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Aug 12, 2024

Do CBDCs promote financial inclusion and strengthen the monetary regulations?

Digital currencies are impacting the financial lives of people and countries around the world; particularly developing countries see the retail Central Bank Digital Currencies (CBDCs) as an opportunity to increase financial inclusion and introduce new monetary policy implementation mechanisms. The decision to launch a digital currency mainly depends upon the goals and objectives being set by the Central Bank of any respective country. Digital currencies help to implement monetary policy more effectively to achieve the financial system stability. Kazakhstan is the leading economy in the Commonwealth of Independent States region; the digital payments market is changing rapidly in Kazakhstan, being driven by fintech innovations and public investments in payment technologies. In this article, we thoroughly discussed how launching of “Digital Tenge” is promoting financial inclusion and strengthening the monetary regulations across Kazakhstan. We took the case of Kazakhstan because it’s the first country from Central Asia which took the initiative of launching digital currency, and the National Bank of Kazakhstan has already announced that implementation of “Digital Tenge” would be completed in Kazakhstan by the end of 2025. The implementation of a “Digital Tenge” as a CBDC in Kazakhstan would expand the range of financial services being available to the nation. Having direct authority over the digital currency will empower the National Bank of Kazakhstan to adopt more efficient monetary policy, exerting influence over interest rates, money supply, and general economic stability. Furthermore, by providing digital financial services to marginalized communities, the digital Tenge would also help to solve the difficulties of financial inclusion in Kazakhstan. The article provides the possible policy routes for the governments of developing countries and the financial regulators about adopting CBDCs for promoting financial inclusion and to strengthen the monetary regulations.

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Oct 18, 2024

Mobile apps for health surveillance: Balancing public health needs with the privacy of personal data

The privacy of personal information is aimed at protecting human rights both under the international human rights regime and the Saudi Arabian constitution and other statutes and regulations, subject only to some exceptions that include the protection of public health. The coronavirus disease 2019 (COVID-19) pandemic has brought about certain challenges that necessitate strategies to augment the conventional surveillance of infectious diseases, contact tracing, isolation, reporting and vaccination. Several governments institutions, and agencies presently adopt mobile applications for collecting, analyzing, managing, and sharing critical personal data of individuals infected with or exposed to COVID-19. While the benefits of sharing private information for achieving public health needs may not be disputed, the risk of breach of personal privacy is enormous. This had forced the national governments into a dilemma of either succumbing to public health needs, strictly respecting and protecting the privacy of individuals, or alternatively, balancing the two conflicting demands. There is a massive body of literature on the security and privacy of such mobile applications, but none has adequately explored and discussed public interest justifications under Saudi Arabian laws for alleged privacy breaches. We examined the health surveillance mobile app technologies currently in use in Saudi Arabia with the aim of determining the potential risks of data breaches under extant data protection laws. The paper recommends, among others, that any potential risk of breach to right to privacy of personal information under the law must be (justified by) the public health needs to protect society during the COVID-19 pandemic.

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Jan 14, 2025

An insight from machine learning perspective for COVID-19 survival prediction in Malaysia based on demographic factor

Malaysia reported its first imported COVID-19 case on 23 January 2020, which marked the country's first confirmed positive case. The first case in Malaysia was from eight close contacts in Johor. The global health landscape has been significantly impacted by the COVID-19 pandemic, with mortality or survival being critical outcomes of interest. This study aims to predict COVID-19 survival occurrences in Malaysia by utilizing machine learning approaches based on demographic factors. The dataset used in this study comprises demographic information of 2,151,315 COVID-19 patients, including nationality, regions, age groups, gender, medical history, vaccine brands, and the number of vaccine doses received between 2020 and 2022. Four machine learning algorithms, namely Logistic Regression, Naïve Bayes, Support Vector Machine, and Artificial Neural Network were employed to assess the relationship between demographic factors and COVID-19 survival. To evaluate the model performance, the datasets are categorized into imbalanced and balanced (down-sampling). The results indicate that the balanced dataset (down-sampling) outperforms the imbalanced dataset in terms of overall accuracy, sensitivity, specificity, precision, and Area Under the Curve (AUC). Based on the analysis, the Artificial Neural Network (ANN) classifier exhibited the highest performance with a specificity 95.2% on a balanced dataset. The model excels in accurately identifying survivors, thereby minimizing false mortality predictions and is selected as the best model for predicting COVID-19 survival. Its capacity to process larger sample sizes, combined with numerous interconnected nodes, enables it to identify complex patterns and extract meaningful insights from diverse datasets, such as demographic factors. Additionally, the optimization of parameters, including the number of layers, learning rate, and activation functions, significantly contributed to its superior accuracy. The study identifies that those of chronic diseases, male, and aged 45 and above as the notable factors associated with lower survival rates among COVID-19 patients. The findings underscore the importance of completing the vaccination series by obtaining at least the second dose, as the first dose alone may not offer sufficient protection. In conclusion, this study successfully achieves its objectives by identifying the optimal dataset configuration and predictive model for forecasting COVID-19 survival based on demographic factors. This network could serve as a benchmark model classifier, offering a valuable tool to predict and promote vaccinations, as well as optimize the general healthcare system during the pandemic outbreak. The study not only contributes to the theoretical understanding of effective COVID-19 prediction but also emphasizes the practical implications of integrating advanced machine learning techniques into pandemic management strategies. Future research can build upon these findings by exploring additional machine learning techniques and considering geographical and environmental factors to further enhance the accuracy of long-term predictions.

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Nov 12, 2024

Transformation processes of professional identity against the background of media convergence

The purpose of the work is to study the transformation processes of constructing professional identity under the influence of new information technologies and to consider the evolution of views on the processes of scientific and practical understanding of new media resources in the context of the development of convergent journalism as a phenomenon of the modern information society. It was established based on the conducted research that the values and beliefs of journalists, reflecting the process of professional self-identification, are forming in the process of choosing certain options among a variety of alternatives and transforming further under the current conditions of the information and communication environment. In the process of the study, the article identifies the features, content, and main trends in the transformational processes of professional identity and professional culture of journalists in the context of technological changes in the media industry. The dynamics of the development of media convergence are shown from the point of view of the mutual influence of traditional and new media and the tendency of improving their technological and dialogue features and capabilities in content creation and broadcasting. An assessment is made of the degree of adaptation of regional media to modern conditions of the information and communication environment in the context of organizational, professional, and communicative convergence.

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Sept 26, 2024

Application and prospect analysis of blockchain technology in intellectual property protection of e-commerce

This article delves into the application of blockchain technology in enhancing intellectual property (IP) protection within the e-commerce sector, providing a comprehensive analysis of its future prospects. By examining the core characteristics and working principles of blockchain, the paper reveals the unique advantages it offers in strengthening IP protection for e-commerce. The article elaborates on how blockchain’s features of decentralization, data immutability, and timestamping contribute to a secure, transparent, and efficient IP protection mechanism in the e-commerce field. Furthermore, the paper discusses the practical application of blockchain technology in IP registration, management, transaction, and rights protection, highlighting its significant impact on security traceability, transaction cost reduction, and efficiency improvement. Lastly, the article anticipates the future role of blockchain technology in IP protection in e-commerce and believes that with continued technological advancements and enhanced policy support, blockchain will play an increasingly pivotal role in this domain. The paper also proposes potential challenges and solutions that require attention, aiming to foster the healthy and sustainable development of blockchain technology.

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Jul 2, 2024

Determinants of the inheritance behaviors among FELDA communities in Malaysia: A study using the PLS-SEM approach

This study aims to identify the impact of inheritance literacy, inheritance socialization, inheritance stress, and peer influence on the inheritance behaviors among FELDA communities in Malaysia. Inheritance literacy pertains to individuals’ comprehension of wealth transfer and estate planning, while peer influencer evaluates friends’ impact on inheritance attitudes; inheritance socialization explores family interactions’ role in shaping inheritance attitudes, and inheritance stress measures emotional strain in inheritance matters, with inheritance behaviors encompassing asset management and wealth transfer decisions for future generations by individuals and families. Understanding inheritance behaviors is crucial, as it helps individuals depict their inheritance knowledge and attitudes toward FELDA inheritance better, fostering a more favorable inheritance attitude. Through self-administered survey questionnaires, data related to FELDA communities are obtained using convenience sampling from 413 respondents. This study applies Partial Least Squares Structural Equation Modeling (PLS-SEM) technique to test the research hypotheses. The present study’s outcome confirms that two determinants, which are inheritance literacy and inheritance socialization significantly influence the inheritance behavior of FELDA communities. However, inheritance stress and peer influence determinants have statistically insignificant influence inheritance behavior. This study’s theoretical framework enriches the discussions on wealth management and financial behavior by refining and expanding upon existing financial behavior theories to incorporate inheritance-specific behaviors. The present study is exclusive in its effort to ascertain the relative importance of both inheritance behavior and the FELDA communities. This paper will assist the government, inheritance service providers, and policymakers in offering innovative economic schemes and designing policies that may enhance the inheritance behavior wellbeing of FELDA communities. This article also provides a roadmap to guide future research in this area.

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