Wireless sensor networks (WSNs) play a crucial role in the Internet of Things (IoT) for ubiquitous data acquisition and tracking. However, the limited battery life of sensor nodes poses significant challenges to the long-term scalability and sustainability of these networks. Wireless power transfer technology offers a promising solution by enabling the recharging of energy-depleted nodes through a wireless portable charging device (WPCD). While this approach can extend node lifespan, it also introduces the challenge of bottleneck nodes—nodes whose remaining energy falls below a critical value of the threshold. The paper addresses this issue by formulating an optimization problem that aims to identify the optimal traveling path for the WPCD based on ant colony optimization (WPCD-ACO), with a focus on minimizing energy consumption and enhancing network stability. To achieve it, we propose an objective function by incorporating a time-varying z phase that is managed through linear programming to efficiently address the bottleneck nodes. Additionally, a gateway node continually updates the remaining energy levels of all nodes and relays this information to the IoT cloud. Our findings indicate that the outage-optimal distance achieved by WPCD-ACO is 6092 m, compared to 7225 m for the shortest path and 6142 m for Dijkstra’s algorithm. Furthermore, the WPCD-ACO minimizes energy consumption to 1.543 KJ, significantly outperforming other methods: single-hop at 4.8643 KJ, GR-Protocol at 3.165 KJ, grid clustering at 2.4839 KJ, and C-SARSA at 2.5869 KJ, respectively. Monte Carlo simulations validate that WPCD-ACO is outshining the existing methods in terms of the network lifetime, stability, survival rate of sensor nodes, and energy consumption.

Background:Organizations are implementing Green Human Resource Management (GHRM) techniques to improve their environmental performance and overall organizational efficiency as environmental sustainability becomes increasingly important in today's economic climate. GHRM incorporates environmental management concepts into human resource procedures in an effort to lessen their impact on the environment and enhance organizational performance. Objective: This study aims to examine how GHRM practices affect organizational performance, specifically how they affect employee engagement, environmental sustainability, and overall company success. Method: Data were gathered using a structured questionnaire designed to assess various aspects of Green HRM and organizational performance. A quantitative survey was distributed to 150 organizations implementing GHRM practices, achieving a response rate of 75%. The survey included questions on environmental performance metrics, employee engagement, and organizational performance. Additionally, qualitative data were collected through in-depth interviews with 20 HR managers and sustainability officers from the surveyed organizations. Data analysis is performed using SPSS version 28.0 for preliminary analyses and AMOS version 28.0 for SEM. The choice of software is based on its robustness and suitability for advanced statistical analysis. Result: The analysis revealed that 68% of organizations reported significant improvements in their environmental performance, including a 15% reduction in energy consumption and a 20% decrease in waste production. Employee engagement scores increased by an average of 25%, with 60% of respondents noting higher job satisfaction linked to GHRM practices. Furthermore, 55% of organizations experienced enhanced overall business performance, including increased profitability and market competitiveness. Despite these positive outcomes, 40% of organizations reported challenges related to initial investment costs and integrating GHRM practices into existing HR systems. Conclusion: GHRM practices positively influence organizational performance by promoting environmental sustainability and increasing employee engagement. Organizations that effectively integrate GHRM into their HR strategies can significantly improve environmental and business performance. However, overcoming initial implementation challenges is crucial for realizing the full benefits of GHRM. Future research should explore longitudinal effects and sector-specific variations in GHRM impact.

The gig economy, characterized by short-term contracts and freelance work, has significantly altered traditional employment models. This shift poses unique challenges and opportunities for Human Resource Management (HRM). As the gig economy grows, understanding the role of HRM in managing gig workers becomes crucial, particularly in terms of employee engagement, motivation, and retention. This research aims to explore the role of HRM practices in the gig economy, focusing on how HRM can effectively manage and support gig workers to enhance organizational performance and worker satisfaction. A comprehensive mixed-method approach was meticulously employed, integrating both quantitative and qualitative techniques to thoroughly assess the role of HRM in the gig economy. The quantitative component involved a structured survey distributed to 250 HR professionals across various industries, with an impressive response rate of 78% (195 respondents). The survey focused on HRM practices such as recruitment (30% of questions), performance management (25%), training (20%), and development (25%). In parallel, qualitative semi-structured interviews were conducted with 40 gig workers from diverse sectors, representing a 10% sampling from the total pool of respondents who participated in the survey. The study utilized SPSS software for quantitative analysis, focusing on multiple regression and factor analysis techniques.These interviews were designed to inclusively explore the gig workers' experiences and expectations regarding HRM practices, providing nuanced insights that complemented the survey data. The quantitative analysis revealed that 68% of HR professionals reported incorporating flexible recruitment strategies tailored to gig workers, with 54% emphasizing performance management systems adapted for short-term contracts. Training and development were less frequently addressed, with only 45% and 38% of respondents indicating specific programs for gig workers.Qualitative interviews further illuminated these findings, with gig workers expressing a strong preference for more inclusive training opportunities (70% of interviewees) and transparent performance management systems (65%). Many gig workers also highlighted the need for development pathways that could lead to longer-term employment or enhanced skills (60%), suggesting a gap between HRM practices and gig worker expectations. The study concludes that HRM plays a critical role in optimizing the gig economy workforce. By adapting HR practices to meet the unique needs of gig workers, organizations can achieve better performance outcomes and improve worker satisfaction. The research underscores the importance of developing HRM frameworks that are flexible, responsive, and aligned with the evolving nature of work in the gig economy.