Regression Analysis for Sustainability: Predicting Energy Use and Carbon Emissions

Abstract

Regression analysis is a powerful statistical tool that enables organizations to understand and predict the relationships between various operational factors and sustainability metrics such as energy usage and carbon emissions. This article explores the application of regression analysis in sustainability, focusing on two key areas: optimizing energy consumption and predicting carbon emissions in supply chain operations. Using real-world examples from manufacturing and the fashion industry, the article demonstrates how regression models can identify significant drivers of energy use and emissions, offering actionable insights for operational improvements. The findings highlight the importance of data-driven decision-making in reducing environmental footprints, optimizing resource usage, and achieving sustainability goals. By leveraging regression analysis, companies can make informed choices that promote efficiency, reduce costs, and enhance their environmental responsibility.