This study explores the role of Technical Support (TS) and Leadership Support (LS) in enhancing Employee Performance (EP) through the development of a Culture of Continuous Learning (CCL) in the Technical Education and Vocational Training (TEVT) sector of southern Punjab. Data from 291 TEVT trainers were analyzed using Smart PLS4. The results show that TS and LS have a positive impact on CCL, leading to improved EP. Employee Engagement (EE) moderates these effects, revealing barriers such as overwhelmed employees, limited relevance of learning programs, and a perceived lack of support and recognition. To overcome these challenges, organizations can provide support structures like mentoring and coaching. These findings emphasize the importance of TS, LS, and CCL in enhancing EP in the TEVT sector and suggest further research to explore additional factors for improved employee performance in resource-constrained environments.

This study explored how employees’ green commitments and attitudes strengthen the impact of Green Human Resource Management Practices (GHRMPs) on the Pro-environmental behavior (Pro-EB) of TEVT graduates & trainers at the workplace. The Technical Education and Vocational Training (TEVT) sector is now focusing on developing strategic, environmentally sustainable policies to develop their employee’s commitments & attitudes toward ecologically friendly activities. Using a convenient sampling technique, data was collected from 286 TEVT Trainers and TEVT graduates, and extracted results after applying PLS-SEM and Bootstrapping analysis showed that Green Human Resource Management Practices through Employee Green Commitments and Employee Green Attitude have a significant positive impact on pro-environmental behaviour. This study provides greater insight for policymakers on developing strong green commitments and attitudes among TEVT Trainers and graduates to achieve sustainable, environmentally friendly behavior at workplace and training institutes. Further in-depth analysis is therefore recommended based on PLS prediction (Q2) results by the addition of another variable.