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رمضانی, سید وحید, کرمی, آیت اله, نوری پور, مهدی. (1403). بررسی رشد بهره‌وری و کارآیی عوامل تولید در بخش کشاورزی استان کهگیلویه و بویراحمد. سامانه مدیریت نشریات علمی, 32(1), 189-221. doi: 10.30490/aead.2024.362499.1524
سید وحید رمضانی; آیت اله کرمی; مهدی نوری پور. "بررسی رشد بهره‌وری و کارآیی عوامل تولید در بخش کشاورزی استان کهگیلویه و بویراحمد". سامانه مدیریت نشریات علمی, 32, 1, 1403, 189-221. doi: 10.30490/aead.2024.362499.1524
رمضانی, سید وحید, کرمی, آیت اله, نوری پور, مهدی. (1403). 'بررسی رشد بهره‌وری و کارآیی عوامل تولید در بخش کشاورزی استان کهگیلویه و بویراحمد', سامانه مدیریت نشریات علمی, 32(1), pp. 189-221. doi: 10.30490/aead.2024.362499.1524
رمضانی, سید وحید, کرمی, آیت اله, نوری پور, مهدی. بررسی رشد بهره‌وری و کارآیی عوامل تولید در بخش کشاورزی استان کهگیلویه و بویراحمد. سامانه مدیریت نشریات علمی, 1403; 32(1): 189-221. doi: 10.30490/aead.2024.362499.1524

بررسی رشد بهره‌وری و کارآیی عوامل تولید در بخش کشاورزی استان کهگیلویه و بویراحمد

اقتصاد کشاورزی و توسعه
دوره 32، شماره 1 - شماره پیاپی 125، خرداد 1403، صفحه 189-221    اصل مقاله (623.72 K)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.30490/aead.2024.362499.1524
نویسندگان
سید وحید رمضانی1؛ آیت اله کرمی* 2؛ مهدی نوری پور3
1دانشجوی کارشناسی ارشد توسعة روستایی، گروه مدیریت توسعة روستایی، دانشکدة کشاورزی، دانشگاه یاسوج، یاسوج، ایران.
2استاد گروه مدیریت توسعة روستایی، دانشکدة کشاورزی، دانشگاه یاسوج، یاسوج، ایران
3استاد گروه مدیریت توسعة روستایی، دانشکدة کشاورزی، دانشگاه یاسوج، یاسوج، ایران.
چکیده
در سال‌های اخیر، اندازه‌گیری و تحلیل دقیق کارآیی و همچنین، استفاده از فناوری‌های نوین در بخش کشاورزی و تأثیر آن بر بهره‌وری کل عوامل در این بخش ضروری و در کانون توجه پژوهشگران گوناگون بوده است. با توجه به توان ویژه استان کهگیلویه و بویراحمد در بخش کشاورزی، بررسی بهره‌وری و کارآیی عوامل تولید در این بخش می‌تواند به بهبود وضعیت اقتصادی و اشتغال در این استان کمک کند. هدف اصلی پژوهش حاضر استفاده از روش غیرپارامتری، تحلیل پوششی داده­ها (DEA) و بهره‌گیری از شاخص مالم‌‏کوئیست به ‏منظور بررسی رشد بهره‌وری و کارآیی عوامل تولید در بخش کشاورزی استان کهگیلویه و بویراحمد بود. برای بررسی رشد بهره‌وری و کارآیی عوامل تولید، داده­‌های پژوهش مقدار مصرف عوامل تولید در بخش کشاورزی استان کهگیلویه و بویراحمد (از جمله مانده تسهیلات در بخش کشاورزی، نیروی کار، بذر، کود شیمیایی و سم) را دربرمی‏گرفت، که از آمارنامه­‌های کشاورزی و گزارش‏‌های هزینه تولید سال‌­های مختلف وزرات جهاد کشاورزی استخراج شدند. تحلیل داده‌­ها با بهره‌‏گیری از نرم‌افزار آماری DEAP2.1 صورت پذیرفت. نتایج نشان داد که تغییرات فناوری بیشترین تأثیر را بر بهره‌وری بخش کشاورزی داشته است و بهبود فناوری و بهره‌وری مدیریت نهاده‌ها می‌تواند بهبود بهره‌وری در بخش کشاورزی را به ‏همراه داشته باشد. همچنین، یافته‌­های پژوهش نشان داد که استفاده بهینه از نهاده‌های مختلف در بخش کشاورزی در بعضی از سال‌ها کارآ و در برخی دیگر از سال‌ها ناکارآ بوده است؛ این ناکارآیی ممکن است به‏دلیل عدم انتخاب ترکیبی مناسب از داده و ستانده باشد. با توجه به نتایج پژوهش حاضر، پیشنهاد می‌شود که برای ارتقای رشد بهره‌وری و توسعه کشاورزی در این استان، بر نوآوری‌های فناوری در بخش کشاورزی، بهبود فرآیندهای مدیریتی و افزایش آگاهی و آموزش کشاورزان تمرکز شود.
کلیدواژه‌ها
تغییرات بهره‌وری؛ کارآیی؛ شاخص مالم‌‏کوئیست؛ تحلیل پوششی داده‌ها (DEA)
عنوان مقاله [English]
Investigating the Productivity Growth and Efficiency of Production Factors in Agricultural Sector of Kohgiluyeh and Boyer-Ahmad Province of Iran
نویسندگان [English]
Sayyed Vahid Ramezani1؛ محمدکاظم مددالهی2؛ Mehdi Nooripoor3
1MSc. Student in Agricultural Development, Department of Rural Development Management, Faculty of Agriculture, Yasouj University, Yasouj, Iran.
2Professor, Department of Rural Development Management, Faculty of Agriculture, Yasouj University, Yasouj, Iran
3Professor of Agricultural Extension and Education, Department of Rural Development Management, Faculty of Agriculture, Yasouj University, Yasouj, Iran.
چکیده [English]
Introduction: Over recent years, the accurate measurement and analysis of efficiency, along with the utilization of innovative technologies in the agricultural sector and its effect on total factor productivity in this sector has been taken into account by different researchers. Considering the significant potential of Kohgiluyeh and Boyer-Ahmad province of Iran in the agricultural field, investigating the productivity growth and efficiency of production factors in this sector can contribute to improving the economic situation and employment in the province.
Materials and Methods: This study mainly aimed at investigating the productivity growth and efficiency of production factors using the non-parametric method, data envelopment analysis and the Malmquist productivity index to calculate productivity growth in the agricultural sector of Kohgiluyeh and Boyer-Ahmad province. For this purpose, the utilized data consisted of production factors in the agricultural sector of Kohgiluyeh and Boyer-Ahmad province (including facility balance, labor, seeds, chemical fertilizers, and pesticides), which were extracted from agricultural statistics and production cost reports of various years obtained from the Ministry of Agriculture-Jahad (MAJ). The data analysis was conducted using the statistical software DEAP2.1.
Results and Discussion: The study results indicated that technological changes had the greatest effect on agricultural productivity, and enhanced technology and input management productivity could contribute to improving agricultural productivity. In addition, the study findings showed that the optimal use of various inputs in agriculture was efficient in some years and inefficient in others. This inefficiency might be due to the lack of selecting an appropriate combination of data and parameters.
Conclusion and Suggestions: Based on the results, it is suggested that there should be focused on technological innovations in agriculture, improving management processes as well as increasing awareness and training of farmers to enhance the productivity growth and agricultural development in the concerned province. In addition, the results of the productivity table using the Malmquist index showed how much productivity changes in the agricultural sector were caused by technical changes and efficiency changes in each year; and all the changes in productivity over the 15-year period were due to the technological changes. Therefore, it is suggested that the agricultural sector should fundamentally review the type, implementation and costing of research as well as how to transfer the findings to the agricultural sector so that in addition to increasing the technological changes, the technical efficiency will increase.
کلیدواژه‌ها [English]
Productivity Changes, Efficiency, Malmquist Index, Data Envelopment Analysis (DEA)
مراجع
  • Abbasian, M., Ahmadzadeh Mashinchi, S., & Sharp, B. (2019). A study on energy efficiency and economic productivity of New Zealand’s agricultural sector. International Journal of Agricultural Management and Development, 9(3), 191-201. DOR: 20.1001.1.21595852.2019.9.3.1.3.
  • Abdeshahi, A., & Ghorbani, M. R. (2019). Estimating technical and scale efficiency of broiler chiken units in Khuzestan province. Journal of Agricultural Economics and Development, 33(3), 299-311. DOI: 10.22067/JEAD2.V33I3.28145. [In Persian]
  • Ahmadikish, A.-A., Ahmadvand, M., & Sharifzadeh, M. (2017). Comparative analysis of the causes of rural underdevelopment: the case of villages in Margoon district of Boyer-Ahmad County. Iranian Agricultural Extension and Education Journal, 12(2), 123-135. DOR: 20.1001.1.20081758.1395.12.2.8.1. [In Persian]
  • Aiabod, A., Moghaddasi, R., & Zeraatkish, S. Y. (2020). Studying of good governance connection with producing and utilizing all factors in group of developing and OECD countries. Agricultural Economics Research, 12(47), 289-318. DOR: 20.1001.1.20086407.1399.12.47.12.6. [In Persian]
  • Alinezhad, A., & Simiari, K. (2013). A hybrid method for project selection by using DEMATEL/DEA. Industrial Management Studies, 11(28), 41-60. DOR: 20.1001.1.22518029.1392.11.28.3.8. [In Persian]
  • Amirtaimoori, S. (2016). Causality relationship between educated labor and total factor productivity growth in Iran’s agricultural sector. Journal of Agricultural Education Administration Research, 8(36), 55-63. DOI: 10.22092/jaear.2016.106620. [In Persian]
  • Anooshehpour, A., Moghaddasi, R., Mohammadinejad, A., & Yazdani, S. (2020). The relationship between energy consumption and total factor productivity in agriculture: application of quantile regression approach. Iranian Energy Economics, 9(34), 65-85. DOI: 10.22054/jiee.2021.56060.1789. [In Persian]
  • Ansari, V., Tahmasebinejad, A., & Salami, H. (2019). Analysis of factor productivity in Iranian agricultural sector in an input-output framework. Agricultural Economics Research, 13(1), 73-103. DOI: 10.22034/iaes.2019.98783.1650. [In Persian]
  • Azimian, M., & Akhavan, P. (2018). Performance analysis of family health teams in petroleum industry health organization: integrative approach of Data Envelopment Analysis and Malmquist. Health Information Management, 15(4), 155-161. DOI: 10.22122/him.v15i4.3530. [In Persian]
  • Baniasadi, M., & Jala’ee Esfandabadi, S. (2016). Analyzing the impact of technology spillovers on total factor productivity of agricultural sector in Iran. Journal of Agricultural Economics and Development, 30(2), 117-126. DOI: 10.22067/jead2.v30i2.54600. [In Persian]
  • Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078-1092. Available at https://www.jstor.org/stable/2631725.
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444. DOI: 10.1016/0377-2217(78)90138-8.
  • Dabiri, F., Khoshnevis Yazdi, S., & Zandi, F. (2013). Agricultural productivity effects on the Iran’s economic growth. Journal of Economics and Business Research, 4(5), 17-31. Available at https://sanad.iau.ir/Journal/jebr/Article/1046189. [In Persian]
  • Darvish Motevally, M. H., Hosseinzadeh Lotfi, F., Shoja, N., & Gholam Abri, A. (2019). Calculating the sustainable supply chain performance in the cement industry (application of network data envelopment analysis model). Economic Modelling, 13(46), 73-100. Available at https://sanad.iau.ir/Journal/eco/Article/995527. [In Persian]
  • Ebrahimi, M. S., & Asadi Khob, H. (2018). The role and importance of agriculture to prevent rural migration: a case study of Bahmai County. Rural Development Strategies, 5(1), 87-104. DOI: 10.22048/rdsj.2018.29123.1374. [In Persian]
  • Emami Meibodi, A., & Vahabi, M. (2022). Measuring capital productivity of companies affiliated to the armed forces, using the data envelopment analysis. Defense Economics, 7(25), 9-37. DOR: 20.1001.1.25382454.1401.7.25.1.9. [In Persian]
  • Fallah Haghighi, N., Ramezanpour Nargesi, G., Abdollahzadeh, G., & Sharifi, Z. (2022). Analyzing the trend of changes in agricultural development among provinces of Iran. Iranian Journal of Agricultural Economics and Development Research, 53(3), 723-737. DOI: 10.22059/ijaedr.2021.331372.669086. [In Persian]
  • Färe, R., Grosskopf, S., & Roos, P. (1998). Malmquist productivity indexes: a survey of theory and practice. In: Index numbers: essays in honour of Sten Malmquist, pp. 127-190. Available at https://link.springer.com/chapter/10.1007/978-94-011-4858-0_4.
  • Fazel-Yazdi, A., & Moeineddin, M. (2017). Measuring the efficiency and productivity of commercial banks in Iran by using a Hybrid Model of Fuzzy TOPSIS, DEA and MPI. Strategic Management Researches, 22(63), 85-111. DOR: 20.1001.1.22285067.1395.22.63.4.4. [In Persian]
  • Hakimipour, N., & Avazalipour, M. (2012). Evaluating productivity changes of entire production factors for large industries in the provinces of Iran, using Malmquist productivity index. Management Researches, 5(15), 135-161. DOI: 10.22111/JMR.2012.665. [In Persian]
  • Hassanpour, B. & Karami, A. (2022). Sources of productivity growth in cereals cultivation in selected provinces in Iran: Improving farm management or technological progress? Agricultural Economics Research, 14(2), 65-84. DOI: 10.30495/jae.2022.25024.2170. [In Persian]
  • Hosseinpour, A., Mahmoudi, N., & Rezaei, M. (2017). Examining total factor production under economic sanctions. Defense Economics, 2(4), 51-69. DOR: 20.1001.1.25382454.1396.2.4.4.5. [In Persian]
  • Hosseinzadeh-Lotfi, F., Ariyanejad, M. B., Ebnerasoul, S. A., & Najafi, S. E. (2010). Evaluating productivity in the units of the powerhouse collection by using MalmQuist Index, Journal of Strategic Management in Industrial Systems, 4(10), 29-42. Available at https://sanad.iau.ir/Journal/imj/Article/923264.
  • Kafaie, M. A., & Bagherzadeh, M. (2016). The impact of key macroeconomic variables on TFP in Iran. Quarterly Journal of Economic Research and Policies, 24(79), 215-243. Available at http://qjerp.ir/article-1-1418-en.html. [In Persian]
  • Kavoosi Kalashami, M., & Khaligh Khiyavi, P. (2016). Analysis of total factor productivity growth. Agricultural Economics Research, 8(2), 157-172. DOR: 20.1001.1.20086407.1395.8.30.8.0. [In Persian]
  • Khaligh Khiyavi, P., & Kavoosi Kalashami, M. (2015). Application of Malmquist approach in analysis of total factor productivity growth of pulses in Iran. Iranian Journal of Pulses Research, 6(1), 127-133. DOI: 10.22067/ijpr.v1394i1.49341. [In Persian]
  • Khazaei, J., Amraei, B., & Esfahani, S. M. J. (2016). Examining the trend of changes in total productivity of tomato production factors in Iran using Malmquist index. Journal of Agricultural Economics Researches, 7(28), 83-98. DOI: 10.22111/JMR.2012.665. [In Persian]
  • Liu, J., Wang, M., Yang, L., Rahman, S., & Sriboonchitta, S. (2020). Agricultural productivity growth and its determinants in south and southeast Asian countries. Sustainability, 12(12), 49-81. DOI: 10.3390/su12124981.
  • Mahmoodi, N., Hosseinpour, A., & Rezaei, M. (2019). Analysis of total factor productivity in selected sectors with the Economic Sanctions Index. Journal of Economic Research [Tahghighat-E-Eghtesadi], 54(3), 659-693. DOI: 10.22059/jte.2019.72776. [In Persian]
  • Mansouri, A. (2018). Application of geographical information system in evaluating productivity growth of sale centers using the Malmquist Productivity Index. Production and Operations Management, 9(2), 159-178. DOI: 10.22108/JPOM.2018.92292.0. [In Persian]
  • Mirzaei Heydari, M., & Bagheri, M. (2022). Seed production, self-sufficiency and agricultural independence. Journal of Seed Research, 12(2), 60-65. DOI: 10.30495/jsr.2023.1989333.1258. [In Persian]
  • Omidpour, F., Rahmani Fazli, A., & Azizpour, F. (2019). An analysis of factors affecting in agricultural efficiency reduction in rural areas (case study: Kakavand district, Delfan County). Researches in Earth Sciences, 10(1), 78-93. DOI: 10.52547/esrj.10.1.78. [In Persian]
  • Osmani F., Dehghani, A., Ghiasi, M., & Gorjipour, M. J. (2024). Evaluation of the environmental efficiency of the agricultural sector in comparison with other economic sectors of Iran by DEA method and Malmquist index. Agricultural Market and Economics, 1(1), 1-9. Available at http://ame.sanru.ac.ir/article-1-23-en.html. [In Persian]
  • Rahmani, N., Keshavarz, A., Tabatabaei, S. S., & Kalhor, R. (2012). Assessing the role of hospital ownership on total factor productivity changes in Qazvin hospitals using Malemquist’s Index and DEA. Payavard, 6(4), 300-310. Available at http://payavard.tums.ac.ir/article-1-22-en.html. [In Persian]
  • Rasekhjahromi, E., & Noraniazad, S. (2018). Evaluation of Tehran transportation system efficiency using Malmquist Index analysis approach DEA. Road, 26(97), 111-124. Available at https://road.bhrc.ac.ir/article_85582.html?lang=fa. [In Persian]
  • Saei, F., Dashti, G., & Sani, F. (2021). Comparison and analysis of total factor productivity of broiler chicken productions in Iran: the application of Fare-Primont Index. Journal of Animal Science Research, 31(2), 71-86. DOI: 10.22034/as.2021.37737.1543. [In Persian]
  • Salarieh, M., Mohamadinejad, A., & Moghaddasi, R. (2016). Impact of technological progress and efficiency changes on the productivity growth of Iran agriculture sector: Data Envelopment Analysis (DEA). Economic Modelling, 10(34), 133-148. Available at https://sanad.iau.ir/fa/Article/995640. [In Persian]
  • Salehi, Z., & Afshin, Z. (2016). Productivity measurment and ranking of research units using Data Envelopment Analysis. Basparesh, 5(4), 92-99. DOI: 10.22063/basparesh.2016.1228. [In Persian]
  • Sardar Shahraki, A., Aliahmadi, N., & Layani, G. (2019). Evaluating the efficiency and productivity of grapevine gardens in Sistan region. Iranian Journal of Agricultural Economics and Development Research, 50(1), 45-63. DOI: 10.22059/ijaedr.2018.244523.668509. [In Persian]
  • Shahabinejad, V., Shahabinejad, H., & Sistani, Y. (2016). Efficiency measurement comparing productivity growth of bank branches in Melli Bank of Kerman province by using Data Envelopment Analysis. Quarterly Journal of Fiscal and Economic Policies, 3(12): 105-124. Available at http://qjfep.ir/article-1-275-en.html. [In Persian]
  • Shahkooeei, M., Rezaei Balf, F., Rabbani, M., & Fallah Jelodar, M. (2022). Data‎ E‎nvelopment Analysis and Malmquist Index for measuring productivity of inefficient‎ International Journal of Industrial Mathematics, 14(4), 479-487. DOI: 10.30495/ijim.2022.64370.1561.
  • Sharifzadeh, M., Aliyari, V., Aliyari, N., & Gholami Kalus, A. (2023). Investigating the impacts of drought on rural households of Kakan district in Boyer Ahmad county. Iranian Agricultural Extension and Education Journal, 18(Special Issue), 73-87. Available at https://www.iaeej.ir/article_169884.html?lang=en. [In Persian]
  • Sheng, Y., Tian, X., Qiao, W., & Peng, C. (2020). Measuring agricultural total factor productivity in China: pattern and drivers over the period of 1978‐2016. Australian Journal of Agricultural and Resource Economics, 64(1), 82-103. DOI: 10.1111/1467-8489.12327.
  • Shivaei, A., & zarrabi, A. (2022). Analyzing the causes of spatial development inequalities in Kohgiluyeh and Boyer-Ahmad province of Iran. Sustainable City, 5(2), 115-130. DOI: 10.22034/jsc.2021.313020.1564. [In Persian]
  • Tahamipour, M., Saleh, I., & Nemati, M. (2014). Measuring and decomposing the total factor productivity growth in varieties of rice in Iran. Applied Field Crops Research, 27(103), DOI: 22092/AJ.2014.101210. [In Persian]
  • Vahedi, J., Dashti, G., & Saei, F. S. (2022). Analysis of total factor productivity growth, technical efficiency and technological change in Iranian poultry industry. Journal of Animal Science Research, 32(2), 63-74. DOI: 10.22034/as.2022.45412.1611. [In Persian]
  • Zali, N., & Sajjadi Asl, S. A. (2017). Identification of the main affective factors on regional undevelopment (case study: Kohgiluyeh and Boyer-Ahmad province). Regional Planning, 7(26), 25-40. DOI: 1001.1.22516735.1396.7.26.3.8. [In Persian]
  • Zanganeh, M., & Rafiei, H. (2019). Survey on convergence in growth of total factor production in agricultural sector of Iran: a case study of corn farming. Agricultural Economics Research, 11(3), 111-126. DOR: 20.1001.1.20086407.1398.11.43.6.5. [In Persian]
آمار
تعداد مشاهده مقاله: 260
تعداد دریافت فایل اصل مقاله: 210


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