Nomophobia, the anxiety experienced when individuals are separated from their mobile phones, is becoming increasingly prevalent in modern workplaces. This study investigates the role of organizational commitment in mitigating nomophobia, with a focus on the mediating influence of the ethical environment. Data were collected from 600 participants and analyzed using Structural Equation Modeling (SEM). The findings show that a strong sense of organizational commitment significantly reduces nomophobia among employees. Additionally, an ethical environment within organizations further mitigates this anxiety by fostering a workplace culture that encourages psychological well-being. This research provides practical insights for organizations looking to reduce the psychological strain associated with digital dependency, emphasizing the importance of both commitment and a strong ethical climate.
This paper examines the effect of governance in Sub-Saharan African (SSA) countries. Specifically, this study investigates (i) the interacting impact of government efficiency, regulatory quality, and the rule of law alongside other socioeconomic variables to determine foreign capital inflow (FCI) based on each economic SSA bloc; and (ii) the characteristic drivers of FCI, impacting economic growth in the SSA countries. Descriptive statistics, static models, least square dummy variables (LSDVs) and the dynamic system general method of moment (GMM) were employed as the study’s estimating techniques. Based on the result of the LSDV, food security and the rule of law significantly impact FCI in the sub-economic blocs in the region. Only six countries across the four economic blocs responded to food security and the rule of law in the model. The dynamic system-GMM provided evidence of five socioeconomic variables and three governance variables contributing to FCI. The findings revealed (i) regulatory quality and the rule of law are governance variables that significantly impacted FCI; and (ii) food security failed to significantly impact FCI in the SSA region. However, inflation, life expectancy, the human capital index, exchange rate and gross domestic product (GDP) growth impacted FCI significantly. In the aggregate, inflation, regulatory quality, exchange rate and the human capital index exhibited positive relationships, while other variables such as life expectancy, government effectiveness and the rule of law appeared significant but inversely impacted FCI in the SSA region. The key policy implication recommendation from this study is that a good legal framework could moderate the flow of foreign capital in favour of growth as it creates a strong foundation for sustainable economic development in the region.
The selection of a suitable place for an activity is an important decision made for a project, which requires assessing it from different points of view. Educational use is one of the most complicated and substantial uses in urban space that requires precise and logical attention to its location and neighborhood with similar and consistent uses. Faculties of universities are educational spaces that should be protected against physical and moral damage to create a healthy educational environment. To do this, it is necessary to find and assess the factors affecting the location of educational spaces. The extant study aimed at finding and assessing the factors affecting the location of educational spaces to locate art and architecture schools or faculties in 4 important universities. The present study is applied developmental research in terms of nature and descriptive-analytical in terms of method. This study used the AHP (Analytical Hierarchy Process) weighing and controlled the prioritization through the TOPSIS (Technique for Order Preference by Similarity) technique in the methodology phase. Since there was no criterion and metric for these centers, six were chosen as the primary metrics after reviewing the relevant theoretical foundations, early investigations, and collecting effective data. Finally, the results indicated the most important factors of vehicular or roadway access, pedestrian access, slope, parking, adjacency, neighborhood, and area. Among the mentioned factors, pedestrian access (w: 0.4231) had the highest weight and was the priority in the location of architecture faculty in studied campuses and areas inside the universities.
The present study focuses on improving Cognitive Radio Networks (CRNs) based on applying machine learning to spectrum sensing in remote learning scenarios. Remote education requires connection dependability and continuity that can be affected by the scarcity of the amount of usable spectrum and suboptimal spectrum usage. The solution for the proposed problem utilizes deep learning approaches, namely CNN and LSTM networks, to enhance the spectrum detection probability (92% detection accuracy) and consequently reduce the number of false alarms (5% false alarm rate) to maximize spectrum utilization efficiency. By developing the cooperative spectrum sensing where many users share their data, the system makes detection more reliable and energy-saving (achieving 92% energy efficiency) which is crucial for sustaining stable connections in educational scenarios. This approach addresses critical challenges in remote education by ensuring scalability across diverse network conditions and maintaining performance on resource-constrained devices like tablets and IoT sensors. Combining CRNs with new technologies like IoT and 5G improves their capabilities and allows these networks to meet the constantly changing loads of distant educational systems. This approach presents another prospect to spectrum management dilemmas in that education delivery needs are met optimally from any STI irrespective of the availability of resources in the locale. The results show that together with machine learning, CRNs can be considered a viable path to improving the networks' performance in the context of remote learning and advancing the future of education in the digital environment. This work also focuses on how machine learning has enabled the enhancement of CRNs for education and provides robust solutions that can meet the increasing needs of online learning.
Currently, there is little study on managing organizational silence in Malaysia post COVID-19 pandemic. This study aims to examine the determinants of organizational silence and the impacts of silence on private sectors and employees. The target respondents are two hundred individuals above 21 years old working in private sectors across Malaysia. Purposive sampling is selected for this study because the target respondents must be individuals working in private sectors across Malaysia. The strongest predictor of organizational silence is the attitudes of immediate superior, followed by attitudes of top management and communication opportunities. This study provides valuable information to the employees and management in the private sector to recognize the behaviors that will create silence within the organization.
This study addresses the impact of the tourism sector on poverty, poverty depth, and poverty severity in Indonesia, focusing on the micro-level dynamics in the province. Despite numerous tourism destinations, their strategic contribution to regional progress remains underexplored. The motivation stems from the need to comprehend the nuanced relationship between tourism and poverty at both the national and local levels, with specific attention to the untapped potential at the province level in Indonesia. We hypothesize that a higher tourism sector GRDP will be inversely correlated with poverty levels, and the inclusion of a Covid-19 variable will reveal a structural impact on poverty dynamics. Employing a Panel Regression Model, secondary data from the Central Statistics Agency (BPS) spanning 2011–2020 is utilized. A panel data regression equation model, including CEM, FEM, and REM, is employed to analyze the intricate relationship between tourism and poverty. The findings demonstrate a negative correlation between higher tourism sector GRDP and the number of poor people. The Covid-19 variable, considered a structural break, reveals a significant association between increased cases and elevated poverty and severity across Indonesian provinces. This study contributes a micro-level analysis of tourism’s role, emphasizing its impact at the provincial level. The findings underscore the need for strategic initiatives to harness the untapped potential of tourism in alleviating poverty and promoting regional progress.
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