Innovation portfolio selection model for the development of digitalizing industrial enterprises

Abstract

In the context of industrial digital transformation, innovation development is no longer a linear process but becomes a dynamic capability of enterprises to strategically adapt, learn, and evolve. This shift requires not only the deployment of digital technologies but also a fundamental rethinking of managerial approaches, decision-making structures, and internal mechanisms for knowledge accumulation. At the same time, due to limited resources and low R&D intensity in the Ukrainian economy, firms often face significant uncertainty when making innovation-related decisions and lack structured methodologies to guide them. Existing theoretical literature emphasizes the importance of organizational learning [3, 5], digital readiness [4], innovation portfolio management [6], and the capacity to absorb and apply external knowledge over time. These factors highlight the need for tailored decision-support tools that not only assess individual initiatives but also shape coherent innovation portfolios aligned with long-term strategic goals.

To solve this problem, the author’s Decision Support Model for Innovation Development (DSM-ID) is introduced. The methodology integrates digital transformation logic, enterprise readiness diagnostics, multi-criteria evaluation, and portfolio-based decision-making. The methodology consists of the following core components: (1) assessment of digital and organizational readiness, (2) construction of a strategic development trajectory, (3) initiative evaluation based on five criteria – transformational effect, internal capability gain, economic feasibility, implementation risk, and digital readiness match, (4) formation of a balanced innovation portfolio, and (5) incorporation of data-driven learning mechanisms. The methodology is illustrated using a scenario involving a representative Ukrainian machine-building enterprise with a limited investment budget and moderate digital maturity. The findings suggest that a strategy combining short-term economic gains with investments in digital infrastructure can effectively support both immediate performance and long-term innovation transformation. The study opens avenues for further empirical research, particularly in validating evaluation criteria, tailoring the methodology to different industries, and enhancing performance indicators.