Exploring determinants of cloud-based enterprise resource planning (ERP) selection and adoption: A qualitative study in the Indian education sector

ABSTRACT

Cloud-based enterprise resource planning (CLERP) provides scalability, flexibility, and cost-savings. The advantages of CLERP are most prominent in developing economies where access to robust information technology (IT) resources is difficult. However, despite the advantages, diffusion of CLERP in such regions remains low. This study aims to explore the drivers of CLERP selection and adoption by proposing a sociotechnical framework integrating three technology adoption theories: diffusion of innovations, task-technology fit, and extended technology acceptance model. The framework is tested using case study methodology based on semi-structured interviews in three higher educational institutions in India. The findings have important implications for both CLERP providers and clients aiming to enhance the rate of diffusion. The results suggest that vendors should focus on providing cost-effective, reliable, secure, standardized, long-term, convenient, and better quality of service and support to clients. Moreover, they should provide free trials and customize their solutions while maintaining a balance between additional costs incurred and business value gained due to customization. The clients, in contrast, should determine organizational fit of the CLERP and train their employees to minimize resistance to its adoption.

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Notes on contributors

Saini Das

Saini Das is an Assistant Professor in the Information Systems area at Indian Institute of Management (IIM), Indore. She received her Ph.D. from the IIM, Lucknow. Her current research interests are information security risk management, cloud computing and e-commerce. She has published in journals such as Journal of Global Information Technology Management, Journal of Cases on Information Technology, Journal of Information Privacy and Security.

Madhukar Dayal

Madhukar Dayal is an Associate Professor in the Information Systems area at IIM, Indore. He received his Ph.D. from the IIM, Ahmedabad. He has served in the Indian Railways for over twenty years. His research interests include cloud computing, scheduling, combinatorial optimization, and compute cluster algorithms for NP-hard problems.