A textometric analysis of Quality 4.0 research

Purpose This study aims to provide a comprehensive, textometric analysis of the evolving Quality 4.0 (Q4.0) research, identifying key themes, emerging trends and critical research gaps in the field. Design/methodology/approach A total of 129 peer-reviewed articles on Q4.0 were analyzed using IRAMUTEQ software. The textometric approach employed includes lexicographic analysis, descending hierarchical classification, factorial correspondence analysis and similarity analysis to uncover underlying patterns in the literature. Findings Three major clusters emerged from the analysis of Q4.0 research: (1) the digital transformation of quality management practices, (2) technological enablers of Q4.0 and (3) organizational implications of Q4.0 adoption. Key themes identified include the integration of Industry 4.0 technologies (e.g. IoT, AI and big data) into traditional quality management systems, the role of artificial intelligence in quality control and the challenges organizations face during Q4.0 implementation. This research also conceptualizes a comprehensive framework that outlines a strategic roadmap for Q4.0 adoption and integration, including the identification of antecedents and consequences of Q4.0 implementation. Additionally, the study proposes a measurement scale for assessing the dimensions of Q4.0. Practical implications The research proposes valuable implications for practitioners and organizations seeking to implement Q4.0 strategies as well as for researchers in the field of digital transformation and quality management. The proposed conceptual framework serves as a practical guide for effectively navigating Q4.0 implementation in diverse organizational contexts. Originality/value This study presents an innovative approach by applying textometric analysis to the field of Q4.0, offering an objective, data-driven perspective on the existing literature. It identifies significant gaps in research and proposes future avenues for investigation. As one of the first studies to develop a conceptual framework for Q4.0, including its antecedents, consequences and a measurement scale, this research provides a foundational contribution to the growing body of knowledge on Q4.0.