This research aims to examine the influence of IHRMP, recruitment and selection, training, compensation, and performance appraisal on the productivity of Faculty Members (FM) productivity working in private universities in the UAE. The study also examines the mediating role of Organizational Commitment (OC) and the moderating role of the Entrepreneurial Mind-set (EM). The research adopted the social exchange theory. A survey was conducted comprising 160 FM. The data was analyzed using Structural Equation Modelling, Smart-PLS. The findings indicate a positive relationship between IHRMP and the productivity of the FM. The findings also show that OC mediates the relationship between IHRMP and the productivity of FM. Finally, an EM was found to moderate the relationship between IHRMP and the productivity of FM.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.

In the context of a globalized economic environment, businesses are facing an increasing number of environmental challenges, prompting them not only to pursue economic benefits but also to focus on environmental protection and social responsibility. Green supply chain management (GSCM) and green innovation have become key strategies for enterprises aiming for sustainable development. This study explores the impact of green supply chain practices on green innovation performance, with a focus on how knowledge management and organizational integration serve as mediating variables in this relationship. Grounded in the resource-based view (RBV) and knowledge-based view (KBV) theories, this research employs surveys and in-depth interviews with companies across various industries, combined with the analysis of structural equation modeling, to reveal the complex relationship between GSCM practices, knowledge management capabilities, levels of organizational integration, and green innovation performance. The results show that GSCM practices significantly enhance corporate green innovation performance through effective knowledge management and organizational integration. These findings enrich the theories of GSCM and green innovation, providing practical guidance for enterprises on how to enhance green innovation performance through strengthening knowledge management and organizational integration. Finally, this study discusses its limitations and suggests possible directions for future research, such as exploring the differences in findings across different industry backgrounds and examining other potential mediating or moderating variables.

This study explores the role of arts management in regional economic development within major Chinese cities, including Beijing, Shanghai, and Shenzhen. Cultural organizations—such as museums, theaters, and galleries—contribute significantly to local economies through tourism, job creation, and the enhancement of cultural branding. Using a qualitative approach, 18 semi-structured interviews with arts managers and policymakers selected based on their influential roles in cultural organizations across these cities. The interviews were analyzed using thematic analysis, which identified key themes including the economic impact of cultural organizations, the influence of government policies, challenges in arts management, and the role of cultural tourism in fostering regional growth. The findings reveal that while government policies play a pivotal role in supporting cultural organizations, providing crucial funding, tax incentives, and infrastructure development, concerns remain about the long-term sustainability of funding due to shifting political and economic priorities. Additionally, arts managers face challenges related to balancing artistic goals with financial viability, particularly as the sector becomes increasingly competitive and technology-dependent. Key challenges identified include securing stable funding sources, adapting to digital technologies, talent retention, and maintaining artistic integrity amid commercial pressures. The study highlights the need for diversified funding models such as public-private partnerships and alternative revenue streams and suggests further exploration into the role of smaller cultural organizations in rural regions to promote inclusive regional development. Practical recommendations include developing strategies to enhance financial sustainability, investing in digital capabilities, and formulating policies that provide long-term support for the cultural sector. Overall, the research contributes to a better understanding of how effective arts management can drive regional economic development and offers practical recommendations for strengthening the sustainability of China’s cultural sector.

Working Capital Management (hereafter WCM) is the strategic tool that helps a company navigate through challenging economic growth, and influence its competitive performance. Thus, this study examines the impact of WCM on the competitiveness of firms operating in the non-financial sectors in Pakistan. We use the Generalized Method of Moments (GMM) technique to ensure the robustness of our results. The study findings reveal that both a large net trade cycle and surplus working capital have a substantial negative impact on firms’ competitiveness within their respective industries. These results suggest that companies should streamline their investments in working capital accounts and concentrate more resources on long-term projects that maximize value to improve their competitiveness compared to other companies. Therefore, firms that are effectively managing their short-term financial affairs are experiencing much better performance in all aspects of firm performance. The research findings highlight the urgent need for governmental initiatives designed to improve WCM practices in these industries. It is imperative for the management of  companies with excess net working capital to maximize their working capital efficiency, aligning it with industry standards to enhance competitiveness. Moreover, policymakers should prioritize easing access to financial alternatives that allow enterprises to maintain an efficient working capital structure without relying on excessive measures. Furthermore, policymakers should be cautious when determining minimum cash balance requirements in a cash-strapped economy where external financing is relatively more expensive than in other regional economies.

The employees in academic sector had to face an abrupt change due to Covid-19 pandemic and transformation of education into online and remote learning. This has led to virtual work intensity as an aftermath that negatively influences employees’ job satisfaction. In addition, due to remote working conditions, the lines between work and life had been dimmed and thus, the current situation is important to be addressed for wellbeing of academic staff. This research specifically aims to examine impact of virtual work intensity on job satisfaction among university staff. Furthermore, mediating effect of organizational support and work-life balance on the aforementioned relationship are analyzed to better understand the underlying effects. Through PLS-SEM and using a questionnaire survey, a total of 183 data were collected from teachers and administrative staff of two universities. The results show that virtual work intensity can hinder job satisfaction, while organizational support and work-life balance can improve job satisfaction of academic employees. This is due to the fact that support, and balance act against work intensity that diminishes wellbeing of individuals. This implies the vital role of organizations (e.g., human resource department) in providing support for their staff, and creating an environment, where academic staff can have a better work-life balance, leading to higher rates of job satisfaction as an important factor for psychological wellbeing.