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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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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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Oct 18, 2024

Flexibility in committee size and the effect on collective performance: The unanimity rule

This paper contributes to the understanding of how flexibility in the number of members in a decision-making committee in a multistage project can enhance the accuracy and efficiency of the decisions taken. While most projects typically employ a fixed number of decision makers, the paper demonstrates the advantages of adjusting the committee size according to the project’s varying complexity at different phases of the project. In particular, we show that allowing for flexibility in the size of a committee increases the likelihood of reaching a correct decision under the unanimity rule. We analyze this issue when the decision maker’s competence is independent of the state of nature and when it is not. The results are compared to those under the simple majority rule.

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Sept 27, 2024

Promotion of sustainable tourism in desert environments: The importance of governance, local actors, and tourism products and services

Desert environments face the challenge of promoting sustainable tourism while balancing economic growth with cultural and environmental preservation. In the context of rapid global tourism expansion, effective destination management becomes crucial for positive economic impact and long-term preservation. This study aims to identify key factors influencing the sustainability of tourism. It explores the interactions between local stakeholders, the supply of tourism products and services, and tourism governance. Utilizing structural equation modeling through the PLS-SEM method, data was collected from 150 stakeholders in desert environments. The findings reveal that the involvement of local tourism stakeholders and the supply of tourism products and services significantly impact sustainable tourism in the desert environment. However, we observe a lack of influence between tourism governance and sustainable desert tourism. The novelty of the study lies in the identification of promotional factors for sustainable desert tourism. The originality of this study lies in its in-depth exploration of the mechanisms for promoting sustainable tourism.

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Dec 27, 2024

Critical thinking and simulation in child welfare: Florida department of children and family’s formative evaluation

An evaluation of the Florida Department of Children and Families (DCF) revealed child welfare professionals required more comprehensive pre-service training. The REAL Academy™ (RA) provided training in critical reasoning, high-fidelity simulation, and administrative tethering. This article is an evaluation of the effectiveness of the redesigned training process. We collected quantitative and qualitative data from five cadres of trainees, including representatives from the DCF, sheriff’s offices, the University of Southern Florida, and community-based care centers. Statistical analyses of quantitative data included correlations, linear regression, and multiple regression, and results indicated the critical thinking training was highly effective, realistic, and relevant, and the simulation exercises helped trainees gauge, manage, and recover from the anxiety and stress inherent in their work. Thematic analyses of qualitative data revealed that trainees placed importance on their roles within the organization, implying the need for a trust-centric configuration, which can be achieved by administrative tethering. Recommendations for future practice include the integration of contemporary teaching methodologies, an emphasis on trauma competency, a focus on improving the workplace culture and environment, the incorporation of virtual reality, the introduction of critical thinking strategies and tools, and the use of high-fidelity simulations.

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Oct 21, 2024

A study intention, implementation and adoption of e-wallet in Indonesia

Using the unified theory of acceptance and use of technology (UTAUT), this study investigated the effect of perceived usefulness, perceived ease of use, social influence, facilitating condition, lifestyle compatibility, and perceived trust on both the intention to use and adoption of an e-wallet among adults. This quantitative study employed a cross-sectional research technique to collect data from 501 respondents via Google Form. The acquired data was assessed using partial least squares structural equation modelling (PLS-SEM). Therefore, perceived usefulness, perceived simplicity of use, social influence, lifestyle compatibility, and perceived trust all had a strong positive impact on both intentions to use and adoption of an e-wallet. This study demonstrated that the intention to use an e-wallet mediated the links between predictors and e-wallet adoption. Respondents’ age and gender moderated the effect of lifestyle compatibility on their intention to use an e-wallet. The study’s findings can assist managers and policymakers establish successful ways that capture customers’ intention to use and experience with employing an e-wallet amid a tumultuous market. Finally, such well-crafted policies may stimulate the digital platform and web-based apps, as well as raise e-wallet acceptance rates in undeveloped countries.

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