Big Data Analytics Integration in ISO 9001:2015 Quality Management Systems: A Dual-Method Systematic and Bibliometric Analysis

DOI

10.2991/978-94-6239-754-5_7How to use a DOI?

Keywords

Big Data Analytics; ISO 9001:2015; Quality Management Systems; Bibliometric Analysis; Systematic Literature Review

Abstract

The integration of Big Data analytics and artificial intelligence into ISO 9001:2015 quality management systems (QMS) has emerged as a defining imperative in Quality 4.0 manufacturing transformation, yet the evidence base underpinning this integration remains fragmented and critically incomplete. This study systematically maps and evaluates 142 peer-reviewed articles published between 2021 and 2026 through an integrated Systematic Literature and bibliometric Network Analysis (SLNA), combining PRISMA-compliant evidence synthesis with VOSviewer-based keyword co-occurrence and temporal overlay analysis. Findings reveal an accelerating publication trajectory, with 39.4% of studies appearing in 2025 alone, dominated by artificial intelligence and machine learning implementations (71.1%) and Big Data analytics platforms (54.2%). However, a critical Technology-QMS integration gap is identified: only 2.1% of studies explicitly addressed ISO 9001:2015 integration requirements--a 34:1 disparity relative to AI/ML coverage (71.1%). Critically, no study measured OEE as a composite metric, and only 2.1% reported OEE-component metrics; merely 5.6% assessed customer satisfaction within a formal QMS context. Bibliometric cluster analysis identified five thematic research clusters with 89% cross-method convergence, confirming the robustness of identified gaps. Synthesising available evidence, this study proposes the BD-QMS Transformation Model--a five-layer framework (Foundation - > Integration - > Intelligence - > Optimisation - > Evolution) validated through expert consensus (92% agreement, n = 12). The BD-QMS Model and the identified five-gap research agenda provide a structured foundation for the next generation of empirical studies directly measuring ISO 9001:2015 quality outcomes in digitally transformed manufacturing environments.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits any noncommercial use, sharing, 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 you modified the licensed material. You do not have permission under this license to share adapted material derived from this chapter or parts of it.

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TY  - CONF
AU  - Yosep Hernawan
AU  - Dian Addinna
AU  - Gilang Garnadi Suryadi
AU  - Rasto
PY  - 2026
DA  - 2026/09/02
TI  - Big Data Analytics Integration in ISO 9001:2015 Quality Management Systems: A Dual-Method Systematic and Bibliometric Analysis
BT  - Proceedings of the International Conference on Digital Transformation in Business and Organisations (ICDTBO 2026)
PB  - Atlantis Press
SP  - 69
EP  - 80
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-754-5_7
DO  - 10.2991/978-94-6239-754-5_7
ID  - Hernawan2026
ER  -