This study examines the intricate interplay between the digital environment and the evolving communication dynamics of Generation Z, specifically focusing on the impact of social media on familial bonds. The research objective is to explore the ways in which Generation Z’s social media consumption patterns shape their relationships and lives, providing insights into the intricate interplay between technology and human connections. Adopting Hirschi and Wellman’s theoretical framework, this investigation employs a survey method, utilizing a questionnaire to gather data from 384 Iranian Generation Z social media users. The findings reveal a significant and negative correlation between family bonds and social media usage, dependency on the platform, and support received from it. Excessive use diminishes interaction and intimacy, highlighting social media’s potential consequences for family relationships, which are crucial for individual and societal well-being. The study underscores the significance of balanced social media usage and encourages initiatives promoting face-to-face interactions, empathy, and responsible digital citizenship. The findings hold significant implications for academics and policymakers in developing strategies that promote responsible digital habits, foster healthy relationships, and contribute to digital citizenship advancement. This may involve regulatory initiatives, guidelines for social media platforms, and public awareness campaigns emphasizing the importance of balanced digital habits.

This study addresses the critical issue of employee turnover intention within Malaysia’s manufacturing sector, focusing on the semiconductor industry, a pivotal component of the inclusive economy growth. The research aims to unveil the determinants of employee turnover intentions through a comprehensive analysis encompassing compensation, career development, work-life balance, and leadership style. Utilizing Herzberg’s Two-Factor Theory as a theoretical framework, the study hypothesizes that motivators (e.g., career development, recognition) and hygiene factors (e.g., compensation, working conditions) significantly influence employees’ intentions to leave. The quantitative research methodology employs a descriptive correlation design to investigate the relationships between the specified variables and turnover intention. Data was collected from executives and managers in northern Malaysia’s semiconductor industry, revealing that compensation, rewards, and work-life balance are significant predictors of turnover intention. At the same time, career development and transformational leadership style show no substantial impact. The findings suggest that manufacturing firms must reevaluate their compensation strategies, foster a conducive work-life balance, and consider a diverse workforce’s evolving needs and expectations to mitigate turnover rates. This study contributes to academic discourse by filling gaps in current literature and offers practical implications for industry stakeholders aiming to enhance employee retention and organizational competitiveness.

The article provides evidence on the effect of local public governance on the impact of public investment on local and regional economic growth, using spatial and regional logic. The research uses the spatial Durbin model and produces a panel data set that was conducted on 63 provinces of Vietnam from 2006 to 2022. Based on the interaction between public governance and public investment, the main findings indicate that their interaction plays an important role in adjusting the effects of public investment and public governance on economic growth not only in the locality but also spillover to neighboring localities in both the short and long terms. It suggests that local public governance not only hampers the impact of local public investment on local economic growth but also has spillover effects on the growth of neighboring provinces or regions in Vietnam. Additionally, the results of detailed analysis of PCI component indicators show that many aspects of local public governance are hindering local economic growth but contributing to promoting neighboring localities economic growth. Or, it has no effect the locality but promote or hinder the regional economic growth. The findings in this study implies that authorities of localities need to be cautious when using resources to improve the various aspects of public governance when designing strategies to enhance the quality of local public governance. It also suggests that this spillover effect is a crucial factor in advocating for more redistributive fiscal policies and regional governance policies aimed at reducing economic disparities caused by territorial boundaries. Therefore, authorities should prioritize regional cooperation strategies in their decisions regarding public governance and public capital allocation.

Recently, the government of Ethiopia has been engaged in modernizing the trans-regional Ethio-Djibouti railway infrastructure using the Belt and Road Initiative. This railway corridor has been serving as the main get way for the landlocked Ethiopia to the port. This article creates an insight about the implications of the Ethio-Djibouti railway corridor by exploring the question: what kinds of urban form and morphological changes evolved due to the railway corridor? To examine the impact of this railway corridor, the article employed stratified sampling and multiple criteria intermediate cities selection method. Accordingly, four (Bishoftu, Mojo, Adama, and Dire Dawa) intermediate cities were selected as case study. The article points out that the railway corridor conceived different kinds of linear urban centers around stations. The identified four intermediate cities attract industries and logistic centers. Those industries, logistic centers, and new railway stations often established at the periphery of intermediate cities resulted labour influx from rural and nearby small urban centers and urban expansion that caused a rural-urban continuum of ribbon settlement and strengthen trade gate way for the landlocked Ethiopia that caused trans-regional integration.

The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.