterprises in Vietnam. It highlights certain strengths - particularly the proactive efforts of larger firms - while also identifying common shortcomings such as the absence of long-term human resource strategies, outdated training approaches, limited collaboration with vocational institutions, and financial constraints. Most workers express a desire to improve skills related to their existing jobs, reflecting a preference for job stability over occupational change. Based on these insights, the paper proposes several solutions to enhance the effectiveness of training programs and promote lifelong learning among the workforce.
Keywords: Fourth Industrial Revolution, Textile and Garment Industry, Workforce Development
Power Dynamics in Classroom Communication: A Case Study of Primary School Teachers in Ho Chi Minh City, Vietnam
No full textThe article analyzes the manifestations of power in language communication of primary school teachers through a survey of actual speech at the Practical Primary School - Saigon University, combined with a questionnaire survey of 29 teachers. The study applies the discourse theory framework of Fairclough (2001), Foucault (1980) and the power classification system of French & Raven (1959) to identify three main types of power: legitimate, rewarding, and coercive. In addition to verbal factors, non-verbal factors such as tone, eye contact, and spatial distance also contribute to consolidating power in the classroom. The results show that power in teacher communication is a soft, flexible and constructive structure, directly affecting students' learning motivation, behavior, and classroom spirit.
Keywords: Linguistic Power, Primary School Teachers, Pedagogical Communication, Classroom Discourse, Soft Power
Comprehensive training programs for U.S. educational leaders: Theoretical strategies for enhancing school performance
No full textThis review paper examines comprehensive training programs for U.S. educational leaders, focusing on theoretical strategies to enhance school performance. It explores vital leadership, pedagogical, and organizational change theories, emphasizing their application in training programs. Critical components such as curriculum design, skill development, and mentorship are discussed, highlighting their importance in preparing influential leaders. Strategies for enhancing school performance, including data-driven decision-making, instructional leadership, and community engagement, are analyzed. The paper also addresses common challenges in implementing training programs and explores emerging innovations and technologies that can enhance training effectiveness. The conclusion underscores the vital role of comprehensive training programs in improving educational leadership and calls for continued research and policy support to sustain these efforts.
Keywords: Educational Leadership, Training Programs, School Performance, Data-Driven Decision Making, Instructional Leadership
Influence of Early Life Experiences, and Religious Beliefs on Positive Mental Health among Undergraduates
No full textMental health among undergraduate students has become a global concern, with traditional research focusing primarily on psychopathological symptoms rather than positive mental health indicators. This study examined the relationship between early life experiences, religious beliefs, and positive mental health among Nigerian undergraduates, addressing a gap in non-Western mental health research. A descriptive cross-sectional study was conducted with 200 undergraduate students selected through convenience sampling. Data were collected using three validated instruments: the Early Life Experiences Scale (ELES), the Centrality of Religiosity Scale (CRS-5), and the Positive Mental Health Scale (PMH). Simple linear regression analyses were performed to test the study hypotheses. The sample comprised 66% females and 34% males, with 99% identifying as Christian. Early life experiences significantly predicted positive mental health, explaining 2.3% of the variance, with negative early experiences associated with poorer mental health outcomes. Religious beliefs also significantly predicted positive mental health, accounting for 7.3% of the variance, with stronger religious beliefs associated with better mental health. The findings demonstrate that adverse early life experiences negatively impact positive mental health, while religious beliefs serve as a protective factor, enhancing mental well-being among Nigerian undergraduates. These results support the integration of early life history and religious considerations in mental health interventions for university students in collectivistic, religious contexts.
Keywords: Positive Mental Health, Early Life Experiences, Religious Beliefs, Undergraduate Students, Nigeria
The effect of organizational communication satisfaction on job satisfaction: A study of SMEs in Ho Chi Minh City, Viet Nam
No full textCommunication plays pivotal role in all functions of organizations. There were many researches explored the relationship between communication and job satisfaction in different areas, as communication activities affect significantly to whole organization performance. In return, the job satisfaction makes up an increase productivity, which contributes the success of organization accordingly. This result was conducted based on data were gathered from 200 employees of SMEs companies in Ho Chi Minh city, Viet Nam, to analyze the effect of organizational communication on job satisfaction, through questionnaire using version of Communication Satisfaction Questionnaire (CSQ), which is developed by Downs and Hazen (1977), which has explored the correlation between communication and job satisfaction previously. This questionnaire was used with 7 dimensions match up with thirty-five statements through 5 level satisfaction of Linkert Scale from 1 to 5 range dissatisfied to very satisfied. Factor analysis, Pearson correlation and regression analysis were used to analyze the final data. The findings revealed strong correlation between communication and job satisfaction. The study highlights the importance of effective communication which helps in boosting employee job satisfaction besides improving performance. The study also highlighted the need for SMEs managers and/or organizers to include all SMEs employees in communication strategies aim to improve communication.
Keywords:Organizational Communication, Communication satisfaction, Job satisfaction, Communication Satisfaction Questionnaire, SMEs
Modeling the impact of IFRS on SMEs in emerging markets
No full textThe adoption of International Financial Reporting Standards (IFRS) has become a significant trend globally, especially for Small and Medium Enterprises (SMEs) in emerging markets. This review aims to model the impact of IFRS adoption on SMEs in emerging economies, focusing on financial performance, access to capital, and business growth. SMEs play a vital role in the economic development of these markets, yet they face unique challenges in adopting IFRS due to resource constraints, regulatory complexities, and the costs associated with implementation. While the benefits of IFRS, such as enhanced financial transparency, improved comparability, and greater access to international markets, are well-documented, the challenges remain largely underexplored, particularly in the context of emerging markets. Using a mixed-method approach, this research combines econometric modeling with qualitative analysis to assess the effects of IFRS adoption on the financial outcomes of SMEs. The review evaluates key financial indicators, such as profitability, liquidity, and access to capital, before and after IFRS implementation. Additionally, interviews with SME owners and financial managers provide insights into the operational challenges encountered during the transition process. The review also investigates the role of regulatory frameworks and the local economic environment in facilitating or hindering IFRS adoption. Findings suggest that while SMEs experience initial challenges in adapting to IFRS, the long-term benefits include improved investor confidence, easier access to capital, and enhanced financial transparency. This also highlights the importance of tailored support from policymakers, including financial incentives, training programs, and regulatory guidance, to aid SMEs in overcoming adoption barriers. This research contributes to the broader understanding of IFRS’s impact on SMEs in emerging markets and offers strategic recommendations for both businesses and policymakers.
Keywords: Modeling, Impact, IFRS, SMEs, Emerging Markets
Generative AI: A new frontier for agric extension service in Africa - revolutionizing farmer information access
No full textExtension services in agriculture are essential in the dissemination of critical information and sustainable agricultural techniques to farmers in Africa. Nevertheless, such services tend to be limited by their reach, language constraints, and lack of context-specific information. With the potential to generate new and context-specific content, Generative Artificial Intelligence (AI) offers a revolutionary means to overcome these constraints and improve agricultural knowledge transfer. This paper investigates the future of Generative AI, with components including Natural Language Processing (NLP), content generation (text, picture, audio, video), context-specific information delivery to individuals, and AI-driven chatbots in reshaping African agricultural extension. We survey applications of AI worldwide in agriculture with examples of success stories along with drawing inferences applicable to Africa. We examine the possible applications of Generative AI in the development of localized recommendations, generating study materials in local regions in local languages, virtual extension agents, and peer-to-peer learning. We also critically analyze the challenges and constraints in the use of AI in African agriculture in terms of infrastructural constraints, digital illiteracy, data availability and affordability of technology. Taking into consideration applicable theories like Technology Acceptance Model (TAM), Diffusion of Innovations Theory, and Social Cognitive Theory, we evaluate factors that affect the adoption and effects of using Generative AI in the agricultural sector. Lastly, we address issues related to ethics and the public and put forth future conduct of studies. We conclude that while there is significant potential in the use of Generative AI, its success depends on due consideration of Africa's particular agricultural context.
Keywords: Generative AI, Artificial Intelligence, Agricultural Extension, Africa, Information Dissemination, Sustainable Agriculture, Digital Agriculture, Knowledge Transfer
Explainable Artificial Intelligence (Al) through human-AI collaborative frameworks: Quantifying trust and interpretability in high-stakes decisions
No full textExplainable Artificial Intelligence (XAI) through human-AI collaborative frameworks is essential for building trust and interpretability in high-stakes decision-making processes. As AI systems are increasingly deployed in critical areas such as healthcare, finance, and criminal justice, the need for transparency and accountability in AI-driven decisions becomes paramount. High-stakes decisions often involve complex, high-consequence outcomes, where understanding and trusting AI predictions are vital. XAI aims to address these concerns by providing understandable, transparent explanations for AI decisions, making it possible for human experts to comprehend and, when necessary, override or adjust AI outputs. Human-AI collaboration focuses on enhancing the decision-making capabilities of both humans and machines by combining the strengths of AI’s computational power with human intuition and experience. By ensuring that AI systems are explainable, this collaboration fosters trust between humans and AI, essential for smooth integration in sensitive fields. Trust is crucial in high-stakes contexts, as users need to rely on AI outputs and integrate them into their decision-making processes. To quantify this trust, various metrics and frameworks have been developed, measuring aspects such as reliability, fairness, and the transparency of AI models. Interpretability is equally vital, as it allows users to trace and understand the rationale behind AI predictions. In high-stakes domains, transparent AI models support legal, ethical, and social accountability, ensuring that decisions are made with a clear understanding of how and why the AI reached a particular conclusion. However, achieving a balance between complex, high-performing AI models and the need for interpretability presents significant challenges. This explores how human-AI collaborative frameworks can address these challenges, enhancing the effectiveness, fairness, and trustworthiness of AI systems in high-stakes decision-making environments.
Keywords: Explainable Artificial Intelligence, Human-Al, Frameworks Trust and Interpretability, High-Stakes Decisions
Social media security: the impact of AI-generated Whatsapp scams on the security and privacy of Whatsapp community groups
Full text linkThe advancement of artificial intelligence (AI) has revolutionised many sectors, including cybersecurity. However, it has enabled cybercriminals to create more sophisticated and convincing scams. This study investigates the impact of AI-generated scams on social media, especially WhatsApp community groups. Although extensive research exists on traditional phishing and social engineering attacks, the implications of AI-generated scams on messaging platforms such as WhatsApp still need to be explored. This study will fill this gap by examining how AI-generated scams impact user security and privacy in WhatsApp Community chat groups. The research employs a mixed-methods approach, combining quantitative analysis of scam incident reports with qualitative surveys of affected users. Data was collected from academic databases, WhatsApp user forums, and direct surveys to analyse the patterns and identify common characteristics of AI-generated scams. The findings revealed that AI-generated scams on WhatsApp are highly personalised and convincing, leveraging advanced AI techniques such as natural language processing and voice cloning. These scams significantly compromise user privacy and security, leading to substantial financial loss and emotional distress. This research contributes significantly to social media security by analysing AI-generated scams on WhatsApp. It underscores the urgent need for enhanced security measures and user education to mitigate such threats. This study also recommends some techniques and strategies to reduce threats to the security and privacy of WhatsApp community groups
Keywords: Artificial Intelligence, Scams, WhatsApp Community Groups, Phishing, Deepfake, Cybersecurity, Voice Cloning
Solid waste management strategies, categorization, and challenges in Ghana's Savannah Region: Systematic review
Full text linkSolid waste management (SWM) in Ghana's Savannah Region faces significant challenges, including weak governance, socio-cultural practices, financial constraints, inadequate infrastructure, and limited community participation. These issues result in ineffective waste collection, open dumping, and burning, leading to environmental pollution and public health risks. Governance challenges stem from weak enforcement of sanitation policies, insufficient funding, and poor stakeholder coordination. Decentralization efforts are hampered by resource constraints, leaving rural communities underserved. Socio-cultural factors, such as traditional practices and low awareness of environmental risks, perpetuate unsustainable behaviors, requiring targeted education and community engagement to promote change. Financial limitations hinder investment in waste management infrastructure like engineered landfills and recycling facilities, while cost-recovery mechanisms and public-private partnerships face operational difficulties. Infrastructure deficits, including inadequate waste collection systems and reliance on open dumpsites, exacerbate environmental risks. The lack of community participation further undermines SWM efforts, as awareness campaigns and mechanisms for involvement remain underdeveloped. Addressing these challenges requires a multi-faceted approach, including strengthening governance frameworks, increasing investment in infrastructure, raising public awareness, and fostering community participation. Supporting informal recycling efforts and tailoring interventions to the region’s socio-economic and cultural context are critical for achieving sustainable SWM in the Savannah Region.
Keywords: Solid Waste Management Ghana, Waste Categorization, and Challenges in Waste Management Savannah Region