Industry 5.0 technologies to enable innovation in the era of twin transition: A case study on the nexus between SMEs and regulators

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Authors: Roberto Cerchione, Antonio Petruzzelli, Armando Papa, Viviana Sicardi
Cited by: 1
References: 108

Abstract

This article examines how regulators can guide the safe and effective adoption of artificial intelligence (AI), blockchain (BC), and brain computer interfaces (BCI), considered as the pivotal 5.0 human-centric enabling technologies. Although prior research recognises regulators as influential actors within innovation systems, limited empirical evidence explains how regulatory expectations are translated into everyday organisational practices, particularly within resource-constrained small and medium enterprises (SMEs). To address this gap, the study employs an exploratory approach by adopting a qualitative case-study design of an SME currently integrating 5.0 enabling technologies into its operational activities to pursue twin transition. Data were collected through a combination of semi-structured interviews and secondary data to provide an in-depth investigation. The findings were analysed and coded through the lenses of institutional and dynamic capabilities theory. The results show that regulatory actors shape organisational adoption of 5.0 technologies by establishing conditions of stability, directionality, legitimacy, and formation that influence how an SME interprets regulatory signals, structures decision-making routines, and develops human and technological capabilities. By highlighting the formative role of regulation in shaping skills development and governance arrangements, this article contributes to research on regulation and innovation by conceptualising regulators as active participants in the co-construction of human-centric innovation systems. The findings offer theoretical insights into regulation as a decision science and provide practical implications for policymakers seeking to support twin transition in resource-constrained organisational contexts.

Fields of Study & Subjects

Digital Transformation in Industry University-Industry-Government Innovation Models Economic Development and Digital Transformation

Publication details

Journal / source
Technological Forecasting and Social Change
Publisher
Elsevier BV
Volume
230
Pages
124761–124761
Publication date
2 June 2026
Language
EN