INSTRUMENTAL LOGIC OF APPLIED RESEARCH AS A BASIS FOR SUBSTANTIATING MANAGERIAL DECISIONS

Abstract

The article substantiates the instrumental logic of applied research in economics and management as a systematic framework for aligning a managerial problem, analytical methods, digital tools, the evidence base, and the resulting managerial decision. The study proceeds from the observation that the practical value of applied research is determined not only by the formal correctness of selected methods, but also by the extent to which the research process ensures a consistent transition from problem formulation to data selection, analytical procedures, interpretation of findings, and the development of justified recommendations. Particular attention is paid to the role of digital tools, including spreadsheet software, business intelligence platforms, online data collection services, open statistical databases, and generative artificial intelligence. These tools significantly expand the technical capabilities of researchers and increase the speed, visibility, and reproducibility of analysis, but they do not replace methods in the methodological sense and do not generate an evidence base by themselves. Their function is primarily operational: they support the technical implementation of analytical procedures, while the quality of research still depends on the relevance of data, the validity of the selected method, and the responsibility of interpretation. The article proposes a functional understanding of research methods. In this approach, a method is characterised not only by its formal affiliation with a particular group, such as quantitative, qualitative, empirical, or economic-mathematical methods, but also by its role in the transition from a managerial problem to a decision. The functional classification covers problem formulation, formation of the information base, diagnosis of the object’s state, explanation of causes, assessment of the external environment, selection of alternatives, verification of practical feasibility, and presentation of results. This makes it possible to evaluate applied research not by the number of declared methods, but by the analytical function each method performs and the evidential result it provides.