INNOVATION TRANSFORMATION STRATEGY FOR HOTEL-RESTAURANT BUSINESS ENTERPRISES

The aim of the article is to provide a theoretical substantiation and develop an approach to formulating a strategy for the innovative transformation of enterprises in the hotel-restaurant business based on the quantitative parameterisation of transformation areas, statistical selection of their parameters using multiple regression analysis, and forecasting the performance of alternative strategic scenarios. Within the scope of the study, the authors substantiate that the specific nature of innovative transformation in hotel-restaurant enterprises lies in the interrelated nature of digital, operational, customer-oriented and marketing changes. Accordingly, these four blocks are proposed as the substantive basis for forming a set of potential transformation parameters. At the same time, the blocks themselves are not treated as direct factors in the regression model; rather, each is operationalised through a system of quantitative indicators that can be statistically tested for their relationship with the selected performance indicator of the enterprise.It has been established that, within the proposed approach, multiple regression analysis performs not only its traditional function of assessing statistical relationships between variables and forecasting the performance indicator, but also facilitates the analytical transition from quantitatively defined parameters of innovative transformation to the formulation of strategic scenarios. Multiple regression analysis does not replace SWOT analysis, PESTEL analysis, benchmarking, expert methods, or the assessment of innovation potential; instead, it complements these approaches with quantitative tools for assessing statistical relationships between transformation parameters and the enterprise’s performance indicator. The application of the proposed approach to data from the Logindariy hotel-restaurant complex demonstrated the possibility of statistically selecting parameters from a pre-defined set of potential factors. The estimated model for the enterprise under study, together with the statistically substantiated parameters derived from it, provided the basis for developing alternative scenarios of innovative transformation. This demonstrated that the proposed approach makes it possible not merely to record the current state of an enterprise, but also to model potential changes in the performance indicator under different quantitative transformation parameters. This demonstrates the practical applicability of the model for the quantitative assessment of alternative development options.