Comprehensive Research on the Multi-Scenario Application and Evolutionary Trajectory of Advanced Data Mining Techniques in Contemporary Corporate Governance: A Systematic Literature Review

DOI

10.2991/978-94-6239-787-3_63How to use a DOI?

Keywords

Data Mining; Machine Learning; Corporate Governance; Decision Support Systems; Explainable Artificial Intelligence

Abstract

Driven by the rapid development of the digital economy and intelligent technologies, enterprises have accumulated massive volumes of heterogeneous data, making data mining a critical tool for data-driven decision-making and digital transformation. This paper adopts a systematic literature review approach to examine the evolution of data mining research and analyze four major categories of techniques: classification, clustering, association rule mining, and deep learning. Furthermore, it reviews the application of data mining across key corporate management functions, including customer relationship management, financial risk management, human resource analytics, supply chain optimization, and strategic decision support. The findings indicate that data mining significantly enhances customer segmentation, risk prediction, demand forecasting, and resource allocation efficiency. Despite these benefits, challenges related to data integration, model interpretability, and privacy protection remain significant barriers to broader adoption. Therefore, future research should focus on hybrid algorithm development, explainable artificial intelligence (XAI), and multi-source data integration. This study provides a comprehensive overview of current research progress and offers practical insights for organizations seeking to improve intelligent decision-making and corporate governance through advanced data mining technologies.

Copyright

© 2026 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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TY  - CONF
AU  - Xinyi Wei
PY  - 2026
DA  - 2026/09/29
TI  - Comprehensive Research on the Multi-Scenario Application and Evolutionary Trajectory of Advanced Data Mining Techniques in Contemporary Corporate Governance: A Systematic Literature Review
BT  - Proceedings of the 2026 4th International Conference on Management Innovation and Economy Development (MIED 2026)
PB  - Atlantis Press
SP  - 624
EP  - 632
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-787-3_63
DO  - 10.2991/978-94-6239-787-3_63
ID  - Wei2026
ER  -