Generational differences shape technological preferences and fundamentally influence workplace motivation and interactions. Our research aims to examine in detail how different generations assess the importance of workplace communication and leadership styles and how these diverse preferences impact workplace motivation and commitment. In our analysis, we studied the behavioral patterns of four generations—Baby Boomers, Generations X, Y, and Z—through anonymous online questionnaires supplemented by in-depth interviews conducted with a leader and a Generation Z employee. To verify our hypotheses, we employed statistical methods, including the Chi-Square test, Spearman’s rank correlation, and cross-tabulation analysis. Our results clearly demonstrated that different generations evaluate the importance of applied leadership and communication styles differently. While Generations Y and Z highly value flexible, supportive leadership styles, older generations, such as the Baby Boomers prefer more traditional, structured approaches. The study confirmed that aligning leadership and communication styles is crucial, as it significantly impacts the workplace atmosphere and employee performance. Our research findings hold both theoretical and practical significance. This research highlights how understanding generational preferences in leadership and communication styles can enhance workplace cohesion and efficiency. The results provide specific guidance for leaders and HR professionals to create a supportive and adaptable environment that effectively meets the needs of diverse generations.

Research in the field of online advertising has focused on the effect of in-stream ads on viewers’ attitudes and intentions to purchase. However, little is known regarding the crucial role of viewer’s control in terms of the ‘skip ad option’ towards the attitude to purchase. This research aims to investigate the effect of in-stream ads on viewers’ attitudes to purchasing with the moderating role of viewer control. Primary data was collected from respondents of Vehari district of Pakistan through a questionnaire based on 5 points Likert scale. 370 questionnaires were incorporated after excluding the questionnaires having missing values. Structural equation modelling was used through SmartPLS-3 software in testing the hypotheses. The findings reveal that, in-stream (emotional, informational, and entertaining) ads have positive impact on viewers’ attitudes, and viewers’ control moderates the relationship between in-stream ads and viewers’ attitudes towards the ads. Further, viewers’ attitude toward the ads has a significant positive impact on viewers’ intention to purchase. To the best of our knowledge this is one of the first studies that examines the effect of in-stream ads on viewers’ attitudes to purchasing with the moderating role of viewer control in the context of a developing country, like Pakistan.

This study aimed to determine the socio-economic poverty status of those living in rural areas using data surveys obtained from household expenditure and income. Machine learning-based classification and clustering models were proven to provide an overview of efforts to determine similarities in poverty characteristics. Efforts to address poverty classification and clustering typically involve comprehensive strategies that aim to improve socio-economic conditions in the affected areas. This research focuses on the combined application of machine learning classification and clustering techniques to analyze poverty. It aims to investigate whether the integration of classification and clustering algorithms can enhance the accuracy of poverty analysis by identifying distinct poverty classes or clusters based on multidimensional indicators. The results showed the superiority of machine learning in mapping poverty in rural areas; therefore, it can be adopted in the private sector and government domains. It is important to have access to relevant and reliable data to apply these machine learning techniques effectively. Data sources may include household surveys, census data, administrative records, satellite imagery, and other socioeconomic indicators. Machine learning classification and clustering analyses are used as a decision support tool to gain an understanding of poverty data from each village. These strategies are also used to describe the profile of poverty clusters in the community in terms of significant socio-economic indicators present in the data. Village clusters based on an analysis of existing poverty indicators are grouped into high, moderate, and low poverty levels. Machine learning can be a valuable tool for analyzing and understanding poverty by classifying individuals or households into different poverty categories and identifying patterns and clusters of poverty. These insights can inform targeted interventions, policy decisions, and resource allocation for poverty reduction programs.

This paper examines the transformative potential of e-government in public administration, focusing on its capacity to enhance service delivery, transparency, accessibility, cost efficiency, and civic engagement. The study identifies key challenges, including inadequate technological infrastructure, cybersecurity vulnerabilities, resistance to change within public institutions, and a lack of public awareness about e-government services. These barriers hinder the seamless operation and adoption of digital government initiatives. Conversely, the study highlights significant opportunities such as streamlined service delivery, enhanced transparency through real-time access to government data, increased accessibility for marginalized and remote communities, substantial cost savings, and greater civic engagement via digital platforms. Addressing these challenges through targeted strategies—enhancing technological infrastructure, bolstering cybersecurity, managing organizational change, and raising public awareness—can help policymakers and public administrators implement more effective and inclusive e-government initiatives. Additionally, the integration of these digital solutions can drive sustainable development and digital inclusion, fostering social equity and economic growth. By leveraging these opportunities, governments can achieve more efficient, transparent, and accountable governance. Ultimately, the successful implementation of e-government can transform the relationship between citizens and the state, building trust and fostering a more participatory democratic process.

The increasing use of social media has played a prominent role in shaping opinions and forming attitudes, especially among university students. They use them increasingly to transfer information, exchange data, and disseminate topics among students and all members of society. Therefore, this study aims to examine these networks and their role in public life, especially in shaping public opinion among university students. The study adopted a descriptive survey approach to achieve its objectives. The study was conducted on a sample of undergraduate students from four Jordanian universities, totaling 832 participants selected through purposive sampling and using the equal distribution method according to variables (gender, university, specialization). The study relied on a questionnaire as a method of data collection and filling out the data from the respondents in the questionnaire. The study found that social media plays a significant role in shaping opinions, beliefs, and ideas, and that its role is unparalleled. Also, the study showed that social media had a significant impact on shaping public opinion in Jordan among university students who use social media extensively and exchange opinions, ideas, and information, contributing to shaping a series of opinions among young people and contributing to their adoption of new ideas or changing their old ones through the dialogue facilitated by these networks, as users exchange and adopt ideas, contributing to shaping a public opinion on an issue. These findings underscore the importance of understanding and leveraging social media and online platforms to effectively communicate with and engage students.