Mukha Taras, Postgraduate student, Department of management, Banking and Insurance, Kharkiv National Automobile and Highway University, Kharkiv, Ukraine

ORCID: 0009-0008-9282-6833
e-mail: hammers.plant@gmail.com

Industry 4.0 in Logistics Process Management: a Model for Building Supply Chain Digital Dynamic Capabilities

Abstract. Introduction. This paper examines how Industry 4.0 digital solutions, such as cloud computing, software as a service (SaaS) applications, process mining and digital twins, can be used to redesign logistics process management and improve supply chain performance from a capability-based perspective. The focus is on digital dynamic capabilities (DDCs), which are a set of routines that enable firms to identify process deviations, recognise improvement opportunities and reconfigure logistics processes within a digitally integrated supply chain.

Purpose. The aim is to develop and justify the DDC-AAA model, which operationalises the formation of DDCs and explains their effect on logistics adaptability and alignment, as well as on measurable results, including service level, lead time, cost efficiency, and sustainability-related KPIs. The study bridges the gap between the adoption of digital technology and capability-based performance improvement.

Results. The study proposes the following: (1) a conceptual DDC-AAA framework that links digital instruments (e.g. cloud platforms, software as a service modules, digital twin modelling and process mining) with the microfoundations of DDC; (2) an indicator system that measures DDC and AAA metrics across sensing, seizing and transforming routines; (3) an alignment matrix that maps coordination mechanisms onto governance levels and digital enablers at strategic, tactical and operational levels; and (4) a forecasting model that translates the DDC index, together with adaptability and alignment metrics, into the expected changes to key logistics KPIs under various scenarios. The results emphasise that the economic effect of digitalisation is not automatic; it depends on the maturity of governance routines, data quality, and inter-organisational agreements.

Conclusions. This research formalises the process by which service-modular digital solutions and cloud-based integration can be converted into dynamic capabilities that enhance adaptability and alignment in logistics. It also offers a practical roadmap for staged capability development and KPI-based monitoring. The proposed model can be used to diagnose, benchmark and evaluate transformation alternatives in supply chains operating under instability.

Keywords: digital dynamic capabilities; Industry 4.0; cloud platforms; SaaS; digital twin; process mining; adaptability; alignment.

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