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

Huseynov R., Aliyeva N., Bezpalov V., Syromyatnikov D.

ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, vol.26, no.2, pp.4119-4132, 2024 (SCI-Expanded) identifier identifier

  • Nəşrin Növü: Article / Article
  • Cild: 26 Say: 2
  • Nəşr tarixi: 2024
  • Doi nömrəsi: 10.1007/s10668-022-02873-8
  • jurnalın adı: ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
  • Jurnalın baxıldığı indekslər: Science Citation Index Expanded (SCI-EXPANDED), Scopus, International Bibliography of Social Sciences, PASCAL, ABI/INFORM, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, Business Source Elite, Business Source Premier, CAB Abstracts, Geobase, Greenfile, Index Islamicus, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Səhifə sayı: pp.4119-4132
  • Açıq Arxiv Kolleksiyası: Məqalə
  • Adres: Bəli

Qısa məlumat

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.