This paper addresses the problem of estimating passenger demand for flights, with a particular focus on the necessity of developing precise forecasts that incorporate intricate and interdependent variables for effective resource planning within the air transport industry. The present paper focuses on the development of a model for medium-term flight demand estimation by flight destinations. This is based on the analysis of historical airline data on dates, departure times, and passenger demand, as well as the consideration of the influence of macroeconomic indicators, namely gross regional product (GRP), median per capita income, and population of departure and arrival points. This paper reviews international experience in the development of demand forecasting models and their use for resource planning in the industry. The developed model was evaluated using historical data on demand for a single turnaround flight operated by an airline. The developed model allows for the forecasting of the distribution of potential demand for airline flight destinations in the medium term, utilizing comprehensive historical data on departure times and flight demand by destination.

This study aimed to comprehensively examine the interactions between actors within the innovation system, focusing specifically on the disposition and utilization of intellectual property rights (IPRs). In order to achieve the stated objective, mathematical modeling, rooted in game theory was adopted to simulate these interactions to identify strategically stable behaviors among stakeholders. Essentially, the study led to the development of a game-theoretic model that described the interaction between IPR holders alongside respective followers. This model effectively considered the impact of public policy on IP protection as a factor in offense detection. The analysis conducted during the course of the investigation thoroughly examined various strategies for protecting IP, including the registration of utility model and invention patents as well as the use of smart contracts for IP registration. Within this context, the use of a smart contract, which is defined as a self-executing contract implemented in the blockchain, where respective terms and conditions are fixed by the parties directly through lines of code, was considered as an alternative strategy for protecting IP. Followers, on the other hand, were observed to adopt a spectrum of strategies, ranging from the acquisition of a license for the legitimate use of IP to imitating innovative processes. For each strategic pathway, a utility function was specified in order to account for innovation profits and costs. The values assigned to the components of these utility functions in line with the existing legislation governing patents in the Russian Federation for 2024. The results obtained from the investigation of the static model, which was specifically carried out to identify the equilibrium, showed that, with regard to the probability of detecting offenses and the amount of penalty, followers adopted different strategies depending on the level of supervision. For instance, when the level of supervision is low or medium, followers were observed to predominantly imitate innovations, and when it is high, the demographic tend to posseess a greater tendency to acquire a license. When supervision is average, the subgame equilibrium was characterized by the following combination: ({Smart contract}; {Imitation Innovation, Imitation Innovation, Imitation Innovation}). Under this equilibrium, the payoff profile was (571,687; 115,475). When supervision is low, the equilibrium remained unchanged, and the resulting payoffs for right holders and followers amounted to (571,687; 131,475), respectively. Simultaneously, the selection of an IP registration strategy through the utilization of a smart contract remains unaltered for rights holders. The novelty of the present study lies in the fact that it introduced additional factors of influence from the state and analyzed the choice of agents' strategies by checking the evolutionary stability of each equilibrium point at different values of payment elements.

Current decision support systems for recommending labor resource allocation and generating production schedules in the systems with decentralized technological process control often fail to account for the impact of participants’ communication strategies on the shifts in target performance indicators, which depend on the alignment between local goals of production units and the global objectives of the system. The goal of the present study is to develop an approach for determining optimal communication parameters among intelligent agents to achieve system-level performance targets using the previously developed multiagent systems (MAS) for optimizing technological processes. The research investigates how agent constraint systems influence both overall system welfare and the individual welfare of agents, considering the shifts in their objective functions driven by preferred communication strategies. A workflow is developed to identify effective constraints. Using this workflow, the study provides recommendations for assigning regional field development plans, accounting for participants’ tendencies toward cooperation. On data where the potential for increasing the region’s flow rate through optimization of labor resource allocation and scheduling of well intervention operations (GTO) does not exceed 6%, the presented solution enabled the development of field plans that result in an additional 1% increase in the predicted oil production region’s flow rate on top of the gain achieved through resource allocation optimization.

This article addresses the problem of insufficient alignment between intellectual property (IP) management processes and research and development (R&D) activities in high-tech enterprises, as well as the lack of formalized consideration of technology and engineering maturity levels in organizational decision-making. These factors hinder the optimization of IP portfolios and lead to reduced effectiveness in the commercialization of intellectual outputs (results of intellectual activity, RIA). The relevance of this issue is driven by intensifying competition and the growing need to enhance the efficiency of R&D operations in knowledge-intensive firms. The aim of the study is to design an IP management system for such enterprises, incorporating the development of an integrated organizational framework and the formalization of lifecycle-related tasks associated with RIA. The study proposes a structural-functional model that captures the interdependencies between IP coordination tasks and the stages of the RIA lifecycle within a comprehensive R&D management system at a high-tech enterprise. The findings provide a foundation for the development of a set of interconnected models and algorithms implementing an integrated IP management approach. This approach ensures the alignment of scientific-technical, legal, and economic logics of management, while improving coordination across the lifecycle of intellectual outputs.