Research ArticleJournal of Scientometric ResearchVol. 13 | Issue 3 | 2024 | pp. 791–805Open access
Unveiling the Evolution of Big Data Analytics Capability: A Comprehensive Analysis
- 1*,
- 2,
- 2
- 1 NMIMS Centre for Distance and Online Education, SVKM NMIMS, Mumbai, Maharashtra, INDIA.
- 2 Information Technology and Systems Area, Indian Institute of Management Kashipur, Kashipur, Uttarakhand, INDIA.
Published in Journal of Scientometric Research
Correspondence: Sunil Pathak
NMIMS Centre for Distance and Online Education, SVKM NMIMS, Mumbai, Maharashtra, INDIA.
Email: sunil.pathak.web@gmail.com
Copyright: © 2024 Manuscript Technomedia. This is an open access article.
- Published:
- Nov 27, 2024
- Received:
- Jan 6, 2024
- Accepted:
- Aug 2, 2024
How to cite
Pathak, S., Krishnaswamy, V., & Sharma, M. (2024). Unveiling the Evolution of Big Data Analytics Capability: A Comprehensive Analysis. Journal of Scientometric Research, 13(3), 791–805. https://doi.org/10.5530/jscires.20041105
Abstract
This paper performs a state-of-the-art literature review of Big Data Analytics Capability (BDAC) to analyze its domain, knowledge structures, theoretical roots, and key research trends. We analyze the domain, knowledge structures, and evolution of the field by applying Lotka’s law, Bradford law, MCP ratio, keyword, citation, and co-citation analysis. Our analysis reveals predominant use of resource-based view and dynamic capability theories among other theories used in BDAC research. The key research themes identified relate to BDAC antecedents, consequences, process/ industry contexts, business intelligence, advanced analytics, and environment dynamics. The study’s implications pertain to the identification of BDAC development, its theoretical roots, and emerging research themes. We also identify interesting research opportunities relating to BDAC as a dynamic capability, BDAC challenges such as failures, maturity, response to market dynamics, and BDAC value at process, firm, and industry levels.
Keywords
Subject
Article metadata
| Title | Unveiling the Evolution of Big Data Analytics Capability: A Comprehensive Analysis |
|---|---|
| Authors | Sunil Pathak; Venkataraghavan Krishnaswamy; Mayank Sharma |
| Affiliations | NMIMS Centre for Distance and Online Education, SVKM NMIMS, Mumbai, Maharashtra, INDIA.; Information Technology and Systems Area, Indian Institute of Management Kashipur, Kashipur, Uttarakhand, INDIA. |
| Corresponding author | sunil.pathak.web@gmail.com |
| Journal | Journal of Scientometric Research |
| Volume / Issue | Vol. 13, Issue 3 (2024) |
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- ChatGPT Research: Insights from Early Studies Using Network Scientometric Approachpp. 688–705
- Bibliographic Coupling and Conceptual Similarity: Are the Bibliographically Coupled Papers also Conceptually Similar?pp. 706–714
- Exploring the Publication Metadata Fields in Web of Science, Scopus and Dimensions: Possibilities and Ease of doing Scientometric Analysispp. 715–731
- A Systematic Review of Reverse Logistics Research: Bibliometric Study of the Years 2013-2023pp. 732–744
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