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Socio-Technical Adoption Framework for Operator 5.0 Cover
Open Access
|Oct 2026

Abstract

This paper develops and provides an ex-ante evaluation of the Socio-Technical Adoption Framework for Operator 5.0 (STAF-Op 5.0), a multi-level socio-technical construct system that structures adoption conditions and cross-level dependencies for implementing and scaling human-centric manufacturing technologies.

The framework was developed abductively as a structured design artefact and evaluated through structured expert review with manufacturing and Industry 4.0/5.0 specialists, combining content-validity ratings and qualitative feedback to refine constructs, level anchoring, and cross-level relations.

The framework separates socio-technical adoption conditions from staging and assessment routines, clarifies how adoption bottlenecks propagate across organisational levels, and provides a structured basis for managing Operator 5.0 technology deployment in manufacturing systems. Experts confirmed levelled construct relevance and clarity and acknowledged the need for explicit vertical relations to diagnose cross-level constraints that hinder stabilisation and scaling beyond pilot projects.

The framework offers an explicit socio-technical adoption overlay for Operator 5.0 that integrates fragmented Industry 5.0 evidence into a coherent multi-level dependency logic, enabling technology-specific solutions to be managed without reducing adoption to isolated tool selection.

The framework provides a readiness diagnostic checklist across four organisational levels, a sequencing logic that is intended to support identification of cross-level misalignment before scale-up, and a governance structure linking workstation interventions to factory-level data, strategy, and ecosystem conditions. This enables structured management of human-centric manufacturing technologies for Operator 5.0 rather than isolated implementation of solutions.

DOI: https://doi.org/10.2478/emj-2026-0013 | Journal eISSN: 2543-912X (formerly 2300-0813) | Journal ISSN: 2543-6597
Language: English
Page range: 1 - 34
Submitted on: Feb 2, 2026
Accepted on: Aug 1, 2026
Published online: Oct 8, 2026
Published in print: Sep 1, 2026
Published by: Bialystok University of Technology
In partnership with: Paradigm Publishing Services

© 2026 Bartłomiej Gładysz, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.