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Region: Economics and Sociology

2023 year, number 4

INTERREGIONAL LARGE-SCALE RAILWAY PROJECTS: ASSESSING THE COMPARATIVE EFFICIENCY OF PROJECT ALTERNATIVES

S.A. Bykadorov1, E.B. Kibalov2
1Siberian Transport University, Novosibirsk, Russia
2Institute of Economics and Industrial Engineering, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
Keywords: interregional large-scale projects, Barentskomur, Severosib, uncertainty, social performance, goal tree, evaluation structure, decision theory criteria, software products

Abstract

This article analyzes two large-scale railway projects, namely, Barentskomur and Severosib, both of which have been under discussion for nearly a century regarding their feasibility. The uncertainty surrounding the outcomes and costs of these north-south megaprojects holds significant strategic implications for Russia. Moreover, in the long run, it may exert an ambiguous impact on social performance. While existing methodologies associate uncertainty with varying degrees of risk and in justifying the design suggest a set of measures to mitigate these risks, both probabilistic and improbable, this article introduces an alternative perspective. Here, we examine the factor of uncertainty in terms of opportunities it presents for the future, adopting a constructive approach. To address the emerging challenges, we employ the tools of neo-system analysis as developed by J. Kornai and G. B. Kleiner. Neo-system analysis, in this context, refers to the creation of a multidimensional future using a comprehensive system for evaluating large-scale projects, supplemented by information and expert technologies. We demonstrate how a suite of domestic software products, originating from the Institute of Economics and Industrial Engineering within the Siberian Branch of the Russian Academy of Sciences and the Siberian Transport University, expands the capabilities of expert methodologies. These tools are invaluable for providing recommendations to decision-makers who deal with intricate investment decisions under conditions of risk and uncertainty.