Cluster analysis as a tool for improving the performance of agricultural enterprises in the agro-industrial sector

Rashad Huseynov (), Naila Aliyeva, Valery Bezpalov and Denis Syromyatnikov
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Rashad Huseynov: Scientific Research Institute of Economic Investigation Under Azerbaijan State University of Economics (UNEC)
Naila Aliyeva: Azerbaijan State University of Economics (UNEC)
Valery Bezpalov: Russian Economic University after G.V. Plekhanov
Denis Syromyatnikov: North-Caucasus Federal University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 2, No 52, 4119-4132

Abstract: Abstract The objective of this study is to develop a comprehensive approach to agricultural enterprise clustering that will allow us to diagnose their market position and identify integration opportunities to increase production outputs. Cluster analysis is used as the methodology in this study. The study analysed 44 agricultural enterprises in Russia. Based on the cluster analysis, four groups of homogeneous agricultural enterprises with diverse activities that are significant in the given economic market segment were identified, within which the mean and limit values of clustering indicators were calculated. We were able to highlight the characteristics of each group of companies thanks to the clustering. The leader cluster was identified, which has a high number of personnel and performance indicators that are above the mean. This cluster's enterprises are industry leaders; they cover a large territory in Russia; they engage in technological, innovative, logistical, and international activities; and they have a high level of strategic planning and management. This generalised characterisation enabled us to compare the main criteria of the clusters, allowing us to identify the field of strategic action to improve production outputs.

Keywords: Cluster analysis; Region; Agriculture; Competitiveness; Technology; Efficiency; Modelling (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-022-02873-8

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