sg

Geography

No. 1 (2025): FarDU ilmiy xabarlari jurnali (TABIIY FANLAR)

EVALUATION OF THE ECONOMIC EFFICIENCY OF AGROINDUSTRIAL CLUSTERS IN SAMARKAND REGION

Submitted
January 18, 2025
Published
2025-02-25

Abstract

This article covers the economic indicators, areas of activity, achieved productivity and employment of agro-industrial clusters in Samarkand region. Also, the level of technical efficiency, that is, the conversion of resources into income, was analyzed using data coverage analysis of the largest cotton-textile clusters in the region: “Afrosiyob Jeans Textile” and “Samarkand Kamalak Invest Textile”.

References

  1. Barrell, R., & Pain, N. (1999). Domestic Institutions, Agglomerations, and Foreign Direct Investment in Europe. European Economic Review, 43, 925-934.
  2. Портер М.Э.Конкуренция. Пер.с англ.-М.: Издат. Дом “Вильямс”, 2001.
  3. Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120 (3): 253-281.
  4. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2 (6): 429-444
  5. Zhu, C., N. Zhu, and, A. Emrouznejad (2020) A combined machine learning algorithms and DEA method for measuring and predicting the efficiency of Chinese manufacturing listed companies, Journal of Management Science and Engineering, https://doi.org/10.1016/j.jmse.2020.10.001.
  6. Zhu, C., N. Zhu, and, A. Emrouznejad (2020) A combined machine learning algorithms and DEA method for measuring and predicting the efficiency of Chinese manufacturing listed companies, Journal of Management Science and Engineering, https://doi.org/10.1016/j.jmse.2020.10.001.
  7. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2 (6): 429-444.
  8. Liu, H., Chen, T., Chiu, Y., & Kuo, F. (2013). A Comparison of Three-Stage DEA and Artificial Neural Network on the Operational Efficiency of Semi-Conductor Firms in Taiwan. Modern Economy, 4: 20-31
  9. Jiang, B., Chen, W., Zhang, H., & Pan, W. (2013). Supplier’s efficiency and performance evaluation using DEA-SVM approach. Journal of Software, 8 (1): 25-30.
  10. Emrouznejad, A., & Shale, E. (2009). A combined neural network and DEA for measuring efficiency of large scale datasets. Computers & Industrial Engineering, 56: 249-254.
  11. Misiunas, N., Oztekin A., Chen Y., & Chandra, K. (2016). DEANN: A healthcare analytic methodology of data envelopment analysis and artificial neural networks for the prediction of organ recipient functional status. Omega, 58: 46-54.
  12. Kirigia JM, Emrouznejad A, Sambo LG. Measurement of technical efficiency of public hospitals in Kenya Using Data Envelopment Analysis 2002. Journal of Medical Systems. 2002;26(1):39–45