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تبیین مدل مفهومی شاخص‌های تاثیرگذار بر اولویت‌بندی محصولات کشاورزی برای ورود به الگوی کشت | ||
| تحقیقات اقتصاد و توسعه کشاورزی ایران | ||
| دوره 51، شماره 4، دی 1399، صفحه 817-831 اصل مقاله (1.28 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijaedr.2020.300604.668899 | ||
| نویسندگان | ||
| نیلوفر یاراحمدی1؛ ابراهیم امیری تکلدانی* 2؛ احمد ماکویی3 | ||
| 1دانشجوی دکتری سازه‌های آبی، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج، ایران | ||
| 2استاد، گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج، ایران | ||
| 3استاد، گروه مهندسی صنایع، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران | ||
| چکیده | ||
| کشاورزی یکی از بخش‌های اساسی تولیدی در هر کشور محسوب می‌شود. افزایش رشد و کارایی این بخش، مستلزم ﺗﺪوﯾﻦ اﻟﮕﻮی ﻣﻨﺎﺳﺐ، دﻗﯿﻖ و واﻗﻊﺑﯿﻨﺎﻧﻪ ﮐﺸﺖ ﻣﺤﺼﻮﻻت ﺑﺮاﺳﺎس اﻫﺪاف و ﻣﻌﯿﺎرﻫﺎی ﻣﺨﺘﻠﻒ در راﺳﺘﺎی ﺗﺄﻣﯿﻦ ﻣﻨﺎﻓﻊ ﮐﻞ ﻣﺠﻤﻮﻋﻪی ذیﻧﻔﻊ ﮐﺸﺎورزی در ﺑﻠﻨﺪﻣﺪت اﺳﺖ. هدف از انجام این پژوهش، شناسایی و رتبه‌بندی شاخص‌های تاثیرگذار بر اولویت‌بندی محصولات کشاورزی به منظور انتخاب در الگوی کشت، با استفاده از روش پژوهش ترکیبی تحلیل عامل اکتشافی و فرآیند تحلیل شبکه‌ای بود. در راستای دستیابی به اهداف پژوهش، ابتدا با بررسی پیشینه تحقیق، شاخص‌های اولویت‌بندی محصولات کشاورزی استخراج و سپس، با استفاده از روش تحلیل عاملی اکتشافی و با استفاده از نرم‌افزار SPSS 25، این شاخص‌ها دسته‌بندی شد و مدل مفهومی عوامل و شاخص‌های تاثیرگذار بر اولویت‌بندی محصولات کشاورزی ساخته شد. در مرحله بعد، با استفاده از روش فرآیند تحلیل شبکه، به رتبه‌بندی شاخص‌ها پرداخته شد. بر اساس نتایج تحقیق، شاخص‌ها تحت شش عامل فرهنگی و اجتماعی، سیاسی، ملاحظات پدافند غیر‌عامل، آب، تاثیرات زیست محیطی و اقتصاد، دسته‌بندی شدند. همچنین، شاخص‌های "هزینه داخلی منابع محصول" با وزن 2277/0، "فرهنگ پذیرش" با وزن 1468/0، "ریسک‌پذیری کشاورز برای پذیرش کشت جدید" با وزن 1160/0 و "نیاز آبیاری محصول" با وزن 0754/0، مهمترین شاخص‌ها در فرآیند سنجش اولویت‌بندی محصولات کشاورزی ارزیابی شدند. مدل مفهومی ارایه شده این تحقیق می‌تواند به انتخاب محصولات برتر برای کشت، کمک کرده و امکان تعیین الگوی کشت بهینه را فراهم آورد. | ||
| کلیدواژه‌ها | ||
| الگوی کشت؛ اولویت‌بندی محصولات کشاورزی؛ هزینه داخلی منابع محصول | ||
| عنوان مقاله [English] | ||
| Structuring a Conceptual Model of Determinant Criteria on Crops' Prioritization to Be Selected in Crop Pattern | ||
| نویسندگان [English] | ||
| Niloufar Yarahmadi1؛ Ebrahim Amiri Tokaldany2؛ Ahmad Makui3 | ||
| 1PhD candidate, Department of Irrigation and Reclamation Engineering, Faculty of Agriculture and Natural Resources, University of Tehran, Karaj, Iran | ||
| 2Professor, Department of Irrigation and Reclamation Engineering, Faculty of Agriculture and Natural Resources, University of Tehran, Karaj, Iran | ||
| 3Professor, Department of Industrial Engineering, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran | ||
| چکیده [English] | ||
| Agricultural sector is one of the main production sectors in each country. Increasing the growth and efficiency of this sector requires the development of a proper, accurate and realistic model of crops planting based on different goals and criteria, in order to provide the benefits of the whole beneficiary community in long term. The purpose of this research was to identify, validate and rank the effective criteria on crops prioritization for being selected in the cropping pattern, using a hybrid research method of exploratory factor analysis and analytical network process. In order to achieving the research goals, in the first phase, by aid of literature reviewing, effective criteria on crops prioritization have been selected, and then by using exploratory factor analysis method and application of SPSS 25 software, these criteria have been loaded on 6 factors named: cultural and social, political, passive defense, water, environmental impacts and economics. The final step of this phase was the construction of the conceptual model of the factors and effective criteria. In second phase the criteria were ranked by using analytical network process method and application of Super Decisions software. According the results the most important criteria in the process of assessing the prioritization of crops are listed as below: “Domestic Resource Cost” with a weight of 0.2277, “consent culture” with a weight of 0.1468, “risk taking attitude of farmer” with a weight of 0.1160, and “crops’ irrigation water demand” with a weight of 0.0754. The conceptual model can facilitate the selection process of crops and ease the designing of optimal crop pattern. | ||
| کلیدواژه‌ها [English] | ||
| Crop Pattern, Crops Prioritization, Domestic Resource Cost | ||
| مراجع | ||
10. Bender, M. J., & Simonovic, S. P. (2000). A fuzzy compromise approach to water resource systems planning under uncertainty. Journal of Fuzzy sets and Systems, 115(1), 35-44. 11. Berbel, J., & Gómez-Limón, J. A. (2000). The impact of water-pricing policy in Spain: an analysis of three irrigated areas. Journal of Agricultural Water Management, 43(2), 219-238. 12. Biswas, A., & Pal, B. B. (2005). Application of fuzzy goal programming technique to land use planning in agricultural system. Omega, 33(5), 391-398. 13. Chin, W. W (1998). Commentary: Issues and Opinion on Structural Equation Modeling. 14. Dahimavy, A., Ghanian, M., Mehrab Ghoochani, O., & Zareyi, H. (2015). Process of application of multi criteria decision making models in prioritizing of water development projects of rural areas in Khuzestan province. Journal of Water and Sustainable Development, 1(3), 9-16. (In Farsi). 15. Davari, A., & Rezazadeh, A. (2014). Modeling structural equations with PLS software. (2nd Ed.). Tehran: The Jihad Daneshgahi Press. (In Farsi). 16. De Koeijer, T. J., Wossink, G. A. A., Smit, A. B., Janssens, S. R. M., Renkema, J. A., & Struik, P. C. (2003). Assessment of the quality of farmers’ environmental management and its effects on resource use efficiency: a Dutch case study. Journal of Agricultural Systems, 78(1), 85-103. 17. Doppler, W., Salman, A. Z., Al-Karablieh, E. K., & Wolff, H. P. (2002). The impact of water price strategies on the allocation of irrigation water: the case of the Jordan Valley. Journal of Agricultural Water Management, 55(3), 171-182. 18. Fallahi, E. & Gholinezhad, S. (2016). Optimal cropping pattern based on multiple economic, regional, and agricultural sustainability criteria in Sari, Iran: Application of a consolidated model of AHP and linear programming. Journal of Agricultural Economics & Development, 30(1), 37-49. (In Farsi). 19. Ferguson, E., & Cox, T. (1993). Exploratory factor analysis: A users’ guide. International journal of selection and assessment, 1(2), 84-94. 20. Galán-Martín, Á., Pozo, C., Guillén-Gosálbez, G., Vallejo, A. A., & Esteller, L. J. (2015). Multi-stage linear programming model for optimizing cropping plan decisions under the new Common Agricultural Policy. Land use policy, 48, 515-524. 21. Garver, M. S., & Mentzer, J. T. (1999). Logistics research methods: employing structural equation modeling to test for construct validity. Journal of business logistics, 20(1), 33-57. 22. Geisser, S. (1975). The predictive sample reuse method with applications. Journal of the American statistical Association, 70(350), 320-328. 23. Gholami, Z., Ebrahimian, H., & Noory H. (2018). Prioritization of major agricultural crops cultivation considering the energy and water costs in Qazvin plain. Journal of Irrigation Science, 41(1), 17-30. (In Farsi). 24. Hatef, H. Sarvary, A. & Daneshvar Kakhaki, M. (2016). Determining of crop optimal pattern for the main crops of Khorasan Razavi province based on production comparative advantage. Journal of Agricultural Economics Research, 8(3), 167-192. (In Farsi). 25. Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing (pp. 277-319). Emerald Group Publishing Limited. 26. Hoe, S. L. (2008). Issues and procedures in adopting structural equation modeling technique. Journal of Applied Quantitative Methods, 3(1), 76-83. 27. Hoelter, J. W. (1983). The analysis of covariance structures: Goodness-of-fit indices. Journal of Sociological Methods & Research, 11(3), 325-344. 28. Howard, M. C. (2016). A review of exploratory factor analysis decisions and overview of current practices: What we are doing and how can we improve?. International Journal of Human-Computer Interaction, 32(1), 51-62. 29. Isalou, A., Ebrahimzadeh, H., & Shahmoradi, B. (2014). Feasibility study of old inefficient urban area interference using analytical network process model: the case study of district 6 of Qom. Journal of Geography and Development, 12(34), 57-68. (In Farsi). 30.Itoh, T., Ishii, H., & Nanseki, T. (2003). A model of crop planning under uncertainty in agricultural management. International Journal of Production Economics, 81, 555-558. 31. Kazemi, J., Dehghan sanch, K., & KHalilzadeh, M. (2017). Ranking of agricultural production using fuzzy multi-attribute decision making approach: the case study of West Azarbayjan. Journalof Agricultural Economics Research, 9(3), 145-162. (In Farsi). 32. Latinopoulos, D., & Mylopoulos, Y. (2005). Optimal allocation of land and water resources in irrigated agriculture by means of goal programming: Application in Loudias river basin. Global Nest Journal, 7(3), 264-273. 33. Lee, D. J., Tipton, T., & Leung, P. (1995). Modelling cropping decisions in a rural developing country: a multiple-objective programming approach. Agricultural Systems, 49(2), 101-111. 34. Mahmoodi, A., & Rasoolzadeh, N. (2016). Determining investment priorities in agriculture sector in Qazvin province using hierarchical analysis method. Journal of Agricultural Economics Researches, 8(2), 1-16. (In Farsi). 35. Mohammadi, Y., Shalavand, M., & Rezapour, K. (2019). Determining an optimal agronomic cropping pattern in productive units by analyzing the regional and national comparative advantages. Iranian Journal of Agricultural Economics and Development Research, 49-2 (4), 719-734. (In Farsi). 36. Mohsenin, Sh., & Esfidani, M.R. (2014). Structural equations based on the partial least squares approach using Smart-PLS software. (1st Ed.). Tehran: The Mehraban Nashr Press. (In Farsi). 37. Moos, R. H., Cronkite, R. C., & Moos, B. S. (1998). The long-term interplay between family and extrafamily resources and depression. Journal of Family Psychology, 12(3), 326. 38. 38-Moradi, M., Shakibaifard, Z., & Shabanali Fami, H. (2017). Ranking the agricultural products in Kermanshah using hierarchical analysis process (AHP). Third National Conference of Water Management on the Farm, Karaj, Soil and Water Research Institute (In Farsi). 39. Niu, G., Li, Y. P., Huang, G. H., Liu, J., & Fan, Y. R. (2016). Crop planning and water resource allocation for sustainable development of an irrigation region in China under multiple uncertainties. Agricultural Water Management, 166, 53-69. 40. Raghavendra, G. S., Kurli, G. V., & Vishal M. (2018). Development and application of linear programming model for multi objective crop planning for optimal benefits, Journal of Engineering Practices and Futuristic Technologies, 1(1), 279-287. 41. Ragkos, A. and Psychoudakis, A. (2008) Minimizing adverse environmental effect of agriculture: a multi-objective programming approach. Operation Research International Journal, 9(3), 267–280. 42. Roosta, K., Teimoori, M., & Falaki, M. (2012). Prioritizing the cultivation of crops in Birjand city by using AHP technique. Journal of Agricultural Economics and Development, 20(79), 47-66. (In Farsi). 43. Sahoo, B., Lohani, A. K., & Sahu, R. K. (2006). Fuzzy multi objective and linear programming based management models for optimal land-water-crop system planning. Water Resources Management, 20(6), 931-948. 44. Sakhdari, H., & Ziaee, S. (2018). Priorities of agricultural development in Khorasan Razavi province: analytical hierarchy process (AHP). Journal of Agricultural Economics Research, 10(1), 207-224. (In Farsi). 45. Sharifi, M., Akram, A., Rafei, Sh., & Sabzehparvar, M. (2014). Prioritization of strategic crops implant in Alborz province using fuzzy Delphi and analytical hierarchy process methods. Journal of Agricultural Machinery, 4(1), 116-124. (In Farsi). 46. 46-Shreedhar, R., Hiremath, C. G., & Shetty, G. G. (2015). Optimization of cropping pattern using linear programming model for Markandeya command area. International Journal of Scientific & Engineering Research, 6(9), 1311-1325. 47. Stone, M. (1974). Cross‐validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B (Methodological), 36(2), 111-133. 48. Ten Berge, H. F. M., Van Ittersum, M. K., Rossing, W. A. H., Van de Ven, G. W. J., & Schans, J. (2000). Farming options for The Netherlands explored by multi-objective modelling. European Journal of Agronomy, 13(2-3), 263-277. 49. Vinzi, V. E., Trinchera, L., & Amato, S. (2010). PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement. In Handbook of partial least squares (pp. 47-82). Springer, Berlin, Heidelberg. 50. Wei, W., Liu, Y., Hu, Z., & Zhao, Y. (2009). An optimal model of dry land multiple-cropping circular economy systems. World Journal of Modeling and Simulation, 5(3), 203-210. 51. Werts, C. E., Linn, R. L., & Jöreskog, K. G. (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), 25-33. 52. Zebardast, E. (2010). The application of analytic network process (ANP) in urban and regional planning. Journal of Fine Arts, Architecture and Urban Design, 2(41), 79-90. (In Farsi). Zebardast, E. (2017). Exploratory factor analysis in urban and regional planning. Journal of Fine Arts, Architecture and Urban Design, 22(2), 5-18. (In Farsi) | ||
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آمار تعداد مشاهده مقاله: 408 تعداد دریافت فایل اصل مقاله: 276 |
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