Decision configurations driving industry 4.0 technology prioritisation: evidence from Australian plastics manufacturing SMEs
Rattachement africain : au. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Plastics manufacturing is often scrutinised for its environmental impact, but has significant potential to benefit from Industry 4.0 (I4.0) technologies. However, generic I4.0 adoption models overlook industry and technology-specific factors, causing resource-constrained plastics SMEs uncertain about how to prioritise technology investments. This study thus examines technology prioritisation decisions using data collected from 28 Australian plastics manufacturing SMEs between November 2024 and May 2025. A sequential mixed-methods approach was employed, combining Relative Importance Index (RII) analysis with fuzzy-set Qualitative Comparative Analysis (fsQCA). The RII analysis identified 18 decision criteria and eight priority I4.0 technologies. The fsQCA results revealed that a common configuration comprising technological infrastructure, technological integration, reliability, compatibility, relative advantage, and data security underpins the prioritisation of most technologies. However, simulation exhibited a distinct pathway in which reliability, ease of use, and compatibility compensated for the absence of broader technological readiness, suggesting a more modular and user-centric route to digitalisation. Environmental factors played a limited role, with competitive pressure and collaboration emerging as decisive only for machine-to-machine communication prioritisation. The findings demonstrate that technology prioritisation is driven by multiple equifinal pathways rather than universal antecedents and that the importance of decision criteria varies across technologies. Theoretically, the study develops a bounded configurational perspective of pre-adoption technology prioritisation by integrating the Technology–Organisation–Environment framework with insights from the Resource-Based View, Dynamic Capabilities Theory, and Technology Acceptance Model within a TOE-Cost(C) framework. Practically, the findings provide SMEs and industry stakeholders with actionable guidance for prioritising I4.0 investments for strengthening digital capabilities.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Decision configurations driving industry 4.0 technology prioritisation: evidence from Australian plastics manufacturing SMEs
- Date Crossref
- 21/08/2026
- Éditeur
- Informa UK Limited
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Les institutions déclarées
Une affiliation ne permet pas de déduire la nationalité d’un auteur.