Title | An integrated SEM-ANN approach for predicting QMS achievements in Industry 4.0 |
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ID_Doc | 67359 |
Authors | Milosevic, I; Ruso, J; Glogovac, M; Arsic, S; Rakic, A |
Title | An integrated SEM-ANN approach for predicting QMS achievements in Industry 4.0 |
Year | 2022 |
Published | Total Quality Management & Business Excellence, 33, 15-16 |
Abstract | Industry 4.0 brings a revolution in using information and communication technologies within business activities. As such, Industry 4.0 enables important space for quality-related improvements but requires a sustained quality management system (QMS). The aim of this study is to predict the influence of ISO 9004:2018 QMS elements on Improvement, Learning, and Innovation achievements in Industry 4.0 using the SEM-ANN approach. The survey included 345 domestic and international companies of different types operating in Serbia. Conclusions demonstrate a direct positive influence between observed constructs (Leadership, Process Management, Resource Management, Performance Management) and Improvement, Learning, and Innovation. Only the Context and Identity of the organisation has a negative direction drawn from SEM analysis. Further, ANN verified SEM results, pointing out that all observed variables are seen as predictors of Improvement, Learning, and Innovation. The importance level corresponds to those elements' SEM ranking. The paper could provide a roadmap towards achieving sustainable results in quality improvement, learning, and innovation in Industry 4.0 era. |