MODELLING DIGITAL MANAGEMENT PERFORMANCE OF ENTERPRISE INVESTMENT PROJECTS
DOI:
https://doi.org/10.32999/ksu2307-8030/2026-60-6Keywords:
digital management, investment project, digital manageability, econometric modelling, project performance, digital investmentAbstract
The article develops a methodological framework for quantitatively assessing the digital performance of enterprise investment project management. The proposed approach shifts the analytical focus from the general level of enterprise digitalization to the digital manageability of individual investment projects. An original Digital Investment Project Management Index (DIPMI) is introduced, integrating seven components: digital planning, project data integration, automated monitoring, predictive analytics, digital risk management, decision automation, and digital integration of project participants. Component weights are determined through a modified entropy-based procedure, while an exponential asymmetry correction factor captures structural imbalances among digital management components. Project outcomes are measured using the Investment Project Performance Index (IPPI), combining investment returns, budget compliance, schedule performance, target achievement, and residual risk. The Digital Management Impact Model (DMIM) is developed to estimate the relationship between digital manageability and investment project performance. The model incorporates investment scale, project complexity, uncertainty, project team experience, interaction effects, and nonlinear digital returns. The computational results indicate diminishing marginal returns from digitalization after projects reach relatively high DIPMI levels. The Digital Management Performance Gap (DMPG) is proposed to estimate the performance reserve associated with transition from the current digital configuration to an economically justified target level. The Marginal Digital Investment Efficiency (MDIE) indicator is additionally introduced to measure the return generated by incremental digital investment. The proposed analytical framework supports quantitative comparison of alternative digital configurations, identification of project-level performance reserves, prioritization of digital transformation initiatives, and allocation of limited digital investment budgets across enterprise investment projects.
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