Al-Kindi Center for Research and Development (KCRD) (E-Journals)
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Unraveling the Retirement Spending Habits in Siquijor, Philippines: Promoting Support Policies for Retirees
No full textRetirement planning remains a significant challenge, with financial literacy gaps influencing retirees\u27 economic security. This study examines the financial resource allocation of retirees in Siquijor, Philippines, shedding light on key spending patterns. Essential living expenses, such as utilities (3.94) and groceries (3.80), take priority, while housing costs remain relatively low (3.02), reflecting the prevalence of extended family living arrangements. Healthcare expenditures are primarily allocated to prescription medications (3.60), while spending on preventive care (3.36) remains limited due to financial constraints. Transportation costs are minimal, as retirees increasingly rely on public transit. Discretionary spending is constrained, with hobbies (2.62) ranking slightly higher than travel (2.60). Charitable giving (2.54) is primarily directed toward local community support rather than institutional donations. Financial assistance to family members (3.46) remains common, reinforcing cultural expectations of intergenerational support. However, retirees allocate limited funds to emergency savings (3.25) and insurance premiums (2.70), increasing their financial vulnerability.These findings highlight retirees\u27 financial pressures, emphasizing the need for targeted policy interventions. Initiatives such as financial literacy programs, healthcare subsidies, senior-friendly transportation options, and enhanced social support systems could improve retirees\u27 financial stability and overall well-being. Furthermore, promoting access to affordable housing, emergency savings mechanisms, and sustainable retirement planning strategies will be crucial in addressing financial insecurity among retirees. This study underscores the importance of a multi-faceted approach in crafting policies that cater to the financial realities of retirees, ensuring a more secure and dignified post-employment life
Organizational Values as Indicators of Organizational Commitment in selected BPO Companies in Metro Manila
No full textThe purpose of the study is to analyze the connection between organizational values and organizational commitment in the Philippine Business Process Outsourcing (BPO) setting. Organizational values were represented by the McDonald and Gandz taxonomy of values while organizational commitment was conceptualized in three forms: affective, normative and continuance commitment. The study was done through employees from selected BPO companies in Metro Manila. The results of the correlation analysis revealed that all the values sets are positively correlated with the three components of commitment, with human relations and open system values having the highest correlations. Meanwhile, regression analysis was also conducted, and the results found that human relations values significantly predicted affective commitment while open system values significantly predicted both affective and continuance commitment. The study recommends that companies should actively promote human relations values or open system values in their workplaces because these values can influence the organizational commitment of employees
Towards Equitable Coverage: Harnessing Machine Learning to Identify and Mitigate Insurance Gaps in the U.S. Healthcare System
No full textDespite advancements in healthcare access, significant disparities persist in health insurance coverage among vulnerable populations in the United States. These gaps disproportionately affect racial and ethnic minorities, low-income groups, and rural communities, leading to poor health outcomes and increased financial strain (U.S. Department of Health and Human Services, 2022). This research explores how machine learning (ML) can be leveraged to identify, predict, and address these coverage gaps using large-scale datasets such as electronic health records (EHRs), insurance enrollment data, and demographic information. By applying predictive analytics, the study aims to uncover patterns of underinsurance and non-enrollment, enabling proactive outreach and policy interventions (Rajkomar, Dean, & Kohane, 2018). The research evaluates current ML models for their accuracy, ethical implications, and effectiveness in informing targeted outreach strategies. Furthermore, it discusses how health policymakers and insurance providers can use these insights to implement data-driven solutions that promote equitable access to care. This study contributes to the ongoing dialogue on health equity, technology integration, and value-based insurance design in public health policy (Obermeyer, Powers, Vogeli, & Mullainathan, 2019)
MAX Effect and Investor Sentiment: Evidence from the Swedish Stock Market
No full textMotivated by existing literature on the impact of maximum daily returns (MAX) on subsequent stock returns and its connection to market sentiment, we investigate the potential effect of MAX on stock performance in Sweden and its relationship with market sentiment. Portfolio-level analyses provide evidence that MAX negatively affects the returns of stocks listed in Sweden, while firm-level cross-sectional regressions indicate that MAX has little to no effect on individual stock returns. Furthermore, the results indicate that the magnitude of the MAX effect is more pronounced when sentiment in the Swedish stock market was low in the previous month. The findings also suggest that high-MAX stocks are likely to retain their high MAX in future months. Finally, all findings remain robust across variations in portfolio sorting methodologies and alternative definitions of MAX
The Impact of Corruption on Bank Credit Risk in selected Sub-Saharan Africa
No full textCorruption is one of societies\u27 core ailments, impacting banks\u27 performance. Corruption may impact lending practices and borrowers’ willingness to repay loans, impacting banks\u27 credit risks. We examine the impact of corruption on banks\u27 credit risks in Sub-Saharan Africa. We use panel data from 10 sub-Saharan African countries from 2012 to 2023. We apply panel data analysis to examine the impact of a battery of control variables on banks\u27 credit risks. Our analysis confirms that control of corruption significantly reduces banks\u27 credit risks. Our results have implications for policymakers who aim to reduce banking risks
Analysis of the Implementation of Regional Regulation No. 14 of 2020 on the Management of Tourist Areas in Improving the Community Economy Based on Local Wisdom: Study at Way Panas Beach, Kalianda District, South Lampung Regency
No full textThe application of Regional Regulation Number 14 of 2020 about the Levy for Recreation and Sports Places in South Lampung Regency is examined in this study, with a focus on the Way Panas Beach tourism area. Based on local knowledge, this study attempts to assess how well area rules enhance the local economy. A qualitative approach is the research methodology employed, and data is gathered through documentation, interviews, and observation. Even though there are issues with infrastructure, community awareness, and oversight, the research findings indicate that the adoption of this rule has improved regional income and community welfare. In order to maximize the administration of tourism destinations based on local knowledge, this study suggests closer cooperation between local governments, communities, and the commercial sector
Blogging about Sustainable Development in the EFL College Classroom
No full textSustainable Development Goals (SDG) are not integrated in any EFL courses that students take at the College of Language Sciences. Therefore, this study proposes a model for integrating topics related to SDGs using a class blog. Each week, a specific and tangible topic related to an SDG from a local or global perspective (no poverty, zero hunger, good health and well-being, quality education, gender equality, clean water and sanitation, affordable and clean energy, decent work and economic growth, industry, innovation, and infrastructure, reduced inequality, sustainable cities and communities, responsible consumption and production, climate action, life below water, life on land, peace, justice, and strong institutions) is posted by the instructor. Blogging about SDG topics goes through three stages: a pre-task, task and post-task phase. The students may search for videos, photos or articles related to the assigned SDG and write a blog post that describes the photo, summarizes the video or article content. Participation goals that require the students to suggest solutions to a problem are integrated. The students write their reactions to the goal, post comments, and feedback on their classmates’ blog posts. They work on their blog posts individually, in pairs, and in small group; synchronously or asynchronously; on a smart phone, tablet, iPad or laptop. In the blogging activity, the instructor serves as a facilitator while the students are blogging. The study gives recommendations for integrating SDG in EFL writing, speaking and reading courses
Enhancing Smart Farming Management in the Bali Cattle Breeding Center, Sobangan, Bali, Indonesia, through “SIDEWI” Electronic Data Information System
No full textThe Sobangan Cattle Breeding Center is currently relying on a manual recording system administered by the office to document cattle data. Due to the substantial number of cattle, such a manual method proves inefficient. The solution lies in SIDEWI, a comprehensive digital recording system for the data. Therefore, this research assessed the breeding center productivity by integrating a digital recording system with maintenance management, addressing the inefficiencies inherent in manual recording. The integration of data through SIDEWI aimed to enhance the accuracy and efficiency of measuring productivity while supporting improvements in maintenance management. The investigation, conducted at Sobangan Cattle Breeding Center in Sobangan Village, Mengwi Sub-district, Badung Regency, spanned from April to November 2023. The program included basic analysis, system development, training, and mentoring. SIDEWI.id, being a digital system, contained features for efficiently managing and recording growth, reproduction, ownership, and health data. The research had the potential to generate more precise and high-quality data, contributing to increased productivity in the cattle farming industry. Through the system, staff could easily access and evaluate the condition of each cattle, facilitating the integration of smart farming management, enhancing productivity, and, becoming a center of excellence for Bali cattle
Massive Open Online Courses (MOOCs): Challenges and Recommendations of School Administrators in Selected Schools in the Philippines
No full textThere are numerous challenges to implementing MOOCs from a school administrator\u27s perspective, such as insufficient technological support, lack of faculty training, and institutional support. This prevents MOOCs from being incorporated into higher education structures because accessibility, instructional quality, and alignment with students\u27 diverse learning needs are all impediments. The challenges were identified to improve the utilization of MOOCs at selected HEIs in the Philippines. The study used mixed-method research to collect data on 65 school administrators\u27 difficulties implementing MOOCs from HEIs in Central Visayas, Philippines. In this case study, to collect the recommendations that could improve the MOOC implementation, these administrators used a three-part researcher-made questionnaire and a validated interview guide. The collected data were further analyzed using frequency, mean, standard deviations, Chi-square test of independence, ANOVA, and thematic analysis. The investigation found that the types of HEIs and the years of working as MOOC administrators significantly correlate with the difficulties they face while applying to MOOCs. MOOCs have been a game changer for learning, making content and experiences more accessible and flexible in new ways. Yet, launching MOOCs exceptionally well in any school requires some legwork. Results show that Central Visayas school administrators face obstacles in fully implementing MOOCs. The challenges range from inadequate technology infrastructure to inadequate faculty training and a general reluctance to adopt new pedagogical practices. To enhance the utilization of MOOCs, the researchers recommend that their action plan be implemented
Artificial Intelligence-Driven Customer Lifetime Value (CLV) Forecasting: Integrating RFM Analysis with Machine Learning for Strategic Customer Retention
No full textCustomer Lifetime Value (CLV) is a critical metric in marketing analytics, enabling businesses to assess long-term profitability and optimize customer retention strategies. Traditional CLV models rely on heuristic approaches such as Regency, Frequency, and Monetary (RFM) analysis, but the advent of Artificial Intelligence (AI) and Machine Learning (ML) has significantly enhanced predictive capabilities. This study explores the integration of AI-driven ML algorithms with RFM analysis to improve CLV forecasting accuracy and enable more personalized customer engagement strategies. By leveraging supervised learning models, such as regression algorithms, decision trees, and neural networks, organizations can segment customers more effectively and predict future purchasing behaviors with greater precision (Lemmens & Gupta, 2020). Moreover, AI-driven approaches allow for dynamic CLV computation, adjusting to real-time customer interactions and behavioral shifts, thereby optimizing retention efforts and marketing expenditures (Gupta & Zeithaml, 2021). The study also evaluates the efficacy of clustering techniques, such as k-means and hierarchical clustering, in refining customer segmentation for targeted marketing interventions (Kumar et al., 2022). Findings suggest that integrating AI-based ML models with RFM analysis significantly improves the accuracy of CLV predictions, leading to higher customer retention rates and long-term business sustainability. This paper contributes to the growing body of literature advocating for AI-driven marketing analytics, demonstrating the strategic advantages of data-driven decision-making in customer relationship management