Objective. Development of the concept of a software platform designed for long-term rentals with an embedded map, a calibrated bidirectional search mechanism (landlords searching for renters and vice versa), and an optimized, simplified process for creating standardized templates of advertisements to streamline and standardize data processing. Methodology and Key Results. The study included an analysis of the long-term real estate rental market platforms and an investigation of user needs. The primary concept of the platform was developed, including key diagrams and a prototype. A detailed implementation plan was outlined to serve as a roadmap for further development.Practical Significance and Scientific Novelty. The practical significance and scientific novelty lie in the development of a comprehensive and innovative approach to the digital transformation of the long-term rental market. The platform will significantly reduce the time required to search for rental properties or tenants through a deep filtering mechanism that evaluates each rental aspect based on predefined parameters. It considers the needs of both tenants and landlords, incorporates built-in localization, and actively integrates cartographic data to support well-informed rental decisions.These mechanisms are made possible by a templated, standardized system for creating rental listings, where each aspect of the rental process is configured by selecting from predefined options, thereby streamlining and accelerating the process. This approach automates listing creation, reduces information noise, and ensures data structuring and comparability. Additionally, because each listing aspect is configured separately, cluster analysis can be applied to the collected data. This enables market forecasting, including price changes, demand fluctuations, and regional rental trends, based on structured data insights. Furthermore, this creates an opportunity for the implementation of cutting-edge scientific advancements, such as artificial intelligence, to personalize rental property and tenant searches based on segmented data. This will enhance the efficiency of the rental search process for both landlords and tenants. The proposed scientific approaches contribute to increasing the effectiveness of rental property searches, reducing users’ time expenditures, and improving rental market analytics.
SHCHUR et al. (Tue,) studied this question.