Fair East Publishers: E-Journals
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Analysis of the challenges and benefits of the integration of automation in supply chain operations
Get PDFThis research seeks to examine the benefits and challenges associated with automation integration. Three research objectives and hypotheses were proposed to assess automation integration in supply chain operations. By employing a quantitative research approach, the study identified and analysed the strategic benefits derived from automation integration as well as the challenges associated with automation. The data was collected through an online questionnaire from one hundred and two (102) supply chain professionals in various industries using a convenient sampling technique. The collected data was analysed using frequency tables, simple percentages, and descriptive statistics (mean and standard deviation). The Pearson Product Moment Correlation Coefficient and regression analyses were used for hypotheses testing, using Statistical Package for Social Sciences (SPSS) version 29. The study empirically establishes that automation integration has a significant relationship with perceived benefits, perceived challenges, and strategies for maximising the benefits. The results of this study support the three hypotheses tested and recommend that organisations prioritise employee training and education initiatives to equip their workforce with the skills necessary to utilise automated systems. Additionally, organisations should collaborate with technology providers and conduct regular assessments of their automation systems to identify areas for improvement and ensure continuous alignment with objectives.
Keywords: Automation Integration, Implementation Strategies, Supply Chain Operations
Cyber-Physical systems security vulnerabilities in manufacturing supply chain operations
Get PDFThe menace of Cyber-Physical (CP) attacks is becoming a major concern, because of the potential adverse effect posed to organizations' supply chain and production activities. For example, product design, equipment destruction, or in some cases, modifications to the manufacturing process, may go unnoticed when adequate measures to protect or deter this issue are not implemented. This study explored the various security vulnerabilities in Cyber-Physical Systems (CPS) in the supply chain system, focusing on the impact of cyberattacks on the production process and data bridge, leading to financial loss. Desktop analysis was adopted through a literature review of existing studies on CP attacks and supply chain management in the manufacturing industry. The study highlights how the security framework and policies in an organization could help reduce risk, whilst still ensuring operational efficiency is maintained. In addition, it contributes to knowledge by evaluating the challenges of CP security and how more proactive prevention and mitigation strategies can be implemented, as well as policies, to help reduce cyberattacks on the supply chain and production system of an organization.
Keywords: Cyber-Physical Systems, Policy, Cyberattack, Manufacturing, Supply Chain, Framework
African regional integration: An analysis of the possibility of advancing towards a supranational structure. a study using SVAR
Get PDFThe objective of this article is to identify the degree of (a)symmetry of macroeconomic shocks affecting African countries in order to test the possibility of progressing towards a supranational structure. To achieve this goal, we employ a structural VAR process to decompose the macroeconomic shocks and then determine their degree of correlation. The results show that the economies of the continent are marked by relatively high degrees of asymmetry, as the responses to the same type of shock differ. Indeed, 79.02% of the correlations of real supply shocks between African countries are asymmetric, as well as 86.76% of the correlations of demand shocks, and 88.13% of the correlations of monetary shocks. Thus, a deepening of integration towards the harmonization of policies would lead to an increase in real divergence between countries, resulting in a reinforcement of the asymmetry of shocks on the African continent.
Keywords: Macroeconomic Shocks, Supranational Structure, SVAR Model, Degrees of Asymmetry. 
A study on how perceived risks of international students impact their Cryptocurrency investments
Get PDFCryptocurrencies have become one of the most disruptive financial innovations, attracting widespread interest worldwide. Despite their growing popularity, the risks associated with the use of cryptocurrencies remain a significant barrier to their adoption. Therefore, this paper examines the impact of perceived risks on international students’ cryptocurrency investment behavior. Results indicate that financial and regulatory risks are major barriers, while operational risks are less influential. Interestingly, security risks positively influence investment when perceived rewards or risk management capabilities are considered. Risk tolerance and cryptocurrency knowledge are strong positive predictors, highlighting the role of financial education in fostering adoption. The results suggest the implementation of specific policies that address perceived risk factors and improve financial literacy among younger generations of investors to support informed and responsible participation in cryptocurrency markets.
Keywords: Cryptocurrency Investments, Perceived Risks, Investments Behavior
Testing psychological contract breach as a moderator between the HPWS and staff turnover intentions relationship?; Evidence from call centre
No full textHigh-performance work system (HPWS) are a set of HR practices aimed at cultivating high performance among the staff along with other favorable organizational and employee outcomes. In the present study, a particular employee outcome namely turnover intention is investigated with HPWS as an explanatory variable. The study also adds the psychological contract breach as another explanatory variable based on the notion that it is influenced by factors outside HPWS. The study utilized quantitative methodology and used survey as a key method of data collection. The focus of the study was selected call center from Islamabad, Pakistan (n=159). The first part of the results includes confirmatory factor analysis (CFA) which based on Cronbach alpha and Average Variance Extracted shows that our constructs had satisfactory reliability and convergent validity. Furthermore, the discriminant validity is also established using the Fornell & Larcker criteria. The path analysis result shows that HPWS dimensions including recruitment & selection (?=-.0367, P<.05); training & development (?=-.473, P<.05); promotion opportunities (?=-.237, P<.05); and autonomy (?=-.257, P<.05) exerted a negative and significant influence on staff turnover intentions. Furthermore, psychological contract breach exerts a positive and significant effect on staff turnover intention (?=.234, P<.05). The moderation result shows that HPWS dimensions and employee turnover intention are partially moderated by psychological contract breach. These results partially support the idea that psychological contract breach is influenced by factors beyond HPWS.
Keywords: HPWS, Psychological Contract, Breach, Turnover Intentions, Staff, Call Centre
Impact of Technology on Education, Analysis, Implications, and Solutions
No full textTechnology has had a significant impact on education, transforming the way students learn, and teachers teach. With the increasing use of technology in the classroom, it has become essential to analyze its impact, implications, and potential solutions. While technology has brought about many benefits, such as improved access to education, enhanced learning experiences, and collaborative learning, it has also presented some challenges, such as the digital divide, student distraction, and privacy concerns. This essay provides a comprehensive analysis of the impact of technology on education, explores its implications, and proposes potential solutions to address the challenges it presents. By examining the various aspects of technology's impact on education, it is possible to gain a better understanding of its potential to improve the quality of education while addressing the challenges that come with its use
Keywords: Education, Technology, Implications and Impact.
 
Advanced underwater image restoration: A comparative study of white balance, dehazing, and contrast enhancement techniques
No full textUnderwater imaging plays a vital role in marine research, environmental monitoring, and underwater robotics. Scattering light effects underwater image quality negatively by creating colorful distortions that also minimize image contrast. All steps of the integrated framework require complete evaluation among white balance correction and dehazing filtering and testing for both contrast adjustment and sharpening methods. The enhancement techniques received evaluations through PSNR and SSIM tests on standard underwater images to determine their achievement results. White balance adjustment delivers the best color accuracy which produces 54.87 dB PSNR and 0.9991 SSIM ratings. These enhancement methods delivered minimal outcome based on their PSNR values which maintained at 6.5 dB. The enhanced contrast visualization from the modification failed to match the quality delivered by the white balance correction. This research develops innovative findings through the combination of different underwater image enhancement techniques which results in an integrated system that enables color correction functions alongside dehazing sharpening and contrast enhancement. The exact measurement of these approaches depends on the evaluation performed through PSNR and SSIM metrological systems. The presented research successfully demonstrated conventional methods for underwater image enhancement while establishing new possibilities for studies about real-time adaptive methods which enhance robotic underwater exploration.
Keywords: Underwater image enhancement, white balance, dehazing, PSNR, SSIM
Innovations in real-time infectious disease surveillance using AI and mobile data
No full textThe integration of artificial intelligence (AI) and mobile health data has ushered in a new era of real-time infectious disease surveillance, offering unprecedented insights into disease dynamics and enabling proactive public health interventions. This paper explores the innovative applications of AI and mobile data in transforming traditional surveillance systems for infectious diseases. By harnessing the power of AI algorithms, coupled with the vast amount of data generated from mobile devices, researchers and public health authorities can now monitor disease outbreaks in real-time with greater accuracy and efficiency. AI-driven predictive models analyze diverse datasets, including demographic information, travel patterns, and social media activity, to detect early signs of disease emergence and predict potential outbreaks. The use of mobile health data provides a wealth of information that was previously inaccessible to traditional surveillance methods. Mobile apps, wearables, and other connected devices enable continuous monitoring of individuals' health indicators, allowing for early detection of symptoms and rapid response to potential threats. Furthermore, geolocation data from mobile devices facilitates the tracking of population movements and the identification of high-risk areas for disease transmission. However, this innovative approach to infectious disease surveillance also presents challenges and ethical considerations. Privacy concerns regarding the collection and use of mobile health data must be carefully addressed to ensure individuals' rights are protected. Additionally, issues related to data quality, interoperability, and algorithm bias need to be mitigated to ensure the reliability and effectiveness of AI-driven surveillance systems. In conclusion, the integration of AI and mobile health data holds immense promise for revolutionizing real-time infectious disease surveillance. By leveraging these technologies, public health authorities can gain valuable insights into disease dynamics, enhance early detection capabilities, and implement targeted interventions to prevent the spread of infectious diseases. However, it is essential to address the challenges and ethical considerations associated with this approach to ensure its responsible and effective implementation.
Keywords: Innovations, Real-Time Infectious Disease, Surveillance, AI, Mobile Data
Identifying Criteria and a Multi-Criteria Decision-Making Model for Assessing Students’ Digital Competence
Get PDFIn the context of rapid digital transformation in higher education, digital competence has emerged as a vital skill for students to succeed in academic and professional environments. This paper aims to identify core criteria and propose a multi-criteria decision-making (MCDM) model for assessing university students' digital competence. Drawing upon international frameworks such as DigComp 2.1, UNESCO’s DLGF, and the newly introduced DCFL, the study synthesizes seven pillars of digital competence, comprising 29 sub-criteria. To enhance evaluation objectivity and accuracy, the paper integrates the MCDM approach, particularly fuzzy logic and AHP methods, to assign weights and assess both qualitative and quantitative indicators. The proposed model allows institutions to measure students’ digital capabilities comprehensively, classify learners into different competency levels, and provide tailored educational support. The findings contribute to the development of evidence-based digital skill assessment tools and serve as a strategic foundation for universities to design targeted digital training programs. This model is particularly relevant for Vietnam’s higher education system as it strives to align with global digital transformation trends.
Keywords: Digital Competence, MCDM, Assessment Framework, Higher Education
The future of learning is personalized: Why investors cannot afford to ignore AI in education
Get PDFInvestments in comprehensive educational resources are vital as their societal value continues to grow. Artificial Intelligence applications in education (EdTech) are increasingly capable of tailoring education to the unique nuances of each learner’s behavior. Investment in EdTech is driven by the expansion of individualized learning approaches that revolve around the prediction and prescription paradigm of learner behavior. To illustrate the timing of this paradigm shift, this paper addresses the extent to which AI prediction and prescription learning approaches are tailored to educational needs. The core argument revolves around the centrality of adaptive learning systems, automated content delivery, predictive analytics, and intelligent tutoring systems. To reflect the value of investment, each stakeholder is given a unique value proposition to consider. In this, improved educational institutional outcomes and student engagement are secondary to the low cost and ease of intervention, predicated on the assumption that education is provided to learners in the country of origin and abroad. Ethical issues of the evolution such as data breaches, algorithmic bias, and even the replacement of teachers in the 4th industrial revolution are some of the issues this paper sheds light upon. Investors who focus on the realization of sustainable and scalable ventures are hardly able to ignore these issues. The paper corroborates the mainstream opinion which states that the growing technological infrastructure, market demand, and real-world validation have made AI in education an asset of unparalleled significance.
Keywords: Artificial Intelligence, Personalized Learning, EdTech, Investment, Adaptive Learning, Learning Analytics, Ethics in AI, Educational Technology