Technoeconomics

UNK RUS 4-5 57212553616 0000-0003-2981-0624 Peter the Great St.Petersburg Polytechnic University Ilin Igor

Saint Petersburg, Russia

Editor's note editor's note https://technoeconomics.spbstu.ru/article/2026.17.1/ 0_4_editorial.pdf

UNK RUS 6-19 Peter the Great St.Petersburg Polytechnic University Vasileva Yana

Saint Petersburg, Russia

Peter the Great St.Petersburg Polytechnic University Sheleyko Viktoria

Saint Petersburg, Russia

Application of the Multi-Criteria Analysis Method to Optimize the Selection of Students for International Exchange Programs This article provides a comprehensive analysis and subsequent optimization of the activities of the International Office operating in the structure of one of the institutes of Peter the Great St. Petersburg Polytechnic University. The relevance of the research is due to the need to increase the effectiveness of the selection of candidates for international academic programs in the face of increasing competition and stricter requirements for the quality of training of participants. The IDEF0 functional modeling methodology was chosen as the main research tool which made it possible to describe and structure the current business processes of the department in detail, fixing their AS-IS state. The analysis of the constructed models revealed a number of systemic problems and "bottlenecks" related to the subjectivity of decision-making and the lack of formalized criteria for evaluating applicants. The logical solution to eliminate the identified shortcomings was the development of a multi-criteria analysis model which formed the basis for creating improved processes in the "as it should be" state. In the practical part of the study, a system of evaluation criteria and corresponding weighting coefficients reflecting the university's priorities was elaborated in detail. The approbation of the developed model based on the hypothetical data of the students confirmed its efficiency, objectivity and practical significance for improving the quality of selection. The final conclusions substantiate the prospects and the possibility of further scaling the proposed model for the needs of other structural divisions of the university and similar organizations. 10.57809/2026.5.2.17.1 378.4 unified university identity interdisciplinary enrichment business process modeling IDEF0 notation bottlenecks multicriteria analysis methods correction factor https://technoeconomics.spbstu.ru/article/2026.17.2/ 1_vasileva_sheleiko.pdf

UNK RUS 20-30 Peter the Great St.Petersburg Polytechnic University Krasnov Valery

Saint Petersburg, Russia

Peter the Great St.Petersburg Polytechnic University Tsmugunov Nikita

Saint Petersburg, Russia

Intelligent Agents Based on Large Language Models in Transport Management: A Comparative Analysis of Approaches to Development and Implementation The paper addresses the “information gap” between objective telemetry data and primary documentation in logistics and road construction, which arises from the growing volume of unstructured information and a shortage of qualified personnel. Two projects aimed at creating intelligent agents to bridge this gap in transport management are examined. Based on a comparative analysis of two implemented solutions, the study identifies common architectural principles. The first project (technical proposal stage) develops an AI‑powered dispatcher assistant that automatically collects and matches requests from external channels with an internal TMS system via deep API integration. The second project (working prototype) implements a workflow on the low‑code n8n platform that extracts, normalises, and compares GLONASS PDF data with accounting records. Both agents share a unified five‑stage cognitive agent model and a hybrid architecture combining a large language model with deterministic logic. The two solutions differ fundamentally in their integration paradigm: deep API integration versus low‑code assembly. This difference determines development speed, total cost of ownership, and scalability. The low‑code prototype achieves a payback period of less than one month, while deep integration offers greater customisation and ERP connectivity at significantly higher initial cost. Criteria for selecting an architectural approach are formulated based on the maturity of a company’s IT landscape. These criteria enable a strategic choice between deep integration and low‑code development depending on business priorities, infrastructure readiness, and available resources. 10.57809/2026.5.2.17.2 330.47 intelligent agents large language models operational efficiency logistics road construction low-code platforms dispatch management transportation auditing digital divide https://technoeconomics.spbstu.ru/article/2026.17.3/ 2_krasnov_tsmugunov.pdf

UNK RUS 31-46 Moscow Financial and Industrial University "Synergy" Kislyuk Lev

Moscow, Russia

Endogenous Token Supply Stability in Algorithmic Blockchain Protocols Three flows govern token supply in blockchain protocols: issuance, burning, and staking lock-ups. We study this supply adjustment mechanism in isolation from price dynamics, treating market returns and on-chain activity as predetermined observables. This design permits analytical examination of supply-side feedbacks without modeling price endogeneity. A representative staker's utility maximization problem yields an equilibrium staking function with a linearly decreasing dependence on market return. From this microeconomic foundation we derive a first-order ordinary differential equation (ODE) for circulating supply with endogenous feedbacks from all three supply channels. 10.57809/2026.5.2.17.3 330.47 tokenomics blockchain circulating supply staking stability analysis Lyapunov function stochastic differential equation Ethereum EIP-1559 algorithmic monetary policy https://technoeconomics.spbstu.ru/article/2026.17.4/ 3_kisluk.pdf

UNK RUS 47-59 Peter the Great St.Petersburg Polytechnic University Yakovleva Alena

Saint Petersburg, Russia

Comparison of NIST Cybersecurity Framework Patterns and the Requirements of Federal Service For Technical and Export Control (FSTEC) Order No. 31: Compliance Matrices and Integration Methodology This study focuses on two of the most significant documents in the field of information security: the international standard NIST Cybersecurity Framework version 2.0 and the Russian regulatory act, FSTEC Order No. 31. The subject of the study is the conceptual and structural relationships between the NIST CSF functions and the groups of information security measures established by Order No. 31. The methodological basis consists of a comparative analysis of the original texts of the documents, Positive Technologies comparison tables, and the TOGAF architectural design methodology. The study resulted in the development of a correspondence matrix comparing 17 groups of measures from Order No. 31 with six functions of the NIST CSF 2.0 core. It was found that coverage of CSF functions by the Order's measures varies from 40-60% for class K3 to 95-100% for class K1, while the Govern function has no direct equivalent in the Russian document. A gap analysis methodology is proposed, allowing organizations to identify missing security measures when integrating the two approaches. Practical recommendations for prioritizing protective measures based on a risk-based approach have been developed. The results can be used in designing information security architectures for organizations working with critical information infrastructure and government information systems. 10.57809/2026.5.2.17.4 330.47 NIST Cybersecurity Framework 2.0 FSTEC Order 31 information security risk management standards integration cybersecurity patterns business architecture critical information infrastructure government information systems information security https://technoeconomics.spbstu.ru/article/2026.17.5/ 4_yakovleva.pdf

UNK RUS 60-71 South Ural State University Liu Qinqin

Chelyabinsk, Russia

Architecture and Mathematical Apparatus of Decision-Support System for Marketplace Sellers The growth of online marketplaces as multi-sided digital platforms has created a decision-making environment for sellers that differs fundamentally from traditional retail, combining a richer behavioral data trace with a narrower set of controllable parameters. This study addresses the resulting gap between the volume of available behavioral data and the absence of an integrated decision support architecture that connects this data to the several distinct types of decisions a seller must make. The aim of the study is to develop an enterprise-architecture model, in the ArchiMate notation, of a decision support system (DSS) for marketplace sellers, together with the mathematical models underlying its analytical and decision-support modules. The study applies methods of systematic literature analysis, enterprise architecture modeling, and mathematical modeling, including discrete-time hazard models and the Kolmogorov-Gabor polynomial. The resulting architecture comprises Businessand Application-layer ArchiMate models spanning four seller roles and four decision scenarios, supported by a shared analytical pipeline and explicit integration with the marketplace platform and external market-data providers. The proposed architecture and mathematical apparatus can be used as a reference design for information systems supporting marketplace sellers and as a basis for further empirical validation. 10.57809/2026.5.2.17.5 330.47 decision support system enterprise architecture ArchiMate marketplace consumer behavior Kolmogorov–Gabor polynomial discrete-time hazard model recommender system https://technoeconomics.spbstu.ru/article/2026.17.6/ 5_liu_qinqin.pdf

UNK RUS 72-85 Peter the Great St.Petersburg Polytechnic University Osipov Gleb

Saint Petersburg, Russia

Patient Data Management In A Commercial Clinic: Audit, Segmentation, And Data Strategy This article examines data management methods in a commercial medical organization. Based on an audit of the information infrastructure of a multidisciplinary clinic, the study describes procedures for patient data profiling and deduplication, develops a KPI system using the Balanced Scorecard methodology, constructs an RFM segmentation model to identify patients at high risk of churn, and proposes a phased data strategy for transitioning toward data-driven management. The paper also provides a systematic review of Data Governance frameworks and digital transformation practices in healthcare, contextualizing the clinic-level findings within broader trends in health data management. 10.57809/2026.5.2.17.6 004.89:614 data management Data Governance data audit data profiling deduplication ETL RFM segmentation patient churn KPI Balanced Scorecard digital transformation healthcare analytics https://technoeconomics.spbstu.ru/article/2026.17.7/ 6_osipov.pdf