A machine learning assisted net zero maturity model for MSMEs in Eastern Uttar Pradesh India

Global warming and climate change have emerged as the predominant issues of this decade. Micro, Small, and Medium Enterprises (MSMEs) substantially contribute to global Greenhouse Gas (GHG) emissions. However, there are limited strategies specifically designed for MSMEs, especially in the Indian context. To formulate customized strategies or action plans for MSMEs, assessing their preparedness for Net Zero practices are essential. A maturity assessment model has been proposed to assess the organizational readiness of Indian MSMEs for the Net Zero transition. The model comprises four parameters: awareness and engagement; knowledge and capabilities; planning and strategy; and physical actions. Based on these parameters, data is collected from various MSMEs and experts through surveys and interviews. Data analysis (DA) techniques and supervised Machine Learning (ML) classification algorithms have been used to categorize MSMEs into four maturity levels. Following the implementation of the model to a varied cohort of MSMEs operating in various domains in India, the findings indicate that 26% of the MSMEs were at an insufficient maturity level, 49% were at a primary maturity level, 17% were at an evolving maturity level, and only 8% were operating at a consolidated maturity level. Results show that 75% of MSMEs operate at the earliest two maturity levels. The proposed maturity model can help MSMEs identify gaps in their organizational readiness and prioritize actions supporting the Net Zero transition. Existing studies have primarily focused on individual sustainability dimensions, whereas the proposed framework provides a comprehensive Net Zero maturity assessment for Indian MSMEs.