Exploring capabilities enabled by smart industrial products: a framework for fully autonomous production planning and control
Purpose This study aims to structure and understand the capabilities enabled by smart industrial products (SIPs) within the production planning and control (PPC) function. It seeks to provide a hierarchical framework that supports the strategic integration of SIPs to achieve full autonomy in PPC. Design/methodology/approach A mixed-method approach was applied, combining a systematic literature review (SLR), expert validation, interpretive structural modeling (ISM) and fuzzy cross-impact matrix multiplication applied to classification analysis, and 12 SIP-enabled capabilities were identified, validated and analyzed to reveal their interrelationships and hierarchical structure. Findings The study proposes a four-level framework – connected, transparent, autonomous decision-making I and autonomous decision-making II – that captures the layered buildup of SIP-enabled capabilities toward PPC autonomy. Foundational capabilities enable higher-order capabilities, providing organizations with a roadmap for prioritizing investments and improving operational performance. Originality/value This is the first study to propose a structured, hierarchical model of SIP-enabled capabilities in PPC. It contributes to both theory and practice by clarifying capability dependencies and offering a roadmap for achieving autonomous PPC through targeted SIP adoption.
Authors
- PAULO EDUARDO PISSARDINI (ORCID: https://orcid.org/0000-0002-2179-1572)
- Gilberto Miller Devós Ganga (ORCID: https://orcid.org/0000-0001-9328-5727)
- Mario Henrique Callefi
- Moacir Godinho Filho
- Guilherme Luz Tortorella
- Elias Ribeiro da Silva
Institutions
- The University of Melbourne (AU)
- University of Southern Denmark (DK)
- Chemnitz University of Technology (DE)
- Industrial Solar (Germany) (DE)
- Decision Sciences (United States) (US)
- Universidade Estadual do Amapá (BR)
Publication Details
- Journal
- Journal of Enterprise Information Management
- Published
- 2026-02-14
- DOI
- https://doi.org/10.1108/jeim-06-2025-0531
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00