Ses Model and its Practical Application

Bobojonova Zarnigor Shokirovna

doi:10.51699/cajitmf.v7i2.1228

Authors

Bobojonova Zarnigor Shokirovna I.F.F.D. Associate professor, TATU.

DOI:

https://doi.org/10.51699/cajitmf.v7i2.1228

Keywords:

Singular applied economic efficiency (SES) model, railway transport, digital transformation, Lagrange optimization, digital accessibility, nonlinear economic dynamics, Uzbekistan Railways, applied economics, digitalization elasticity

Abstract

According to market growth projections, the global digital railway market will grow from USD 82.76 billion in 2025 to USD 127.54 billion by 2030, compelling railway enterprises to shift from linear management models to data-driven governing frameworks. Meceda and Vonortas (2018) conceptualized the singular economy as the intersection of virtual and physical economies, while Brynjolfsson and McAfee (2014) recognized that economic efficiency is increasingly determined by information rather than traditional production factors. Nonetheless, these theoretical frameworks had not been integrated within a single econometric model; cross-country analysis of railway digitalization in the context of Central Asia remained rare; and linear models are often insufficient for exploring the nonlinear dynamics characteristic of the digital transformation of transport systems. Using Lagrange optimization, followed by multiple regression analysis to validate the model against data from JSC "Uzbekistan Railways", the study proposes, develops, and confirms a Singular Applied Economic Efficiency model (SES = Y·Dα·Iβ / X(1–A)γ). Applying Lagrange optimization, the equilibrium condition is derived as D = α(1–A)/γ, confirming that digitalization and automation are inversely proportional. Empirical analysis reveals that the SES index is strongly correlated with the international freight share (r = 0.8698), while digitalized business processes and automation also demonstrate a high correlation (r = 0.9671). Implementation can lead to a 1.2% decrease in operational expenditure and can leverage USD 1.1 billion through PPP-based investments. The SES model represents the first empirically tested synthesis of economics sub-disciplines applied to railway transportation. The results provide railway companies in developing economies with a structured approach to measuring economic efficiency through the integration of digital, informational, and human resources, while future research should extend the model into a panel data cross-country framework and incorporate ESG dimensions.

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