Green Human Resource Management, Technological Innovation, and Organizational Sustainability: Evidence from Manufacturing Enterprises

Abstract

Green Human Resource Management (GHRM) has emerged as a strategic approach for enhancing organizational sustainability by integrating employee development with sustainable management practices. However, empirical evidence linking GHRM, technological innovation, and organizational sustainability using workforce analytics remains limited, particularly within manufacturing enterprises. This study investigated these relationships using a cleaned human resource analytics dataset comprising 2,845 employee records collected from manufacturing organizations. Because direct measures of GHRM and organizational sustainability were unavailable, employee training, engagement, satisfaction, work–life balance, performance ratings, and workforce development indicators were employed as validated proxy variables. A quantitative cross-sectional research design was adopted, and statistical analyses were performed using Python through descriptive statistics, frequency analysis, correlation assessment, and graphical visualization. The findings revealed balanced distributions across employee engagement, satisfaction, work–life balance, and training activities, indicating a stable organizational environment that supports sustainable workforce development. Internal and external training programmes were implemented with comparable frequency, while consistent employee development investments reflected the organizations' commitment to capability enhancement. The results further demonstrated that technological innovation contributes more effectively to organizational sustainability when supported by structured human resource practices and continuous employee development. Overall, the study highlights the value of integrating workforce analytics with strategic human resource management to strengthen organizational resilience, improve employee capability, and promote sustainable organizational performance within manufacturing enterprises.