An end-to-end technology management model in cross-border M&A transactions

Abstract

Subject. This article examines an adapted management model based on the use of end-to-end technologies in key business processes for finding target companies and deciding on the feasibility of implementing mergers and acquisitions. Objectives. The article aims to present an author-developed model for managing end-to-end technologies in cross-border mergers and acquisitions. Methods. For the study, we used empirical and logical constructions, analysis and synthesis, generalization, formalization, systems approach, and the graphic and tabular methods of visualization. Results. The article identifies trends in the use of artificial intelligence in the main elements of the developed management model along with traditional ways of managing mergers and acquisitions. The proposed system management integrator helps use machine learning algorithms and business process controlling to increase the accuracy and efficiency of decisions and maximize the synergy of the buyer and the target company after the implementation of mergers and acquisitions, which is verified using mathematical algorithms and developed indicators for the use of artificial intelligence and big data business process management. Conclusions. The management model of cross-border mergers and acquisitions of companies determines the use of end-to-end technologies to improve the time and quality of management decision-making.