The Journal for Information Professionals
Asia Pacific Journal of Information Systems (APJIS), a Scopus and ABDC indexed journal, is a
flagship journal of the information systems (IS) field in the Asia Pacific region.
ISSN 2288-5404 (Print) / ISSN 2288-6818 (Online)
Editor : Youngsok Bang
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Current Issue
| Date | March 2026 |
|---|---|
| Vol. No. | Vol. 36 No. 1 |
| DOI | https://doi.org/10.14329/apjis.2026.36.1.45 |
| Page | 45~66 |
| Title | Assessment of Gen AI Readiness Factors in the Indian Cement Industry: A COPRAS-Based Prioritization |
| Author | Satish Chandra Pandey, Sambit Kumar Dash, Naveen Virmani |
| Keyword | Gen-AI, Cement Industry, Readiness Factors, Criteria, COPRAS |
| Abstract | Generative AI (Gen-AI) is getting importance in enhancing business competitiveness and overcoming environmental and economic concerns. However, its adoption and readiness assessment is subjected to various complexities. Therefore, the presented study aims for exploring various readiness factors impacting Gen-AI adoption. With the help of the Technology–Organization–Environment (TOE) theoretical framework, the presented study provided the framework of 14 readiness factors (RF) to support the adoption. The readiness factors including quality control automation, talent availability, data security and governance, ecosystem access were explored using literature review and further confirmed using expert opinion. Also, seven criteria including connectivity, Cloud–Edge Orchestration, Semantic consistency, decentralization were identified. Analytic Hierarchy Process (AHP) was used to compute criteria weights. Then, readiness factors were mapped with seven criteria, and COPRAS method was used to prioritize the readiness factors. The top readiness factors investigated as digital infrastructure, ethical & regulatory preparedness, data readiness quality and maturity, and organizational readiness. In the next step, sensitivity analysis was conducted by changing criteria weights and analyzed that relative ranking of readiness factors remains same. This research results are highly useful for industry managers and practitioners in adopting Gen-AI and opens a revolutionary potential for conducting further research in this direction. |
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