| Issue |
E3S Web Conf.
Volume 692, 2026
3rd International Conference on Intelligent and Sustainable Power and Energy Systems (ISPES 2025)
|
|
|---|---|---|
| Article Number | 03012 | |
| Number of page(s) | 13 | |
| Section | Artificial Intelligence and Human-Computer Interaction | |
| DOI | https://doi.org/10.1051/e3sconf/202669203012 | |
| Published online | 04 February 2026 | |
Assessing the Effects of Enterprise Resource Planning on the Higher Education Sector in India
1 Department of Electronics and Communication Engineering, Sri Venkateshwara College of Engineering, Bengaluru, India
2 REVA business school, REVA University, Bengaluru, India
3 Department of Management Studies, Nitte Meenakshi Institute of Technology (NMIT), Bengaluru, India
4 Department of Management Studies, CMR university, Bangalore, India
5 Department of Economics, Government First Grade College for Women Balmatta, Mangaluru, India
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
The higher education sector in India is growing and plays a significant role in the country’s economic development and in shaping the future. Although the government has initiated programs such as the New Education Policy (NEP) across the higher education sector, shortcomings such as poor infrastructure, lack of coordination among departments, poor communication among stakeholders, inefficient processes, and issues related to decision-making still exist. Introducing the Enterprise Resource Planning (ERP) in the higher education sector can overcome these issues to a certain extent. This research focuses on the impact of ERP in the higher education sector and how it improves overall processes. Here, primary data collected from the relevant stakeholders are used to analyse the impact of ERP in the higher education sector. Overall, 250 responses were collected from the stakeholders, and performance was evaluated using basic statistical methods. The qualitative analysis is carried out to determine overall operational efficiency, data accuracy, and accessibility. Finally, an overall operational efficiency improvement of 75% was obtained, and an improvement in data accuracy and accessibility of 80%.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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