Abstract
The study of the economic process can be presented as a chain of reflections on the causes and consequences of the particular phenomenon’s occurrence, within the framework of which scientists try to study and understand the nature of cause-and-effect relationships and find out the mechanisms of their occurrence. This article discusses three well-known conceptual approaches to the assessment of causation in socioeconomic sciences: successionist causation, configurational causation, and generative causation. The author gives his own interpretation of these approaches, constructs graphic interpretations, and also offers such concepts as a linear sequence of factors, the causal field, and the causal space of factors in the economy and socioeconomic processes. Within the framework of these approaches, the development trends of these and new models are formulated, taking into account the transition of the world economy to a digital format. The article contains specific examples from the author of the causality models’ implementation in scientific research related to assessing the impact of corporate culture on the main indicators of an organization’s performance in various contexts.
Highlights
The issues of causality’s assessment of relationships in economics are discussed in a wide range of scientific areas, including philosophy, psychology, economics, management, physics, and chemistry.It is quite obvious that the mechanisms of the emergence of cause-and-effect relationships are universal in relation to the subject and object of research
Experimental and quasi-experimental methods have become the basis of research practice in the field of searching for the causality of connections in economics, which made it possible to make a real revolution of reliability [2] in the field of empirical socioeconomic research
The purpose of this article is to propose a formalization of causality models within the framework of the three approaches discussed above, to assess their transformation in the digital economy, and to show examples of evaluating causality in economics based on one of the intellectual methods: fuzzy logic
Summary
The issues of causality’s assessment of relationships in economics are discussed in a wide range of scientific areas, including philosophy, psychology, economics, management, physics, and chemistry. The configurational causation approach implies the study of the socioeconomic process based on the comparison or comparative analysis of data This means that research begins with the study of some cases of a set of socioeconomic processes or phenomena that have similarities and differences. The three scientific approaches described above transformed with the transition to a digital economy, since a completely different data analysis toolkit appeared This was due to the development of tools for data analysis, cloud systems, and mining technologies, and due to a significant increase in the data itself, the organization of accumulation, storage, and use in the study of various economic processes. The purpose of this article is to propose a formalization of causality models within the framework of the three approaches discussed above, to assess their transformation in the digital economy, and to show examples of evaluating causality in economics based on one of the intellectual methods: fuzzy logic
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