SAMARQAND VILOYATI AGROSANOAT KLASTERLARINING IQTISODIY SAMARADORLIGINI BAHOLASH

##plugins.themes.bootstrap3.article.sidebar##

PDF
Nashr qilingan: fev 25, 2025
Kalit so‘zlar:
agrosanoat klasterlari, paxta-to‘qimachilik klasterlari, g‘allachilik klasterlari, meva-sabzavotchilik klasterlari, “Afrosiyob Jeans Tekstil” klasteri, “Samarqand Kamalak Invest Tekstil” klasteri

##plugins.themes.bootstrap3.article.main##

Boboyev Shodiyor Xurozmatovich
Sharof Rashidov nomidagi Samarqand davlat universiteti
https://orcid.org/0009-0008-9683-4398

Annotatsiya

Ushbu maqolada Samarqand viloyatidagi agrosanoat klasterlarining iqtisodiy ko‘rsatkichlari, faoliyat yo‘nalishlari, erishilgan hosildorlik va ulardagi aholi bandligi yoritilgan. Hamda viloyatdagi eng yirik paxta-to‘qimachilik klasterlaridan “Afrosiyob Jeans Tekstil” va “Samarqand Kamalak Invest Tekstil” agrosanoat klasterlarining ma‘lumotlar qamrovi tahlili yordamida texnik samaradorlik darajasi, ya‘ni resurslarning daromadga aylanishi tahlil qilingan.


 


 

##plugins.themes.bootstrap3.article.details##

Qanday qilib iqtibos keltirish kerak
Boboyev, S. (2025). SAMARQAND VILOYATI AGROSANOAT KLASTERLARINING IQTISODIY SAMARADORLIGINI BAHOLASH. Farg’ona Davlat Universiteti, 31(1), 131. Retrieved from https://journal.fdu.uz/index.php/sjfsu/article/view/5650
Maqola
№. 1 (2025): FarDU ilmiy xabarlari jurnali (TABIIY FANLAR)
Bo‘lim
Geografiya
Creative Commons litsenziyasi

Tsya robota litsenzuetsya vydpovídno do Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 xalqaro litsenziyasi.

muallifning biografiyasi

Boboyev Shodiyor Xurozmatovich, Sharof Rashidov nomidagi Samarqand davlat universiteti

Sharof Rashidov nomidagi Samarqand davlat universiteti tayanch doktoranti

Foydalaniladigan adabiyotlar

Barrell, R., & Pain, N. (1999). Domestic Institutions, Agglomerations, and Foreign Direct Investment in Europe. European Economic Review, 43, 925-934.

Портер М.Э.Конкуренция. Пер.с англ.-М.: Издат. Дом “Вильямс”, 2001.

Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120 (3): 253-281.

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2 (6): 429-444

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.

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.

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2 (6): 429-444.

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

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.

Emrouznejad, A., & Shale, E. (2009). A combined neural network and DEA for measuring efficiency of large scale datasets. Computers & Industrial Engineering, 56: 249-254.

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.

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