A mathematical correlation between green supply chain management practices and supply chain performance variables: A model of cubical regression

Abstract

The study conducted an exploratory analysis using the cubical regression technique to determine the Influence of various green supply practices on supply chain performance. Specifically, the study aimed to establish a relationship between green practices and performance, with the Indian leather industry serving as the context for a cross-case analysis. Through five case studies, the research examined five propositions, focusing on different green practices and their impact on performance parameters in the industry. The study’s main objective was to identify essential green practices that top management should consider in handling performance parameters. The research analyzed the Influence of these practices on critical performance parameters and used a cubical regression model to represent performance parameters against various green techniques graphically. The findings revealed that eco-friendly approaches significantly enhance product quality, customer satisfaction, and operational efficiency. Additionally, the study outlined factors that can affect green supply chain management. Finally, a cubical regression model was plotted on a curve to identify the Model that most strongly correlates with the Indian leather industry’s multiple performance indicators concerning green supply practices. Overall, the study offers valuable insights into the impact of green practices on performance parameters and guides top management in adopting eco-friendly approaches to enhance their supply chain performance.

Keywords

• GSCM
• Cubical regression
• Case study approach