تعیین کارایی و حد مطلوب استفاده از نهاده‌های تولید قارچ خوراکی تحت شرایط عدم حتمیت در ایران

نوع مقاله : مقالات پژوهشی

نویسندگان

1 دانشگاه علوم کشاورزی و منابع طبیعی خوزستان

2 دانشیار اقتصاد کشاورزی-دانشگاه علوم کشاورزی و منابع طبیعی خوزستان

3 دانش آموخته دکتر اقتصاد کشاورزی- دانشگاه علوم کشاورزی و منابع طبیعی ساری

4 دانشجوی کارشناسی ارشد- دانشگاه علوم کشاورزی و منابع طبیعی خوزستان

10.22067/jead.2021.69647.1029

چکیده

کشت و پرورش قارچ خوراکی، با توجه به ارزش‌های غذایی و دارویی و هم‌چنین مزایای اقتصادی آن به سرعت در حال گسترش است. با این وجود عدم کسب دانش مورد نیاز و مدیریت اصولی ممکن است تولیدکنندگان را با مشکلات زیادی مواجه کرده و یا حتی به مرز ورشکستگی اقتصادی نزدیک سازد. در همین راستا، هدف از انجام این مطالعه مقایسه کارایی فنی، فنی خالص و مقیاس کشت قارچ در استان‌های کشور و تعیین میزان مطلوب استفاده از نهاده‌ها می‌باشد. در ضمن به دلیل اینکه در دنیای واقعی معمولاً ورودی‌ها و خروجی‌ها به صورت غیر دقیق و یا حتی مبهم هستند، در این تحقیق از مدل تحلیل پوششی داده‌های استوار به جای مدل DEA سنتی بهره گرفته شد. داده‌های ورودی و خروجی مدل مورد استفاده در این مطالعه از مرکز آمار ایران برای سال 1395 جمع‌آوری شد. طبق نتایج این مطالعه در تمامی سطوح احتمال انحراف محدودیت، کارایی فنی خالص بالاتر از کارایی مقیاس و کارایی فنی بوده است. این امر بیانگر دانش و مهارت بالای این تولیدکنندگان بوده و پایین بودن کارایی فنی تولیدکنندگان به دلیل بهینه نبودن مقیاس تولید آن‌ها است. مهم‌ترین نهاده‌ای که باعث عدم کارایی واحدها شده است، نهاده "هزینه اسپان" بوده و با استفاده بهینه از این نهاده می‌توان تا حدود 70 درصد هزینه این نهاده را کاهش داد. از دیگر نتایج این مطالعه این است که با کاهش احتمال انحراف هر محدودیت از کران خود، میزان کارایی فنی کاهش و درصد کاهش در مقدار نهاده‌ها نسبت به مقدار واقعی، افزایش یافته است. این امر بر اهمیت استفاده از مدل‌های RDEA جهت انطباق بیشتر نتایج با دنیای واقعی می‌افزاید. توصیه می‌شود که سیاست‌گذاران امکان دسترسی به تسهیلات برای تولیدکنندگان با مقیاس کوچک را فراهم نموده و موجبات افزایش صرفه‌های ناشی از مقیاس را برای آنان فراهم نمایند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Determining the Efficiency and Optimal Use of Inputs under Uncertainty Conditions for Production of Edible Mushrooms in Iran

نویسندگان [English]

  • M. Mardani Najafabadi 1
  • A. Abdeshahi 2
  • F. Yavari 3
  • F. Naghibeiranvand 4
1 Agriculture Sciences and Natural Resources University of Khuzestan
2 Associated professor of agricultural economics- Agriculture Sciences and Natural Resources University of Khuzestan
3 PhD student in Agricultural Economics - Agricultural Sciences and Natural Resources University of Sari
4 Ms. Student- Agriculture Sciences and Natural Resources University of Khuzestan
چکیده [English]

Introduction: The cultivation of edible mushrooms is expanding rapidly due to its nutritional and medicinal values as well as its economic benefits. However, lack of knowledge and principled management may cause many problems for producers or even bring them closer to the bankruptcy brink. The first step to improve the efficiency of units is finding an appropriate method to measure it. Data Envelopment Analysis (DEA) is one of the methods that is widely used to evaluate the relative efficiency of a homogenous set of DMUs. Despite the many advantages of this model, the high sensitivity of DEA to even a small change in the data reduces the validity of its results. In fact the conventional DEA assumes that input and output data are without any deviation. However, the observed values of the input and output data in real-life problems are sometimes imprecise or vague. So In this paper, to deal with uncertainty in data the linear robust optimization framework of Bertsimas and Sim (2004) was used to compare technical efficiency of Iranian mushroom-producing provinces and determine the optimum use of inputs.
Materials and Methods: According to the purpose of this study, a robust data envelopment analysis (RDEA) model with imprecise inputs and outputs was used. The method is based on the robust optimization approach of Bertsimas and Sim (2004) which with the introduction of the conservative parameter (Γ) for each constraint, adjusts robustness in an optimisation model against the level of conservatism of the solution. The value of Γ is dependent on the maximum probability of constraint violation (p) and numbers of uncertain data in every constraint (n). So this RDEA model allows adjustment of level of robustness of the solution to trade-off between protection against constraint violation and conservatism of efficiency scores. In order to estimate the models, the GAMS software was used and related data was gathered from Statistical Center of Iran.
Results and Discussion: In this paper to distinguish the causes of technical inefficiency, pure technical efficiency and scale efficiency were measured. According to the results of this model, at all levels of P, the pure technical efficiency was higher than the scale efficiency and technical efficiency, and its value was higher than 98% in all cases. This indicates that mushroom producers have a high level of knowledge and skills in this field and shows that the cause of low technical efficiency of the producers is their non-optimal scale. In addition, according to the results of both RDEA and DEA models, the most important input that has caused the inefficiency of the units is the "seed cost" input and with optimal use of this input, the cost of that can be reduced by about 70% (in ε=0.1 and P=1). Another result of this study is that with the reduction of the Probability of constraint violation, the rate of technical efficiency has decreased. For example in ε=0.1, if P is reclined from 1 (no protection against uncertainty) to 0.8 and 0.1, the average technical efficiency is reduced from 93% to 89% and 85% respectively. Also when ε is increased from 10 to 20 and 30 percent (in P=0.1) the average technical efficiency is reduced from 85 to 83 and 82 percent. On the contrary by reducing P, the percentages of reduction compare to the actual value is increased. For instance by reducing P from 1 to 0.8 and 0.1 the percentages of reduction of "seed cost" are decreased from 70% to 78% and 80% respectively. This results highlights the importance of using RDEA models to more conformity of the results to the real world.
Conclusion: Based on the results the low technical efficiency of the producers is because of their non-optimal scale. Therefore, it is recommended to consider the optimal size unit for those who want to enter this activity. On the other hand, the policymakers should improve access to facilities so the small units could enlarge their unit if it's necessary. Also considering the experience of successful mushroom farms, self-reliance in production of mushroom seeds can greatly reduce inefficiency of the units. Eventually considering that the level of uncertainty has a great impact on the efficiency results and the optimal level of inputs, future researches on the appropriate level of uncertainty according to the real conditions of production can improve the results of the RDEA model.

کلیدواژه‌ها [English]

  • Data Envelopment Analysis
  • Input-oriented efficiency
  • Mushroom
  • Robust optimization
  1. Abdi E., Dashti G., Ghahremanzadeh M., Hosseinzad J. 2016. Analyzing the technical efficiency and technology gap of poultry units in Sanandaj County. Journal of Animal Science Researches 26(3): 49-61. (In Persian with English abstract)
  2. Atıcı K.B., and Gülpınar N. 2016. Robust DEA Approaches to Performance Evaluation of Olive Oil Production Under Uncertainty, Robustness Analysis in Decision Aiding, Optimization, and Analytics. Springer, pp. 299-318.
  3. Barnes A. 2006. Does multi-functionality affect technical efficiency? A non-parametric analysis of the Scottish dairy industry. Journal of Environmental Management 80(4): 287-294.
  4. Bertsimas D., and Sim M. 2004. The price of robustness. Journal of Operations Research Letters 52(1): 35–53.
  5. Charnes A., Cooper W.W., and Rhodes E. 1978. Measuring the efficiency of decision-making units. European Journal of Operational Research 2(6): 429-444.
  6. Dlamini N.P., Masuku M.B., and Rugambisa J.I. 2018. Technical Efficiency of Mushroom Farmers in Swaziland. Development 6, 145-156.
  7. Farashah H.R., Tabatabaeifar S.A., Rajabipour A., Sefeedpari P. 2013. Energy Efficiency analysis of white button mushroom producers in Alburz Province of Iran: A data envelopment analysis approach.
  8. Farrell M.J. 1957. The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. Series A (General) 120(3): 253-290.
  9. Farsi M., Pouyanfar H. 2013. Cultivation and modification of edible white button mushroom Jehad-e Daneshgahi of Mashhad, Mashhad. (In Persian)
  10. Mardani M., and Salarpour M. 2015. Measuring technical efficiency of potato production in Iran using robust data envelopment analysis. Information Processing in Agriculture 2(1): 6-14.
  11. Mardani Najafabadi M., and Abdeshahi A. 2019. Evaluating Uncertainty of Palm Trees Efficiency in Ahvaz County: Application of Robust Data Envelopment Approach and Monte Carlo Simulation. Journal of Agricultural Economics and Development 33(2): 191-204. (In Persian with English abstract)
  12. Mardani Najafabadi M., Mirzaei A., Abdeshahi A., and Azarm H. 2020. Determining the efficiency of broiler chicken units in Sistan region, using interval data envelopment analysis and Mont Carlo simulation approach. Iranian Journal of Agricultural Economics and Development Research 51(2): 179-194. (In Persian with English abstract)
  13. Mardani Najafabadi M., Mirzaei A., and Ohadi N. 2021. Investigating the Rice Energy Efficiency Using Interval Fuzzy Data Envelopment Analysis Model (Case Study: Rice Farmers in Golestan Province). Iranian Journal of Agricultural Economics and Development Research 51(4): 661-677. (In Persian with English abstract)
  14. Mardani Najafabadi M., and Taki M. 2020. Robust data envelopment analysis with Monte Carlo simulation model for optimization the energy consumption in agriculture. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 1-15.
  15. Mardani Najafabadi M., and Ziaee S. 2017. Determining the efficiency of irrigated wheat farms in Neyshabur County under uncertainty. Journal of Agricultural Economics and Development 30(2): 136-147. (In Persian with English abstract)
  16. Mardani Najafabadi M., Ziaee S., Nikouei A., Ahmadpour Borazjani M. 2019. Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study. Agricultural Systems 173: 218-232.
  17. Moheban P., Mousavi S.N., and Nagafi B. 2017. Efficiency of Agricultural Processing Industry in Iran. Agricultural Economics Research 8(32): 79-100. (In Persian with English abstract)
  18. Nadi A., Hori H., Sadeghi Z., and Shaban M. 2015. Assessing the impact of environmental variables on the technical efficiency of major edible mushroom producers using a two-step process, International Conference on Management and Economics in the 21st Century. (In Persian with English abstract)
  19. Ohadi N., Shahraki J., Pahlavani M., Mardani Najafabadi M. 2019. Evaluating and Ranking of Environmental Efficiency of Oil-Rich Countries. Economic Development Policy 6(2): 124-146. (In Persian with English abstract)
  20. Omrani H. 2013. Robust data envelopment analysis model with fuzzy perturbation in inputs and outputs. International Journal of Industrial and Systems Engineering 15(4): 426-442.
  21. Qasemi-Kordkheili P., Asoodar M.A., Taki M., and Keramati-E-Asl M.S. 2013. Energy consumption pattern and optimization of energy inputs usage for button mushroom production. International Journal of Agriculture 3(2): 361.
  22. Sabouhi M., and Mardani M. 2017. Linear robust data envelopment analysis: CCR model with uncertain data. International Journal of Productivity and Quality Management 22(2): 262-280.
  23. Sadjadi S., and Omrani H. 2008. Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies. Energy Policy 36(11): 4247-4254.
  24. Sadrnia H., Khojastehpour M., Aghel H., and Olya A.S.R. 2017. Analysis of different inputs share and determination of energy Indices in broilers production in Mashhad city. Journal of Agricultural Machinery 7(1): 285-297. (In Persian with English abstract)
  25. Saedi A. 2005. Analysis of Factors Affecting the Profitability of Greenhouse Mushroom in Tehran Province, Agriculture and Natural Resources. Tehran. (In Persian with English abstract)
  26. Saleh A., Saedi A., and Yazdani S. 2008. Analysis of Factors Affecting the Profitability of Botton Mushroom Firms in Tehran Province. Pajouhesh-Va-Sazandegi 21(3): 53-61. (In Persian with English abstract)
  27. Salehi M. 2013. Energy required and economical analysis of button mushroom production in Isfahan district using data envelopment analysis, Agricultural Mechanization Engineering. (In Persian with English abstract)
  28. Shokouhi A.H., Hatami-Marbini A., Tavana M., and Saati S. 2010. A robust optimization approach for imprecise data envelopment analysis. Computers & Industrial Engineering 59(3): 387-397.
  29. Statistical Center of Iran, 2017. Amount and cost of inputs for edible mushroom production by provinces of Iran. https://www.amar.org.ir/. (In Persian)
  30. Statistical Center of Iran, 2018. Amount and cost of inputs for edible mushroom production by provinces of Iran. https://www.amar.org.ir/. (In Persian)
  31. Thi Vu H., Peng K.C., and Purnamasari M. 2018. Technical Efficiency of Edible Mushroom production farms in Thai Nguyen province, Vietnam. International Journal of Scientific & Engineering Research 9(7): 264-270.