ECONOMIC EFFECTS OF AI-ALGORITHMIC PRICING ON ENTERPRISES IN THE RENTAL BUSINESS

Abstract

The article explores algorithmic pricing as an economic mechanism for integrating artificial intelligence into revenue management systems for short-term rental (STR) businesses in the context of the Industry 4.0 and Industry 5.0 paradigms. It is argued that pricing driven by artificial intelligence goes beyond purely technological innovation and becomes a factor in the structural transformation of market coordination, changing the nature of the interaction between demand and supply on digital platforms. From an economic point of view, the implementation of algorithmic pricing systems generates significant internal effects associated with increased productivity of management processes and increased revenues. At the same time, structural limitations also appear, in particular, additional transaction costs in the form of commission payments and costs of adapting business processes to work with algorithmic systems. The evolution of revenue management models is analyzed - from rule-based systems to adaptive machine learning algorithms capable of forming pricing decisions in a mode close to real time. The economic effects of algorithmic pricing at the individual level of the business entity, the local market level and the general economic level are determined, in particular the impact on the rationalization of the revenue behavior of STR operators, the speed of adaptation of price signals in local markets, as well as the efficiency of resource allocation and redistribution of economic surplus in the digital economy. It is shown that increasing the efficiency of revenue management in the logic of Industry 4.0 is accompanied by new challenges for competitive interaction, consumer welfare and regulatory policy, which necessitates the addition of algorithmic optimization with human-centric and ethical constraints characteristic of the Industry 5.0 paradigm.