A semiotics-informed conceptual maturity model for industrial IoT integration
Purpose This study aims to develop a descriptive maturity model for evaluating the integration of IIoT technologies within enterprise environments. Although IIoT enables data-driven and automated operations, integration remains complex because of technological and organisational interdependencies. Existing models lack conceptual consistency and provide limited insight into operational integration. The study therefore proposes a theory-informed maturity model, specifically focused on IIoT integration into business operations. Design/methodology/approach The study uses a maturity model development methodology guided by design science research. It draws on literature-based insights to develop the initial model components and applies a theoretical foundation to interpret and structure the model dimensions. The model was then evaluated and refined through two design cycles involving expert interviews. Findings The maturity model comprises four dimensions: physical object, data, process and business service, organised and interpreted using the Semiotic Ladder and five maturity levels: pre-pilot, pilot, operational, organisation-scale and ecosystem-scale. It also identifies the key capabilities required to effectively integrate IIoT into business operations. Originality/value This study develops a theory-informed maturity model based on the semiotic ladder of organisational semiotics, offering a novel semiotics-based perspective for conceptualising and assessing IIoT maturity. It explicitly focuses on the integration of IIoT into business operations, emphasising the key dimensions required to support this integration.
Authors
- Wasana Bandara (ORCID: https://orcid.org/0000-0003-2785-7859)
- Alireza Nili (ORCID: https://orcid.org/0000-0003-1183-7626)
- Alistair Barros
- Kevin C. Desouza
- Himashi Sandamini Widana Kankanamge (ORCID: https://orcid.org/0009-0003-1506-5640)
Institutions
- Queensland University of Technology (AU)
Publication Details
- Journal
- Journal of Enterprise Information Management
- Published
- 2026-09-10
- DOI
- https://doi.org/10.1108/jeim-11-2025-1147
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00