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In today’s business landscape, drawing upon the critical role of environmental sustainability, this study investigates the intricate relationship between green human resource management practices (GHRMP), big data analytics capability (BDAC), green competitive advantage (GCA) and environmental performance (EP), further moderated by managerial environmental concern (MEC).

This study employs a quantitative approach using the latest version of SmartPLS 4 version 4.0.9.6 on a data sample of 467 participants representing a diverse range of manufacturing SMEs. Data were collected from managers and directors using a structured questionnaire and analyzed using structural equation modeling (SEM). This study contributes to the existing knowledge by integrating GHRMP and BDAC within the GCA framework, providing a comprehensive understanding of how these practices enhance SME`s sustainability.

The findings provide valuable insights into the manufacturing sector, aiming to enhance SMEs' green competitive advantage. Implementing GHRMP fosters environmental awareness within the workforce, and building BDAC allows for effectively translating that GHRMP into actionable insights, maximizing the potential for achieving GCA. Furthermore, recognizing MEC’s moderating role strengthens positive environmental outcomes associated with GCA. The findings confirm that GHRMP and BDAC are valuable resources and key drivers contributing to competitive advantage in sustainability of enterprises.

For SMEs, our findings suggest that strategically integrating GHRMP with BDAC not only boosts environmental stewardship but also improves operational efficiency and market positioning. This research outlines actionable steps for SMEs aiming to achieve sustainability targets while enhancing profitability. This research provides actionable insights for SMEs in strategic decision-making and policy formulation, aiding SMEs in navigating the complexities of sustainable development effectively.

This study contributes to the existing knowledge by integrating GHRMP and BDAC within the GCA framework, providing a robust theoretical explanation of how HRM practices and BDAC help SMEs gain green competitiveness. The implication of this study reveals that SMEs implementing and integrating green HRM practices with advanced data analytics are more likely to gain competitive advantage. This study draws theoretical support from the resource-based view (RBV) theory, positing that a firm’s sustainable competitive advantage stems from its unique and valuable resources and capabilities that are difficult for competitors to imitate or substitute.

This research was initiated by motivation from a real business problem that delves into lean management practices in dairy farm operations. It investigates how lean management practices can be applied as an improvement strategy in the dairy business to evaluate its impact on performance, where profitability is a decisive factor.

Based on the qualitative design, a 5-phase action research methodology was used in this study, where multiple data collection sources were used, including focus group discussions, on-site observation or Gemba walks and process mapping. The impact is evaluated by comparing the key performance measures with the same period before and after research.

The research revealed that lean management practices can significantly improve dairy business performance. It explained vital aspects of lean management practices and their sequence with examples of first-hand applications. It explained, how lean management practices were applied in dairy farm operations. Furthermore, the research resulted in significant benefits, in terms of quality, cost and profitability.

This research was conducted in a real business setting in the field environment, to improve dairy business performance. It was a distinctive application of lean management practices to solve a national problem. This could be used as a road map to bring continuous improvement at the national level to improve the performance of food value chains.

This research is unique because it addresses the methodological, population and empirical gaps in dairy farm operations. It adds value to the existing knowledge base by sharing best practices, developed and implemented for the first time to the best of our knowledge, like high-level process mapping and performance measures at different levels. Furthermore, the solutions can be simulated in related farm operations to bring breakthrough improvements in dairy business performance.