Rural Innovation and Sustainable Business Models for Viksit Bharat 2047: A Data-Driven Analysis of ERP, Automation, and Machine Learning Adoption in Indian Industries
Abstract: The rise of Industry 4.0 technologies, such as Enterprise Resource Planning (ERP), industrial automation, and machine learning (ML), has revolutionized the competition in the industrial sectors in India. However, the uptake of these technologies in rural and semi-urban industrial systems is still empirically under-investigated, although they can be a driver for inclusive growth and sustainable industrial business change. The present empirical study focuses on the adoption trends, productivity impacts and sustainability benefits of ERP, automation and ML integration in the Indian industry sector, especially within the rural and peri-urban manufacturing and agribusiness clusters in Odisha. The study is based on structured survey data of 312 respondents from five industry verticals within the context of Viksit Bharat 2047 vision. The research uses Structural Equation Modeling (SEM) and multiple hierarchical regression to validate a conceptual model specifically created for the rural context, the Rural Digital Technology Adoption Model (RDTAM) through seven tested pathways. The findings reveal that ERP adoption has a significant impact on enhancing the coordination of the supply chain (β = 0.423, p
Keywords: ERP Systems, Industrial Automation, Machine Learning, Rural Innovation, Sustainable Business Models, Viksit Bharat 2047, Industry 4.0, Indian Industries, Digital Technology Adoption
How to Cite?: Deepak Kumar Mishra, Sunil Dhal, Subash Chandra Nath, "Rural Innovation and Sustainable Business Models for Viksit Bharat 2047: A Data-Driven Analysis of ERP, Automation, and Machine Learning Adoption in Indian Industries", Volume 15 Issue 5, May 2026, International Journal of Science and Research (IJSR), Pages: 1591-1598, https://www.ijsr.net/getabstract.php?paperid=SR26422120551, DOI: https://dx.doi.org/10.21275/SR26422120551