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This study examines the impact of urbanization on growth and the role of international financial flows in the urbanization-growth nexus.

The study applies the panel least square estimation to examine the impact of urbanization on growth using panel data from 50 developing countries from 1980 to 2016. Further, addressing the endogeneity issues in panel estimations, the study applies the dynamic System-GMM approach to investigate the role of financial flows in urbanization and their impact on economic growth in developing countries.

Contrary to the conventional literature, we found a non-linear (U-shaped) relationship between urbanization and growth. Our findings demonstrate that growth is reduced at a lower level of urbanization due to less availability, concentration, and synchronization of production factors. The concentration of physical and human capital and technological advancement in urban areas help developing countries achieve economic growth at a higher level of urbanization. Robust estimations divulged that foreign aid spent on infrastructure development and expanding urban regions helps promote economic growth. Nevertheless, as a resilient factor, remittances buffer the rapid pace of urbanization and reduce growth by resisting the migration of labor and capital from rural to urban areas.

The paper's findings suggest policymakers promote urban infrastructure and development using local and international funds since its increased level spurs economic growth. Further, the results advise policymakers to reduce aid dependency, attract FDI, and facilitate the easy and low-cost transfer of money to promote remittance inflows since both FDI and remittances positively contribute to economic growth.

The paper contributes significantly to the literature by determining the U-shaped relationship between urbanization and growth and highlighting the role of international flows in the urbanization-growth nexus.

The objective is to develop a more effective model that simplifies and accelerates the news classification process using advanced text mining and deep learning (DL) techniques. A distributed framework utilizing Bidirectional Encoder Representations from Transformers (BERT) was developed to classify news headlines. This approach leverages various text mining and DL techniques on a distributed infrastructure, aiming to offer an alternative to traditional news classification methods.

This study focuses on the classification of distinct types of news by analyzing tweets from various news channels. It addresses the limitations of using benchmark datasets for news classification, which often result in models that are impractical for real-world applications.

The framework’s effectiveness was evaluated on a newly proposed dataset and two additional benchmark datasets from the Kaggle repository, assessing the performance of each text mining and classification method across these datasets. The results of this study demonstrate that the proposed strategy significantly outperforms other approaches in terms of accuracy and execution time. This indicates that the distributed framework, coupled with the use of BERT for text analysis, provides a robust solution for analyzing large volumes of data efficiently. The findings also highlight the value of the newly released corpus for further research in news classification and emotion classification, suggesting its potential to facilitate advancements in these areas.

This research introduces an innovative distributed framework for news classification that addresses the shortcomings of models trained on benchmark datasets. By utilizing cutting-edge techniques and a novel dataset, the study offers significant improvements in accuracy and processing speed. The release of the corpus represents a valuable contribution to the field, enabling further exploration into news and emotion classification. This work sets a new standard for the analysis of news data, offering practical implications for the development of more effective and efficient news classification systems.

This study aims to find out how pomposia fruit powder (Syzygium cumini L.) mixed with roasted coffee (RCO) affected antioxidants, phytochemicals, lipid peroxidation inhibition and sensory attributes.

Pomposia fruits (Syzygium cumini L.) powder (PFP) was integrated with RCO at levels of 0.0%, 5.0%, 10.0%, 15.0% and 20.0%. RCO, PFP and binary mixtures containing RCO: PFP were evaluated for their total phenolics (TP), total flavonoids (TF), anthocyanin content (AC), antioxidant activity and phenolic compounds fractionation. The oxidative indices of coffee oil samples were measured throughout different storage intervals. Additionally, sensory characteristics of RCO enriched with different PFP doses were evaluated.

PFP samples exhibited the greatest TP content (1910 mg/100 g), whereas RCO samples had the lowest concentration (1090 mg/100 g). As more PFP was added, the corresponding coffee blends’ concentrations of TP, TF and AC were improved significantly. PFP possesses a radical-scavenging activity that is about 1.20 times more than RCO’s. DPPH (2,2-diphenyl-1-picrylhydrazyl) radical-scavenging activity jumped significantly from 74.13% in control (untreated) samples to 77.64%, 78.39% and 80.15% for samples enriched with 10.0%, 15.0% and 20% PFP, respectively. Significant increases in gallic acid, hesperidine, benzoic acid, chlorogenic acid, hispertin, catechol, quercetin, pyrogallol and rutin were detected when RCO was mixed with different quantities of PFP. At the end of storage trial, the coffee oil treated with 20% PFP had AV, PV and TBA values that were about 1.70, 1.95 and 1.66 times lower, respectively, than those of the control sample that had not had PFP addition. The RCO with 5.0% PFP achieved the greatest over acceptability grades.

To the best of the authors’ knowledge, this study was the first study to evaluate the effect of incorporating various level of pomposia fruit powder into RCO. The findings shows that adding different concentrations of pomposia fruit powder into RCO can indeed enhance the radical-scavenging activity of the coffee and potentially extend its shelf life.

This study aims to investigate the impact of liquidity creation (LC) on the profitability and stability of banks while considering the moderating role of corruption.

Panel data from 23 conventional banks and five Islamic banks in Pakistan spanning from 2008 to 2021 were used for analysis. The study used fixed effect and random effect models, along with the generalized method of moments estimation to ensure robustness of the results.

The study reveals a negative relationship between LC and banking profitability, but a positive association with banking stability. Additionally, corruption is found to play a moderating role in the relationship between LC, profitability and stability in the banking sector of Pakistan.

The findings have practical implications for bank managers and investors, emphasizing the negative relationship between LC and profitability in Pakistan. Moreover, the study highlights the significant impact of corruption on bank performance, which can guide policymakers in formulating strategies to strengthen the banking sector and prevent financial turmoil in the future.

This study makes a significant contribution to the existing literature by examining the moderating role of corruption in the relationship between LC, profitability and stability in both conventional and Islamic banks.

This study aims to theoretically discuss and empirically test the mediating mechanism of psychological distress and the moderating effects of Islamic work ethics (IWE) in the relationship between despotic leadership and adaptive performance.

A three-wave survey was used to gather the data from middle managers and their supervisors of construction firms in Pakistan. The final sample consisted of 304 respondents and data analysis was performed through SEM analysis.

Despotic leadership enhances employees’ psychological distress which results in a negative impact on adaptive performance. In addition, IWE played a buffering role in mitigating the harmful impacts of despotic leadership on adaptive performance.

The study is among the pioneers that have investigated how despotic leadership impacts employees’ adaptive performance via the underlying mechanism of psychological distress through the conservation of resources and social exchange theory lens.

Metaverse is one of the decade’s most exciting and transformative technological innovations. While the metaverse holds immense promise, it has potential risks and dark sides. This research aims to investigate and identify the crucial dark dimensions associated with the metaverse platforms.

Employing a qualitative phenomenological methodology, the authors interviewed 45 metaverse users to unravel dark dimensions related to the metaverse. Analyzing the themes extracted from the participants' insights revealed an alignment with the underpinnings of the Technology Threat Avoidance (TTA) theory.

The findings of this study revealed seven major dark dimensions: addiction and dependency, isolation and loneliness, mental health issues, privacy and security, cyberbullying and harassment, digital identity theft and financial exploitation.

The study helps organizations and metaverse platforms understand the crucial dark dimensions of the metaverse. This study concludes by synthesizing prevalent themes and proposing propositions, offering insights for practical application and policy considerations.

This study provides a deeper understanding of the dark side of the metaverse environment from a user perspective using the underpinnings of TTA theory.

In recent years, the global focus has increasingly shifted toward the adoption of electric vehicles (EVs) due to growing concerns about environmental sustainability and the imperative of reducing greenhouse gas emissions. The transportation sector, a significant contributor to air pollution and climate change, faces increasing pressure to embrace EVs as a solution. However, the resistance exhibited by customers toward adopting new technology poses a substantial obstacle to the widespread adoption of EVs. Drawing on the link between theory of reasoned action (TRA) and self-congruity theory, this research aims to determine the factors that affect the customer intention toward EV.

The research conducts a questionnaire collecting 950 respondents from the Egyptian market. The research used primary quantitative data from online and self-administered questionnaires.

The findings indicated that green trust, price sensitivity and reliability have a positive impact on customer’s intention. However, self-image congruence was not affecting customer intention. For the moderating role of financial self-efficacy, it is affecting the relationship between price sensitivity and customer’s purchase intentions toward EV.

This research will expand the theory by conceptualizing its abstract notions through research variables and implementing them in the Egyptian market. Furthermore, it links the two distinct theories. This knowledge can be utilized by policymakers and stakeholders to expedite the adoption of EVs in the Egyptian market.

This study presents a conceptual framework for managers and policymakers about the factors that affect the customer to buy EVs, since the international organizations emphasize eco-friendly transportation systems.

Talent management is conducted to maximize an organization's overall performance and efficiency which helps to serve as a competitive advantage. Human resource management is a concept which includes human-related activities, but talent management is a strategy which helps to get new talent, develop their skill sets and provide better employee engagement and experience to retain the top potential employees in an organization. Improvement in recruiting and retention of a workforce results from a well-executed talent acquisition approach. In the 21st century, employee retention has become a primary concern for the organizations specially with work from home and hybrid models.

The workforce for tomorrow is going to be very different from what it has been. Technology is transforming the way people work within organizations. The workplace is rapidly evolving in terms of people and processes and is going through a lot of technological changes. The terminologies such as automation, artificial intelligence, augmented reality and block chain technologies are slowly becoming part of the workplace and everyday activities of the organization.

The challenges are many and especially post-pandemic organizations are going through some major changes such as a mindset shift of employees to take up more remote working opportunities, building virtual teams, increase in the gig economy workers (contractual workers) and a diverse workforce which makes it even more challenging for the organization to manage and retain talent.

This study attempts to examine how employee orientations and paranoid arousal intersect and influence the voice behaviors of employees, as they significantly influence workplace practices.

Drawing on a multi-source and multi-time-based survey, the data were collected from 37 supervisors and 270 employees in 80 branches of 11 microfinance banks. SmartPLS-4.1 was used to test the measurement and structural model. A total of 307 questionnaires were used for the data analysis.

This research presents the contrasting results of employee orientations with voice behavior. Results support the direct relationship between paranoid arousal and promotive-prohibitive voice behaviors. However, no support was found for approach-avoidance orientation and promotive-prohibitive voice behaviors.

Employees' ability to voice-out in organizations depends on several motivational factors, consolidated into three areas – organizational culture, leadership, and individual traits. Organizations must implement a culture of transparency and open communication. Participative and inclusive leadership styles increase the quality of relationships with employees, stimulating a promotive voice. A support system for employees is needed to advance in their careers, increasing promotive behaviors.

The study adds value to the existing body of knowledge by studying approach-avoidance orientations and voice behaviors through the lens of paranoid arousal in the framework.

Agriculture is one of the oldest socio-economic activities. It involves growing valuable plants and animals for human existence. Sustainable agriculture should be understood in light of the global sustainable development movement, which emphasizes balancing environment, society and economics. With the ongoing effects of the COVID-19 pandemic and the recent war between Russia and Ukraine, sustainable agriculture can help eliminate food insecurity caused by food shortages and agricultural sector disruptions. Recently, investors, practitioners, academicians, researchers, regulators and financiers are increasingly interested in using Islamic financing products and qualified Shari'ah-compliance contracts to promote sustainable agriculture. Many Organization of Islamic Cooperation (OIC) states still rely on agriculture for socioeconomic growth. These countries are major contributors to Islamic financial growth. This study assesses Islamic finance’s role in promoting sustainable agriculture in selected OIC countries. The researchers use qualitative methods and meta-analysis data to determine the constraints and benefits of implementing Islamic financial products for sustainable agriculture. This study suggests that OIC state governments should promote sustainable agriculture. OIC member states have different achievements relating to their sustainable agriculture. Based on socio-economic factors, agriculture policies or plans, leadership and political will, Islamic finance products and Shari'ah-compliance contracts are found underutilized in meeting sustainable agriculture and sector stakeholders’ needs. A solid Islamic financial framework for sustainable agriculture, good governance and improved agriculture policy are needed.