Educational Marketing Tools on the Way to Costumer: Analogies with Approaches in Technical Systems Description

Abstract

The article deals with the creation of a "box" model for describing the non-material complex “marketing of educational services” - “university” by analogy with the description of technical systems. The “box” approach has been studied in various industries, including marketing. Studies have shown that despite the similarity of names, the “box” approach in describing marketing strategies cannot fully explain the mechanism of influence of the educational service provider (university) on the customer. The results of the bibliometric analysis for the queries “educational market”, “neuromarketing”, and “educational marketing” showed that the process of marketing educational products takes place in the directions from the “supplier” of services to the “supplier” of services. This feature was considered when describing the educational marketing complex using the “box” approach. An attempt is made to describe each characteristic of the “white” box model concerning the complex “marketing of educational services” - “university”. In the course of the description, it was established that the “box” model should be supplemented with blocks for the complex testing and parametric identification of the model’s output parameters (responses). The list of parameters X, K, U, Z, and Y can be expanded; however, the fundamental approach to modeling a system will remain unchanged, in the center of which is the customer and the supplied. A feature of the model is a non-standard approach to parametric identification. In contrast to the material model, the intangible object “marketing of educational services” - “university” can have several options for parametric identification. The “white” box model with blocks for the complex testing and parametric identification of output parameters (responses) of the model allows you to move from a qualitative to a quantitative description of the main characteristics of an object and predict its behavior depending on the purpose of parametric identification.