VERTICAL CLUSTERING IN WOOL PRODUCTION AND DEEP PROCESSING

The relevance of the topic is caused by the fact that the existing potential for creating value chains in the production and deep processing of wool is used limited and ineffective. Agricultural producers are limited in opportunities to sell sheep products profitably, and light industry enterprises are experiencing a shortage of quality raw materials of Russian production. The purpose of the study is to substantiate the foundations of the concept of creating vertical clusters for the production and deep processing of wool. It is revealed that the main problems in the sphere of production and deep processing of wool in Russia are the lack of vertical links between producers, processors and consumers of raw materials; disproportionate nature of the distribution of value added in the chains of resource movement. Together, this leads to the displacement of domestic producers from the Russian market and the degradation of production sectors of the economy. To solve these problems, a conceptual approach to the creation of a vertical cluster of production and deep processing of wool, including producers of primary raw materials and four levels of its processing, is proposed. The novelty of the author’s proposals is to develop a framework for creating vertical clusters for the production and deep processing of wool, difference from known locations is integrated and cross-sectoral approach to clustering in forms of cooperation and integration in production stages with the alignment a fair chain of added value formation. The practical significance of the proposed directions is the possibility of maximizing the economic effect in the real sector and public utility from the construction of a vertical cluster for the production and deep processing of wool.

light industry, management, integration, clustering, cooperation, procurement, wool processing, sheep breeding, import substitution, modernization, competition.

Lidzhi-Goryaev D. V. Vertical clustering in wool production and deep processing. Business. Education. Law, 2020, no. 1, pp. 241–244. DOI: 10.25683/VOLBI.2020.50.159.