Computer support to procedures for assessing the impact of big-scale railway projects on public performance indicators

The article substantiates the need to take into account the uncertainty factor when evaluating large-scale railway projects. An algorithm for evaluating the accounting of the uncertainty factor is proposed, which is fundamentally different from the hierarchy analysis method by T. Saati, the disadvantages of this method are highlighted, and the author's method is proposed. We show that the effects of large-scale projects affect economic development itself. Therefore, the article demonstrates the necessity to evaluate projects in conjunction with the economic scenario. We evaluate three different mainlines (Lensk-Kamchatka Mainline, Transpolar Mainline and the mainline connecting the mainland and Sakhalin Island) under three scenarios of possible project environment. We suggest using three levels of assessment for large-scale railway projects consecutively: macro-level, meso-level, and micro-level. This classification allows to gradually reduce the level of uncertainty. Thus, the information obtained at the previous assessment level becomes the input for the following level. Each of the assessment levels is accompanied by appropriate software. The article provides a brief description of the functionality and the need to use appropriate software products as the stages of large-scale projects progress from their conception to implementation.