Proceedings of the International Conference on Operations & Supply Chain Management 2025 (ICOSCM 2025)

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AI-Powered Text Mining for Strategic Knowledge Visioning and Innovation Management

Authors
Vimal Kumar1, Rishab Manekar1, Sahilali Saiyed2, Pratima Verma3, *, Sandeep Kumar Gupta4
1Department of Information Management, Chaoyang University of Technology, Taichung, Taiwan
2Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan
3Strategic Management Area, Indian Institute of Management Kozhikode, Kozhikode, India
4Symbiosis Institute of Operations Management, Symbiosis International (Deemed University), Pune, India
*Corresponding author. Email: Way2pratima@gmail.com
Corresponding Author
Pratima Verma
Available Online 24 December 2025.
DOI
10.2991/978-94-6463-914-8_18How to use a DOI?
Keywords
Artificial Intelligence; Text Mining; Innovation Management; Knowledge Visioning; Sustainable Competitive Advantage
Abstract

In today’s data-driven economy, strategic knowledge visioning is critical for fostering innovation and sustaining competitive advantage. This paper explores how artificial intelligence (AI)-enabled text mining of secondary data sources such as patents, academic publications, and business reports can enhance innovation management. Leveraging natural language processing techniques, including keyword extraction, semantic clustering, and trend forecasting, the study identifies emerging technological domains and innovation hotspots relevant to sustainable industrial management. The analysis uncovers knowledge gaps and future opportunities that organizations can integrate into research and development roadmaps. By mapping innovation landscapes using machine learning-based text analytics, businesses can anticipate market shifts, align technological capabilities with sustainability goals, and proactively manage innovation pipelines. The research contributes a scalable AI-driven framework for evidence-based strategic planning, enabling organizations to make informed decisions on technology adoption, resource allocation, and sustainability-focused innovation strategies.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Operations & Supply Chain Management 2025 (ICOSCM 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
24 December 2025
ISBN
978-94-6463-914-8
ISSN
2352-5428
DOI
10.2991/978-94-6463-914-8_18How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Vimal Kumar
AU  - Rishab Manekar
AU  - Sahilali Saiyed
AU  - Pratima Verma
AU  - Sandeep Kumar Gupta
PY  - 2025
DA  - 2025/12/24
TI  - AI-Powered Text Mining for Strategic Knowledge Visioning and Innovation Management
BT  - Proceedings of the International Conference on Operations & Supply Chain Management 2025 (ICOSCM 2025)
PB  - Atlantis Press
SP  - 271
EP  - 277
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-914-8_18
DO  - 10.2991/978-94-6463-914-8_18
ID  - Kumar2025
ER  -